mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-12-12 01:12:12 +00:00
5540 lines
268 KiB
Python
5540 lines
268 KiB
Python
import ast
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import io
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import json
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import logging
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import math
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import os.path as p
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import random
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import socket
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import string
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import threading
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import time
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from contextlib import contextmanager
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import avro.datafile
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import avro.io
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import avro.schema
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import kafka.errors
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import pytest
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from confluent_kafka.avro.cached_schema_registry_client import (
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CachedSchemaRegistryClient,
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)
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from confluent_kafka.avro.serializer.message_serializer import MessageSerializer
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from google.protobuf.internal.encoder import _VarintBytes
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from kafka import BrokerConnection, KafkaAdminClient, KafkaConsumer, KafkaProducer
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from kafka.admin import NewTopic
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from kafka.protocol.admin import DescribeGroupsRequest_v1
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from kafka.protocol.group import MemberAssignment
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from helpers.client import QueryRuntimeException
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from helpers.cluster import ClickHouseCluster, is_arm
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from helpers.network import PartitionManager
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from helpers.test_tools import TSV
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from . import kafka_pb2, message_with_repeated_pb2, social_pb2
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# protoc --version
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# libprotoc 3.0.0
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# # to create kafka_pb2.py
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# protoc --python_out=. kafka.proto
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if is_arm():
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pytestmark = pytest.mark.skip
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# TODO: add test for run-time offset update in CH, if we manually update it on Kafka side.
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# TODO: add test for SELECT LIMIT is working.
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KAFKA_TOPIC_OLD = "old_t"
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KAFKA_CONSUMER_GROUP_OLD = "old_cg"
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KAFKA_TOPIC_NEW = "new_t"
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KAFKA_CONSUMER_GROUP_NEW = "new_cg"
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cluster = ClickHouseCluster(__file__)
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instance = cluster.add_instance(
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"instance",
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main_configs=["configs/kafka.xml", "configs/named_collection.xml"],
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user_configs=["configs/users.xml"],
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with_kafka=True,
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with_zookeeper=True, # For Replicated Table
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keeper_required_feature_flags=[
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"create_if_not_exists"
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], # new Kafka doesn't work without this feature
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macros={
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"kafka_broker": "kafka1",
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"kafka_topic_old": KAFKA_TOPIC_OLD,
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"kafka_group_name_old": KAFKA_CONSUMER_GROUP_OLD,
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"kafka_topic_new": KAFKA_TOPIC_NEW,
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"kafka_group_name_new": KAFKA_CONSUMER_GROUP_NEW,
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"kafka_client_id": "instance",
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"kafka_format_json_each_row": "JSONEachRow",
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},
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clickhouse_path_dir="clickhouse_path",
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)
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def get_kafka_producer(port, serializer, retries):
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errors = []
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for _ in range(retries):
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try:
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producer = KafkaProducer(
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bootstrap_servers="localhost:{}".format(port),
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value_serializer=serializer,
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)
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logging.debug("Kafka Connection establised: localhost:{}".format(port))
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return producer
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except Exception as e:
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errors += [str(e)]
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time.sleep(1)
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raise Exception("Connection not establised, {}".format(errors))
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def producer_serializer(x):
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return x.encode() if isinstance(x, str) else x
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def kafka_create_topic(
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admin_client,
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topic_name,
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num_partitions=1,
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replication_factor=1,
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max_retries=50,
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config=None,
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):
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logging.debug(
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f"Kafka create topic={topic_name}, num_partitions={num_partitions}, replication_factor={replication_factor}"
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)
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topics_list = [
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NewTopic(
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name=topic_name,
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num_partitions=num_partitions,
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replication_factor=replication_factor,
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topic_configs=config,
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)
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]
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retries = 0
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while True:
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try:
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admin_client.create_topics(new_topics=topics_list, validate_only=False)
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logging.debug("Admin client succeed")
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return
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except Exception as e:
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retries += 1
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time.sleep(0.5)
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if retries < max_retries:
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logging.warning(f"Failed to create topic {e}")
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else:
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raise
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def kafka_delete_topic(admin_client, topic, max_retries=50):
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result = admin_client.delete_topics([topic])
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for topic, e in result.topic_error_codes:
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if e == 0:
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logging.debug(f"Topic {topic} deleted")
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else:
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logging.error(f"Failed to delete topic {topic}: {e}")
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retries = 0
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while True:
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topics_listed = admin_client.list_topics()
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logging.debug(f"TOPICS LISTED: {topics_listed}")
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if topic not in topics_listed:
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return
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else:
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retries += 1
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time.sleep(0.5)
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if retries > max_retries:
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raise Exception(f"Failed to delete topics {topic}, {result}")
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@contextmanager
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def kafka_topic(
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admin_client,
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topic_name,
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num_partitions=1,
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replication_factor=1,
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max_retries=50,
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config=None,
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):
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kafka_create_topic(
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admin_client,
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topic_name,
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num_partitions,
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replication_factor,
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max_retries,
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config,
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)
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try:
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yield None
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finally:
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# Code to release resource, e.g.:
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kafka_delete_topic(admin_client, topic_name, max_retries)
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@contextmanager
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def existing_kafka_topic(admin_client, topic_name, max_retries=50):
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try:
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yield None
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finally:
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kafka_delete_topic(admin_client, topic_name, max_retries)
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def get_admin_client(kafka_cluster):
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return KafkaAdminClient(
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bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
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)
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def kafka_produce(kafka_cluster, topic, messages, timestamp=None, retries=15):
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logging.debug(
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"kafka_produce server:{}:{} topic:{}".format(
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"localhost", kafka_cluster.kafka_port, topic
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)
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)
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producer = get_kafka_producer(
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kafka_cluster.kafka_port, producer_serializer, retries
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)
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for message in messages:
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producer.send(topic=topic, value=message, timestamp_ms=timestamp)
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producer.flush()
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## just to ensure the python client / producer is working properly
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def kafka_producer_send_heartbeat_msg(max_retries=50):
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kafka_produce(kafka_cluster, "test_heartbeat_topic", ["test"], retries=max_retries)
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def kafka_consume(kafka_cluster, topic, need_decode=True, timestamp=0):
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consumer = KafkaConsumer(
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bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
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auto_offset_reset="earliest",
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)
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consumer.subscribe(topics=(topic))
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for toppar, messages in list(consumer.poll(5000).items()):
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if toppar.topic == topic:
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for message in messages:
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assert timestamp == 0 or message.timestamp / 1000 == timestamp
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if need_decode:
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yield message.value.decode()
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else:
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yield message.value
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consumer.unsubscribe()
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consumer.close()
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def kafka_produce_protobuf_messages(kafka_cluster, topic, start_index, num_messages):
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data = b""
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for i in range(start_index, start_index + num_messages):
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msg = kafka_pb2.KeyValuePair()
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msg.key = i
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msg.value = str(i)
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serialized_msg = msg.SerializeToString()
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data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
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producer = KafkaProducer(
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bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
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value_serializer=producer_serializer,
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)
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producer.send(topic=topic, value=data)
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producer.flush()
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logging.debug(("Produced {} messages for topic {}".format(num_messages, topic)))
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def kafka_consume_with_retry(
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kafka_cluster,
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topic,
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expected_messages,
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need_decode=True,
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timestamp=0,
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retry_count=20,
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sleep_time=0.1,
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):
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messages = []
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try_count = 0
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while try_count < retry_count:
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try_count += 1
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messages.extend(
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kafka_consume(
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kafka_cluster, topic, need_decode=need_decode, timestamp=timestamp
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)
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)
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if len(messages) == expected_messages:
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break
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time.sleep(sleep_time)
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if len(messages) != expected_messages:
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raise Exception(f"Got only {len(messages)} messages")
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return messages
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def kafka_produce_protobuf_messages_no_delimiters(
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kafka_cluster, topic, start_index, num_messages
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):
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data = ""
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producer = KafkaProducer(
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bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
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)
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for i in range(start_index, start_index + num_messages):
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msg = kafka_pb2.KeyValuePair()
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msg.key = i
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msg.value = str(i)
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serialized_msg = msg.SerializeToString()
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producer.send(topic=topic, value=serialized_msg)
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producer.flush()
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logging.debug("Produced {} messages for topic {}".format(num_messages, topic))
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def kafka_produce_protobuf_social(kafka_cluster, topic, start_index, num_messages):
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data = b""
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for i in range(start_index, start_index + num_messages):
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msg = social_pb2.User()
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msg.username = "John Doe {}".format(i)
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msg.timestamp = 1000000 + i
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serialized_msg = msg.SerializeToString()
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data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
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producer = KafkaProducer(
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bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
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value_serializer=producer_serializer,
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)
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producer.send(topic=topic, value=data)
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producer.flush()
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logging.debug(("Produced {} messages for topic {}".format(num_messages, topic)))
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def avro_message(value):
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schema = avro.schema.make_avsc_object(
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{
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"name": "row",
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"type": "record",
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"fields": [
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{"name": "id", "type": "long"},
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{"name": "blockNo", "type": "int"},
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{"name": "val1", "type": "string"},
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{"name": "val2", "type": "float"},
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{"name": "val3", "type": "int"},
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],
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}
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)
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bytes_writer = io.BytesIO()
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# writer = avro.io.DatumWriter(schema)
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# encoder = avro.io.BinaryEncoder(bytes_writer)
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# writer.write(value, encoder)
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# DataFileWrite seems to be mandatory to get schema encoded
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writer = avro.datafile.DataFileWriter(bytes_writer, avro.io.DatumWriter(), schema)
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if isinstance(value, list):
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for v in value:
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writer.append(v)
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else:
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writer.append(value)
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writer.flush()
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raw_bytes = bytes_writer.getvalue()
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writer.close()
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bytes_writer.close()
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return raw_bytes
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def avro_confluent_message(schema_registry_client, value):
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# type: (CachedSchemaRegistryClient, dict) -> str
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serializer = MessageSerializer(schema_registry_client)
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schema = avro.schema.make_avsc_object(
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{
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"name": "row",
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"type": "record",
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"fields": [
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{"name": "id", "type": "long"},
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{"name": "blockNo", "type": "int"},
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{"name": "val1", "type": "string"},
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{"name": "val2", "type": "float"},
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{"name": "val3", "type": "int"},
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],
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}
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)
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return serializer.encode_record_with_schema("test_subject", schema, value)
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def create_settings_string(settings):
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if settings is None:
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return ""
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def format_value(value):
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if isinstance(value, str):
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return f"'{value}'"
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elif isinstance(value, bool):
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return str(int(value))
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return str(value)
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settings_string = "SETTINGS "
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keys = settings.keys()
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first_key = next(iter(settings))
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settings_string += str(first_key) + " = " + format_value(settings[first_key])
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for key in keys:
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if key == first_key:
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continue
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settings_string += ", " + str(key) + " = " + format_value(settings[key])
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return settings_string
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def generate_old_create_table_query(
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table_name,
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columns_def,
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database="test",
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brokers="{kafka_broker}:19092",
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topic_list="{kafka_topic_new}",
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consumer_group="{kafka_group_name_new}",
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format="{kafka_format_json_each_row}",
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row_delimiter="\\n",
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keeper_path=None, # it is not used, but it is easier to handle keeper_path and replica_name like this
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replica_name=None,
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settings=None,
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):
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settings_string = create_settings_string(settings)
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query = f"""CREATE TABLE {database}.{table_name} ({columns_def}) ENGINE = Kafka('{brokers}', '{topic_list}', '{consumer_group}', '{format}', '{row_delimiter}')
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{settings_string}"""
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logging.debug(f"Generated old create query: {query}")
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return query
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def generate_new_create_table_query(
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table_name,
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columns_def,
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database="test",
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brokers="{kafka_broker}:19092",
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topic_list="{kafka_topic_new}",
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consumer_group="{kafka_group_name_new}",
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format="{kafka_format_json_each_row}",
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row_delimiter="\\n",
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keeper_path=None,
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replica_name=None,
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settings=None,
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):
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if settings is None:
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settings = {}
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if keeper_path is None:
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keeper_path = f"/clickhouse/{{database}}/{table_name}"
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if replica_name is None:
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replica_name = "r1"
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settings["kafka_keeper_path"] = keeper_path
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settings["kafka_replica_name"] = replica_name
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settings_string = create_settings_string(settings)
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query = f"""CREATE TABLE {database}.{table_name} ({columns_def}) ENGINE = Kafka('{brokers}', '{topic_list}', '{consumer_group}', '{format}', '{row_delimiter}')
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{settings_string}
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SETTINGS allow_experimental_kafka_offsets_storage_in_keeper=1"""
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logging.debug(f"Generated new create query: {query}")
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return query
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def must_use_thread_per_consumer(generator):
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if generator == generate_old_create_table_query:
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return False
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if generator == generate_new_create_table_query:
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return True
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raise Exception("Unexpected generator")
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def get_topic_postfix(generator):
|
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if generator == generate_old_create_table_query:
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return "old"
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if generator == generate_new_create_table_query:
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return "new"
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raise Exception("Unexpected generator")
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|
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# Tests
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@pytest.mark.parametrize(
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"create_query_generator, do_direct_read",
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[(generate_old_create_table_query, True), (generate_new_create_table_query, False)],
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)
|
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def test_kafka_column_types(kafka_cluster, create_query_generator, do_direct_read):
|
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def assert_returned_exception(e):
|
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assert e.value.returncode == 36
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assert (
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"KafkaEngine doesn't support DEFAULT/MATERIALIZED/EPHEMERAL expressions for columns."
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in str(e.value)
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)
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|
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# check column with DEFAULT expression
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with pytest.raises(QueryRuntimeException) as exception:
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instance.query(create_query_generator("kafka", "a Int, b Int DEFAULT 0"))
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assert_returned_exception(exception)
|
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|
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# check EPHEMERAL
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with pytest.raises(QueryRuntimeException) as exception:
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instance.query(create_query_generator("kafka", "a Int, b Int EPHEMERAL"))
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assert_returned_exception(exception)
|
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|
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# check MATERIALIZED
|
|
with pytest.raises(QueryRuntimeException) as exception:
|
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instance.query(
|
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"""
|
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CREATE TABLE test.kafka (a Int, b String MATERIALIZED toString(a))
|
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ENGINE = Kafka('{kafka_broker}:19092', '{kafka_topic_new}', '{kafka_group_name_new}', '{kafka_format_json_each_row}', '\\n')
|
|
"""
|
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)
|
|
assert_returned_exception(exception)
|
|
|
|
if do_direct_read:
|
|
# check ALIAS
|
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instance.query(
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create_query_generator(
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"kafka",
|
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"a Int, b String Alias toString(a)",
|
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settings={"kafka_commit_on_select": True},
|
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)
|
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)
|
|
messages = []
|
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for i in range(5):
|
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messages.append(json.dumps({"a": i}))
|
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kafka_produce(kafka_cluster, KAFKA_TOPIC_NEW, messages)
|
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result = ""
|
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expected = TSV(
|
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"""
|
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0\t0
|
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1\t1
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2\t2
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3\t3
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4\t4
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"""
|
|
)
|
|
retries = 50
|
|
while retries > 0:
|
|
result += instance.query("SELECT a, b FROM test.kafka", ignore_error=True)
|
|
if TSV(result) == expected:
|
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break
|
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retries -= 1
|
|
time.sleep(0.5)
|
|
|
|
assert TSV(result) == expected
|
|
|
|
instance.query("DROP TABLE test.kafka SYNC")
|
|
|
|
|
|
def test_kafka_settings_old_syntax(kafka_cluster):
|
|
assert TSV(
|
|
instance.query(
|
|
"SELECT * FROM system.macros WHERE macro like 'kafka%' ORDER BY macro",
|
|
ignore_error=True,
|
|
)
|
|
) == TSV(
|
|
f"""kafka_broker kafka1
|
|
kafka_client_id instance
|
|
kafka_format_json_each_row JSONEachRow
|
|
kafka_group_name_new {KAFKA_CONSUMER_GROUP_NEW}
|
|
kafka_group_name_old {KAFKA_CONSUMER_GROUP_OLD}
|
|
kafka_topic_new new_t
|
|
kafka_topic_old old_t
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka('{kafka_broker}:19092', '{kafka_topic_old}', '{kafka_group_name_old}', '{kafka_format_json_each_row}', '\\n')
|
|
SETTINGS kafka_commit_on_select = 1;
|
|
"""
|
|
)
|
|
|
|
# Don't insert malformed messages since old settings syntax
|
|
# doesn't support skipping of broken messages.
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, KAFKA_TOPIC_OLD, messages)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
members = describe_consumer_group(kafka_cluster, KAFKA_CONSUMER_GROUP_OLD)
|
|
assert members[0]["client_id"] == "ClickHouse-instance-test-kafka"
|
|
# text_desc = kafka_cluster.exec_in_container(kafka_cluster.get_container_id('kafka1'),"kafka-consumer-groups --bootstrap-server localhost:9092 --describe --members --group old --verbose"))
|
|
|
|
|
|
def test_kafka_settings_new_syntax(kafka_cluster):
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = '{kafka_broker}:19092',
|
|
kafka_topic_list = '{kafka_topic_new}',
|
|
kafka_group_name = '{kafka_group_name_new}',
|
|
kafka_format = '{kafka_format_json_each_row}',
|
|
kafka_row_delimiter = '\\n',
|
|
kafka_commit_on_select = 1,
|
|
kafka_client_id = '{kafka_client_id} test 1234',
|
|
kafka_skip_broken_messages = 1;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(25):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, KAFKA_TOPIC_NEW, messages)
|
|
|
|
# Insert couple of malformed messages.
|
|
kafka_produce(kafka_cluster, KAFKA_TOPIC_NEW, ["}{very_broken_message,"])
|
|
kafka_produce(kafka_cluster, KAFKA_TOPIC_NEW, ["}another{very_broken_message,"])
|
|
|
|
messages = []
|
|
for i in range(25, 50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, KAFKA_TOPIC_NEW, messages)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
members = describe_consumer_group(kafka_cluster, KAFKA_CONSUMER_GROUP_NEW)
|
|
assert members[0]["client_id"] == "instance test 1234"
|
|
|
|
|
|
def test_kafka_settings_predefined_macros(kafka_cluster):
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = '{kafka_broker}:19092',
|
|
kafka_topic_list = '{database}_{table}_topic',
|
|
kafka_group_name = '{database}_{table}_group',
|
|
kafka_format = '{kafka_format_json_each_row}',
|
|
kafka_row_delimiter = '\\n',
|
|
kafka_commit_on_select = 1,
|
|
kafka_client_id = '{database}_{table} test 1234',
|
|
kafka_skip_broken_messages = 1;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, "test_kafka_topic", messages)
|
|
|
|
result = instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
kafka_check_result(result, True)
|
|
|
|
members = describe_consumer_group(kafka_cluster, "test_kafka_group")
|
|
assert members[0]["client_id"] == "test_kafka test 1234"
|
|
|
|
|
|
def test_kafka_json_as_string(kafka_cluster):
|
|
kafka_produce(
|
|
kafka_cluster,
|
|
"kafka_json_as_string",
|
|
[
|
|
'{"t": 123, "e": {"x": "woof"} }',
|
|
"",
|
|
'{"t": 124, "e": {"x": "test"} }',
|
|
'{"F1":"V1","F2":{"F21":"V21","F22":{},"F23":"V23","F24":"2019-12-24T16:28:04"},"F3":"V3"}',
|
|
],
|
|
)
|
|
|
|
# 'tombstone' record (null value) = marker of deleted record
|
|
producer = KafkaProducer(
|
|
bootstrap_servers="localhost:{}".format(cluster.kafka_port),
|
|
value_serializer=producer_serializer,
|
|
key_serializer=producer_serializer,
|
|
)
|
|
producer.send(topic="kafka_json_as_string", key="xxx")
|
|
producer.flush()
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (field String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'kafka_json_as_string',
|
|
kafka_group_name = 'kafka_json_as_string',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONAsString',
|
|
kafka_flush_interval_ms=1000;
|
|
"""
|
|
)
|
|
|
|
result = instance.query("SELECT * FROM test.kafka;")
|
|
expected = """\
|
|
{"t": 123, "e": {"x": "woof"} }
|
|
{"t": 124, "e": {"x": "test"} }
|
|
{"F1":"V1","F2":{"F21":"V21","F22":{},"F23":"V23","F24":"2019-12-24T16:28:04"},"F3":"V3"}
|
|
"""
|
|
assert TSV(result) == TSV(expected)
|
|
assert instance.contains_in_log(
|
|
"Parsing of message (topic: kafka_json_as_string, partition: 0, offset: [0-9]*) return no rows"
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_formats(kafka_cluster, create_query_generator):
|
|
schema_registry_client = CachedSchemaRegistryClient(
|
|
{"url": f"http://localhost:{kafka_cluster.schema_registry_port}"}
|
|
)
|
|
|
|
# data was dumped from clickhouse itself in a following manner
|
|
# clickhouse-client --format=Native --query='SELECT toInt64(number) as id, toUInt16( intDiv( id, 65536 ) ) as blockNo, reinterpretAsString(19777) as val1, toFloat32(0.5) as val2, toUInt8(1) as val3 from numbers(100) ORDER BY id' | xxd -ps | tr -d '\n' | sed 's/\(..\)/\\x\1/g'
|
|
|
|
all_formats = {
|
|
## Text formats ##
|
|
# dumped with clickhouse-client ... | perl -pe 's/\n/\\n/; s/\t/\\t/g;'
|
|
"JSONEachRow": {
|
|
"data_sample": [
|
|
'{"id":"0","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n',
|
|
'{"id":"1","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"2","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"3","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"4","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"5","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"6","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"7","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"8","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"9","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"10","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"11","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"12","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"13","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"14","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"15","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n',
|
|
'{"id":"0","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n',
|
|
],
|
|
"supports_empty_value": True,
|
|
},
|
|
# JSONAsString doesn't fit to that test, and tested separately
|
|
"JSONCompactEachRow": {
|
|
"data_sample": [
|
|
'["0", 0, "AM", 0.5, 1]\n',
|
|
'["1", 0, "AM", 0.5, 1]\n["2", 0, "AM", 0.5, 1]\n["3", 0, "AM", 0.5, 1]\n["4", 0, "AM", 0.5, 1]\n["5", 0, "AM", 0.5, 1]\n["6", 0, "AM", 0.5, 1]\n["7", 0, "AM", 0.5, 1]\n["8", 0, "AM", 0.5, 1]\n["9", 0, "AM", 0.5, 1]\n["10", 0, "AM", 0.5, 1]\n["11", 0, "AM", 0.5, 1]\n["12", 0, "AM", 0.5, 1]\n["13", 0, "AM", 0.5, 1]\n["14", 0, "AM", 0.5, 1]\n["15", 0, "AM", 0.5, 1]\n',
|
|
'["0", 0, "AM", 0.5, 1]\n',
|
|
],
|
|
"supports_empty_value": True,
|
|
},
|
|
"JSONCompactEachRowWithNamesAndTypes": {
|
|
"data_sample": [
|
|
'["id", "blockNo", "val1", "val2", "val3"]\n["Int64", "UInt16", "String", "Float32", "UInt8"]\n["0", 0, "AM", 0.5, 1]\n',
|
|
'["id", "blockNo", "val1", "val2", "val3"]\n["Int64", "UInt16", "String", "Float32", "UInt8"]\n["1", 0, "AM", 0.5, 1]\n["2", 0, "AM", 0.5, 1]\n["3", 0, "AM", 0.5, 1]\n["4", 0, "AM", 0.5, 1]\n["5", 0, "AM", 0.5, 1]\n["6", 0, "AM", 0.5, 1]\n["7", 0, "AM", 0.5, 1]\n["8", 0, "AM", 0.5, 1]\n["9", 0, "AM", 0.5, 1]\n["10", 0, "AM", 0.5, 1]\n["11", 0, "AM", 0.5, 1]\n["12", 0, "AM", 0.5, 1]\n["13", 0, "AM", 0.5, 1]\n["14", 0, "AM", 0.5, 1]\n["15", 0, "AM", 0.5, 1]\n',
|
|
'["id", "blockNo", "val1", "val2", "val3"]\n["Int64", "UInt16", "String", "Float32", "UInt8"]\n["0", 0, "AM", 0.5, 1]\n',
|
|
# ''
|
|
# On empty message exception: Cannot parse input: expected '[' at end of stream., Stack trace (when copying this message, always include the lines below):
|
|
# /src/IO/ReadHelpers.h:175: DB::assertChar(char, DB::ReadBuffer&) @ 0x15db231a in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/JSONCompactEachRowRowInputFormat.cpp:0: DB::JSONCompactEachRowRowInputFormat::readPrefix() @ 0x1dee6bd6 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/IRowInputFormat.cpp:0: DB::IRowInputFormat::generate() @ 0x1de72710 in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"TSKV": {
|
|
"data_sample": [
|
|
"id=0\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\n",
|
|
"id=1\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=2\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=3\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=4\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=5\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=6\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=7\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=8\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=9\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=10\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=11\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=12\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=13\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=14\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=15\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\n",
|
|
"id=0\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\n",
|
|
# ''
|
|
# On empty message exception: Unexpected end of stream while reading key name from TSKV format
|
|
# /src/Processors/Formats/Impl/TSKVRowInputFormat.cpp:88: DB::readName(DB::ReadBuffer&, StringRef&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >&) @ 0x1df8c098 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/TSKVRowInputFormat.cpp:114: DB::TSKVRowInputFormat::readRow(std::__1::vector<COW<DB::IColumn>::mutable_ptr<DB::IColumn>, std::__1::allocator<COW<DB::IColumn>::mutable_ptr<DB::IColumn> > >&, DB::RowReadExtension&) @ 0x1df8ae3e in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/IRowInputFormat.cpp:64: DB::IRowInputFormat::generate() @ 0x1de727cf in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"CSV": {
|
|
"data_sample": [
|
|
'0,0,"AM",0.5,1\n',
|
|
'1,0,"AM",0.5,1\n2,0,"AM",0.5,1\n3,0,"AM",0.5,1\n4,0,"AM",0.5,1\n5,0,"AM",0.5,1\n6,0,"AM",0.5,1\n7,0,"AM",0.5,1\n8,0,"AM",0.5,1\n9,0,"AM",0.5,1\n10,0,"AM",0.5,1\n11,0,"AM",0.5,1\n12,0,"AM",0.5,1\n13,0,"AM",0.5,1\n14,0,"AM",0.5,1\n15,0,"AM",0.5,1\n',
|
|
'0,0,"AM",0.5,1\n',
|
|
],
|
|
"supports_empty_value": True,
|
|
},
|
|
"TSV": {
|
|
"data_sample": [
|
|
"0\t0\tAM\t0.5\t1\n",
|
|
"1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"0\t0\tAM\t0.5\t1\n",
|
|
],
|
|
"supports_empty_value": True,
|
|
},
|
|
"CSVWithNames": {
|
|
"data_sample": [
|
|
'"id","blockNo","val1","val2","val3"\n0,0,"AM",0.5,1\n',
|
|
'"id","blockNo","val1","val2","val3"\n1,0,"AM",0.5,1\n2,0,"AM",0.5,1\n3,0,"AM",0.5,1\n4,0,"AM",0.5,1\n5,0,"AM",0.5,1\n6,0,"AM",0.5,1\n7,0,"AM",0.5,1\n8,0,"AM",0.5,1\n9,0,"AM",0.5,1\n10,0,"AM",0.5,1\n11,0,"AM",0.5,1\n12,0,"AM",0.5,1\n13,0,"AM",0.5,1\n14,0,"AM",0.5,1\n15,0,"AM",0.5,1\n',
|
|
'"id","blockNo","val1","val2","val3"\n0,0,"AM",0.5,1\n',
|
|
# '',
|
|
# On empty message exception happens: Attempt to read after eof
|
|
# /src/IO/VarInt.h:122: DB::throwReadAfterEOF() @ 0x15c34487 in /usr/bin/clickhouse
|
|
# /src/IO/ReadHelpers.cpp:583: void DB::readCSVStringInto<std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> > >(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >&, DB::ReadBuffer&, DB::FormatSettings::CSV const&) @ 0x15c961e1 in /usr/bin/clickhouse
|
|
# /src/IO/ReadHelpers.cpp:678: DB::readCSVString(std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char> >&, DB::ReadBuffer&, DB::FormatSettings::CSV const&) @ 0x15c8dfae in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/CSVRowInputFormat.cpp:170: DB::CSVRowInputFormat::readPrefix() @ 0x1dec46f7 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/IRowInputFormat.cpp:0: DB::IRowInputFormat::generate() @ 0x1de72710 in /usr/bin/clickhouse
|
|
# /src/Processors/ISource.cpp:48: DB::ISource::work() @ 0x1dd79737 in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"Values": {
|
|
"data_sample": [
|
|
"(0,0,'AM',0.5,1)",
|
|
"(1,0,'AM',0.5,1),(2,0,'AM',0.5,1),(3,0,'AM',0.5,1),(4,0,'AM',0.5,1),(5,0,'AM',0.5,1),(6,0,'AM',0.5,1),(7,0,'AM',0.5,1),(8,0,'AM',0.5,1),(9,0,'AM',0.5,1),(10,0,'AM',0.5,1),(11,0,'AM',0.5,1),(12,0,'AM',0.5,1),(13,0,'AM',0.5,1),(14,0,'AM',0.5,1),(15,0,'AM',0.5,1)",
|
|
"(0,0,'AM',0.5,1)",
|
|
],
|
|
"supports_empty_value": True,
|
|
},
|
|
"TSVWithNames": {
|
|
"data_sample": [
|
|
"id\tblockNo\tval1\tval2\tval3\n0\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\n1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\n0\t0\tAM\t0.5\t1\n",
|
|
],
|
|
"supports_empty_value": True,
|
|
},
|
|
"TSVWithNamesAndTypes": {
|
|
"data_sample": [
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n0\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n0\t0\tAM\t0.5\t1\n",
|
|
# '',
|
|
# On empty message exception happens: Cannot parse input: expected '\n' at end of stream.
|
|
# /src/IO/ReadHelpers.cpp:84: DB::throwAtAssertionFailed(char const*, DB::ReadBuffer&) @ 0x15c8d8ec in /usr/bin/clickhouse
|
|
# /src/IO/ReadHelpers.h:175: DB::assertChar(char, DB::ReadBuffer&) @ 0x15db231a in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/TabSeparatedRowInputFormat.cpp:24: DB::skipTSVRow(DB::ReadBuffer&, unsigned long) @ 0x1df92fac in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/TabSeparatedRowInputFormat.cpp:168: DB::TabSeparatedRowInputFormat::readPrefix() @ 0x1df92df0 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/IRowInputFormat.cpp:0: DB::IRowInputFormat::generate() @ 0x1de72710 in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"CustomSeparated": {
|
|
"data_sample": [
|
|
"0\t0\tAM\t0.5\t1\n",
|
|
"1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"0\t0\tAM\t0.5\t1\n",
|
|
],
|
|
},
|
|
"Template": {
|
|
"data_sample": [
|
|
'(id = 0, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)',
|
|
'(id = 1, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 2, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 3, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 4, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 5, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 6, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 7, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 8, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 9, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 10, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 11, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 12, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 13, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 14, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 15, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)',
|
|
'(id = 0, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)',
|
|
],
|
|
"extra_settings": {"format_template_row": "template_row.format"},
|
|
},
|
|
"Regexp": {
|
|
"data_sample": [
|
|
'(id = 0, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)',
|
|
'(id = 1, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 2, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 3, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 4, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 5, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 6, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 7, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 8, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 9, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 10, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 11, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 12, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 13, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 14, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)\n(id = 15, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)',
|
|
'(id = 0, blockNo = 0, val1 = "AM", val2 = 0.5, val3 = 1)',
|
|
# ''
|
|
# On empty message exception happens: Line "" doesn't match the regexp.: (at row 1)
|
|
# /src/Processors/Formats/Impl/RegexpRowInputFormat.cpp:140: DB::RegexpRowInputFormat::readRow(std::__1::vector<COW<DB::IColumn>::mutable_ptr<DB::IColumn>, std::__1::allocator<COW<DB::IColumn>::mutable_ptr<DB::IColumn> > >&, DB::RowReadExtension&) @ 0x1df82fcb in /usr/bin/clickhouse
|
|
],
|
|
"extra_settings": {
|
|
"format_regexp": r"\(id = (.+?), blockNo = (.+?), val1 = \"(.+?)\", val2 = (.+?), val3 = (.+?)\)",
|
|
"format_regexp_escaping_rule": "Escaped",
|
|
},
|
|
},
|
|
## BINARY FORMATS
|
|
# dumped with
|
|
# clickhouse-client ... | xxd -ps -c 200 | tr -d '\n' | sed 's/\(..\)/\\x\1/g'
|
|
"Native": {
|
|
"data_sample": [
|
|
b"\x05\x01\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x00\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x55\x49\x6e\x74\x31\x36\x00\x00\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01",
|
|
b"\x05\x0f\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x06\x00\x00\x00\x00\x00\x00\x00\x07\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x09\x00\x00\x00\x00\x00\x00\x00\x0a\x00\x00\x00\x00\x00\x00\x00\x0b\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x00\x00\x00\x00\x00\x00\x0d\x00\x00\x00\x00\x00\x00\x00\x0e\x00\x00\x00\x00\x00\x00\x00\x0f\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x55\x49\x6e\x74\x31\x36\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01",
|
|
b"\x05\x01\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x00\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x55\x49\x6e\x74\x31\x36\x00\x00\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01",
|
|
# ''
|
|
# On empty message exception happens: DB::Exception: Attempt to read after eof
|
|
# 1. DB::throwReadAfterEOF() @ 0xb76449b in /usr/bin/clickhouse
|
|
# 2. ? @ 0xb79cb0b in /usr/bin/clickhouse
|
|
# 3. DB::NativeReader::read() @ 0x16e7a084 in /usr/bin/clickhouse
|
|
# 4. DB::NativeInputFormat::generate() @ 0x16f76922 in /usr/bin/clickhouse
|
|
# 5. DB::ISource::tryGenerate() @ 0x16e90bd5 in /usr/bin/clickhouse
|
|
# 6. DB::ISource::work() @ 0x16e9087a in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"MsgPack": {
|
|
"data_sample": [
|
|
b"\x00\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01",
|
|
b"\x01\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x02\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x03\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x04\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x05\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x06\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x07\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x08\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x09\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x0a\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x0b\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x0c\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x0d\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x0e\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01\x0f\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01",
|
|
b"\x00\x00\xa2\x41\x4d\xca\x3f\x00\x00\x00\x01",
|
|
# ''
|
|
# On empty message exception happens: Unexpected end of file while parsing msgpack object.: (at row 1)
|
|
# coming from Processors/Formats/Impl/MsgPackRowInputFormat.cpp:170
|
|
],
|
|
},
|
|
"RowBinary": {
|
|
"data_sample": [
|
|
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x02\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x03\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x04\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x05\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x06\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x07\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x08\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x09\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0a\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0b\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0c\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0d\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0e\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0f\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
# ''
|
|
# On empty message exception happens: DB::Exception: Cannot read all data. Bytes read: 0. Bytes expected: 8.
|
|
# /src/IO/ReadBuffer.h:157: DB::ReadBuffer::readStrict(char*, unsigned long) @ 0x15c6894d in /usr/bin/clickhouse
|
|
# /src/IO/ReadHelpers.h:108: void DB::readPODBinary<long>(long&, DB::ReadBuffer&) @ 0x15c67715 in /usr/bin/clickhouse
|
|
# /src/IO/ReadHelpers.h:737: std::__1::enable_if<is_arithmetic_v<long>, void>::type DB::readBinary<long>(long&, DB::ReadBuffer&) @ 0x15e7afbd in /usr/bin/clickhouse
|
|
# /src/DataTypes/DataTypeNumberBase.cpp:180: DB::DataTypeNumberBase<long>::deserializeBinary(DB::IColumn&, DB::ReadBuffer&) const @ 0x1cace581 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/BinaryRowInputFormat.cpp:22: DB::BinaryRowInputFormat::readRow(std::__1::vector<COW<DB::IColumn>::mutable_ptr<DB::IColumn>, std::__1::allocator<COW<DB::IColumn>::mutable_ptr<DB::IColumn> > >&, DB::RowReadExtension&) @ 0x1dea2c0b in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"RowBinaryWithNamesAndTypes": {
|
|
"data_sample": [
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x55\x49\x6e\x74\x31\x36\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x55\x49\x6e\x74\x31\x36\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x02\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x03\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x04\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x05\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x06\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x07\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x08\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x09\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0a\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0b\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0c\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0d\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0e\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0f\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x55\x49\x6e\x74\x31\x36\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
# ''
|
|
# !!! On empty message segfault: Address not mapped to object
|
|
# /contrib/FastMemcpy/FastMemcpy.h:666: memcpy_fast @ 0x21742d65 in /usr/bin/clickhouse
|
|
# /contrib/FastMemcpy/memcpy_wrapper.c:5: memcpy @ 0x21738235 in /usr/bin/clickhouse
|
|
# /src/IO/ReadBuffer.h:145: DB::ReadBuffer::read(char*, unsigned long) @ 0x15c369d7 in /usr/bin/clickhouse
|
|
# /src/IO/ReadBuffer.h:155: DB::ReadBuffer::readStrict(char*, unsigned long) @ 0x15c68878 in /usr/bin/clickhouse
|
|
# /src/DataTypes/DataTypeString.cpp:84: DB::DataTypeString::deserializeBinary(DB::IColumn&, DB::ReadBuffer&) const @ 0x1cad12e7 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/BinaryRowInputFormat.cpp:22: DB::BinaryRowInputFormat::readRow(std::__1::vector<COW<DB::IColumn>::mutable_ptr<DB::IColumn>, std::__1::allocator<COW<DB::IColumn>::mutable_ptr<DB::IColumn> > >&, DB::RowReadExtension&) @ 0x1dea2c0b in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"Protobuf": {
|
|
"data_sample": [
|
|
b"\x0b\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01",
|
|
b"\x0d\x08\x01\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x02\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x03\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x04\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x05\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x06\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x07\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x08\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x09\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x0a\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x0b\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x0c\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x0d\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x0e\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01\x0d\x08\x0f\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01",
|
|
b"\x0b\x1a\x02\x41\x4d\x25\x00\x00\x00\x3f\x28\x01",
|
|
# ''
|
|
# On empty message exception: Attempt to read after eof
|
|
# /src/IO/ReadBuffer.h:184: DB::ReadBuffer::throwReadAfterEOF() @ 0x15c9699b in /usr/bin/clickhouse
|
|
# /src/Formats/ProtobufReader.h:115: DB::ProtobufReader::SimpleReader::startMessage() @ 0x1df4f828 in /usr/bin/clickhouse
|
|
# /src/Formats/ProtobufReader.cpp:1119: DB::ProtobufReader::startMessage() @ 0x1df5356c in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/ProtobufRowInputFormat.cpp:25: DB::ProtobufRowInputFormat::readRow(std::__1::vector<COW<DB::IColumn>::mutable_ptr<DB::IColumn>, std::__1::allocator<COW<DB::IColumn>::mutable_ptr<DB::IColumn> > >&, DB::RowReadExtension&) @ 0x1df4cc71 in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/IRowInputFormat.cpp:64: DB::IRowInputFormat::generate() @ 0x1de727cf in /usr/bin/clickhouse
|
|
],
|
|
"extra_settings": {"kafka_schema": "test:TestMessage"},
|
|
},
|
|
"ORC": {
|
|
"data_sample": [
|
|
b"\x4f\x52\x43\x11\x00\x00\x0a\x06\x12\x04\x08\x01\x50\x00\x2b\x00\x00\x0a\x13\x0a\x03\x00\x00\x00\x12\x0c\x08\x01\x12\x06\x08\x00\x10\x00\x18\x00\x50\x00\x30\x00\x00\xe3\x12\xe7\x62\x65\x00\x01\x21\x3e\x0e\x46\x25\x0e\x2e\x46\x03\x21\x46\x03\x09\xa6\x00\x06\x00\x32\x00\x00\xe3\x92\xe4\x62\x65\x00\x01\x21\x01\x0e\x46\x25\x2e\x2e\x26\x47\x5f\x21\x20\x96\x60\x09\x60\x00\x00\x36\x00\x00\xe3\x92\xe1\x62\x65\x00\x01\x21\x61\x0e\x46\x23\x5e\x2e\x46\x03\x21\x66\x03\x3d\x53\x29\x10\x11\xc0\x00\x00\x2b\x00\x00\x0a\x13\x0a\x03\x00\x00\x00\x12\x0c\x08\x01\x12\x06\x08\x02\x10\x02\x18\x02\x50\x00\x05\x00\x00\xff\x00\x03\x00\x00\x30\x07\x00\x00\x40\x00\x80\x05\x00\x00\x41\x4d\x07\x00\x00\x42\x00\x80\x03\x00\x00\x0a\x07\x00\x00\x42\x00\x80\x05\x00\x00\xff\x01\x88\x00\x00\x4d\xca\xc1\x0a\x80\x30\x0c\x03\xd0\x2e\x6b\xcb\x98\x17\xf1\x14\x50\xfc\xff\xcf\xb4\x66\x1e\x3c\x84\x47\x9a\xce\x1c\xb9\x1b\xb7\xf9\xda\x48\x09\x9e\xb2\xf3\x92\xce\x5b\x86\xf6\x56\x7f\x21\x41\x2f\x51\xa6\x7a\xd7\x1d\xe5\xea\xae\x3d\xca\xd5\x83\x71\x60\xd8\x17\xfc\x62\x0f\xa8\x00\x00\xe3\x4a\xe6\x62\xe1\x60\x0c\x60\xe0\xe2\xe3\x60\x14\x62\xe3\x60\x10\x60\x90\x60\x08\x60\x88\x60\xe5\x12\xe0\x60\x54\xe2\xe0\x62\x34\x10\x62\x34\x90\x60\x02\x8a\x70\x71\x09\x01\x45\xb8\xb8\x98\x1c\x7d\x85\x80\x58\x82\x05\x28\xc6\xcd\x25\xca\xc1\x68\xc4\x0b\x52\xc5\x6c\xa0\x67\x2a\x05\x22\xc0\x4a\x21\x86\x31\x09\x30\x81\xb5\xb2\x02\x00\x36\x01\x00\x25\x8c\xbd\x0a\xc2\x30\x14\x85\x73\x6f\x92\xf6\x92\x6a\x09\x01\x21\x64\x92\x4e\x75\x91\x58\x71\xc9\x64\x27\x5d\x2c\x1d\x5d\xfd\x59\xc4\x42\x37\x5f\xc0\x17\xe8\x23\x9b\xc6\xe1\x3b\x70\x0f\xdf\xb9\xc4\xf5\x17\x5d\x41\x5c\x4f\x60\x37\xeb\x53\x0d\x55\x4d\x0b\x23\x01\xb9\x90\x2e\xbf\x0f\xe3\xe3\xdd\x8d\x0e\x5f\x4f\x27\x3e\xb7\x61\x97\xb2\x49\xb9\xaf\x90\x20\x92\x27\x32\x2a\x6b\xf4\xf3\x0d\x1e\x82\x20\xe8\x59\x28\x09\x4c\x46\x4c\x33\xcb\x7a\x76\x95\x41\x47\x9f\x14\x78\x03\xde\x62\x6c\x54\x30\xb1\x51\x0a\xdb\x8b\x89\x58\x11\xbb\x22\xac\x08\x9a\xe5\x6c\x71\xbf\x3d\xb8\x39\x92\xfa\x7f\x86\x1a\xd3\x54\x1e\xa7\xee\xcc\x7e\x08\x9e\x01\x10\x01\x18\x80\x80\x10\x22\x02\x00\x0c\x28\x57\x30\x06\x82\xf4\x03\x03\x4f\x52\x43\x18",
|
|
b"\x4f\x52\x43\x11\x00\x00\x0a\x06\x12\x04\x08\x0f\x50\x00\x2b\x00\x00\x0a\x13\x0a\x03\x00\x00\x00\x12\x0c\x08\x0f\x12\x06\x08\x00\x10\x00\x18\x00\x50\x00\x30\x00\x00\xe3\x12\xe7\x62\x65\x00\x01\x21\x3e\x0e\x7e\x25\x0e\x2e\x46\x43\x21\x46\x4b\x09\xad\x00\x06\x00\x33\x00\x00\x0a\x17\x0a\x03\x00\x00\x00\x12\x10\x08\x0f\x22\x0a\x0a\x02\x41\x4d\x12\x02\x41\x4d\x18\x3c\x50\x00\x3a\x00\x00\xe3\x92\xe1\x62\x65\x00\x01\x21\x61\x0e\x7e\x23\x5e\x2e\x46\x03\x21\x66\x03\x3d\x53\x29\x66\x73\x3d\xd3\x00\x06\x00\x2b\x00\x00\x0a\x13\x0a\x03\x00\x00\x00\x12\x0c\x08\x0f\x12\x06\x08\x02\x10\x02\x18\x1e\x50\x00\x05\x00\x00\x0c\x00\x2b\x00\x00\x31\x32\x33\x34\x35\x36\x37\x38\x39\x31\x30\x31\x31\x31\x32\x31\x33\x31\x34\x31\x35\x09\x00\x00\x06\x01\x03\x02\x09\x00\x00\xc0\x0e\x00\x00\x07\x00\x00\x42\x00\x80\x05\x00\x00\x41\x4d\x0a\x00\x00\xe3\xe2\x42\x01\x00\x09\x00\x00\xc0\x0e\x02\x00\x05\x00\x00\x0c\x01\x94\x00\x00\x2d\xca\xc1\x0e\x80\x30\x08\x03\xd0\xc1\x60\x2e\xf3\x62\x76\x6a\xe2\x0e\xfe\xff\x57\x5a\x3b\x0f\xe4\x51\xe8\x68\xbd\x5d\x05\xe7\xf8\x34\x40\x3a\x6e\x59\xb1\x64\xe0\x91\xa9\xbf\xb1\x97\xd2\x95\x9d\x1e\xca\x55\x3a\x6d\xb4\xd2\xdd\x0b\x74\x9a\x74\xf7\x12\x39\xbd\x97\x7f\x7c\x06\xbb\xa6\x8d\x97\x17\xb4\x00\x00\xe3\x4a\xe6\x62\xe1\xe0\x0f\x60\xe0\xe2\xe3\xe0\x17\x62\xe3\x60\x10\x60\x90\x60\x08\x60\x88\x60\xe5\x12\xe0\xe0\x57\xe2\xe0\x62\x34\x14\x62\xb4\x94\xd0\x02\x8a\xc8\x73\x09\x01\x45\xb8\xb8\x98\x1c\x7d\x85\x80\x58\xc2\x06\x28\x26\xc4\x25\xca\xc1\x6f\xc4\xcb\xc5\x68\x20\xc4\x6c\xa0\x67\x2a\xc5\x6c\xae\x67\x0a\x14\xe6\x87\x1a\xc6\x24\xc0\x24\x21\x07\x32\x0c\x00\x4a\x01\x00\xe3\x60\x16\x58\xc3\x24\xc5\xcd\xc1\x2c\x30\x89\x51\xc2\x4b\xc1\x57\x83\x5f\x49\x83\x83\x47\x88\x95\x91\x89\x99\x85\x55\x8a\x3d\x29\x27\x3f\x39\xdb\x2f\x5f\x8a\x29\x33\x45\x8a\xa5\x2c\x31\xc7\x10\x4c\x1a\x81\x49\x63\x25\x26\x0e\x46\x20\x66\x07\x63\x36\x0e\x3e\x0d\x26\x03\x10\x9f\xd1\x80\xdf\x8a\x85\x83\x3f\x80\xc1\x8a\x8f\x83\x5f\x88\x8d\x83\x41\x80\x41\x82\x21\x80\x21\x82\xd5\x4a\x80\x83\x5f\x89\x83\x8b\xd1\x50\x88\xd1\x52\x42\x0b\x28\x22\x6f\x25\x04\x14\xe1\xe2\x62\x72\xf4\x15\x02\x62\x09\x1b\xa0\x98\x90\x95\x28\x07\xbf\x11\x2f\x17\xa3\x81\x10\xb3\x81\x9e\xa9\x14\xb3\xb9\x9e\x29\x50\x98\x1f\x6a\x18\x93\x00\x93\x84\x1c\xc8\x30\x87\x09\x7e\x1e\x0c\x00\x08\xa8\x01\x10\x01\x18\x80\x80\x10\x22\x02\x00\x0c\x28\x5d\x30\x06\x82\xf4\x03\x03\x4f\x52\x43\x18",
|
|
b"\x4f\x52\x43\x11\x00\x00\x0a\x06\x12\x04\x08\x01\x50\x00\x2b\x00\x00\x0a\x13\x0a\x03\x00\x00\x00\x12\x0c\x08\x01\x12\x06\x08\x00\x10\x00\x18\x00\x50\x00\x30\x00\x00\xe3\x12\xe7\x62\x65\x00\x01\x21\x3e\x0e\x46\x25\x0e\x2e\x46\x03\x21\x46\x03\x09\xa6\x00\x06\x00\x32\x00\x00\xe3\x92\xe4\x62\x65\x00\x01\x21\x01\x0e\x46\x25\x2e\x2e\x26\x47\x5f\x21\x20\x96\x60\x09\x60\x00\x00\x36\x00\x00\xe3\x92\xe1\x62\x65\x00\x01\x21\x61\x0e\x46\x23\x5e\x2e\x46\x03\x21\x66\x03\x3d\x53\x29\x10\x11\xc0\x00\x00\x2b\x00\x00\x0a\x13\x0a\x03\x00\x00\x00\x12\x0c\x08\x01\x12\x06\x08\x02\x10\x02\x18\x02\x50\x00\x05\x00\x00\xff\x00\x03\x00\x00\x30\x07\x00\x00\x40\x00\x80\x05\x00\x00\x41\x4d\x07\x00\x00\x42\x00\x80\x03\x00\x00\x0a\x07\x00\x00\x42\x00\x80\x05\x00\x00\xff\x01\x88\x00\x00\x4d\xca\xc1\x0a\x80\x30\x0c\x03\xd0\x2e\x6b\xcb\x98\x17\xf1\x14\x50\xfc\xff\xcf\xb4\x66\x1e\x3c\x84\x47\x9a\xce\x1c\xb9\x1b\xb7\xf9\xda\x48\x09\x9e\xb2\xf3\x92\xce\x5b\x86\xf6\x56\x7f\x21\x41\x2f\x51\xa6\x7a\xd7\x1d\xe5\xea\xae\x3d\xca\xd5\x83\x71\x60\xd8\x17\xfc\x62\x0f\xa8\x00\x00\xe3\x4a\xe6\x62\xe1\x60\x0c\x60\xe0\xe2\xe3\x60\x14\x62\xe3\x60\x10\x60\x90\x60\x08\x60\x88\x60\xe5\x12\xe0\x60\x54\xe2\xe0\x62\x34\x10\x62\x34\x90\x60\x02\x8a\x70\x71\x09\x01\x45\xb8\xb8\x98\x1c\x7d\x85\x80\x58\x82\x05\x28\xc6\xcd\x25\xca\xc1\x68\xc4\x0b\x52\xc5\x6c\xa0\x67\x2a\x05\x22\xc0\x4a\x21\x86\x31\x09\x30\x81\xb5\xb2\x02\x00\x36\x01\x00\x25\x8c\xbd\x0a\xc2\x30\x14\x85\x73\x6f\x92\xf6\x92\x6a\x09\x01\x21\x64\x92\x4e\x75\x91\x58\x71\xc9\x64\x27\x5d\x2c\x1d\x5d\xfd\x59\xc4\x42\x37\x5f\xc0\x17\xe8\x23\x9b\xc6\xe1\x3b\x70\x0f\xdf\xb9\xc4\xf5\x17\x5d\x41\x5c\x4f\x60\x37\xeb\x53\x0d\x55\x4d\x0b\x23\x01\xb9\x90\x2e\xbf\x0f\xe3\xe3\xdd\x8d\x0e\x5f\x4f\x27\x3e\xb7\x61\x97\xb2\x49\xb9\xaf\x90\x20\x92\x27\x32\x2a\x6b\xf4\xf3\x0d\x1e\x82\x20\xe8\x59\x28\x09\x4c\x46\x4c\x33\xcb\x7a\x76\x95\x41\x47\x9f\x14\x78\x03\xde\x62\x6c\x54\x30\xb1\x51\x0a\xdb\x8b\x89\x58\x11\xbb\x22\xac\x08\x9a\xe5\x6c\x71\xbf\x3d\xb8\x39\x92\xfa\x7f\x86\x1a\xd3\x54\x1e\xa7\xee\xcc\x7e\x08\x9e\x01\x10\x01\x18\x80\x80\x10\x22\x02\x00\x0c\x28\x57\x30\x06\x82\xf4\x03\x03\x4f\x52\x43\x18",
|
|
# ''
|
|
# On empty message exception: IOError: File size too small, Stack trace (when copying this message, always include the lines below):
|
|
# /src/Processors/Formats/Impl/ORCBlockInputFormat.cpp:36: DB::ORCBlockInputFormat::generate() @ 0x1df282a6 in /usr/bin/clickhouse
|
|
# /src/Processors/ISource.cpp:48: DB::ISource::work() @ 0x1dd79737 in /usr/bin/clickhouse
|
|
],
|
|
},
|
|
"CapnProto": {
|
|
"data_sample": [
|
|
b"\x00\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x02\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x3f\x01\x00\x00\x00\x1a\x00\x00\x00\x41\x4d\x00\x00\x00\x00\x00\x00",
|
|
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|
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b"\x00\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x02\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x3f\x01\x00\x00\x00\x1a\x00\x00\x00\x41\x4d\x00\x00\x00\x00\x00\x00",
|
|
# ''
|
|
# On empty message exception: Cannot read all data. Bytes read: 0. Bytes expected: 4.
|
|
# /src/IO/ReadBuffer.h:157: DB::ReadBuffer::readStrict(char*, unsigned long) @ 0x15c6894d in /usr/bin/clickhouse
|
|
# /src/Processors/Formats/Impl/CapnProtoRowInputFormat.cpp:212: DB::CapnProtoRowInputFormat::readMessage() @ 0x1ded1cab in /usr/bin/clickhouse
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|
# /src/Processors/Formats/Impl/CapnProtoRowInputFormat.cpp:241: DB::CapnProtoRowInputFormat::readRow(std::__1::vector<COW<DB::IColumn>::mutable_ptr<DB::IColumn>, std::__1::allocator<COW<DB::IColumn>::mutable_ptr<DB::IColumn> > >&, DB::RowReadExtension&) @ 0x1ded205d in /usr/bin/clickhouse
|
|
],
|
|
"extra_settings": {"kafka_schema": "test:TestRecordStruct"},
|
|
},
|
|
"Parquet": {
|
|
"data_sample": [
|
|
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|
|
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|
|
],
|
|
},
|
|
"AvroConfluent": {
|
|
"data_sample": [
|
|
avro_confluent_message(
|
|
schema_registry_client,
|
|
{"id": 0, "blockNo": 0, "val1": str("AM"), "val2": 0.5, "val3": 1},
|
|
),
|
|
b"".join(
|
|
[
|
|
avro_confluent_message(
|
|
schema_registry_client,
|
|
{
|
|
"id": id,
|
|
"blockNo": 0,
|
|
"val1": str("AM"),
|
|
"val2": 0.5,
|
|
"val3": 1,
|
|
},
|
|
)
|
|
for id in range(1, 16)
|
|
]
|
|
),
|
|
avro_confluent_message(
|
|
schema_registry_client,
|
|
{"id": 0, "blockNo": 0, "val1": str("AM"), "val2": 0.5, "val3": 1},
|
|
),
|
|
],
|
|
"extra_settings": {
|
|
"format_avro_schema_registry_url": "http://{}:{}".format(
|
|
kafka_cluster.schema_registry_host,
|
|
kafka_cluster.schema_registry_port,
|
|
)
|
|
},
|
|
"supports_empty_value": True,
|
|
},
|
|
"Avro": {
|
|
# It seems impossible to send more than one avro file per a message
|
|
# because of nature of Avro: blocks go one after another
|
|
"data_sample": [
|
|
avro_message(
|
|
{"id": 0, "blockNo": 0, "val1": str("AM"), "val2": 0.5, "val3": 1}
|
|
),
|
|
avro_message(
|
|
[
|
|
{
|
|
"id": id,
|
|
"blockNo": 0,
|
|
"val1": str("AM"),
|
|
"val2": 0.5,
|
|
"val3": 1,
|
|
}
|
|
for id in range(1, 16)
|
|
]
|
|
),
|
|
avro_message(
|
|
{"id": 0, "blockNo": 0, "val1": str("AM"), "val2": 0.5, "val3": 1}
|
|
),
|
|
],
|
|
"supports_empty_value": False,
|
|
},
|
|
"Arrow": {
|
|
"data_sample": [
|
|
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},
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"ArrowStream": {
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"data_sample": [
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|
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b"\xff\xff\xff\xff\x48\x01\x00\x00\x10\x00\x00\x00\x00\x00\x0a\x00\x0c\x00\x06\x00\x05\x00\x08\x00\x0a\x00\x00\x00\x00\x01\x03\x00\x0c\x00\x00\x00\x08\x00\x08\x00\x00\x00\x04\x00\x08\x00\x00\x00\x04\x00\x00\x00\x05\x00\x00\x00\xe4\x00\x00\x00\x9c\x00\x00\x00\x6c\x00\x00\x00\x34\x00\x00\x00\x04\x00\x00\x00\x40\xff\xff\xff\x00\x00\x00\x02\x18\x00\x00\x00\x0c\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x72\xff\xff\xff\x08\x00\x00\x00\x04\x00\x00\x00\x76\x61\x6c\x33\x00\x00\x00\x00\x6c\xff\xff\xff\x00\x00\x00\x03\x20\x00\x00\x00\x14\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x00\x00\x06\x00\x08\x00\x06\x00\x06\x00\x00\x00\x00\x00\x01\x00\x04\x00\x00\x00\x76\x61\x6c\x32\x00\x00\x00\x00\xa0\xff\xff\xff\x00\x00\x00\x05\x18\x00\x00\x00\x10\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x04\x00\x04\x00\x04\x00\x00\x00\x04\x00\x00\x00\x76\x61\x6c\x31\x00\x00\x00\x00\xcc\xff\xff\xff\x00\x00\x00\x02\x20\x00\x00\x00\x14\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x00\x00\x06\x00\x08\x00\x04\x00\x06\x00\x00\x00\x10\x00\x00\x00\x07\x00\x00\x00\x62\x6c\x6f\x63\x6b\x4e\x6f\x00\x10\x00\x14\x00\x08\x00\x00\x00\x07\x00\x0c\x00\x00\x00\x10\x00\x10\x00\x00\x00\x00\x00\x00\x02\x24\x00\x00\x00\x14\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x08\x00\x0c\x00\x08\x00\x07\x00\x08\x00\x00\x00\x00\x00\x00\x01\x40\x00\x00\x00\x02\x00\x00\x00\x69\x64\x00\x00\xff\xff\xff\xff\x58\x01\x00\x00\x14\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x16\x00\x06\x00\x05\x00\x08\x00\x0c\x00\x0c\x00\x00\x00\x00\x03\x03\x00\x18\x00\x00\x00\x30\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0a\x00\x18\x00\x0c\x00\x04\x00\x08\x00\x0a\x00\x00\x00\xcc\x00\x00\x00\x10\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x0b\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x10\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x10\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x18\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x20\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x20\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x28\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x28\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x41\x4d\x00\x00\x00\x00\x00\x00\x00\x00\x00\x3f\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\xff\xff\xff\xff\x00\x00\x00\x00",
|
|
],
|
|
},
|
|
}
|
|
|
|
topic_postfix = str(hash(create_query_generator))
|
|
for format_name, format_opts in list(all_formats.items()):
|
|
logging.debug(f"Set up {format_name}")
|
|
topic_name = f"format_tests_{format_name}-{topic_postfix}"
|
|
data_sample = format_opts["data_sample"]
|
|
data_prefix = []
|
|
# prepend empty value when supported
|
|
if format_opts.get("supports_empty_value", False):
|
|
data_prefix = data_prefix + [""]
|
|
kafka_produce(kafka_cluster, topic_name, data_prefix + data_sample)
|
|
|
|
extra_settings = format_opts.get("extra_settings") or {}
|
|
extra_settings["kafka_flush_interval_ms"] = 1000
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE IF EXISTS test.kafka_{format_name};
|
|
|
|
{create_query};
|
|
|
|
DROP TABLE IF EXISTS test.kafka_{format_name}_mv;
|
|
|
|
CREATE MATERIALIZED VIEW test.kafka_{format_name}_mv ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT *, _topic, _partition, _offset FROM test.kafka_{format_name};
|
|
""".format(
|
|
topic_name=topic_name,
|
|
format_name=format_name,
|
|
create_query=create_query_generator(
|
|
f"kafka_{format_name}",
|
|
"id Int64, blockNo UInt16, val1 String, val2 Float32, val3 UInt8",
|
|
topic_list=f"{topic_name}",
|
|
consumer_group=f"{topic_name}_group",
|
|
format=format_name,
|
|
settings=extra_settings,
|
|
),
|
|
)
|
|
)
|
|
raw_expected = """\
|
|
0 0 AM 0.5 1 {topic_name} 0 {offset_0}
|
|
1 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
2 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
3 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
4 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
5 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
6 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
7 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
8 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
9 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
10 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
11 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
12 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
13 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
14 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
15 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
0 0 AM 0.5 1 {topic_name} 0 {offset_2}
|
|
"""
|
|
|
|
expected_rows_count = raw_expected.count("\n")
|
|
result_checker = lambda res: res.count("\n") == expected_rows_count
|
|
res = instance.query_with_retry(
|
|
f"SELECT * FROM test.kafka_{list(all_formats.keys())[-1]}_mv;",
|
|
retry_count=30,
|
|
sleep_time=1,
|
|
check_callback=result_checker,
|
|
)
|
|
assert result_checker(res)
|
|
|
|
for format_name, format_opts in list(all_formats.items()):
|
|
logging.debug(("Checking {}".format(format_name)))
|
|
topic_name = f"format_tests_{format_name}-{topic_postfix}"
|
|
# shift offsets by 1 if format supports empty value
|
|
offsets = (
|
|
[1, 2, 3] if format_opts.get("supports_empty_value", False) else [0, 1, 2]
|
|
)
|
|
result = instance.query_with_retry(
|
|
"SELECT * FROM test.kafka_{format_name}_mv;".format(
|
|
format_name=format_name
|
|
),
|
|
check_callback=lambda x: x.count("\n") == raw_expected.count("\n"),
|
|
)
|
|
expected = raw_expected.format(
|
|
topic_name=topic_name,
|
|
offset_0=offsets[0],
|
|
offset_1=offsets[1],
|
|
offset_2=offsets[2],
|
|
)
|
|
assert TSV(result) == TSV(expected), "Proper result for format: {}".format(
|
|
format_name
|
|
)
|
|
kafka_delete_topic(get_admin_client(kafka_cluster), topic_name)
|
|
|
|
|
|
# Since everything is async and shaky when receiving messages from Kafka,
|
|
# we may want to try and check results multiple times in a loop.
|
|
def kafka_check_result(result, check=False, ref_file="test_kafka_json.reference"):
|
|
fpath = p.join(p.dirname(__file__), ref_file)
|
|
with open(fpath) as reference:
|
|
if check:
|
|
assert TSV(result) == TSV(reference)
|
|
else:
|
|
return TSV(result) == TSV(reference)
|
|
|
|
|
|
def decode_avro(message):
|
|
b = io.BytesIO(message)
|
|
ret = avro.datafile.DataFileReader(b, avro.io.DatumReader())
|
|
|
|
output = io.StringIO()
|
|
for record in ret:
|
|
print(record, file=output)
|
|
return output.getvalue()
|
|
|
|
|
|
# https://stackoverflow.com/a/57692111/1555175
|
|
def describe_consumer_group(kafka_cluster, name):
|
|
client = BrokerConnection("localhost", kafka_cluster.kafka_port, socket.AF_INET)
|
|
client.connect_blocking()
|
|
|
|
list_members_in_groups = DescribeGroupsRequest_v1(groups=[name])
|
|
future = client.send(list_members_in_groups)
|
|
while not future.is_done:
|
|
for resp, f in client.recv():
|
|
f.success(resp)
|
|
|
|
(
|
|
error_code,
|
|
group_id,
|
|
state,
|
|
protocol_type,
|
|
protocol,
|
|
members,
|
|
) = future.value.groups[0]
|
|
|
|
res = []
|
|
for member in members:
|
|
(member_id, client_id, client_host, member_metadata, member_assignment) = member
|
|
member_info = {}
|
|
member_info["member_id"] = member_id
|
|
member_info["client_id"] = client_id
|
|
member_info["client_host"] = client_host
|
|
member_topics_assignment = []
|
|
for topic, partitions in MemberAssignment.decode(member_assignment).assignment:
|
|
member_topics_assignment.append({"topic": topic, "partitions": partitions})
|
|
member_info["assignment"] = member_topics_assignment
|
|
res.append(member_info)
|
|
return res
|
|
|
|
|
|
# Fixtures
|
|
|
|
|
|
@pytest.fixture(scope="module")
|
|
def kafka_cluster():
|
|
try:
|
|
cluster.start()
|
|
kafka_id = instance.cluster.kafka_docker_id
|
|
print(("kafka_id is {}".format(kafka_id)))
|
|
yield cluster
|
|
finally:
|
|
cluster.shutdown()
|
|
|
|
|
|
@pytest.fixture(autouse=True)
|
|
def kafka_setup_teardown():
|
|
instance.query("DROP DATABASE IF EXISTS test SYNC; CREATE DATABASE test;")
|
|
admin_client = get_admin_client(cluster)
|
|
|
|
def get_topics_to_delete():
|
|
return [t for t in admin_client.list_topics() if not t.startswith("_")]
|
|
|
|
topics = get_topics_to_delete()
|
|
logging.debug(f"Deleting topics: {topics}")
|
|
result = admin_client.delete_topics(topics)
|
|
for topic, error in result.topic_error_codes:
|
|
if error != 0:
|
|
logging.warning(f"Received error {error} while deleting topic {topic}")
|
|
else:
|
|
logging.info(f"Deleted topic {topic}")
|
|
|
|
retries = 0
|
|
topics = get_topics_to_delete()
|
|
while len(topics) != 0:
|
|
logging.info(f"Existing topics: {topics}")
|
|
if retries >= 5:
|
|
raise Exception(f"Failed to delete topics {topics}")
|
|
retries += 1
|
|
time.sleep(0.5)
|
|
yield # run test
|
|
|
|
|
|
# Tests
|
|
def test_kafka_issue11308(kafka_cluster):
|
|
# Check that matview does respect Kafka SETTINGS
|
|
kafka_produce(
|
|
kafka_cluster,
|
|
"issue11308",
|
|
[
|
|
'{"t": 123, "e": {"x": "woof"} }',
|
|
'{"t": 123, "e": {"x": "woof"} }',
|
|
'{"t": 124, "e": {"x": "test"} }',
|
|
],
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.persistent_kafka (
|
|
time UInt64,
|
|
some_string String
|
|
)
|
|
ENGINE = MergeTree()
|
|
ORDER BY time;
|
|
|
|
CREATE TABLE test.kafka (t UInt64, `e.x` String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'issue11308',
|
|
kafka_group_name = 'issue11308',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_row_delimiter = '\\n',
|
|
kafka_flush_interval_ms=1000,
|
|
input_format_import_nested_json = 1;
|
|
|
|
CREATE MATERIALIZED VIEW test.persistent_kafka_mv TO test.persistent_kafka AS
|
|
SELECT
|
|
`t` AS `time`,
|
|
`e.x` AS `some_string`
|
|
FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
while int(instance.query("SELECT count() FROM test.persistent_kafka")) < 3:
|
|
time.sleep(1)
|
|
|
|
result = instance.query("SELECT * FROM test.persistent_kafka ORDER BY time;")
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.persistent_kafka;
|
|
DROP TABLE test.persistent_kafka_mv;
|
|
"""
|
|
)
|
|
|
|
expected = """\
|
|
123 woof
|
|
123 woof
|
|
124 test
|
|
"""
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
def test_kafka_issue4116(kafka_cluster):
|
|
# Check that format_csv_delimiter parameter works now - as part of all available format settings.
|
|
kafka_produce(
|
|
kafka_cluster,
|
|
"issue4116",
|
|
["1|foo", "2|bar", "42|answer", "100|multi\n101|row\n103|message"],
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (a UInt64, b String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'issue4116',
|
|
kafka_group_name = 'issue4116',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'CSV',
|
|
kafka_row_delimiter = '\\n',
|
|
format_csv_delimiter = '|';
|
|
"""
|
|
)
|
|
|
|
result = instance.query("SELECT * FROM test.kafka ORDER BY a;")
|
|
|
|
expected = """\
|
|
1 foo
|
|
2 bar
|
|
42 answer
|
|
100 multi
|
|
101 row
|
|
103 message
|
|
"""
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
def test_kafka_consumer_hang(kafka_cluster):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
topic_name = "consumer_hang"
|
|
kafka_create_topic(admin_client, topic_name, num_partitions=8)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic_name}',
|
|
kafka_group_name = '{topic_name}',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_num_consumers = 8;
|
|
CREATE TABLE test.view (key UInt64, value UInt64) ENGINE = Memory();
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.wait_for_log_line("kafka.*Stalled", repetitions=20)
|
|
|
|
# This should trigger heartbeat fail,
|
|
# which will trigger REBALANCE_IN_PROGRESS,
|
|
# and which can lead to consumer hang.
|
|
kafka_cluster.pause_container("kafka1")
|
|
instance.wait_for_log_line("heartbeat error")
|
|
kafka_cluster.unpause_container("kafka1")
|
|
|
|
# logging.debug("Attempt to drop")
|
|
instance.query("DROP TABLE test.kafka")
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
# original problem appearance was a sequence of the following messages in librdkafka logs:
|
|
# BROKERFAIL -> |ASSIGN| -> REBALANCE_IN_PROGRESS -> "waiting for rebalance_cb" (repeated forever)
|
|
# so it was waiting forever while the application will execute queued rebalance callback
|
|
|
|
# from a user perspective: we expect no hanging 'drop' queries
|
|
# 'dr'||'op' to avoid self matching
|
|
assert (
|
|
int(
|
|
instance.query(
|
|
"select count() from system.processes where position(lower(query),'dr'||'op')>0"
|
|
)
|
|
)
|
|
== 0
|
|
)
|
|
|
|
# cleanup unread messages so kafka will not wait reading consumers to delete topic
|
|
instance.query(
|
|
f"""
|
|
CREATE TABLE test.kafka (key UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic_name}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = '{topic_name}',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_num_consumers = 8;
|
|
"""
|
|
)
|
|
|
|
num_read = int(instance.query("SELECT count() FROM test.kafka"))
|
|
logging.debug(f"read {num_read} from {topic_name} before delete")
|
|
instance.query("DROP TABLE test.kafka")
|
|
kafka_delete_topic(admin_client, topic_name)
|
|
|
|
|
|
def test_kafka_consumer_hang2(kafka_cluster):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
topic_name = "consumer_hang2"
|
|
kafka_create_topic(admin_client, topic_name)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.kafka2;
|
|
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'consumer_hang2',
|
|
kafka_group_name = 'consumer_hang2',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONEachRow';
|
|
|
|
CREATE TABLE test.kafka2 (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'consumer_hang2',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = 'consumer_hang2',
|
|
kafka_format = 'JSONEachRow';
|
|
"""
|
|
)
|
|
|
|
# first consumer subscribe the topic, try to poll some data, and go to rest
|
|
instance.query("SELECT * FROM test.kafka")
|
|
|
|
# second consumer do the same leading to rebalance in the first
|
|
# consumer, try to poll some data
|
|
instance.query("SELECT * FROM test.kafka2")
|
|
|
|
# echo 'SELECT * FROM test.kafka; SELECT * FROM test.kafka2; DROP TABLE test.kafka;' | clickhouse client -mn &
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
|
|
# first consumer has pending rebalance callback unprocessed (no poll after select)
|
|
# one of those queries was failing because of
|
|
# https://github.com/edenhill/librdkafka/issues/2077
|
|
# https://github.com/edenhill/librdkafka/issues/2898
|
|
instance.query("DROP TABLE test.kafka")
|
|
instance.query("DROP TABLE test.kafka2")
|
|
|
|
# from a user perspective: we expect no hanging 'drop' queries
|
|
# 'dr'||'op' to avoid self matching
|
|
assert (
|
|
int(
|
|
instance.query(
|
|
"select count() from system.processes where position(lower(query),'dr'||'op')>0"
|
|
)
|
|
)
|
|
== 0
|
|
)
|
|
kafka_delete_topic(admin_client, topic_name)
|
|
|
|
|
|
# sequential read from different consumers leads to breaking lot of kafka invariants
|
|
# (first consumer will get all partitions initially, and may have problems in doing polls every 60 sec)
|
|
def test_kafka_read_consumers_in_parallel(kafka_cluster):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
topic_name = "read_consumers_in_parallel"
|
|
kafka_create_topic(admin_client, topic_name, num_partitions=8)
|
|
|
|
cancel = threading.Event()
|
|
|
|
def produce():
|
|
while not cancel.is_set():
|
|
messages = []
|
|
for _ in range(100):
|
|
messages.append(json.dumps({"key": 0, "value": 0}))
|
|
kafka_produce(kafka_cluster, "read_consumers_in_parallel", messages)
|
|
time.sleep(1)
|
|
|
|
kafka_thread = threading.Thread(target=produce)
|
|
kafka_thread.start()
|
|
|
|
# when we have more than 1 consumer in a single table,
|
|
# and kafka_thread_per_consumer=0
|
|
# all the consumers should be read in parallel, not in sequence.
|
|
# then reading in parallel 8 consumers with 1 seconds kafka_poll_timeout_ms and less than 1 sec limit
|
|
# we should have exactly 1 poll per consumer (i.e. 8 polls) every 1 seconds (from different threads)
|
|
# in case parallel consuming is not working we will have only 1 poll every 1 seconds (from the same thread).
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic_name}',
|
|
kafka_group_name = '{topic_name}',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_num_consumers = 8,
|
|
kafka_thread_per_consumer = 0,
|
|
kafka_poll_timeout_ms = 1000,
|
|
kafka_flush_interval_ms = 999;
|
|
CREATE TABLE test.view (key UInt64, value UInt64) ENGINE = Memory();
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.wait_for_log_line(
|
|
"kafka.*Polled batch of [0-9]+.*read_consumers_in_parallel",
|
|
repetitions=64,
|
|
look_behind_lines=100,
|
|
timeout=30, # we should get 64 polls in ~8 seconds, but when read sequentially it will take more than 64 sec
|
|
)
|
|
|
|
cancel.set()
|
|
kafka_thread.join()
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
DROP TABLE test.kafka;
|
|
"""
|
|
)
|
|
kafka_delete_topic(admin_client, topic_name)
|
|
|
|
|
|
def test_kafka_csv_with_delimiter(kafka_cluster):
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append("{i}, {i}".format(i=i))
|
|
kafka_produce(kafka_cluster, "csv", messages)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'csv',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = 'csv',
|
|
kafka_format = 'CSV';
|
|
"""
|
|
)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
def test_kafka_tsv_with_delimiter(kafka_cluster):
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append("{i}\t{i}".format(i=i))
|
|
kafka_produce(kafka_cluster, "tsv", messages)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'tsv',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = 'tsv',
|
|
kafka_format = 'TSV';
|
|
"""
|
|
)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
def test_kafka_select_empty(kafka_cluster):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
topic_name = "empty"
|
|
kafka_create_topic(admin_client, topic_name)
|
|
|
|
instance.query(
|
|
f"""
|
|
CREATE TABLE test.kafka (key UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic_name}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = '{topic_name}',
|
|
kafka_format = 'TSV',
|
|
kafka_row_delimiter = '\\n';
|
|
"""
|
|
)
|
|
|
|
assert int(instance.query("SELECT count() FROM test.kafka")) == 0
|
|
kafka_delete_topic(admin_client, topic_name)
|
|
|
|
|
|
def test_kafka_json_without_delimiter(kafka_cluster):
|
|
messages = ""
|
|
for i in range(25):
|
|
messages += json.dumps({"key": i, "value": i}) + "\n"
|
|
kafka_produce(kafka_cluster, "json", [messages])
|
|
|
|
messages = ""
|
|
for i in range(25, 50):
|
|
messages += json.dumps({"key": i, "value": i}) + "\n"
|
|
kafka_produce(kafka_cluster, "json", [messages])
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'json',
|
|
kafka_group_name = 'json',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONEachRow';
|
|
"""
|
|
)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
def test_kafka_protobuf(kafka_cluster):
|
|
kafka_produce_protobuf_messages(kafka_cluster, "pb", 0, 20)
|
|
kafka_produce_protobuf_messages(kafka_cluster, "pb", 20, 1)
|
|
kafka_produce_protobuf_messages(kafka_cluster, "pb", 21, 29)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'pb',
|
|
kafka_group_name = 'pb',
|
|
kafka_format = 'Protobuf',
|
|
kafka_commit_on_select = 1,
|
|
kafka_schema = 'kafka.proto:KeyValuePair';
|
|
"""
|
|
)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
def test_kafka_string_field_on_first_position_in_protobuf(kafka_cluster):
|
|
# https://github.com/ClickHouse/ClickHouse/issues/12615
|
|
kafka_produce_protobuf_social(
|
|
kafka_cluster, "string_field_on_first_position_in_protobuf", 0, 20
|
|
)
|
|
kafka_produce_protobuf_social(
|
|
kafka_cluster, "string_field_on_first_position_in_protobuf", 20, 1
|
|
)
|
|
kafka_produce_protobuf_social(
|
|
kafka_cluster, "string_field_on_first_position_in_protobuf", 21, 29
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (
|
|
username String,
|
|
timestamp Int32
|
|
) ENGINE = Kafka()
|
|
SETTINGS
|
|
kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'string_field_on_first_position_in_protobuf',
|
|
kafka_group_name = 'string_field_on_first_position_in_protobuf',
|
|
kafka_format = 'Protobuf',
|
|
kafka_commit_on_select = 1,
|
|
kafka_schema = 'social:User';
|
|
"""
|
|
)
|
|
|
|
result = instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
expected = """\
|
|
John Doe 0 1000000
|
|
John Doe 1 1000001
|
|
John Doe 2 1000002
|
|
John Doe 3 1000003
|
|
John Doe 4 1000004
|
|
John Doe 5 1000005
|
|
John Doe 6 1000006
|
|
John Doe 7 1000007
|
|
John Doe 8 1000008
|
|
John Doe 9 1000009
|
|
John Doe 10 1000010
|
|
John Doe 11 1000011
|
|
John Doe 12 1000012
|
|
John Doe 13 1000013
|
|
John Doe 14 1000014
|
|
John Doe 15 1000015
|
|
John Doe 16 1000016
|
|
John Doe 17 1000017
|
|
John Doe 18 1000018
|
|
John Doe 19 1000019
|
|
John Doe 20 1000020
|
|
John Doe 21 1000021
|
|
John Doe 22 1000022
|
|
John Doe 23 1000023
|
|
John Doe 24 1000024
|
|
John Doe 25 1000025
|
|
John Doe 26 1000026
|
|
John Doe 27 1000027
|
|
John Doe 28 1000028
|
|
John Doe 29 1000029
|
|
John Doe 30 1000030
|
|
John Doe 31 1000031
|
|
John Doe 32 1000032
|
|
John Doe 33 1000033
|
|
John Doe 34 1000034
|
|
John Doe 35 1000035
|
|
John Doe 36 1000036
|
|
John Doe 37 1000037
|
|
John Doe 38 1000038
|
|
John Doe 39 1000039
|
|
John Doe 40 1000040
|
|
John Doe 41 1000041
|
|
John Doe 42 1000042
|
|
John Doe 43 1000043
|
|
John Doe 44 1000044
|
|
John Doe 45 1000045
|
|
John Doe 46 1000046
|
|
John Doe 47 1000047
|
|
John Doe 48 1000048
|
|
John Doe 49 1000049
|
|
"""
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
def test_kafka_protobuf_no_delimiter(kafka_cluster):
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'pb_no_delimiter',
|
|
kafka_group_name = 'pb_no_delimiter',
|
|
kafka_format = 'ProtobufSingle',
|
|
kafka_commit_on_select = 1,
|
|
kafka_schema = 'kafka.proto:KeyValuePair';
|
|
"""
|
|
)
|
|
|
|
kafka_produce_protobuf_messages_no_delimiters(
|
|
kafka_cluster, "pb_no_delimiter", 0, 20
|
|
)
|
|
kafka_produce_protobuf_messages_no_delimiters(
|
|
kafka_cluster, "pb_no_delimiter", 20, 1
|
|
)
|
|
kafka_produce_protobuf_messages_no_delimiters(
|
|
kafka_cluster, "pb_no_delimiter", 21, 29
|
|
)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka_writer (key UInt64, value String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'pb_no_delimiter',
|
|
kafka_group_name = 'pb_no_delimiter',
|
|
kafka_format = 'ProtobufSingle',
|
|
kafka_commit_on_select = 1,
|
|
kafka_schema = 'kafka.proto:KeyValuePair';
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"INSERT INTO test.kafka_writer VALUES (13,'Friday'),(42,'Answer to the Ultimate Question of Life, the Universe, and Everything'), (110, 'just a number')"
|
|
)
|
|
|
|
time.sleep(1)
|
|
|
|
result = instance.query("SELECT * FROM test.kafka ORDER BY key", ignore_error=True)
|
|
|
|
expected = """\
|
|
13 Friday
|
|
42 Answer to the Ultimate Question of Life, the Universe, and Everything
|
|
110 just a number
|
|
"""
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_materialized_view(kafka_cluster, create_query_generator):
|
|
topic_name = "mv"
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
|
|
{create_query_generator("kafka", "key UInt64, value UInt64", topic_list=topic_name, consumer_group="mv")};
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
result = instance.query_with_retry(
|
|
"SELECT * FROM test.view", check_callback=kafka_check_result
|
|
)
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
DROP TABLE test.kafka;
|
|
"""
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, log_line",
|
|
[
|
|
(
|
|
generate_new_create_table_query,
|
|
r"kafka.*Saved offset [0-9]+ for topic-partition \[recreate_kafka_table:[0-9]+",
|
|
),
|
|
(
|
|
generate_old_create_table_query,
|
|
"kafka.*Committed offset [0-9]+.*recreate_kafka_table",
|
|
),
|
|
],
|
|
)
|
|
def test_kafka_recreate_kafka_table(kafka_cluster, create_query_generator, log_line):
|
|
"""
|
|
Checks that materialized view work properly after dropping and recreating the Kafka table.
|
|
"""
|
|
topic_name = "recreate_kafka_table"
|
|
thread_per_consumer = must_use_thread_per_consumer(create_query_generator)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name, num_partitions=6):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group="recreate_kafka_table_group",
|
|
settings={
|
|
"kafka_num_consumers": 4,
|
|
"kafka_flush_interval_ms": 1000,
|
|
"kafka_skip_broken_messages": 1048577,
|
|
"kafka_thread_per_consumer": thread_per_consumer,
|
|
},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{create_query};
|
|
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(120):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, "recreate_kafka_table", messages)
|
|
|
|
instance.wait_for_log_line(
|
|
log_line,
|
|
repetitions=6,
|
|
look_behind_lines=100,
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.rotate_logs()
|
|
|
|
kafka_produce(kafka_cluster, "recreate_kafka_table", messages)
|
|
|
|
instance.query(create_query)
|
|
|
|
instance.wait_for_log_line(
|
|
log_line,
|
|
repetitions=6,
|
|
look_behind_lines=100,
|
|
)
|
|
|
|
# data was not flushed yet (it will be flushed 7.5 sec after creating MV)
|
|
assert (
|
|
int(
|
|
instance.query_with_retry(
|
|
sql="SELECT count() FROM test.view",
|
|
check_callback=lambda x: x == 240,
|
|
)
|
|
)
|
|
== 240
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.kafka;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, log_line",
|
|
[
|
|
(generate_old_create_table_query, "Committed offset {offset}"),
|
|
(
|
|
generate_new_create_table_query,
|
|
r"kafka.*Saved offset [0-9]+ for topic-partition \[{topic}:[0-9]+\]",
|
|
),
|
|
],
|
|
)
|
|
def test_librdkafka_compression(kafka_cluster, create_query_generator, log_line):
|
|
"""
|
|
Regression for UB in snappy-c (that is used in librdkafka),
|
|
backport pr is [1].
|
|
|
|
[1]: https://github.com/ClickHouse-Extras/librdkafka/pull/3
|
|
|
|
Example of corruption:
|
|
|
|
2020.12.10 09:59:56.831507 [ 20 ] {} <Error> void DB::StorageKafka::threadFunc(size_t): Code: 27. DB::Exception: Cannot parse input: expected '"' before: 'foo"}': (while reading the value of key value): (at row 1)
|
|
|
|
To trigger this regression there should duplicated messages
|
|
|
|
Orignal reproducer is:
|
|
$ gcc --version |& fgrep gcc
|
|
gcc (GCC) 10.2.0
|
|
$ yes foobarbaz | fold -w 80 | head -n10 >| in-…
|
|
$ make clean && make CFLAGS='-Wall -g -O2 -ftree-loop-vectorize -DNDEBUG=1 -DSG=1 -fPIC'
|
|
$ ./verify in
|
|
final comparision of in failed at 20 of 100
|
|
|
|
"""
|
|
|
|
supported_compression_types = ["gzip", "snappy", "lz4", "zstd", "uncompressed"]
|
|
|
|
messages = []
|
|
expected = []
|
|
|
|
value = "foobarbaz" * 10
|
|
number_of_messages = 50
|
|
for i in range(number_of_messages):
|
|
messages.append(json.dumps({"key": i, "value": value}))
|
|
expected.append(f"{i}\t{value}")
|
|
|
|
expected = "\n".join(expected)
|
|
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
for compression_type in supported_compression_types:
|
|
logging.debug(("Check compression {}".format(compression_type)))
|
|
|
|
topic_name = "test_librdkafka_compression_{}".format(compression_type)
|
|
topic_config = {"compression.type": compression_type}
|
|
with kafka_topic(admin_client, topic_name, config=topic_config):
|
|
instance.query(
|
|
"""{create_query};
|
|
|
|
CREATE TABLE test.view (key UInt64, value String)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
""".format(
|
|
create_query=create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value String",
|
|
topic_list=topic_name,
|
|
format="JSONEachRow",
|
|
settings={"kafka_flush_interval_ms": 1000},
|
|
),
|
|
)
|
|
)
|
|
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
instance.wait_for_log_line(
|
|
log_line.format(offset=number_of_messages, topic=topic_name)
|
|
)
|
|
result = instance.query("SELECT * FROM test.view")
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
instance.query("DROP TABLE test.kafka SYNC")
|
|
instance.query("DROP TABLE test.consumer SYNC")
|
|
instance.query("DROP TABLE test.view SYNC")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_new_create_table_query, generate_old_create_table_query],
|
|
)
|
|
def test_kafka_materialized_view_with_subquery(kafka_cluster, create_query_generator):
|
|
topic_name = "mysq"
|
|
logging.debug(f"Using topic {topic_name}")
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
|
|
{create_query};
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM (SELECT * FROM test.kafka);
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
result = instance.query_with_retry(
|
|
"SELECT * FROM test.view",
|
|
check_callback=kafka_check_result,
|
|
retry_count=40,
|
|
sleep_time=0.75,
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_many_materialized_views(kafka_cluster, create_query_generator):
|
|
topic_name = f"mmv-{get_topic_postfix(create_query_generator)}"
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=f"{topic_name}-group",
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view1;
|
|
DROP TABLE IF EXISTS test.view2;
|
|
DROP TABLE IF EXISTS test.consumer1;
|
|
DROP TABLE IF EXISTS test.consumer2;
|
|
{create_query};
|
|
CREATE TABLE test.view1 (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE TABLE test.view2 (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer1 TO test.view1 AS
|
|
SELECT * FROM test.kafka;
|
|
CREATE MATERIALIZED VIEW test.consumer2 TO test.view2 AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
result1 = instance.query_with_retry(
|
|
"SELECT * FROM test.view1", check_callback=kafka_check_result
|
|
)
|
|
result2 = instance.query_with_retry(
|
|
"SELECT * FROM test.view2", check_callback=kafka_check_result
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer1;
|
|
DROP TABLE test.consumer2;
|
|
DROP TABLE test.view1;
|
|
DROP TABLE test.view2;
|
|
"""
|
|
)
|
|
|
|
kafka_check_result(result1, True)
|
|
kafka_check_result(result2, True)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_flush_on_big_message(kafka_cluster, create_query_generator):
|
|
# Create batches of messages of size ~100Kb
|
|
kafka_messages = 1000
|
|
batch_messages = 1000
|
|
topic_name = "flush" + get_topic_postfix(create_query_generator)
|
|
messages = [
|
|
json.dumps({"key": i, "value": "x" * 100}) * batch_messages
|
|
for i in range(kafka_messages)
|
|
]
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
with existing_kafka_topic(admin_client, topic_name):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value String",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={"kafka_max_block_size": 10},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{create_query};
|
|
CREATE TABLE test.view (key UInt64, value String)
|
|
ENGINE = MergeTree
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
received = False
|
|
while not received:
|
|
try:
|
|
offsets = admin_client.list_consumer_group_offsets(topic_name)
|
|
for topic, offset in list(offsets.items()):
|
|
if topic.topic == topic_name and offset.offset == kafka_messages:
|
|
received = True
|
|
break
|
|
except kafka.errors.GroupCoordinatorNotAvailableError:
|
|
continue
|
|
|
|
while True:
|
|
result = instance.query("SELECT count() FROM test.view")
|
|
if int(result) == kafka_messages * batch_messages:
|
|
break
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
assert (
|
|
int(result) == kafka_messages * batch_messages
|
|
), "ClickHouse lost some messages: {}".format(result)
|
|
|
|
|
|
def test_kafka_virtual_columns(kafka_cluster):
|
|
topic_config = {
|
|
# default retention, since predefined timestamp_ms is used.
|
|
"retention.ms": "-1",
|
|
}
|
|
with kafka_topic(get_admin_client(kafka_cluster), "virt1", config=topic_config):
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'virt1',
|
|
kafka_group_name = 'virt1',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONEachRow';
|
|
"""
|
|
)
|
|
|
|
messages = ""
|
|
for i in range(25):
|
|
messages += json.dumps({"key": i, "value": i}) + "\n"
|
|
kafka_produce(kafka_cluster, "virt1", [messages], 0)
|
|
|
|
messages = ""
|
|
for i in range(25, 50):
|
|
messages += json.dumps({"key": i, "value": i}) + "\n"
|
|
kafka_produce(kafka_cluster, "virt1", [messages], 0)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query(
|
|
"""SELECT _key, key, _topic, value, _offset, _partition, _timestamp = 0 ? '0000-00-00 00:00:00' : toString(_timestamp) AS _timestamp FROM test.kafka""",
|
|
ignore_error=True,
|
|
)
|
|
if kafka_check_result(result, False, "test_kafka_virtual1.reference"):
|
|
break
|
|
|
|
kafka_check_result(result, True, "test_kafka_virtual1.reference")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_virtual_columns_with_materialized_view(
|
|
kafka_cluster, create_query_generator
|
|
):
|
|
topic_config = {
|
|
# default retention, since predefined timestamp_ms is used.
|
|
"retention.ms": "-1",
|
|
}
|
|
# the topic name is hardcoded in reference, it doesn't worth to create two reference files to have separate topics,
|
|
# as the context manager will always clean up the topic
|
|
topic_name = "virt2"
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=f"{topic_name}-group",
|
|
)
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name, config=topic_config):
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{create_query};
|
|
CREATE TABLE test.view (key UInt64, value UInt64, kafka_key String, topic String, offset UInt64, partition UInt64, timestamp Nullable(DateTime('UTC')))
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT *, _key as kafka_key, _topic as topic, _offset as offset, _partition as partition, _timestamp = 0 ? '0000-00-00 00:00:00' : toString(_timestamp) as timestamp FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({"key": i, "value": i}))
|
|
kafka_produce(kafka_cluster, topic_name, messages, 0)
|
|
|
|
def check_callback(result):
|
|
return kafka_check_result(result, False, "test_kafka_virtual2.reference")
|
|
|
|
result = instance.query_with_retry(
|
|
"SELECT kafka_key, key, topic, value, offset, partition, timestamp FROM test.view ORDER BY kafka_key, key",
|
|
check_callback=check_callback,
|
|
)
|
|
|
|
kafka_check_result(result, True, "test_kafka_virtual2.reference")
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
|
|
def insert_with_retry(instance, values, table_name="kafka", max_try_count=5):
|
|
try_count = 0
|
|
while True:
|
|
logging.debug(f"Inserting, try_count is {try_count}")
|
|
try:
|
|
try_count += 1
|
|
instance.query(f"INSERT INTO test.{table_name} VALUES {values}")
|
|
break
|
|
except QueryRuntimeException as e:
|
|
if "Local: Timed out." in str(e) and try_count < max_try_count:
|
|
continue
|
|
else:
|
|
raise
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_insert(kafka_cluster, create_query_generator):
|
|
topic_name = "insert1" + get_topic_postfix(create_query_generator)
|
|
|
|
instance.query(
|
|
create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="TSV",
|
|
)
|
|
)
|
|
|
|
message_count = 50
|
|
values = []
|
|
for i in range(message_count):
|
|
values.append("({i}, {i})".format(i=i))
|
|
values = ",".join(values)
|
|
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
insert_with_retry(instance, values)
|
|
|
|
messages = kafka_consume_with_retry(kafka_cluster, topic_name, message_count)
|
|
result = "\n".join(messages)
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_produce_consume(kafka_cluster, create_query_generator):
|
|
topic_name = "insert2" + get_topic_postfix(create_query_generator)
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="TSV",
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{create_query};
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
messages_num = 10000
|
|
|
|
def insert():
|
|
values = []
|
|
for i in range(messages_num):
|
|
values.append("({i}, {i})".format(i=i))
|
|
values = ",".join(values)
|
|
|
|
insert_with_retry(instance, values)
|
|
|
|
threads = []
|
|
threads_num = 16
|
|
for _ in range(threads_num):
|
|
threads.append(threading.Thread(target=insert))
|
|
for thread in threads:
|
|
time.sleep(random.uniform(0, 1))
|
|
thread.start()
|
|
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
expected_row_count = messages_num * threads_num
|
|
result = instance.query_with_retry(
|
|
"SELECT count() FROM test.view",
|
|
sleep_time=1,
|
|
retry_count=20,
|
|
check_callback=lambda result: int(result) == expected_row_count,
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
for thread in threads:
|
|
thread.join()
|
|
|
|
assert (
|
|
int(result) == expected_row_count
|
|
), "ClickHouse lost some messages: {}".format(result)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_commit_on_block_write(kafka_cluster, create_query_generator):
|
|
topic_name = "block" + get_topic_postfix(create_query_generator)
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={"kafka_max_block_size": 100},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{create_query};
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
cancel = threading.Event()
|
|
|
|
# We need to pass i as a reference. Simple integers are passed by value.
|
|
# Making an array is probably the easiest way to "force pass by reference".
|
|
i = [0]
|
|
|
|
def produce(i):
|
|
while not cancel.is_set():
|
|
messages = []
|
|
for _ in range(101):
|
|
messages.append(json.dumps({"key": i[0], "value": i[0]}))
|
|
i[0] += 1
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
kafka_thread = threading.Thread(target=produce, args=[i])
|
|
kafka_thread.start()
|
|
|
|
instance.query_with_retry(
|
|
"SELECT count() FROM test.view",
|
|
sleep_time=1,
|
|
check_callback=lambda res: int(res) >= 100,
|
|
)
|
|
|
|
cancel.set()
|
|
|
|
instance.query("DROP TABLE test.kafka SYNC")
|
|
|
|
instance.query(create_query)
|
|
kafka_thread.join()
|
|
|
|
instance.query_with_retry(
|
|
"SELECT uniqExact(key) FROM test.view",
|
|
sleep_time=1,
|
|
check_callback=lambda res: int(res) >= i[0],
|
|
)
|
|
|
|
result = int(instance.query("SELECT count() == uniqExact(key) FROM test.view"))
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
kafka_thread.join()
|
|
|
|
assert result == 1, "Messages from kafka get duplicated!"
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, log_line",
|
|
[
|
|
(generate_old_create_table_query, "kafka.*Committed offset 2.*virt2_[01]"),
|
|
(
|
|
generate_new_create_table_query,
|
|
r"kafka.*Saved offset 2 for topic-partition \[virt2_[01]:[0-9]+",
|
|
),
|
|
],
|
|
)
|
|
def test_kafka_virtual_columns2(kafka_cluster, create_query_generator, log_line):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
topic_config = {
|
|
# default retention, since predefined timestamp_ms is used.
|
|
"retention.ms": "-1",
|
|
}
|
|
thread_per_consumer = must_use_thread_per_consumer(create_query_generator)
|
|
topic_name_0 = "virt2_0"
|
|
topic_name_1 = "virt2_1"
|
|
consumer_group = "virt2" + get_topic_postfix(create_query_generator)
|
|
with kafka_topic(admin_client, topic_name_0, num_partitions=2, config=topic_config):
|
|
with kafka_topic(
|
|
admin_client, topic_name_1, num_partitions=2, config=topic_config
|
|
):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"value UInt64",
|
|
topic_list=f"{topic_name_0},{topic_name_1}",
|
|
consumer_group=consumer_group,
|
|
settings={
|
|
"kafka_num_consumers": 2,
|
|
"kafka_thread_per_consumer": thread_per_consumer,
|
|
},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT value, _key, _topic, _partition, _offset, toUnixTimestamp(_timestamp), toUnixTimestamp64Milli(_timestamp_ms), _headers.name, _headers.value FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
producer = KafkaProducer(
|
|
bootstrap_servers="localhost:{}".format(cluster.kafka_port),
|
|
value_serializer=producer_serializer,
|
|
key_serializer=producer_serializer,
|
|
)
|
|
|
|
producer.send(
|
|
topic=topic_name_0,
|
|
value=json.dumps({"value": 1}),
|
|
partition=0,
|
|
key="k1",
|
|
timestamp_ms=1577836801001,
|
|
headers=[("content-encoding", b"base64")],
|
|
)
|
|
producer.send(
|
|
topic=topic_name_0,
|
|
value=json.dumps({"value": 2}),
|
|
partition=0,
|
|
key="k2",
|
|
timestamp_ms=1577836802002,
|
|
headers=[
|
|
("empty_value", b""),
|
|
("", b"empty name"),
|
|
("", b""),
|
|
("repetition", b"1"),
|
|
("repetition", b"2"),
|
|
],
|
|
)
|
|
producer.flush()
|
|
|
|
producer.send(
|
|
topic=topic_name_0,
|
|
value=json.dumps({"value": 3}),
|
|
partition=1,
|
|
key="k3",
|
|
timestamp_ms=1577836803003,
|
|
headers=[("b", b"b"), ("a", b"a")],
|
|
)
|
|
producer.send(
|
|
topic=topic_name_0,
|
|
value=json.dumps({"value": 4}),
|
|
partition=1,
|
|
key="k4",
|
|
timestamp_ms=1577836804004,
|
|
headers=[("a", b"a"), ("b", b"b")],
|
|
)
|
|
producer.flush()
|
|
|
|
producer.send(
|
|
topic=topic_name_1,
|
|
value=json.dumps({"value": 5}),
|
|
partition=0,
|
|
key="k5",
|
|
timestamp_ms=1577836805005,
|
|
)
|
|
producer.send(
|
|
topic=topic_name_1,
|
|
value=json.dumps({"value": 6}),
|
|
partition=0,
|
|
key="k6",
|
|
timestamp_ms=1577836806006,
|
|
)
|
|
producer.flush()
|
|
|
|
producer.send(
|
|
topic=topic_name_1,
|
|
value=json.dumps({"value": 7}),
|
|
partition=1,
|
|
key="k7",
|
|
timestamp_ms=1577836807007,
|
|
)
|
|
producer.send(
|
|
topic=topic_name_1,
|
|
value=json.dumps({"value": 8}),
|
|
partition=1,
|
|
key="k8",
|
|
timestamp_ms=1577836808008,
|
|
)
|
|
producer.flush()
|
|
|
|
instance.wait_for_log_line(log_line, repetitions=4, look_behind_lines=6000)
|
|
|
|
members = describe_consumer_group(kafka_cluster, consumer_group)
|
|
# pprint.pprint(members)
|
|
# members[0]['client_id'] = 'ClickHouse-instance-test-kafka-0'
|
|
# members[1]['client_id'] = 'ClickHouse-instance-test-kafka-1'
|
|
|
|
result = instance.query(
|
|
"SELECT * FROM test.view ORDER BY value", ignore_error=True
|
|
)
|
|
|
|
expected = f"""\
|
|
1 k1 {topic_name_0} 0 0 1577836801 1577836801001 ['content-encoding'] ['base64']
|
|
2 k2 {topic_name_0} 0 1 1577836802 1577836802002 ['empty_value','','','repetition','repetition'] ['','empty name','','1','2']
|
|
3 k3 {topic_name_0} 1 0 1577836803 1577836803003 ['b','a'] ['b','a']
|
|
4 k4 {topic_name_0} 1 1 1577836804 1577836804004 ['a','b'] ['a','b']
|
|
5 k5 {topic_name_1} 0 0 1577836805 1577836805005 [] []
|
|
6 k6 {topic_name_1} 0 1 1577836806 1577836806006 [] []
|
|
7 k7 {topic_name_1} 1 0 1577836807 1577836807007 [] []
|
|
8 k8 {topic_name_1} 1 1 1577836808 1577836808008 [] []
|
|
"""
|
|
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
instance.rotate_logs()
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, do_direct_read",
|
|
[(generate_old_create_table_query, True), (generate_new_create_table_query, False)],
|
|
)
|
|
def test_kafka_producer_consumer_separate_settings(
|
|
kafka_cluster, create_query_generator, do_direct_read
|
|
):
|
|
instance.rotate_logs()
|
|
instance.query(
|
|
create_query_generator(
|
|
"test_kafka",
|
|
"key UInt64",
|
|
topic_list="separate_settings",
|
|
consumer_group="test",
|
|
)
|
|
)
|
|
|
|
if do_direct_read:
|
|
instance.query("SELECT * FROM test.test_kafka")
|
|
instance.query("INSERT INTO test.test_kafka VALUES (1)")
|
|
|
|
assert instance.contains_in_log("Kafka producer created")
|
|
assert instance.contains_in_log("Created #0 consumer")
|
|
|
|
kafka_conf_warnings = instance.grep_in_log("rdk:CONFWARN")
|
|
|
|
assert kafka_conf_warnings is not None
|
|
|
|
for warn in kafka_conf_warnings.strip().split("\n"):
|
|
# this setting was applied via old syntax and applied on both consumer
|
|
# and producer configurations
|
|
assert "heartbeat.interval.ms" in warn
|
|
|
|
kafka_consumer_applied_properties = instance.grep_in_log("Consumer set property")
|
|
kafka_producer_applied_properties = instance.grep_in_log("Producer set property")
|
|
|
|
assert kafka_consumer_applied_properties is not None
|
|
assert kafka_producer_applied_properties is not None
|
|
|
|
# global settings should be applied for consumer and producer
|
|
global_settings = {
|
|
"debug": "topic,protocol,cgrp,consumer",
|
|
"statistics.interval.ms": "600",
|
|
}
|
|
|
|
for name, value in global_settings.items():
|
|
property_in_log = f"{name}:{value}"
|
|
assert property_in_log in kafka_consumer_applied_properties
|
|
assert property_in_log in kafka_producer_applied_properties
|
|
|
|
settings_topic__separate_settings__consumer = {"session.timeout.ms": "6001"}
|
|
|
|
for name, value in settings_topic__separate_settings__consumer.items():
|
|
property_in_log = f"{name}:{value}"
|
|
assert property_in_log in kafka_consumer_applied_properties
|
|
assert property_in_log not in kafka_producer_applied_properties
|
|
|
|
producer_settings = {"transaction.timeout.ms": "60001"}
|
|
|
|
for name, value in producer_settings.items():
|
|
property_in_log = f"{name}:{value}"
|
|
assert property_in_log not in kafka_consumer_applied_properties
|
|
assert property_in_log in kafka_producer_applied_properties
|
|
|
|
# Should be ignored, because it is inside producer tag
|
|
producer_legacy_syntax__topic_separate_settings = {"message.timeout.ms": "300001"}
|
|
|
|
for name, value in producer_legacy_syntax__topic_separate_settings.items():
|
|
property_in_log = f"{name}:{value}"
|
|
assert property_in_log not in kafka_consumer_applied_properties
|
|
assert property_in_log not in kafka_producer_applied_properties
|
|
|
|
# Old syntax, applied on consumer and producer
|
|
legacy_syntax__topic_separated_settings = {"heartbeat.interval.ms": "302"}
|
|
|
|
for name, value in legacy_syntax__topic_separated_settings.items():
|
|
property_in_log = f"{name}:{value}"
|
|
assert property_in_log in kafka_consumer_applied_properties
|
|
assert property_in_log in kafka_producer_applied_properties
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, log_line",
|
|
[
|
|
(generate_new_create_table_query, "Saved offset 5"),
|
|
(generate_old_create_table_query, "Committed offset 5"),
|
|
],
|
|
)
|
|
def test_kafka_produce_key_timestamp(kafka_cluster, create_query_generator, log_line):
|
|
topic_name = "insert3"
|
|
topic_config = {
|
|
# default retention, since predefined timestamp_ms is used.
|
|
"retention.ms": "-1",
|
|
}
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name, config=topic_config):
|
|
writer_create_query = create_query_generator(
|
|
"kafka_writer",
|
|
"key UInt64, value UInt64, _key String, _timestamp DateTime('UTC')",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="TSV",
|
|
)
|
|
reader_create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64, inserted_key String, inserted_timestamp DateTime('UTC')",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="TSV",
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{writer_create_query};
|
|
{reader_create_query};
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT key, value, inserted_key, toUnixTimestamp(inserted_timestamp), _key, _topic, _partition, _offset, toUnixTimestamp(_timestamp) FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"INSERT INTO test.kafka_writer VALUES ({},{},'{}',toDateTime({}))".format(
|
|
1, 1, "k1", 1577836801
|
|
)
|
|
)
|
|
instance.query(
|
|
"INSERT INTO test.kafka_writer VALUES ({},{},'{}',toDateTime({}))".format(
|
|
2, 2, "k2", 1577836802
|
|
)
|
|
)
|
|
instance.query(
|
|
"INSERT INTO test.kafka_writer VALUES ({},{},'{}',toDateTime({})),({},{},'{}',toDateTime({}))".format(
|
|
3, 3, "k3", 1577836803, 4, 4, "k4", 1577836804
|
|
)
|
|
)
|
|
instance.query(
|
|
"INSERT INTO test.kafka_writer VALUES ({},{},'{}',toDateTime({}))".format(
|
|
5, 5, "k5", 1577836805
|
|
)
|
|
)
|
|
|
|
instance.wait_for_log_line(log_line)
|
|
|
|
expected = """\
|
|
1 1 k1 1577836801 k1 insert3 0 0 1577836801
|
|
2 2 k2 1577836802 k2 insert3 0 1 1577836802
|
|
3 3 k3 1577836803 k3 insert3 0 2 1577836803
|
|
4 4 k4 1577836804 k4 insert3 0 3 1577836804
|
|
5 5 k5 1577836805 k5 insert3 0 4 1577836805
|
|
"""
|
|
|
|
result = instance.query_with_retry(
|
|
"SELECT * FROM test.view ORDER BY value",
|
|
ignore_error=True,
|
|
retry_count=5,
|
|
sleep_time=1,
|
|
check_callback=lambda res: TSV(res) == TSV(expected),
|
|
)
|
|
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_insert_avro(kafka_cluster, create_query_generator):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
topic_config = {
|
|
# default retention, since predefined timestamp_ms is used.
|
|
"retention.ms": "-1",
|
|
}
|
|
topic_name = "avro1" + get_topic_postfix(create_query_generator)
|
|
with kafka_topic(admin_client, topic_name, config=topic_config):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64, _timestamp DateTime('UTC')",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="Avro",
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
{create_query}
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"INSERT INTO test.kafka select number*10 as key, number*100 as value, 1636505534 as _timestamp from numbers(4) SETTINGS output_format_avro_rows_in_file = 2, output_format_avro_codec = 'deflate'"
|
|
)
|
|
|
|
message_count = 2
|
|
messages = kafka_consume_with_retry(
|
|
kafka_cluster,
|
|
topic_name,
|
|
message_count,
|
|
need_decode=False,
|
|
timestamp=1636505534,
|
|
)
|
|
|
|
result = ""
|
|
for a_message in messages:
|
|
result += decode_avro(a_message) + "\n"
|
|
|
|
expected_result = """{'key': 0, 'value': 0, '_timestamp': 1636505534}
|
|
{'key': 10, 'value': 100, '_timestamp': 1636505534}
|
|
|
|
{'key': 20, 'value': 200, '_timestamp': 1636505534}
|
|
{'key': 30, 'value': 300, '_timestamp': 1636505534}
|
|
|
|
"""
|
|
assert result == expected_result
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_produce_consume_avro(kafka_cluster, create_query_generator):
|
|
topic_name = "insert_avro" + get_topic_postfix(create_query_generator)
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
num_rows = 75
|
|
|
|
writer_create_query = create_query_generator(
|
|
"kafka_writer",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="Avro",
|
|
)
|
|
|
|
reader_create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="Avro",
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.kafka_writer;
|
|
|
|
{writer_create_query};
|
|
{reader_create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT key, value FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"INSERT INTO test.kafka_writer select number*10 as key, number*100 as value from numbers({num_rows}) SETTINGS output_format_avro_rows_in_file = 7".format(
|
|
num_rows=num_rows
|
|
)
|
|
)
|
|
|
|
instance.wait_for_log_line(
|
|
"Committed offset {offset}".format(offset=math.ceil(num_rows / 7))
|
|
)
|
|
|
|
expected_num_rows = instance.query(
|
|
"SELECT COUNT(1) FROM test.view", ignore_error=True
|
|
)
|
|
assert int(expected_num_rows) == num_rows
|
|
|
|
expected_max_key = instance.query(
|
|
"SELECT max(key) FROM test.view", ignore_error=True
|
|
)
|
|
assert int(expected_max_key) == (num_rows - 1) * 10
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_flush_by_time(kafka_cluster, create_query_generator):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
topic_name = "flush_by_time" + get_topic_postfix(create_query_generator)
|
|
|
|
with kafka_topic(admin_client, topic_name):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 100,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
|
|
{create_query};
|
|
|
|
CREATE TABLE test.view (key UInt64, value UInt64, ts DateTime64(3) MATERIALIZED now64(3))
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
"""
|
|
)
|
|
|
|
cancel = threading.Event()
|
|
|
|
def produce():
|
|
while not cancel.is_set():
|
|
messages = [json.dumps({"key": 0, "value": 0})]
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
time.sleep(0.8)
|
|
|
|
kafka_thread = threading.Thread(target=produce)
|
|
kafka_thread.start()
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
# By default the flush timeout should be 7.5 seconds => 18 seconds should be enough for 2 flushes, but not for 3
|
|
time.sleep(18)
|
|
|
|
result = instance.query("SELECT uniqExact(ts), count() >= 15 FROM test.view")
|
|
|
|
cancel.set()
|
|
kafka_thread.join()
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
assert TSV(result) == TSV("2 1")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_flush_by_block_size(kafka_cluster, create_query_generator):
|
|
topic_name = "flush_by_block_size" + get_topic_postfix(create_query_generator)
|
|
|
|
cancel = threading.Event()
|
|
|
|
def produce():
|
|
while not cancel.is_set():
|
|
messages = []
|
|
messages.append(json.dumps({"key": 0, "value": 0}))
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
kafka_thread = threading.Thread(target=produce)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
kafka_thread.start()
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 100,
|
|
"kafka_poll_max_batch_size": 1,
|
|
"kafka_flush_interval_ms": 120000,
|
|
},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
|
|
{create_query};
|
|
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
# Wait for Kafka engine to consume this data
|
|
while 1 != int(
|
|
instance.query(
|
|
"SELECT count() FROM system.parts WHERE database = 'test' AND table = 'view' AND name = 'all_1_1_0'"
|
|
)
|
|
):
|
|
time.sleep(0.5)
|
|
|
|
cancel.set()
|
|
kafka_thread.join()
|
|
|
|
# more flushes can happens during test, we need to check only result of first flush (part named all_1_1_0).
|
|
result = instance.query("SELECT count() FROM test.view WHERE _part='all_1_1_0'")
|
|
# logging.debug(result)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
# 100 = first poll should return 100 messages (and rows)
|
|
# not waiting for stream_flush_interval_ms
|
|
assert (
|
|
int(result) == 100
|
|
), "Messages from kafka should be flushed when block of size kafka_max_block_size is formed!"
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_lot_of_partitions_partial_commit_of_bulk(
|
|
kafka_cluster, create_query_generator
|
|
):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
|
|
topic_name = "topic_with_multiple_partitions2" + get_topic_postfix(
|
|
create_query_generator
|
|
)
|
|
with kafka_topic(admin_client, topic_name):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 211,
|
|
"kafka_flush_interval_ms": 500,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
{create_query};
|
|
CREATE TABLE test.view (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
count = 0
|
|
for dummy_msg in range(1000):
|
|
rows = []
|
|
for dummy_row in range(random.randrange(3, 10)):
|
|
count = count + 1
|
|
rows.append(json.dumps({"key": count, "value": count}))
|
|
messages.append("\n".join(rows))
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
instance.wait_for_log_line("kafka.*Stalled", repetitions=5)
|
|
|
|
result = instance.query(
|
|
"SELECT count(), uniqExact(key), max(key) FROM test.view"
|
|
)
|
|
logging.debug(result)
|
|
assert TSV(result) == TSV("{0}\t{0}\t{0}".format(count))
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
"""
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, log_line",
|
|
[
|
|
(generate_old_create_table_query, "{}.*Polled offset [0-9]+"),
|
|
(generate_new_create_table_query, "{}.*Saved offset"),
|
|
],
|
|
)
|
|
def test_kafka_rebalance(kafka_cluster, create_query_generator, log_line):
|
|
NUMBER_OF_CONSURRENT_CONSUMERS = 11
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE IF EXISTS test.destination;
|
|
CREATE TABLE test.destination (
|
|
key UInt64,
|
|
value UInt64,
|
|
_topic String,
|
|
_key String,
|
|
_offset UInt64,
|
|
_partition UInt64,
|
|
_timestamp Nullable(DateTime('UTC')),
|
|
_consumed_by LowCardinality(String)
|
|
)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
"""
|
|
)
|
|
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
topic_name = "topic_with_multiple_partitions" + get_topic_postfix(
|
|
create_query_generator
|
|
)
|
|
table_name_prefix = "kafka_consumer"
|
|
keeper_path = f"/clickhouse/{{database}}/{table_name_prefix}"
|
|
with kafka_topic(admin_client, topic_name, num_partitions=11):
|
|
cancel = threading.Event()
|
|
|
|
msg_index = [0]
|
|
|
|
def produce():
|
|
while not cancel.is_set():
|
|
messages = []
|
|
for _ in range(59):
|
|
messages.append(
|
|
json.dumps({"key": msg_index[0], "value": msg_index[0]})
|
|
)
|
|
msg_index[0] += 1
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
kafka_thread = threading.Thread(target=produce)
|
|
kafka_thread.start()
|
|
|
|
for consumer_index in range(NUMBER_OF_CONSURRENT_CONSUMERS):
|
|
table_name = f"{table_name_prefix}{consumer_index}"
|
|
replica_name = f"r{consumer_index}"
|
|
logging.debug(f"Setting up {consumer_index}")
|
|
|
|
create_query = create_query_generator(
|
|
table_name,
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
keeper_path=keeper_path,
|
|
replica_name=replica_name,
|
|
settings={
|
|
"kafka_max_block_size": 33,
|
|
"kafka_flush_interval_ms": 500,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.{table_name};
|
|
DROP TABLE IF EXISTS test.{table_name}_mv;
|
|
{create_query};
|
|
CREATE MATERIALIZED VIEW test.{table_name}_mv TO test.destination AS
|
|
SELECT
|
|
key,
|
|
value,
|
|
_topic,
|
|
_key,
|
|
_offset,
|
|
_partition,
|
|
_timestamp,
|
|
'{table_name}' as _consumed_by
|
|
FROM test.{table_name};
|
|
"""
|
|
)
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
# Waiting for test.kafka_consumerX to start consume ...
|
|
instance.wait_for_log_line(log_line.format(table_name))
|
|
|
|
cancel.set()
|
|
|
|
# I leave last one working by intent (to finish consuming after all rebalances)
|
|
for consumer_index in range(NUMBER_OF_CONSURRENT_CONSUMERS - 1):
|
|
logging.debug(("Dropping test.kafka_consumer{}".format(consumer_index)))
|
|
instance.query(
|
|
"DROP TABLE IF EXISTS test.kafka_consumer{} SYNC".format(consumer_index)
|
|
)
|
|
|
|
# logging.debug(instance.query('SELECT count(), uniqExact(key), max(key) + 1 FROM test.destination'))
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
|
|
while 1:
|
|
messages_consumed = int(
|
|
instance.query("SELECT uniqExact(key) FROM test.destination")
|
|
)
|
|
if messages_consumed >= msg_index[0]:
|
|
break
|
|
time.sleep(1)
|
|
logging.debug(
|
|
(
|
|
"Waiting for finishing consuming (have {}, should be {})".format(
|
|
messages_consumed, msg_index[0]
|
|
)
|
|
)
|
|
)
|
|
|
|
logging.debug(
|
|
(
|
|
instance.query(
|
|
"SELECT count(), uniqExact(key), max(key) + 1 FROM test.destination"
|
|
)
|
|
)
|
|
)
|
|
|
|
# Some queries to debug...
|
|
# SELECT * FROM test.destination where key in (SELECT key FROM test.destination group by key having count() <> 1)
|
|
# select number + 1 as key from numbers(4141) x left join test.destination using (key) where test.destination.key = 0;
|
|
# SELECT * FROM test.destination WHERE key between 2360 and 2370 order by key;
|
|
# select _partition from test.destination group by _partition having count() <> max(_offset) + 1;
|
|
# select toUInt64(0) as _partition, number + 1 as _offset from numbers(400) x left join test.destination using (_partition,_offset) where test.destination.key = 0 order by _offset;
|
|
# SELECT * FROM test.destination WHERE _partition = 0 and _offset between 220 and 240 order by _offset;
|
|
|
|
# CREATE TABLE test.reference (key UInt64, value UInt64) ENGINE = Kafka SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
# kafka_topic_list = 'topic_with_multiple_partitions',
|
|
# kafka_group_name = 'rebalance_test_group_reference',
|
|
# kafka_format = 'JSONEachRow',
|
|
# kafka_max_block_size = 100000;
|
|
#
|
|
# CREATE MATERIALIZED VIEW test.reference_mv Engine=Log AS
|
|
# SELECT key, value, _topic,_key,_offset, _partition, _timestamp, 'reference' as _consumed_by
|
|
# FROM test.reference;
|
|
#
|
|
# select * from test.reference_mv left join test.destination using (key,_topic,_offset,_partition) where test.destination._consumed_by = '';
|
|
|
|
result = int(
|
|
instance.query("SELECT count() == uniqExact(key) FROM test.destination")
|
|
)
|
|
|
|
for consumer_index in range(NUMBER_OF_CONSURRENT_CONSUMERS):
|
|
logging.debug(("kafka_consumer{}".format(consumer_index)))
|
|
table_name = "kafka_consumer{}".format(consumer_index)
|
|
instance.query(
|
|
"""
|
|
DROP TABLE IF EXISTS test.{0};
|
|
DROP TABLE IF EXISTS test.{0}_mv;
|
|
""".format(
|
|
table_name
|
|
)
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE IF EXISTS test.destination;
|
|
"""
|
|
)
|
|
|
|
kafka_thread.join()
|
|
|
|
assert result == 1, "Messages from kafka get duplicated!"
|
|
|
|
|
|
# TODO(antaljanosbenjamin): find another way to make insertion fail
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[
|
|
generate_old_create_table_query,
|
|
# generate_new_create_table_query,
|
|
],
|
|
)
|
|
def test_kafka_no_holes_when_write_suffix_failed(kafka_cluster, create_query_generator):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
topic_name = "no_holes_when_write_suffix_failed" + get_topic_postfix(
|
|
create_query_generator
|
|
)
|
|
|
|
with kafka_topic(admin_client, topic_name):
|
|
messages = [json.dumps({"key": j + 1, "value": "x" * 300}) for j in range(22)]
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value String",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 20,
|
|
"kafka_flush_interval_ms": 2000,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view SYNC;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
|
|
{create_query};
|
|
|
|
CREATE TABLE test.view (key UInt64, value String)
|
|
ENGINE = ReplicatedMergeTree('/clickhouse/kafkatest/tables/{topic_name}', 'node1')
|
|
ORDER BY key;
|
|
"""
|
|
)
|
|
|
|
# init PartitionManager (it starts container) earlier
|
|
pm = PartitionManager()
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka
|
|
WHERE NOT sleepEachRow(0.25);
|
|
"""
|
|
)
|
|
|
|
instance.wait_for_log_line("Polled batch of 20 messages")
|
|
# the tricky part here is that disconnect should happen after write prefix, but before write suffix
|
|
# we have 0.25 (sleepEachRow) * 20 ( Rows ) = 5 sec window after "Polled batch of 20 messages"
|
|
# while materialized view is working to inject zookeeper failure
|
|
pm.drop_instance_zk_connections(instance)
|
|
instance.wait_for_log_line(
|
|
"Error.*(Connection loss|Coordination::Exception).*while pushing to view"
|
|
)
|
|
pm.heal_all()
|
|
instance.wait_for_log_line("Committed offset 22")
|
|
|
|
result = instance.query(
|
|
"SELECT count(), uniqExact(key), max(key) FROM test.view"
|
|
)
|
|
logging.debug(result)
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view SYNC;
|
|
"""
|
|
)
|
|
|
|
assert TSV(result) == TSV("22\t22\t22")
|
|
|
|
|
|
def test_exception_from_destructor(kafka_cluster):
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'xyz',
|
|
kafka_group_name = '',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONEachRow';
|
|
"""
|
|
)
|
|
instance.query_and_get_error(
|
|
"""
|
|
SELECT * FROM test.kafka;
|
|
"""
|
|
)
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'xyz',
|
|
kafka_group_name = '',
|
|
kafka_format = 'JSONEachRow';
|
|
"""
|
|
)
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka;
|
|
"""
|
|
)
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
assert TSV(instance.query("SELECT 1")) == TSV("1")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_commits_of_unprocessed_messages_on_drop(kafka_cluster, create_query_generator):
|
|
topic_name = "commits_of_unprocessed_messages_on_drop" + get_topic_postfix(
|
|
create_query_generator
|
|
)
|
|
messages = [json.dumps({"key": j + 1, "value": j + 1}) for j in range(1)]
|
|
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=f"{topic_name}_test_group",
|
|
settings={
|
|
"kafka_max_block_size": 1000,
|
|
"kafka_flush_interval_ms": 1000,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.destination SYNC;
|
|
CREATE TABLE test.destination (
|
|
key UInt64,
|
|
value UInt64,
|
|
_topic String,
|
|
_key String,
|
|
_offset UInt64,
|
|
_partition UInt64,
|
|
_timestamp Nullable(DateTime('UTC')),
|
|
_consumed_by LowCardinality(String)
|
|
)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.kafka_consumer TO test.destination AS
|
|
SELECT
|
|
key,
|
|
value,
|
|
_topic,
|
|
_key,
|
|
_offset,
|
|
_partition,
|
|
_timestamp
|
|
FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
# Waiting for test.kafka_consumer to start consume
|
|
instance.wait_for_log_line("Committed offset [0-9]+")
|
|
|
|
cancel = threading.Event()
|
|
|
|
i = [2]
|
|
|
|
def produce():
|
|
while not cancel.is_set():
|
|
messages = []
|
|
for _ in range(113):
|
|
messages.append(json.dumps({"key": i[0], "value": i[0]}))
|
|
i[0] += 1
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
time.sleep(0.5)
|
|
|
|
kafka_thread = threading.Thread(target=produce)
|
|
kafka_thread.start()
|
|
time.sleep(4)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka SYNC;
|
|
"""
|
|
)
|
|
|
|
new_create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=f"{topic_name}_test_group",
|
|
settings={
|
|
"kafka_max_block_size": 10000,
|
|
"kafka_flush_interval_ms": 1000,
|
|
},
|
|
)
|
|
instance.query(new_create_query)
|
|
|
|
cancel.set()
|
|
instance.wait_for_log_line("kafka.*Stalled", repetitions=5)
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
# SELECT key, _timestamp, _offset FROM test.destination where runningDifference(key) <> 1 ORDER BY key;
|
|
|
|
result = instance.query(
|
|
"SELECT count(), uniqExact(key), max(key) FROM test.destination"
|
|
)
|
|
logging.debug(result)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka_consumer SYNC;
|
|
DROP TABLE test.destination SYNC;
|
|
"""
|
|
)
|
|
|
|
kafka_thread.join()
|
|
assert TSV(result) == TSV("{0}\t{0}\t{0}".format(i[0] - 1)), "Missing data!"
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_bad_reschedule(kafka_cluster, create_query_generator):
|
|
topic_name = "test_bad_reschedule" + get_topic_postfix(create_query_generator)
|
|
|
|
messages = [json.dumps({"key": j + 1, "value": j + 1}) for j in range(20000)]
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 1000,
|
|
"kafka_flush_interval_ms": 1000,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.destination ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT
|
|
key,
|
|
now() as consume_ts,
|
|
value,
|
|
_topic,
|
|
_key,
|
|
_offset,
|
|
_partition,
|
|
_timestamp
|
|
FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.wait_for_log_line("Committed offset 20000")
|
|
|
|
assert (
|
|
int(
|
|
instance.query(
|
|
"SELECT max(consume_ts) - min(consume_ts) FROM test.destination"
|
|
)
|
|
)
|
|
< 8
|
|
)
|
|
|
|
|
|
def test_kafka_duplicates_when_commit_failed(kafka_cluster):
|
|
messages = [json.dumps({"key": j + 1, "value": "x" * 300}) for j in range(22)]
|
|
kafka_produce(kafka_cluster, "duplicates_when_commit_failed", messages)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE IF EXISTS test.view SYNC;
|
|
DROP TABLE IF EXISTS test.consumer SYNC;
|
|
|
|
CREATE TABLE test.kafka (key UInt64, value String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'duplicates_when_commit_failed',
|
|
kafka_group_name = 'duplicates_when_commit_failed',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_max_block_size = 20,
|
|
kafka_flush_interval_ms = 1000;
|
|
|
|
CREATE TABLE test.view (key UInt64, value String)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE MATERIALIZED VIEW test.consumer TO test.view AS
|
|
SELECT * FROM test.kafka
|
|
WHERE NOT sleepEachRow(0.25);
|
|
"""
|
|
)
|
|
|
|
instance.wait_for_log_line("Polled batch of 20 messages")
|
|
# the tricky part here is that disconnect should happen after write prefix, but before we do commit
|
|
# we have 0.25 (sleepEachRow) * 20 ( Rows ) = 5 sec window after "Polled batch of 20 messages"
|
|
# while materialized view is working to inject zookeeper failure
|
|
kafka_cluster.pause_container("kafka1")
|
|
|
|
# if we restore the connection too fast (<30sec) librdkafka will not report any timeout
|
|
# (alternative is to decrease the default session timeouts for librdkafka)
|
|
#
|
|
# when the delay is too long (>50sec) broker will decide to remove us from the consumer group,
|
|
# and will start answering "Broker: Unknown member"
|
|
instance.wait_for_log_line(
|
|
"Exception during commit attempt: Local: Waiting for coordinator", timeout=45
|
|
)
|
|
instance.wait_for_log_line("All commit attempts failed", look_behind_lines=500)
|
|
|
|
kafka_cluster.unpause_container("kafka1")
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
instance.wait_for_log_line("Committed offset 22")
|
|
|
|
result = instance.query("SELECT count(), uniqExact(key), max(key) FROM test.view")
|
|
logging.debug(result)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.consumer SYNC;
|
|
DROP TABLE test.view SYNC;
|
|
"""
|
|
)
|
|
|
|
# After https://github.com/edenhill/librdkafka/issues/2631
|
|
# timeout triggers rebalance, making further commits to the topic after getting back online
|
|
# impossible. So we have a duplicate in that scenario, but we report that situation properly.
|
|
assert TSV(result) == TSV("42\t22\t22")
|
|
|
|
|
|
# if we came to partition end we will repeat polling until reaching kafka_max_block_size or flush_interval
|
|
# that behavior is a bit questionable - we can just take a bigger pauses between polls instead -
|
|
# to do more job in a single pass, and give more rest for a thread.
|
|
# But in cases of some peaky loads in kafka topic the current contract sounds more predictable and
|
|
# easier to understand, so let's keep it as is for now.
|
|
# also we can came to eof because we drained librdkafka internal queue too fast
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_premature_flush_on_eof(kafka_cluster, create_query_generator):
|
|
topic_name = "premature_flush_on_eof" + get_topic_postfix(create_query_generator)
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
)
|
|
instance.query(
|
|
f"""
|
|
{create_query};
|
|
CREATE TABLE test.destination (
|
|
key UInt64,
|
|
value UInt64,
|
|
_topic String,
|
|
_key String,
|
|
_offset UInt64,
|
|
_partition UInt64,
|
|
_timestamp Nullable(DateTime('UTC')),
|
|
_consumed_by LowCardinality(String)
|
|
)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
"""
|
|
)
|
|
|
|
# messages created here will be consumed immediately after MV creation
|
|
# reaching topic EOF.
|
|
# But we should not do flush immediately after reaching EOF, because
|
|
# next poll can return more data, and we should respect kafka_flush_interval_ms
|
|
# and try to form bigger block
|
|
messages = [json.dumps({"key": 1, "value": 1})]
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
instance.query(
|
|
"""
|
|
CREATE MATERIALIZED VIEW test.kafka_consumer TO test.destination AS
|
|
SELECT
|
|
key,
|
|
value,
|
|
_topic,
|
|
_key,
|
|
_offset,
|
|
_partition,
|
|
_timestamp
|
|
FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
# all subscriptions/assignments done during select, so it start sending data to test.destination
|
|
# immediately after creation of MV
|
|
|
|
instance.wait_for_log_line("Polled batch of 1 messages")
|
|
instance.wait_for_log_line("Stalled")
|
|
|
|
# produce more messages after delay
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
# data was not flushed yet (it will be flushed 7.5 sec after creating MV)
|
|
assert int(instance.query("SELECT count() FROM test.destination")) == 0
|
|
|
|
instance.wait_for_log_line("Committed offset 2")
|
|
|
|
# it should be single part, i.e. single insert
|
|
result = instance.query(
|
|
"SELECT _part, count() FROM test.destination group by _part"
|
|
)
|
|
assert TSV(result) == TSV("all_1_1_0\t2")
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka_consumer;
|
|
DROP TABLE test.destination;
|
|
"""
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator, do_direct_read",
|
|
[(generate_old_create_table_query, True), (generate_new_create_table_query, False)],
|
|
)
|
|
def test_kafka_unavailable(kafka_cluster, create_query_generator, do_direct_read):
|
|
number_of_messages = 20000
|
|
topic_name = "test_bad_reschedule" + get_topic_postfix(create_query_generator)
|
|
messages = [
|
|
json.dumps({"key": j + 1, "value": j + 1}) for j in range(number_of_messages)
|
|
]
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
kafka_cluster.pause_container("kafka1")
|
|
|
|
create_query = create_query_generator(
|
|
"test_bad_reschedule",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={"kafka_max_block_size": 1000},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.destination_unavailable ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT
|
|
key,
|
|
now() as consume_ts,
|
|
value,
|
|
_topic,
|
|
_key,
|
|
_offset,
|
|
_partition,
|
|
_timestamp
|
|
FROM test.test_bad_reschedule;
|
|
"""
|
|
)
|
|
|
|
if do_direct_read:
|
|
instance.query("SELECT * FROM test.test_bad_reschedule")
|
|
instance.query("SELECT count() FROM test.destination_unavailable")
|
|
|
|
# enough to trigger issue
|
|
time.sleep(30)
|
|
kafka_cluster.unpause_container("kafka1")
|
|
|
|
result = instance.query_with_retry(
|
|
"SELECT count() FROM test.destination_unavailable",
|
|
sleep_time=1,
|
|
check_callback=lambda res: int(res) == number_of_messages,
|
|
)
|
|
|
|
assert int(result) == number_of_messages
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_issue14202(kafka_cluster, create_query_generator):
|
|
"""
|
|
INSERT INTO Kafka Engine from an empty SELECT sub query was leading to failure
|
|
"""
|
|
|
|
topic_name = "issue14202" + get_topic_postfix(create_query_generator)
|
|
create_query = create_query_generator(
|
|
"kafka_q",
|
|
"t UInt64, some_string String",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
)
|
|
instance.query(
|
|
f"""
|
|
CREATE TABLE test.empty_table (
|
|
dt Date,
|
|
some_string String
|
|
)
|
|
ENGINE = MergeTree()
|
|
PARTITION BY toYYYYMM(dt)
|
|
ORDER BY some_string;
|
|
|
|
{create_query};
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"INSERT INTO test.kafka_q SELECT t, some_string FROM ( SELECT dt AS t, some_string FROM test.empty_table )"
|
|
)
|
|
# check instance is alive
|
|
assert TSV(instance.query("SELECT 1")) == TSV("1")
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.empty_table;
|
|
DROP TABLE test.kafka_q;
|
|
"""
|
|
)
|
|
|
|
|
|
def test_kafka_csv_with_thread_per_consumer(kafka_cluster):
|
|
instance.query(
|
|
"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = 'csv_with_thread_per_consumer',
|
|
kafka_group_name = 'csv_with_thread_per_consumer',
|
|
kafka_format = 'CSV',
|
|
kafka_row_delimiter = '\\n',
|
|
kafka_num_consumers = 4,
|
|
kafka_commit_on_select = 1,
|
|
kafka_thread_per_consumer = 1;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append("{i}, {i}".format(i=i))
|
|
kafka_produce(kafka_cluster, "csv_with_thread_per_consumer", messages)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
def random_string(size=8):
|
|
return "".join(random.choices(string.ascii_uppercase + string.digits, k=size))
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_engine_put_errors_to_stream(kafka_cluster, create_query_generator):
|
|
topic_name = "kafka_engine_put_errors_to_stream" + get_topic_postfix(
|
|
create_query_generator
|
|
)
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"i Int64, s String",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 128,
|
|
"kafka_handle_error_mode": "stream",
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.kafka_data;
|
|
DROP TABLE IF EXISTS test.kafka_errors;
|
|
{create_query};
|
|
CREATE MATERIALIZED VIEW test.kafka_data (i Int64, s String)
|
|
ENGINE = MergeTree
|
|
ORDER BY i
|
|
AS SELECT i, s FROM test.kafka WHERE length(_error) == 0;
|
|
CREATE MATERIALIZED VIEW test.kafka_errors (topic String, partition Int64, offset Int64, raw String, error String)
|
|
ENGINE = MergeTree
|
|
ORDER BY (topic, offset)
|
|
AS SELECT
|
|
_topic AS topic,
|
|
_partition AS partition,
|
|
_offset AS offset,
|
|
_raw_message AS raw,
|
|
_error AS error
|
|
FROM test.kafka WHERE length(_error) > 0;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(128):
|
|
if i % 2 == 0:
|
|
messages.append(json.dumps({"i": i, "s": random_string(8)}))
|
|
else:
|
|
# Unexpected json content for table test.kafka.
|
|
messages.append(
|
|
json.dumps({"i": "n_" + random_string(4), "s": random_string(8)})
|
|
)
|
|
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
instance.wait_for_log_line("Committed offset 128")
|
|
|
|
assert TSV(instance.query("SELECT count() FROM test.kafka_data")) == TSV("64")
|
|
assert TSV(instance.query("SELECT count() FROM test.kafka_errors")) == TSV("64")
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka;
|
|
DROP TABLE test.kafka_data;
|
|
DROP TABLE test.kafka_errors;
|
|
"""
|
|
)
|
|
|
|
|
|
def gen_normal_json():
|
|
return '{"i":1000, "s":"ABC123abc"}'
|
|
|
|
|
|
def gen_malformed_json():
|
|
return '{"i":"n1000", "s":"1000"}'
|
|
|
|
|
|
def gen_message_with_jsons(jsons=10, malformed=0):
|
|
s = io.StringIO()
|
|
|
|
# we don't care on which position error will be added
|
|
# (we skip whole broken message), but we need to be
|
|
# sure that at least one error will be added,
|
|
# otherwise test will fail.
|
|
error_pos = random.randint(0, jsons - 1)
|
|
|
|
for i in range(jsons):
|
|
if malformed and i == error_pos:
|
|
s.write(gen_malformed_json())
|
|
else:
|
|
s.write(gen_normal_json())
|
|
s.write(" ")
|
|
return s.getvalue()
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_engine_put_errors_to_stream_with_random_malformed_json(
|
|
kafka_cluster, create_query_generator
|
|
):
|
|
topic_name = (
|
|
"kafka_engine_put_errors_to_stream_with_random_malformed_json"
|
|
+ get_topic_postfix(create_query_generator)
|
|
)
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"i Int64, s String",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
settings={
|
|
"kafka_max_block_size": 100,
|
|
"kafka_poll_max_batch_size": 1,
|
|
"kafka_handle_error_mode": "stream",
|
|
},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.kafka_data;
|
|
DROP TABLE IF EXISTS test.kafka_errors;
|
|
{create_query};
|
|
CREATE MATERIALIZED VIEW test.kafka_data (i Int64, s String)
|
|
ENGINE = MergeTree
|
|
ORDER BY i
|
|
AS SELECT i, s FROM test.kafka WHERE length(_error) == 0;
|
|
CREATE MATERIALIZED VIEW test.kafka_errors (topic String, partition Int64, offset Int64, raw String, error String)
|
|
ENGINE = MergeTree
|
|
ORDER BY (topic, offset)
|
|
AS SELECT
|
|
_topic AS topic,
|
|
_partition AS partition,
|
|
_offset AS offset,
|
|
_raw_message AS raw,
|
|
_error AS error
|
|
FROM test.kafka WHERE length(_error) > 0;
|
|
"""
|
|
)
|
|
|
|
messages = []
|
|
for i in range(128):
|
|
if i % 2 == 0:
|
|
messages.append(gen_message_with_jsons(10, 1))
|
|
else:
|
|
messages.append(gen_message_with_jsons(10, 0))
|
|
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
instance.wait_for_log_line("Committed offset 128")
|
|
# 64 good messages, each containing 10 rows
|
|
assert TSV(instance.query("SELECT count() FROM test.kafka_data")) == TSV("640")
|
|
# 64 bad messages, each containing some broken row
|
|
assert TSV(instance.query("SELECT count() FROM test.kafka_errors")) == TSV("64")
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.kafka;
|
|
DROP TABLE test.kafka_data;
|
|
DROP TABLE test.kafka_errors;
|
|
"""
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_formats_with_broken_message(kafka_cluster, create_query_generator):
|
|
# data was dumped from clickhouse itself in a following manner
|
|
# clickhouse-client --format=Native --query='SELECT toInt64(number) as id, toUInt16( intDiv( id, 65536 ) ) as blockNo, reinterpretAsString(19777) as val1, toFloat32(0.5) as val2, toUInt8(1) as val3 from numbers(100) ORDER BY id' | xxd -ps | tr -d '\n' | sed 's/\(..\)/\\x\1/g'
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
|
|
all_formats = {
|
|
## Text formats ##
|
|
# dumped with clickhouse-client ... | perl -pe 's/\n/\\n/; s/\t/\\t/g;'
|
|
"JSONEachRow": {
|
|
"data_sample": [
|
|
'{"id":"0","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n',
|
|
'{"id":"1","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"2","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"3","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"4","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"5","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"6","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"7","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"8","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"9","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"10","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"11","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"12","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"13","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"14","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n{"id":"15","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n',
|
|
'{"id":"0","blockNo":0,"val1":"AM","val2":0.5,"val3":1}\n',
|
|
# broken message
|
|
'{"id":"0","blockNo":"BAD","val1":"AM","val2":0.5,"val3":1}',
|
|
],
|
|
"expected": {
|
|
"raw_message": '{"id":"0","blockNo":"BAD","val1":"AM","val2":0.5,"val3":1}',
|
|
"error": 'Cannot parse input: expected \'"\' before: \'BAD","val1":"AM","val2":0.5,"val3":1}\': (while reading the value of key blockNo)',
|
|
},
|
|
"supports_empty_value": True,
|
|
"printable": True,
|
|
},
|
|
# JSONAsString doesn't fit to that test, and tested separately
|
|
"JSONCompactEachRow": {
|
|
"data_sample": [
|
|
'["0", 0, "AM", 0.5, 1]\n',
|
|
'["1", 0, "AM", 0.5, 1]\n["2", 0, "AM", 0.5, 1]\n["3", 0, "AM", 0.5, 1]\n["4", 0, "AM", 0.5, 1]\n["5", 0, "AM", 0.5, 1]\n["6", 0, "AM", 0.5, 1]\n["7", 0, "AM", 0.5, 1]\n["8", 0, "AM", 0.5, 1]\n["9", 0, "AM", 0.5, 1]\n["10", 0, "AM", 0.5, 1]\n["11", 0, "AM", 0.5, 1]\n["12", 0, "AM", 0.5, 1]\n["13", 0, "AM", 0.5, 1]\n["14", 0, "AM", 0.5, 1]\n["15", 0, "AM", 0.5, 1]\n',
|
|
'["0", 0, "AM", 0.5, 1]\n',
|
|
# broken message
|
|
'["0", "BAD", "AM", 0.5, 1]',
|
|
],
|
|
"expected": {
|
|
"raw_message": '["0", "BAD", "AM", 0.5, 1]',
|
|
"error": "Cannot parse input: expected '\"' before: 'BAD\", \"AM\", 0.5, 1]': (while reading the value of key blockNo)",
|
|
},
|
|
"supports_empty_value": True,
|
|
"printable": True,
|
|
},
|
|
"JSONCompactEachRowWithNamesAndTypes": {
|
|
"data_sample": [
|
|
'["id", "blockNo", "val1", "val2", "val3"]\n["Int64", "UInt16", "String", "Float32", "UInt8"]\n["0", 0, "AM", 0.5, 1]\n',
|
|
'["id", "blockNo", "val1", "val2", "val3"]\n["Int64", "UInt16", "String", "Float32", "UInt8"]\n["1", 0, "AM", 0.5, 1]\n["2", 0, "AM", 0.5, 1]\n["3", 0, "AM", 0.5, 1]\n["4", 0, "AM", 0.5, 1]\n["5", 0, "AM", 0.5, 1]\n["6", 0, "AM", 0.5, 1]\n["7", 0, "AM", 0.5, 1]\n["8", 0, "AM", 0.5, 1]\n["9", 0, "AM", 0.5, 1]\n["10", 0, "AM", 0.5, 1]\n["11", 0, "AM", 0.5, 1]\n["12", 0, "AM", 0.5, 1]\n["13", 0, "AM", 0.5, 1]\n["14", 0, "AM", 0.5, 1]\n["15", 0, "AM", 0.5, 1]\n',
|
|
'["id", "blockNo", "val1", "val2", "val3"]\n["Int64", "UInt16", "String", "Float32", "UInt8"]\n["0", 0, "AM", 0.5, 1]\n',
|
|
# broken message
|
|
'["0", "BAD", "AM", 0.5, 1]',
|
|
],
|
|
"expected": {
|
|
"raw_message": '["0", "BAD", "AM", 0.5, 1]',
|
|
"error": "Cannot parse JSON string: expected opening quote",
|
|
},
|
|
"printable": True,
|
|
},
|
|
"TSKV": {
|
|
"data_sample": [
|
|
"id=0\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\n",
|
|
"id=1\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=2\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=3\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=4\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=5\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=6\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=7\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=8\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=9\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=10\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=11\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=12\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=13\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=14\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\nid=15\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\n",
|
|
"id=0\tblockNo=0\tval1=AM\tval2=0.5\tval3=1\n",
|
|
# broken message
|
|
"id=0\tblockNo=BAD\tval1=AM\tval2=0.5\tval3=1\n",
|
|
],
|
|
"expected": {
|
|
"raw_message": "id=0\tblockNo=BAD\tval1=AM\tval2=0.5\tval3=1\n",
|
|
"error": "Found garbage after field in TSKV format: blockNo: (at row 1)\n",
|
|
},
|
|
"printable": True,
|
|
},
|
|
"CSV": {
|
|
"data_sample": [
|
|
'0,0,"AM",0.5,1\n',
|
|
'1,0,"AM",0.5,1\n2,0,"AM",0.5,1\n3,0,"AM",0.5,1\n4,0,"AM",0.5,1\n5,0,"AM",0.5,1\n6,0,"AM",0.5,1\n7,0,"AM",0.5,1\n8,0,"AM",0.5,1\n9,0,"AM",0.5,1\n10,0,"AM",0.5,1\n11,0,"AM",0.5,1\n12,0,"AM",0.5,1\n13,0,"AM",0.5,1\n14,0,"AM",0.5,1\n15,0,"AM",0.5,1\n',
|
|
'0,0,"AM",0.5,1\n',
|
|
# broken message
|
|
'0,"BAD","AM",0.5,1\n',
|
|
],
|
|
"expected": {
|
|
"raw_message": '0,"BAD","AM",0.5,1\n',
|
|
"error": "Cannot parse input: expected '\"' before: 'BAD\",\"AM\",0.5,1\\n'",
|
|
},
|
|
"printable": True,
|
|
"supports_empty_value": True,
|
|
},
|
|
"TSV": {
|
|
"data_sample": [
|
|
"0\t0\tAM\t0.5\t1\n",
|
|
"1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"0\t0\tAM\t0.5\t1\n",
|
|
# broken message
|
|
"0\tBAD\tAM\t0.5\t1\n",
|
|
],
|
|
"expected": {
|
|
"raw_message": "0\tBAD\tAM\t0.5\t1\n",
|
|
"error": "Cannot parse input: expected '\\t' before: 'BAD\\tAM\\t0.5\\t1\\n'",
|
|
},
|
|
"supports_empty_value": True,
|
|
"printable": True,
|
|
},
|
|
"CSVWithNames": {
|
|
"data_sample": [
|
|
'"id","blockNo","val1","val2","val3"\n0,0,"AM",0.5,1\n',
|
|
'"id","blockNo","val1","val2","val3"\n1,0,"AM",0.5,1\n2,0,"AM",0.5,1\n3,0,"AM",0.5,1\n4,0,"AM",0.5,1\n5,0,"AM",0.5,1\n6,0,"AM",0.5,1\n7,0,"AM",0.5,1\n8,0,"AM",0.5,1\n9,0,"AM",0.5,1\n10,0,"AM",0.5,1\n11,0,"AM",0.5,1\n12,0,"AM",0.5,1\n13,0,"AM",0.5,1\n14,0,"AM",0.5,1\n15,0,"AM",0.5,1\n',
|
|
'"id","blockNo","val1","val2","val3"\n0,0,"AM",0.5,1\n',
|
|
# broken message
|
|
'"id","blockNo","val1","val2","val3"\n0,"BAD","AM",0.5,1\n',
|
|
],
|
|
"expected": {
|
|
"raw_message": '"id","blockNo","val1","val2","val3"\n0,"BAD","AM",0.5,1\n',
|
|
"error": "Cannot parse input: expected '\"' before: 'BAD\",\"AM\",0.5,1\\n'",
|
|
},
|
|
"printable": True,
|
|
},
|
|
"Values": {
|
|
"data_sample": [
|
|
"(0,0,'AM',0.5,1)",
|
|
"(1,0,'AM',0.5,1),(2,0,'AM',0.5,1),(3,0,'AM',0.5,1),(4,0,'AM',0.5,1),(5,0,'AM',0.5,1),(6,0,'AM',0.5,1),(7,0,'AM',0.5,1),(8,0,'AM',0.5,1),(9,0,'AM',0.5,1),(10,0,'AM',0.5,1),(11,0,'AM',0.5,1),(12,0,'AM',0.5,1),(13,0,'AM',0.5,1),(14,0,'AM',0.5,1),(15,0,'AM',0.5,1)",
|
|
"(0,0,'AM',0.5,1)",
|
|
# broken message
|
|
"(0,'BAD','AM',0.5,1)",
|
|
],
|
|
"expected": {
|
|
"raw_message": "(0,'BAD','AM',0.5,1)",
|
|
"error": "Cannot parse string 'BAD' as UInt16: syntax error at begin of string. Note: there are toUInt16OrZero and toUInt16OrNull functions, which returns zero/NULL instead of throwing exception",
|
|
},
|
|
"supports_empty_value": True,
|
|
"printable": True,
|
|
},
|
|
"TSVWithNames": {
|
|
"data_sample": [
|
|
"id\tblockNo\tval1\tval2\tval3\n0\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\n1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\n0\t0\tAM\t0.5\t1\n",
|
|
# broken message
|
|
"id\tblockNo\tval1\tval2\tval3\n0\tBAD\tAM\t0.5\t1\n",
|
|
],
|
|
"expected": {
|
|
"raw_message": "id\tblockNo\tval1\tval2\tval3\n0\tBAD\tAM\t0.5\t1\n",
|
|
"error": "Cannot parse input: expected '\\t' before: 'BAD\\tAM\\t0.5\\t1\\n",
|
|
},
|
|
"supports_empty_value": True,
|
|
"printable": True,
|
|
},
|
|
"TSVWithNamesAndTypes": {
|
|
"data_sample": [
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n0\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n1\t0\tAM\t0.5\t1\n2\t0\tAM\t0.5\t1\n3\t0\tAM\t0.5\t1\n4\t0\tAM\t0.5\t1\n5\t0\tAM\t0.5\t1\n6\t0\tAM\t0.5\t1\n7\t0\tAM\t0.5\t1\n8\t0\tAM\t0.5\t1\n9\t0\tAM\t0.5\t1\n10\t0\tAM\t0.5\t1\n11\t0\tAM\t0.5\t1\n12\t0\tAM\t0.5\t1\n13\t0\tAM\t0.5\t1\n14\t0\tAM\t0.5\t1\n15\t0\tAM\t0.5\t1\n",
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n0\t0\tAM\t0.5\t1\n",
|
|
# broken message
|
|
"id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n0\tBAD\tAM\t0.5\t1\n",
|
|
],
|
|
"expected": {
|
|
"raw_message": "id\tblockNo\tval1\tval2\tval3\nInt64\tUInt16\tString\tFloat32\tUInt8\n0\tBAD\tAM\t0.5\t1\n",
|
|
"error": "Cannot parse input: expected '\\t' before: 'BAD\\tAM\\t0.5\\t1\\n'",
|
|
},
|
|
"printable": True,
|
|
},
|
|
"Native": {
|
|
"data_sample": [
|
|
b"\x05\x01\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x00\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x55\x49\x6e\x74\x31\x36\x00\x00\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01",
|
|
b"\x05\x0f\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x06\x00\x00\x00\x00\x00\x00\x00\x07\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\x09\x00\x00\x00\x00\x00\x00\x00\x0a\x00\x00\x00\x00\x00\x00\x00\x0b\x00\x00\x00\x00\x00\x00\x00\x0c\x00\x00\x00\x00\x00\x00\x00\x0d\x00\x00\x00\x00\x00\x00\x00\x0e\x00\x00\x00\x00\x00\x00\x00\x0f\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x55\x49\x6e\x74\x31\x36\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01\x01",
|
|
b"\x05\x01\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x00\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x55\x49\x6e\x74\x31\x36\x00\x00\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01",
|
|
# broken message
|
|
b"\x05\x01\x02\x69\x64\x05\x49\x6e\x74\x36\x34\x00\x00\x00\x00\x00\x00\x00\x00\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x06\x53\x74\x72\x69\x6e\x67\x03\x42\x41\x44\x04\x76\x61\x6c\x31\x06\x53\x74\x72\x69\x6e\x67\x02\x41\x4d\x04\x76\x61\x6c\x32\x07\x46\x6c\x6f\x61\x74\x33\x32\x00\x00\x00\x3f\x04\x76\x61\x6c\x33\x05\x55\x49\x6e\x74\x38\x01",
|
|
],
|
|
"expected": {
|
|
"raw_message": "050102696405496E743634000000000000000007626C6F636B4E6F06537472696E67034241440476616C3106537472696E6702414D0476616C3207466C6F617433320000003F0476616C330555496E743801",
|
|
"error": "Cannot parse string 'BAD' as UInt16",
|
|
},
|
|
"printable": False,
|
|
},
|
|
"RowBinary": {
|
|
"data_sample": [
|
|
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x02\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x03\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x04\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x05\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x06\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x07\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x08\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x09\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0a\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0b\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0c\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0d\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0e\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0f\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
# broken message
|
|
b"\x00\x00\x00\x00\x00\x00\x00\x00\x03\x42\x41\x44\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
],
|
|
"expected": {
|
|
"raw_message": "00000000000000000342414402414D0000003F01",
|
|
"error": "Cannot read all data. Bytes read: 9. Bytes expected: 65.: (at row 1)\n",
|
|
},
|
|
"printable": False,
|
|
},
|
|
"RowBinaryWithNamesAndTypes": {
|
|
"data_sample": [
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x55\x49\x6e\x74\x31\x36\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x55\x49\x6e\x74\x31\x36\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x02\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x03\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x04\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x05\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x06\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x07\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x08\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x09\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0a\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0b\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0c\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0d\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0e\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01\x0f\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x55\x49\x6e\x74\x31\x36\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
# broken message
|
|
b"\x05\x02\x69\x64\x07\x62\x6c\x6f\x63\x6b\x4e\x6f\x04\x76\x61\x6c\x31\x04\x76\x61\x6c\x32\x04\x76\x61\x6c\x33\x05\x49\x6e\x74\x36\x34\x06\x53\x74\x72\x69\x6e\x67\x06\x53\x74\x72\x69\x6e\x67\x07\x46\x6c\x6f\x61\x74\x33\x32\x05\x55\x49\x6e\x74\x38\x00\x00\x00\x00\x00\x00\x00\x00\x03\x42\x41\x44\x02\x41\x4d\x00\x00\x00\x3f\x01",
|
|
],
|
|
"expected": {
|
|
"raw_message": "0502696407626C6F636B4E6F0476616C310476616C320476616C3305496E74363406537472696E6706537472696E6707466C6F617433320555496E743800000000000000000342414402414D0000003F01",
|
|
"error": "Type of 'blockNo' must be UInt16, not String",
|
|
},
|
|
"printable": False,
|
|
},
|
|
"ORC": {
|
|
"data_sample": [
|
|
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# broken message
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|
|
],
|
|
"expected": {
|
|
"raw_message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
|
|
"error": "Cannot parse string 'BAD' as UInt16: syntax error at begin of string. Note: there are toUInt16OrZero and toUInt16OrNull functions, which returns zero/NULL instead of throwing exception.",
|
|
},
|
|
"printable": False,
|
|
},
|
|
}
|
|
|
|
topic_name_prefix = "format_tests_4_stream_"
|
|
topic_name_postfix = get_topic_postfix(create_query_generator)
|
|
for format_name, format_opts in list(all_formats.items()):
|
|
logging.debug(f"Set up {format_name}")
|
|
topic_name = f"{topic_name_prefix}{format_name}{topic_name_postfix}"
|
|
data_sample = format_opts["data_sample"]
|
|
data_prefix = []
|
|
raw_message = "_raw_message"
|
|
# prepend empty value when supported
|
|
if format_opts.get("supports_empty_value", False):
|
|
data_prefix = data_prefix + [""]
|
|
if format_opts.get("printable", False) == False:
|
|
raw_message = "hex(_raw_message)"
|
|
kafka_produce(kafka_cluster, topic_name, data_prefix + data_sample)
|
|
create_query = create_query_generator(
|
|
f"kafka_{format_name}",
|
|
"id Int64, blockNo UInt16, val1 String, val2 Float32, val3 UInt8",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format=format_name,
|
|
settings={
|
|
"kafka_handle_error_mode": "stream",
|
|
"kafka_flush_interval_ms": 1000,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka_{format_name};
|
|
|
|
{create_query};
|
|
|
|
DROP TABLE IF EXISTS test.kafka_data_{format_name}_mv;
|
|
CREATE MATERIALIZED VIEW test.kafka_data_{format_name}_mv ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT *, _topic, _partition, _offset FROM test.kafka_{format_name}
|
|
WHERE length(_error) = 0;
|
|
|
|
DROP TABLE IF EXISTS test.kafka_errors_{format_name}_mv;
|
|
CREATE MATERIALIZED VIEW test.kafka_errors_{format_name}_mv ENGINE=MergeTree ORDER BY tuple() AS
|
|
SELECT {raw_message} as raw_message, _error as error, _topic as topic, _partition as partition, _offset as offset FROM test.kafka_{format_name}
|
|
WHERE length(_error) > 0;
|
|
"""
|
|
)
|
|
|
|
raw_expected = """\
|
|
0 0 AM 0.5 1 {topic_name} 0 {offset_0}
|
|
1 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
2 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
3 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
4 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
5 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
6 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
7 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
8 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
9 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
10 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
11 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
12 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
13 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
14 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
15 0 AM 0.5 1 {topic_name} 0 {offset_1}
|
|
0 0 AM 0.5 1 {topic_name} 0 {offset_2}
|
|
"""
|
|
|
|
expected_rows_count = raw_expected.count("\n")
|
|
result_checker = lambda res: res.count("\n") == expected_rows_count
|
|
res = instance.query_with_retry(
|
|
f"SELECT * FROM test.kafka_data_{list(all_formats.keys())[-1]}_mv;",
|
|
retry_count=30,
|
|
sleep_time=1,
|
|
check_callback=result_checker,
|
|
)
|
|
assert result_checker(res)
|
|
|
|
for format_name, format_opts in list(all_formats.items()):
|
|
logging.debug(f"Checking {format_name}")
|
|
topic_name = f"{topic_name_prefix}{format_name}{topic_name_postfix}"
|
|
# shift offsets by 1 if format supports empty value
|
|
offsets = (
|
|
[1, 2, 3] if format_opts.get("supports_empty_value", False) else [0, 1, 2]
|
|
)
|
|
result = instance.query(
|
|
"SELECT * FROM test.kafka_data_{format_name}_mv;".format(
|
|
format_name=format_name
|
|
)
|
|
)
|
|
expected = raw_expected.format(
|
|
topic_name=topic_name,
|
|
offset_0=offsets[0],
|
|
offset_1=offsets[1],
|
|
offset_2=offsets[2],
|
|
)
|
|
# print(('Checking result\n {result} \n expected \n {expected}\n'.format(result=str(result), expected=str(expected))))
|
|
assert TSV(result) == TSV(expected), "Proper result for format: {}".format(
|
|
format_name
|
|
)
|
|
errors_result = json.loads(
|
|
instance.query(
|
|
"SELECT raw_message, error FROM test.kafka_errors_{format_name}_mv format JSONEachRow".format(
|
|
format_name=format_name
|
|
)
|
|
)
|
|
)
|
|
# print(errors_result.strip())
|
|
# print(errors_expected.strip())
|
|
assert (
|
|
errors_result["raw_message"] == format_opts["expected"]["raw_message"]
|
|
), "Proper raw_message for format: {}".format(format_name)
|
|
# Errors text can change, just checking prefixes
|
|
assert (
|
|
format_opts["expected"]["error"] in errors_result["error"]
|
|
), "Proper error for format: {}".format(format_name)
|
|
kafka_delete_topic(admin_client, topic_name)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[
|
|
generate_old_create_table_query,
|
|
generate_new_create_table_query,
|
|
],
|
|
)
|
|
def test_kafka_consumer_failover(kafka_cluster, create_query_generator):
|
|
topic_name = "kafka_consumer_failover" + get_topic_postfix(create_query_generator)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name, num_partitions=2):
|
|
consumer_group = f"{topic_name}_group"
|
|
create_queries = []
|
|
for counter in range(3):
|
|
create_queries.append(
|
|
create_query_generator(
|
|
f"kafka{counter+1}",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=consumer_group,
|
|
settings={
|
|
"kafka_max_block_size": 1,
|
|
"kafka_poll_timeout_ms": 200,
|
|
},
|
|
)
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
{create_queries[0]};
|
|
{create_queries[1]};
|
|
{create_queries[2]};
|
|
|
|
CREATE TABLE test.destination (
|
|
key UInt64,
|
|
value UInt64,
|
|
_consumed_by LowCardinality(String)
|
|
)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
|
|
CREATE MATERIALIZED VIEW test.kafka1_mv TO test.destination AS
|
|
SELECT key, value, 'kafka1' as _consumed_by
|
|
FROM test.kafka1;
|
|
|
|
CREATE MATERIALIZED VIEW test.kafka2_mv TO test.destination AS
|
|
SELECT key, value, 'kafka2' as _consumed_by
|
|
FROM test.kafka2;
|
|
|
|
CREATE MATERIALIZED VIEW test.kafka3_mv TO test.destination AS
|
|
SELECT key, value, 'kafka3' as _consumed_by
|
|
FROM test.kafka3;
|
|
"""
|
|
)
|
|
|
|
producer = KafkaProducer(
|
|
bootstrap_servers="localhost:{}".format(cluster.kafka_port),
|
|
value_serializer=producer_serializer,
|
|
key_serializer=producer_serializer,
|
|
)
|
|
|
|
## all 3 attached, 2 working
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 1, "value": 1}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 1, "value": 1}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
|
|
count_query = "SELECT count() FROM test.destination"
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > 0
|
|
)
|
|
|
|
## 2 attached, 2 working
|
|
instance.query("DETACH TABLE test.kafka1")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 2, "value": 2}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 2, "value": 2}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
## 1 attached, 1 working
|
|
instance.query("DETACH TABLE test.kafka2")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 3, "value": 3}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 3, "value": 3}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
## 2 attached, 2 working
|
|
instance.query("ATTACH TABLE test.kafka1")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 4, "value": 4}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 4, "value": 4}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
## 1 attached, 1 working
|
|
instance.query("DETACH TABLE test.kafka3")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 5, "value": 5}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 5, "value": 5}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
## 2 attached, 2 working
|
|
instance.query("ATTACH TABLE test.kafka2")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 6, "value": 6}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 6, "value": 6}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
## 3 attached, 2 working
|
|
instance.query("ATTACH TABLE test.kafka3")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 7, "value": 7}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 7, "value": 7}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
## 2 attached, same 2 working
|
|
instance.query("DETACH TABLE test.kafka3")
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 8, "value": 8}),
|
|
partition=0,
|
|
)
|
|
producer.send(
|
|
topic=topic_name,
|
|
value=json.dumps({"key": 8, "value": 8}),
|
|
partition=1,
|
|
)
|
|
producer.flush()
|
|
prev_count = instance.query_with_retry(
|
|
count_query, check_callback=lambda res: int(res) > prev_count
|
|
)
|
|
|
|
|
|
def test_kafka_predefined_configuration(kafka_cluster):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
topic_name = "conf"
|
|
kafka_create_topic(admin_client, topic_name)
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append("{i}, {i}".format(i=i))
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
instance.query(
|
|
f"""
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64) ENGINE = Kafka(kafka1, kafka_format='CSV');
|
|
"""
|
|
)
|
|
|
|
result = ""
|
|
while True:
|
|
result += instance.query("SELECT * FROM test.kafka", ignore_error=True)
|
|
if kafka_check_result(result):
|
|
break
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
# https://github.com/ClickHouse/ClickHouse/issues/26643
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_issue26643(kafka_cluster, create_query_generator):
|
|
producer = KafkaProducer(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
|
|
value_serializer=producer_serializer,
|
|
)
|
|
topic_name = "test_issue26643" + get_topic_postfix(create_query_generator)
|
|
thread_per_consumer = must_use_thread_per_consumer(create_query_generator)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
msg = message_with_repeated_pb2.Message(
|
|
tnow=1629000000,
|
|
server="server1",
|
|
clien="host1",
|
|
sPort=443,
|
|
cPort=50000,
|
|
r=[
|
|
message_with_repeated_pb2.dd(
|
|
name="1", type=444, ttl=123123, data=b"adsfasd"
|
|
),
|
|
message_with_repeated_pb2.dd(name="2"),
|
|
],
|
|
method="GET",
|
|
)
|
|
|
|
data = b""
|
|
serialized_msg = msg.SerializeToString()
|
|
data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
|
|
|
|
msg = message_with_repeated_pb2.Message(tnow=1629000002)
|
|
|
|
serialized_msg = msg.SerializeToString()
|
|
data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
|
|
|
|
producer.send(topic_name, value=data)
|
|
|
|
data = _VarintBytes(len(serialized_msg)) + serialized_msg
|
|
producer.send(topic_name, value=data)
|
|
producer.flush()
|
|
|
|
create_query = create_query_generator(
|
|
"test_queue",
|
|
"""`tnow` UInt32,
|
|
`server` String,
|
|
`client` String,
|
|
`sPort` UInt16,
|
|
`cPort` UInt16,
|
|
`r.name` Array(String),
|
|
`r.class` Array(UInt16),
|
|
`r.type` Array(UInt16),
|
|
`r.ttl` Array(UInt32),
|
|
`r.data` Array(String),
|
|
`method` String""",
|
|
topic_list=topic_name,
|
|
consumer_group=f"{topic_name}_group",
|
|
format="Protobuf",
|
|
settings={
|
|
"kafka_schema": "message_with_repeated.proto:Message",
|
|
"kafka_skip_broken_messages": 10000,
|
|
"kafka_thread_per_consumer": thread_per_consumer,
|
|
},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
{create_query};
|
|
|
|
SET allow_suspicious_low_cardinality_types=1;
|
|
|
|
CREATE TABLE test.log
|
|
(
|
|
`tnow` DateTime('Asia/Istanbul') CODEC(DoubleDelta, LZ4),
|
|
`server` LowCardinality(String),
|
|
`client` LowCardinality(String),
|
|
`sPort` LowCardinality(UInt16),
|
|
`cPort` UInt16 CODEC(T64, LZ4),
|
|
`r.name` Array(String),
|
|
`r.class` Array(LowCardinality(UInt16)),
|
|
`r.type` Array(LowCardinality(UInt16)),
|
|
`r.ttl` Array(LowCardinality(UInt32)),
|
|
`r.data` Array(String),
|
|
`method` LowCardinality(String)
|
|
)
|
|
ENGINE = MergeTree
|
|
PARTITION BY toYYYYMMDD(tnow)
|
|
ORDER BY (tnow, server)
|
|
TTL toDate(tnow) + toIntervalMonth(1000)
|
|
SETTINGS index_granularity = 16384, merge_with_ttl_timeout = 7200;
|
|
|
|
CREATE MATERIALIZED VIEW test.test_consumer TO test.log AS
|
|
SELECT
|
|
toDateTime(a.tnow) AS tnow,
|
|
a.server AS server,
|
|
a.client AS client,
|
|
a.sPort AS sPort,
|
|
a.cPort AS cPort,
|
|
a.`r.name` AS `r.name`,
|
|
a.`r.class` AS `r.class`,
|
|
a.`r.type` AS `r.type`,
|
|
a.`r.ttl` AS `r.ttl`,
|
|
a.`r.data` AS `r.data`,
|
|
a.method AS method
|
|
FROM test.test_queue AS a;
|
|
"""
|
|
)
|
|
|
|
instance.wait_for_log_line("Committed offset")
|
|
result = instance.query("SELECT * FROM test.log")
|
|
|
|
expected = """\
|
|
2021-08-15 07:00:00 server1 443 50000 ['1','2'] [0,0] [444,0] [123123,0] ['adsfasd',''] GET
|
|
2021-08-15 07:00:02 0 0 [] [] [] [] []
|
|
2021-08-15 07:00:02 0 0 [] [] [] [] []
|
|
"""
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_num_consumers_limit(kafka_cluster, create_query_generator):
|
|
instance.query("DROP TABLE IF EXISTS test.kafka")
|
|
|
|
thread_per_consumer = must_use_thread_per_consumer(create_query_generator)
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
settings={
|
|
"kafka_num_consumers": 100,
|
|
"kafka_thread_per_consumer": thread_per_consumer,
|
|
},
|
|
)
|
|
error = instance.query_and_get_error(create_query)
|
|
|
|
assert (
|
|
"BAD_ARGUMENTS" in error
|
|
and "The number of consumers can not be bigger than" in error
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
SET kafka_disable_num_consumers_limit = 1;
|
|
{create_query};
|
|
"""
|
|
)
|
|
|
|
instance.query("DROP TABLE test.kafka")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_format_with_prefix_and_suffix(kafka_cluster, create_query_generator):
|
|
topic_name = "custom" + get_topic_postfix(create_query_generator)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="CustomSeparated",
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
{create_query};
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
"INSERT INTO test.kafka select number*10 as key, number*100 as value from numbers(2) settings format_custom_result_before_delimiter='<prefix>\n', format_custom_result_after_delimiter='<suffix>\n'"
|
|
)
|
|
|
|
message_count = 2
|
|
messages = kafka_consume_with_retry(kafka_cluster, topic_name, message_count)
|
|
|
|
assert len(messages) == 2
|
|
|
|
assert (
|
|
"".join(messages)
|
|
== "<prefix>\n0\t0\n<suffix>\n<prefix>\n10\t100\n<suffix>\n"
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_max_rows_per_message(kafka_cluster, create_query_generator):
|
|
topic_name = "custom_max_rows_per_message" + get_topic_postfix(
|
|
create_query_generator
|
|
)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
num_rows = 5
|
|
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="CustomSeparated",
|
|
settings={
|
|
"format_custom_result_before_delimiter": "<prefix>\n",
|
|
"format_custom_result_after_delimiter": "<suffix>\n",
|
|
"kafka_max_rows_per_message": 3,
|
|
},
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY (key, value) AS
|
|
SELECT key, value FROM test.kafka;
|
|
"""
|
|
)
|
|
|
|
instance.query(
|
|
f"INSERT INTO test.kafka select number*10 as key, number*100 as value from numbers({num_rows}) settings format_custom_result_before_delimiter='<prefix>\n', format_custom_result_after_delimiter='<suffix>\n'"
|
|
)
|
|
|
|
message_count = 2
|
|
messages = kafka_consume_with_retry(kafka_cluster, topic_name, message_count)
|
|
|
|
assert len(messages) == message_count
|
|
|
|
assert (
|
|
"".join(messages)
|
|
== "<prefix>\n0\t0\n10\t100\n20\t200\n<suffix>\n<prefix>\n30\t300\n40\t400\n<suffix>\n"
|
|
)
|
|
|
|
instance.query_with_retry(
|
|
"SELECT count() FROM test.view",
|
|
check_callback=lambda res: int(res) == num_rows,
|
|
)
|
|
|
|
result = instance.query("SELECT * FROM test.view")
|
|
assert result == "0\t0\n10\t100\n20\t200\n30\t300\n40\t400\n"
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_row_based_formats(kafka_cluster, create_query_generator):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
|
|
for format_name in [
|
|
"TSV",
|
|
"TSVWithNamesAndTypes",
|
|
"TSKV",
|
|
"CSV",
|
|
"CSVWithNamesAndTypes",
|
|
"CustomSeparatedWithNamesAndTypes",
|
|
"Values",
|
|
"JSON",
|
|
"JSONEachRow",
|
|
"JSONCompactEachRow",
|
|
"JSONCompactEachRowWithNamesAndTypes",
|
|
"JSONObjectEachRow",
|
|
"Avro",
|
|
"RowBinary",
|
|
"RowBinaryWithNamesAndTypes",
|
|
"MsgPack",
|
|
]:
|
|
logging.debug("Checking {format_name}")
|
|
|
|
topic_name = format_name + get_topic_postfix(create_query_generator)
|
|
table_name = f"kafka_{format_name}"
|
|
|
|
with kafka_topic(admin_client, topic_name):
|
|
num_rows = 10
|
|
max_rows_per_message = 5
|
|
message_count = num_rows / max_rows_per_message
|
|
|
|
create_query = create_query_generator(
|
|
table_name,
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format=format_name,
|
|
settings={"kafka_max_rows_per_message": max_rows_per_message},
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.{table_name};
|
|
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY (key, value) AS
|
|
SELECT key, value FROM test.{table_name};
|
|
|
|
INSERT INTO test.{table_name} SELECT number * 10 as key, number * 100 as value FROM numbers({num_rows});
|
|
"""
|
|
)
|
|
|
|
messages = kafka_consume_with_retry(
|
|
kafka_cluster, topic_name, message_count, need_decode=False
|
|
)
|
|
|
|
assert len(messages) == message_count
|
|
|
|
instance.query_with_retry(
|
|
"SELECT count() FROM test.view",
|
|
check_callback=lambda res: int(res) == num_rows,
|
|
)
|
|
|
|
result = instance.query("SELECT * FROM test.view")
|
|
expected = ""
|
|
for i in range(num_rows):
|
|
expected += str(i * 10) + "\t" + str(i * 100) + "\n"
|
|
assert result == expected
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_block_based_formats_1(kafka_cluster, create_query_generator):
|
|
topic_name = "pretty_space" + get_topic_postfix(create_query_generator)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
create_query = create_query_generator(
|
|
"kafka",
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format="PrettySpace",
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
|
|
{create_query};
|
|
|
|
INSERT INTO test.kafka SELECT number * 10 as key, number * 100 as value FROM numbers(5) settings max_block_size=2, optimize_trivial_insert_select=0, output_format_pretty_color=1, output_format_pretty_row_numbers=0;
|
|
"""
|
|
)
|
|
|
|
message_count = 3
|
|
messages = kafka_consume_with_retry(kafka_cluster, topic_name, message_count)
|
|
assert len(messages) == 3
|
|
|
|
data = []
|
|
for message in messages:
|
|
splitted = message.split("\n")
|
|
assert splitted[0] == " \x1b[1mkey\x1b[0m \x1b[1mvalue\x1b[0m"
|
|
assert splitted[1] == ""
|
|
assert splitted[-1] == ""
|
|
data += [line.split() for line in splitted[2:-1]]
|
|
|
|
assert data == [
|
|
["0", "0"],
|
|
["10", "100"],
|
|
["20", "200"],
|
|
["30", "300"],
|
|
["40", "400"],
|
|
]
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_block_based_formats_2(kafka_cluster, create_query_generator):
|
|
admin_client = get_admin_client(kafka_cluster)
|
|
num_rows = 100
|
|
message_count = 9
|
|
|
|
for format_name in [
|
|
"JSONColumns",
|
|
"Native",
|
|
"Arrow",
|
|
"Parquet",
|
|
"ORC",
|
|
"JSONCompactColumns",
|
|
]:
|
|
topic_name = format_name + get_topic_postfix(create_query_generator)
|
|
table_name = f"kafka_{format_name}"
|
|
logging.debug(f"Checking format {format_name}")
|
|
with kafka_topic(admin_client, topic_name):
|
|
create_query = create_query_generator(
|
|
table_name,
|
|
"key UInt64, value UInt64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
format=format_name,
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.{table_name};
|
|
|
|
{create_query};
|
|
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY (key, value) AS
|
|
SELECT key, value FROM test.{table_name};
|
|
|
|
INSERT INTO test.{table_name} SELECT number * 10 as key, number * 100 as value FROM numbers({num_rows}) settings max_block_size=12, optimize_trivial_insert_select=0;
|
|
"""
|
|
)
|
|
messages = kafka_consume_with_retry(
|
|
kafka_cluster, topic_name, message_count, need_decode=False
|
|
)
|
|
assert len(messages) == message_count
|
|
|
|
rows = int(
|
|
instance.query_with_retry(
|
|
"SELECT count() FROM test.view",
|
|
check_callback=lambda res: int(res) == num_rows,
|
|
)
|
|
)
|
|
|
|
assert rows == num_rows
|
|
|
|
result = instance.query("SELECT * FROM test.view ORDER by key")
|
|
expected = ""
|
|
for i in range(num_rows):
|
|
expected += str(i * 10) + "\t" + str(i * 100) + "\n"
|
|
assert result == expected
|
|
|
|
|
|
def test_system_kafka_consumers(kafka_cluster):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
|
|
topic = "system_kafka_cons"
|
|
kafka_create_topic(admin_client, topic)
|
|
|
|
# Check that format_csv_delimiter parameter works now - as part of all available format settings.
|
|
kafka_produce(
|
|
kafka_cluster,
|
|
topic,
|
|
["1|foo", "2|bar", "42|answer", "100|multi\n101|row\n103|message"],
|
|
)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
|
|
CREATE TABLE test.kafka (a UInt64, b String)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic}',
|
|
kafka_group_name = '{topic}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'CSV',
|
|
kafka_row_delimiter = '\\n',
|
|
format_csv_delimiter = '|';
|
|
"""
|
|
)
|
|
|
|
result = instance.query("SELECT * FROM test.kafka ORDER BY a;")
|
|
|
|
result_system_kafka_consumers = instance.query(
|
|
"""
|
|
create or replace function stable_timestamp as
|
|
(d)->multiIf(d==toDateTime('1970-01-01 00:00:00'), 'never', abs(dateDiff('second', d, now())) < 30, 'now', toString(d));
|
|
|
|
SELECT database, table, length(consumer_id), assignments.topic, assignments.partition_id,
|
|
assignments.current_offset,
|
|
if(length(exceptions.time)>0, exceptions.time[1]::String, 'never') as last_exception_time_,
|
|
if(length(exceptions.text)>0, exceptions.text[1], 'no exception') as last_exception_,
|
|
stable_timestamp(last_poll_time) as last_poll_time_, num_messages_read, stable_timestamp(last_commit_time) as last_commit_time_,
|
|
num_commits, stable_timestamp(last_rebalance_time) as last_rebalance_time_,
|
|
num_rebalance_revocations, num_rebalance_assignments, is_currently_used
|
|
FROM system.kafka_consumers WHERE database='test' and table='kafka' format Vertical;
|
|
"""
|
|
)
|
|
logging.debug(f"result_system_kafka_consumers: {result_system_kafka_consumers}")
|
|
assert (
|
|
result_system_kafka_consumers
|
|
== """Row 1:
|
|
──────
|
|
database: test
|
|
table: kafka
|
|
length(consumer_id): 67
|
|
assignments.topic: ['system_kafka_cons']
|
|
assignments.partition_id: [0]
|
|
assignments.current_offset: [4]
|
|
last_exception_time_: never
|
|
last_exception_: no exception
|
|
last_poll_time_: now
|
|
num_messages_read: 4
|
|
last_commit_time_: now
|
|
num_commits: 1
|
|
last_rebalance_time_: never
|
|
num_rebalance_revocations: 0
|
|
num_rebalance_assignments: 1
|
|
is_currently_used: 0
|
|
"""
|
|
)
|
|
|
|
instance.query("DROP TABLE test.kafka")
|
|
kafka_delete_topic(admin_client, topic)
|
|
|
|
|
|
def test_system_kafka_consumers_rebalance(kafka_cluster, max_retries=15):
|
|
# based on test_kafka_consumer_hang2
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
|
|
producer = KafkaProducer(
|
|
bootstrap_servers="localhost:{}".format(cluster.kafka_port),
|
|
value_serializer=producer_serializer,
|
|
key_serializer=producer_serializer,
|
|
)
|
|
|
|
topic = "system_kafka_cons2"
|
|
kafka_create_topic(admin_client, topic, num_partitions=2)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.kafka2;
|
|
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic}',
|
|
kafka_group_name = '{topic}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONEachRow';
|
|
|
|
CREATE TABLE test.kafka2 (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = '{topic}',
|
|
kafka_format = 'JSONEachRow';
|
|
"""
|
|
)
|
|
|
|
producer.send(topic=topic, value=json.dumps({"key": 1, "value": 1}), partition=0)
|
|
producer.send(topic=topic, value=json.dumps({"key": 11, "value": 11}), partition=1)
|
|
time.sleep(3)
|
|
|
|
# first consumer subscribe the topic, try to poll some data, and go to rest
|
|
instance.query("SELECT * FROM test.kafka")
|
|
|
|
# second consumer do the same leading to rebalance in the first
|
|
# consumer, try to poll some data
|
|
instance.query("SELECT * FROM test.kafka2")
|
|
|
|
producer.send(topic=topic, value=json.dumps({"key": 1, "value": 1}), partition=0)
|
|
producer.send(topic=topic, value=json.dumps({"key": 10, "value": 10}), partition=1)
|
|
time.sleep(3)
|
|
|
|
instance.query("SELECT * FROM test.kafka")
|
|
instance.query("SELECT * FROM test.kafka2")
|
|
instance.query("SELECT * FROM test.kafka")
|
|
instance.query("SELECT * FROM test.kafka2")
|
|
|
|
result_system_kafka_consumers = instance.query(
|
|
"""
|
|
create or replace function stable_timestamp as
|
|
(d)->multiIf(d==toDateTime('1970-01-01 00:00:00'), 'never', abs(dateDiff('second', d, now())) < 30, 'now', toString(d));
|
|
SELECT database, table, length(consumer_id), assignments.topic, assignments.partition_id,
|
|
assignments.current_offset,
|
|
if(length(exceptions.time)>0, exceptions.time[1]::String, 'never') as last_exception_time_,
|
|
if(length(exceptions.text)>0, exceptions.text[1], 'no exception') as last_exception_,
|
|
stable_timestamp(last_poll_time) as last_poll_time_, stable_timestamp(last_commit_time) as last_commit_time_,
|
|
num_commits, stable_timestamp(last_rebalance_time) as last_rebalance_time_,
|
|
num_rebalance_revocations, num_rebalance_assignments, is_currently_used
|
|
FROM system.kafka_consumers WHERE database='test' and table IN ('kafka', 'kafka2') format Vertical;
|
|
"""
|
|
)
|
|
logging.debug(f"result_system_kafka_consumers: {result_system_kafka_consumers}")
|
|
assert (
|
|
result_system_kafka_consumers
|
|
== """Row 1:
|
|
──────
|
|
database: test
|
|
table: kafka
|
|
length(consumer_id): 67
|
|
assignments.topic: ['system_kafka_cons2']
|
|
assignments.partition_id: [0]
|
|
assignments.current_offset: [2]
|
|
last_exception_time_: never
|
|
last_exception_: no exception
|
|
last_poll_time_: now
|
|
last_commit_time_: now
|
|
num_commits: 2
|
|
last_rebalance_time_: now
|
|
num_rebalance_revocations: 1
|
|
num_rebalance_assignments: 2
|
|
is_currently_used: 0
|
|
|
|
Row 2:
|
|
──────
|
|
database: test
|
|
table: kafka2
|
|
length(consumer_id): 68
|
|
assignments.topic: ['system_kafka_cons2']
|
|
assignments.partition_id: [1]
|
|
assignments.current_offset: [2]
|
|
last_exception_time_: never
|
|
last_exception_: no exception
|
|
last_poll_time_: now
|
|
last_commit_time_: now
|
|
num_commits: 1
|
|
last_rebalance_time_: never
|
|
num_rebalance_revocations: 0
|
|
num_rebalance_assignments: 1
|
|
is_currently_used: 0
|
|
"""
|
|
)
|
|
|
|
instance.query("DROP TABLE test.kafka")
|
|
instance.query("DROP TABLE test.kafka2")
|
|
|
|
kafka_delete_topic(admin_client, topic)
|
|
|
|
|
|
def test_system_kafka_consumers_rebalance_mv(kafka_cluster, max_retries=15):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
|
|
producer = KafkaProducer(
|
|
bootstrap_servers="localhost:{}".format(cluster.kafka_port),
|
|
value_serializer=producer_serializer,
|
|
key_serializer=producer_serializer,
|
|
)
|
|
|
|
topic = "system_kafka_cons_mv"
|
|
kafka_create_topic(admin_client, topic, num_partitions=2)
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka;
|
|
DROP TABLE IF EXISTS test.kafka2;
|
|
DROP TABLE IF EXISTS test.kafka_persistent;
|
|
DROP TABLE IF EXISTS test.kafka_persistent2;
|
|
|
|
CREATE TABLE test.kafka (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic}',
|
|
kafka_group_name = '{topic}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_format = 'JSONEachRow';
|
|
|
|
CREATE TABLE test.kafka2 (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{topic}',
|
|
kafka_commit_on_select = 1,
|
|
kafka_group_name = '{topic}',
|
|
kafka_format = 'JSONEachRow';
|
|
|
|
CREATE TABLE test.kafka_persistent (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
CREATE TABLE test.kafka_persistent2 (key UInt64, value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
|
|
CREATE MATERIALIZED VIEW test.persistent_kafka_mv TO test.kafka_persistent AS
|
|
SELECT key, value
|
|
FROM test.kafka;
|
|
|
|
CREATE MATERIALIZED VIEW test.persistent_kafka_mv2 TO test.kafka_persistent2 AS
|
|
SELECT key, value
|
|
FROM test.kafka2;
|
|
"""
|
|
)
|
|
|
|
producer.send(topic=topic, value=json.dumps({"key": 1, "value": 1}), partition=0)
|
|
producer.send(topic=topic, value=json.dumps({"key": 11, "value": 11}), partition=1)
|
|
time.sleep(3)
|
|
|
|
retries = 0
|
|
result_rdkafka_stat = ""
|
|
while True:
|
|
result_rdkafka_stat = instance.query(
|
|
"""
|
|
SELECT table, JSONExtractString(rdkafka_stat, 'type')
|
|
FROM system.kafka_consumers WHERE database='test' and table = 'kafka' format Vertical;
|
|
"""
|
|
)
|
|
if result_rdkafka_stat.find("consumer") or retries > max_retries:
|
|
break
|
|
retries += 1
|
|
time.sleep(1)
|
|
|
|
assert (
|
|
result_rdkafka_stat
|
|
== """Row 1:
|
|
──────
|
|
table: kafka
|
|
JSONExtractString(rdkafka_stat, 'type'): consumer
|
|
"""
|
|
)
|
|
|
|
instance.query("DROP TABLE test.kafka")
|
|
instance.query("DROP TABLE test.kafka2")
|
|
instance.query("DROP TABLE test.kafka_persistent")
|
|
instance.query("DROP TABLE test.kafka_persistent2")
|
|
instance.query("DROP TABLE test.persistent_kafka_mv")
|
|
instance.query("DROP TABLE test.persistent_kafka_mv2")
|
|
|
|
kafka_delete_topic(admin_client, topic)
|
|
|
|
|
|
def test_formats_errors(kafka_cluster):
|
|
admin_client = KafkaAdminClient(
|
|
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
|
|
)
|
|
|
|
for format_name in [
|
|
"Template",
|
|
"Regexp",
|
|
"TSV",
|
|
"TSVWithNamesAndTypes",
|
|
"TSKV",
|
|
"CSV",
|
|
"CSVWithNames",
|
|
"CSVWithNamesAndTypes",
|
|
"CustomSeparated",
|
|
"CustomSeparatedWithNames",
|
|
"CustomSeparatedWithNamesAndTypes",
|
|
"Values",
|
|
"JSON",
|
|
"JSONEachRow",
|
|
"JSONStringsEachRow",
|
|
"JSONCompactEachRow",
|
|
"JSONCompactEachRowWithNamesAndTypes",
|
|
"JSONObjectEachRow",
|
|
"Avro",
|
|
"RowBinary",
|
|
"RowBinaryWithNamesAndTypes",
|
|
"MsgPack",
|
|
"JSONColumns",
|
|
"JSONCompactColumns",
|
|
"JSONColumnsWithMetadata",
|
|
"BSONEachRow",
|
|
"Native",
|
|
"Arrow",
|
|
"Parquet",
|
|
"ORC",
|
|
"JSONCompactColumns",
|
|
"Npy",
|
|
"ParquetMetadata",
|
|
"CapnProto",
|
|
"Protobuf",
|
|
"ProtobufSingle",
|
|
"ProtobufList",
|
|
"DWARF",
|
|
"HiveText",
|
|
"MySQLDump",
|
|
]:
|
|
with kafka_topic(admin_client, format_name):
|
|
table_name = f"kafka_{format_name}"
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.{table_name};
|
|
|
|
CREATE TABLE test.{table_name} (key UInt64, value UInt64)
|
|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
|
kafka_topic_list = '{format_name}',
|
|
kafka_group_name = '{format_name}',
|
|
kafka_format = '{format_name}',
|
|
kafka_max_rows_per_message = 5,
|
|
format_template_row='template_row.format',
|
|
format_regexp='id: (.+?)',
|
|
input_format_with_names_use_header=0,
|
|
format_schema='key_value_message:Message';
|
|
|
|
CREATE MATERIALIZED VIEW test.view ENGINE=MergeTree ORDER BY (key, value) AS
|
|
SELECT key, value FROM test.{table_name};
|
|
"""
|
|
)
|
|
|
|
kafka_produce(
|
|
kafka_cluster,
|
|
format_name,
|
|
["Broken message\nBroken message\nBroken message\n"],
|
|
)
|
|
|
|
num_errors = int(
|
|
instance.query_with_retry(
|
|
f"SELECT length(exceptions.text) from system.kafka_consumers where database = 'test' and table = '{table_name}'",
|
|
check_callback=lambda res: int(res) > 0,
|
|
)
|
|
)
|
|
|
|
assert num_errors > 0
|
|
|
|
instance.query(f"DROP TABLE test.{table_name}")
|
|
instance.query("DROP TABLE test.view")
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_multiple_read_in_materialized_views(kafka_cluster, create_query_generator):
|
|
topic_name = "multiple_read_from_mv" + get_topic_postfix(create_query_generator)
|
|
|
|
with kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
create_query = create_query_generator(
|
|
"kafka_multiple_read_input",
|
|
"id Int64",
|
|
topic_list=topic_name,
|
|
consumer_group=topic_name,
|
|
)
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.kafka_multiple_read_input SYNC;
|
|
DROP TABLE IF EXISTS test.kafka_multiple_read_table;
|
|
DROP TABLE IF EXISTS test.kafka_multiple_read_mv;
|
|
|
|
{create_query};
|
|
|
|
CREATE TABLE test.kafka_multiple_read_table (id Int64)
|
|
ENGINE = MergeTree
|
|
ORDER BY id;
|
|
|
|
|
|
CREATE MATERIALIZED VIEW test.kafka_multiple_read_mv TO test.kafka_multiple_read_table AS
|
|
SELECT id
|
|
FROM test.kafka_multiple_read_input
|
|
WHERE id NOT IN (
|
|
SELECT id
|
|
FROM test.kafka_multiple_read_table
|
|
WHERE id IN (
|
|
SELECT id
|
|
FROM test.kafka_multiple_read_input
|
|
)
|
|
);
|
|
"""
|
|
)
|
|
|
|
kafka_produce(
|
|
kafka_cluster, topic_name, [json.dumps({"id": 42}), json.dumps({"id": 43})]
|
|
)
|
|
|
|
expected_result = "42\n43\n"
|
|
res = instance.query_with_retry(
|
|
f"SELECT id FROM test.kafka_multiple_read_table ORDER BY id",
|
|
check_callback=lambda res: res == expected_result,
|
|
)
|
|
assert res == expected_result
|
|
|
|
# Verify that the query deduplicates the records as it meant to be
|
|
messages = []
|
|
for _ in range(0, 10):
|
|
messages.append(json.dumps({"id": 42}))
|
|
messages.append(json.dumps({"id": 43}))
|
|
|
|
messages.append(json.dumps({"id": 44}))
|
|
|
|
kafka_produce(kafka_cluster, topic_name, messages)
|
|
|
|
expected_result = "42\n43\n44\n"
|
|
res = instance.query_with_retry(
|
|
f"SELECT id FROM test.kafka_multiple_read_table ORDER BY id",
|
|
check_callback=lambda res: res == expected_result,
|
|
)
|
|
assert res == expected_result
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE test.kafka_multiple_read_input;
|
|
DROP TABLE test.kafka_multiple_read_table;
|
|
DROP TABLE test.kafka_multiple_read_mv;
|
|
"""
|
|
)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"create_query_generator",
|
|
[generate_old_create_table_query, generate_new_create_table_query],
|
|
)
|
|
def test_kafka_null_message(kafka_cluster, create_query_generator):
|
|
topic_name = "null_message"
|
|
|
|
instance.query(
|
|
f"""
|
|
DROP TABLE IF EXISTS test.null_message_view;
|
|
DROP TABLE IF EXISTS test.null_message_consumer;
|
|
DROP TABLE IF EXISTS test.null_message_kafka;
|
|
|
|
{create_query_generator("null_message_kafka", "value UInt64", topic_list=topic_name, consumer_group="mv")};
|
|
CREATE TABLE test.null_message_view (value UInt64)
|
|
ENGINE = MergeTree()
|
|
ORDER BY value;
|
|
CREATE MATERIALIZED VIEW test.null_message_consumer TO test.null_message_view AS
|
|
SELECT * FROM test.null_message_kafka;
|
|
"""
|
|
)
|
|
|
|
message_key_values = []
|
|
for i in range(5):
|
|
# Here the key is key for Kafka message
|
|
message = json.dumps({"value": i}) if i != 3 else None
|
|
message_key_values.append({"key": f"{i}".encode(), "message": message})
|
|
|
|
producer = get_kafka_producer(kafka_cluster.kafka_port, producer_serializer, 15)
|
|
for message_kv in message_key_values:
|
|
producer.send(
|
|
topic=topic_name, key=message_kv["key"], value=message_kv["message"]
|
|
)
|
|
producer.flush()
|
|
|
|
expected = TSV(
|
|
"""
|
|
0
|
|
1
|
|
2
|
|
4
|
|
"""
|
|
)
|
|
with existing_kafka_topic(get_admin_client(kafka_cluster), topic_name):
|
|
result = instance.query_with_retry(
|
|
"SELECT * FROM test.null_message_view",
|
|
check_callback=lambda res: TSV(res) == expected,
|
|
)
|
|
|
|
assert expected == TSV(result)
|
|
|
|
instance.query(
|
|
"""
|
|
DROP TABLE test.null_message_consumer SYNC;
|
|
DROP TABLE test.null_message_view;
|
|
DROP TABLE test.null_message_kafka SYNC;
|
|
"""
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
cluster.start()
|
|
input("Cluster created, press any key to destroy...")
|
|
cluster.shutdown()
|