ClickHouse/tests/integration/test_storage_kafka/test.py
2023-08-10 22:35:05 +00:00

4841 lines
245 KiB
Python

import json
import os.path as p
import random
import socket
import threading
import time
import logging
import io
import string
import ast
import math
import avro.schema
import avro.io
import avro.datafile
from confluent_kafka.avro.cached_schema_registry_client import (
CachedSchemaRegistryClient,
)
from confluent_kafka.avro.serializer.message_serializer import MessageSerializer
import kafka.errors
import pytest
from google.protobuf.internal.encoder import _VarintBytes
from helpers.client import QueryRuntimeException
from helpers.cluster import ClickHouseCluster
from helpers.network import PartitionManager
from helpers.test_tools import TSV
from kafka import KafkaAdminClient, KafkaProducer, KafkaConsumer, BrokerConnection
from kafka.protocol.admin import DescribeGroupsRequest_v1
from kafka.protocol.group import MemberAssignment
from kafka.admin import NewTopic
# protoc --version
# libprotoc 3.0.0
# # to create kafka_pb2.py
# protoc --python_out=. kafka.proto
from . import kafka_pb2
from . import social_pb2
from . import message_with_repeated_pb2
# TODO: add test for run-time offset update in CH, if we manually update it on Kafka side.
# TODO: add test for SELECT LIMIT is working.
cluster = ClickHouseCluster(__file__)
instance = cluster.add_instance(
"instance",
main_configs=["configs/kafka.xml", "configs/named_collection.xml"],
user_configs=["configs/users.xml"],
with_kafka=True,
with_zookeeper=True, # For Replicated Table
macros={
"kafka_broker": "kafka1",
"kafka_topic_old": "old",
"kafka_group_name_old": "old",
"kafka_topic_new": "new",
"kafka_group_name_new": "new",
"kafka_client_id": "instance",
"kafka_format_json_each_row": "JSONEachRow",
},
clickhouse_path_dir="clickhouse_path",
)
def get_kafka_producer(port, serializer, retries):
errors = []
for _ in range(retries):
try:
producer = KafkaProducer(
bootstrap_servers="localhost:{}".format(port),
value_serializer=serializer,
)
logging.debug("Kafka Connection establised: localhost:{}".format(port))
return producer
except Exception as e:
errors += [str(e)]
time.sleep(1)
raise Exception("Connection not establised, {}".format(errors))
def producer_serializer(x):
return x.encode() if isinstance(x, str) else x
def kafka_create_topic(
admin_client,
topic_name,
num_partitions=1,
replication_factor=1,
max_retries=50,
config=None,
):
logging.debug(
f"Kafka create topic={topic_name}, num_partitions={num_partitions}, replication_factor={replication_factor}"
)
topics_list = [
NewTopic(
name=topic_name,
num_partitions=num_partitions,
replication_factor=replication_factor,
topic_configs=config,
)
]
retries = 0
while True:
try:
admin_client.create_topics(new_topics=topics_list, validate_only=False)
logging.debug("Admin client succeed")
return
except Exception as e:
retries += 1
time.sleep(0.5)
if retries < max_retries:
logging.warning(f"Failed to create topic {e}")
else:
raise
def kafka_delete_topic(admin_client, topic, max_retries=50):
result = admin_client.delete_topics([topic])
for topic, e in result.topic_error_codes:
if e == 0:
logging.debug(f"Topic {topic} deleted")
else:
logging.error(f"Failed to delete topic {topic}: {e}")
retries = 0
while True:
topics_listed = admin_client.list_topics()
logging.debug(f"TOPICS LISTED: {topics_listed}")
if topic not in topics_listed:
return
else:
retries += 1
time.sleep(0.5)
if retries > max_retries:
raise Exception(f"Failed to delete topics {topic}, {result}")
def kafka_produce(kafka_cluster, topic, messages, timestamp=None, retries=15):
logging.debug(
"kafka_produce server:{}:{} topic:{}".format(
"localhost", kafka_cluster.kafka_port, topic
)
)
producer = get_kafka_producer(
kafka_cluster.kafka_port, producer_serializer, retries
)
for message in messages:
producer.send(topic=topic, value=message, timestamp_ms=timestamp)
producer.flush()
## just to ensure the python client / producer is working properly
def kafka_producer_send_heartbeat_msg(max_retries=50):
kafka_produce(kafka_cluster, "test_heartbeat_topic", ["test"], retries=max_retries)
def kafka_consume(kafka_cluster, topic, needDecode=True, timestamp=0):
consumer = KafkaConsumer(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
auto_offset_reset="earliest",
)
consumer.subscribe(topics=(topic))
for toppar, messages in list(consumer.poll(5000).items()):
if toppar.topic == topic:
for message in messages:
assert timestamp == 0 or message.timestamp / 1000 == timestamp
if needDecode:
yield message.value.decode()
else:
yield message.value
consumer.unsubscribe()
consumer.close()
def kafka_produce_protobuf_messages(kafka_cluster, topic, start_index, num_messages):
data = b""
for i in range(start_index, start_index + num_messages):
msg = kafka_pb2.KeyValuePair()
msg.key = i
msg.value = str(i)
serialized_msg = msg.SerializeToString()
data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
producer = KafkaProducer(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
value_serializer=producer_serializer,
)
producer.send(topic=topic, value=data)
producer.flush()
logging.debug(("Produced {} messages for topic {}".format(num_messages, topic)))
def kafka_produce_protobuf_messages_no_delimeters(
kafka_cluster, topic, start_index, num_messages
):
data = ""
producer = KafkaProducer(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
for i in range(start_index, start_index + num_messages):
msg = kafka_pb2.KeyValuePair()
msg.key = i
msg.value = str(i)
serialized_msg = msg.SerializeToString()
producer.send(topic=topic, value=serialized_msg)
producer.flush()
logging.debug("Produced {} messages for topic {}".format(num_messages, topic))
def kafka_produce_protobuf_social(kafka_cluster, topic, start_index, num_messages):
data = b""
for i in range(start_index, start_index + num_messages):
msg = social_pb2.User()
msg.username = "John Doe {}".format(i)
msg.timestamp = 1000000 + i
serialized_msg = msg.SerializeToString()
data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
producer = KafkaProducer(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
value_serializer=producer_serializer,
)
producer.send(topic=topic, value=data)
producer.flush()
logging.debug(("Produced {} messages for topic {}".format(num_messages, topic)))
def avro_message(value):
schema = avro.schema.make_avsc_object(
{
"name": "row",
"type": "record",
"fields": [
{"name": "id", "type": "long"},
{"name": "blockNo", "type": "int"},
{"name": "val1", "type": "string"},
{"name": "val2", "type": "float"},
{"name": "val3", "type": "int"},
],
}
)
bytes_writer = io.BytesIO()
# writer = avro.io.DatumWriter(schema)
# encoder = avro.io.BinaryEncoder(bytes_writer)
# writer.write(value, encoder)
# DataFileWrite seems to be mandatory to get schema encoded
writer = avro.datafile.DataFileWriter(bytes_writer, avro.io.DatumWriter(), schema)
if isinstance(value, list):
for v in value:
writer.append(v)
else:
writer.append(value)
writer.flush()
raw_bytes = bytes_writer.getvalue()
writer.close()
bytes_writer.close()
return raw_bytes
def avro_confluent_message(schema_registry_client, value):
# type: (CachedSchemaRegistryClient, dict) -> str
serializer = MessageSerializer(schema_registry_client)
schema = avro.schema.make_avsc_object(
{
"name": "row",
"type": "record",
"fields": [
{"name": "id", "type": "long"},
{"name": "blockNo", "type": "int"},
{"name": "val1", "type": "string"},
{"name": "val2", "type": "float"},
{"name": "val3", "type": "int"},
],
}
)
return serializer.encode_record_with_schema("test_subject", schema, value)
# Tests
def test_kafka_column_types(kafka_cluster):
def assert_returned_exception(e):
assert e.value.returncode == 36
assert (
"KafkaEngine doesn't support DEFAULT/MATERIALIZED/EPHEMERAL expressions for columns."
in str(e.value)
)
# check column with DEFAULT expression
with pytest.raises(QueryRuntimeException) as exception:
instance.query(
"""
CREATE TABLE test.kafka (a Int, b Int DEFAULT 0)
ENGINE = Kafka('{kafka_broker}:19092', '{kafka_topic_new}', '{kafka_group_name_new}', '{kafka_format_json_each_row}', '\\n')
"""
)
assert_returned_exception(exception)
# check EPHEMERAL
with pytest.raises(QueryRuntimeException) as exception:
instance.query(
"""
CREATE TABLE test.kafka (a Int, b Int EPHEMERAL)
ENGINE = Kafka('{kafka_broker}:19092', '{kafka_topic_new}', '{kafka_group_name_new}', '{kafka_format_json_each_row}', '\\n')
"""
)
assert_returned_exception(exception)
# check ALIAS
instance.query(
"""
CREATE TABLE test.kafka (a Int, b String Alias toString(a))
ENGINE = Kafka('{kafka_broker}:19092', '{kafka_topic_new}', '{kafka_group_name_new}', '{kafka_format_json_each_row}', '\\n')
SETTINGS kafka_commit_on_select = 1;
"""
)
messages = []
for i in range(5):
messages.append(json.dumps({"a": i}))
kafka_produce(kafka_cluster, "new", messages)
result = ""
expected = TSV(
"""
0\t0
1\t1
2\t2
3\t3
4\t4
"""
)
retries = 50
while retries > 0:
result += instance.query("SELECT a, b FROM test.kafka", ignore_error=True)
if TSV(result) == expected:
break
retries -= 1
assert TSV(result) == expected
instance.query("DROP TABLE test.kafka SYNC")
# check MATERIALIZED
with pytest.raises(QueryRuntimeException) as exception:
instance.query(
"""
CREATE TABLE test.kafka (a Int, b String MATERIALIZED toString(a))
ENGINE = Kafka('{kafka_broker}:19092', '{kafka_topic_new}', '{kafka_group_name_new}', '{kafka_format_json_each_row}', '\\n')
"""
)
assert_returned_exception(exception)
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(
"""kafka_broker kafka1
kafka_client_id instance
kafka_format_json_each_row JSONEachRow
kafka_group_name_new new
kafka_group_name_old old
kafka_topic_new new
kafka_topic_old old
"""
)
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, "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, "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, "new", messages)
# Insert couple of malformed messages.
kafka_produce(kafka_cluster, "new", ["}{very_broken_message,"])
kafka_produce(kafka_cluster, "new", ["}another{very_broken_message,"])
messages = []
for i in range(25, 50):
messages.append(json.dumps({"key": i, "value": i}))
kafka_produce(kafka_cluster, "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, "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"
)
def test_kafka_formats(kafka_cluster):
schema_registry_client = CachedSchemaRegistryClient(
"http://localhost:{}".format(kafka_cluster.schema_registry_port)
)
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_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": r", format_regexp='\(id = (.+?), blockNo = (.+?), val1 = \"(.+?)\", val2 = (.+?), val3 = (.+?)\)', 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": [
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# ''
# !!! 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",
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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": [
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# ''
# 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": {
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# ''
# 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
# /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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],
},
"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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},
"ArrowStream": {
"data_sample": [
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],
},
}
for format_name, format_opts in list(all_formats.items()):
logging.debug(("Set up {}".format(format_name)))
topic_name = "format_tests_{}".format(format_name)
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)
instance.query(
"""
DROP TABLE IF EXISTS test.kafka_{format_name};
CREATE TABLE test.kafka_{format_name} (
id Int64,
blockNo UInt16,
val1 String,
val2 Float32,
val3 UInt8
) ENGINE = Kafka()
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = '{topic_name}',
kafka_group_name = '{topic_name}_group',
kafka_format = '{format_name}',
kafka_flush_interval_ms = 1000 {extra_settings};
DROP TABLE IF EXISTS test.kafka_{format_name}_mv;
CREATE MATERIALIZED VIEW test.kafka_{format_name}_mv Engine=Log AS
SELECT *, _topic, _partition, _offset FROM test.kafka_{format_name};
""".format(
topic_name=topic_name,
format_name=format_name,
extra_settings=format_opts.get("extra_settings") or "",
)
)
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")
instance.query_with_retry(
f"SELECT * FROM test.kafka_{list(all_formats.keys())[-1]}_mv;",
retry_count=30,
sleep_time=1,
check_callback=lambda res: res.count("\n") == expected_rows_count,
)
for format_name, format_opts in list(all_formats.items()):
logging.debug(("Checking {}".format(format_name)))
topic_name = f"format_tests_{format_name}"
# 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_{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],
)
assert TSV(result) == TSV(expected), "Proper result for format: {}".format(
format_name
)
kafka_delete_topic(admin_client, 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; CREATE DATABASE test;")
# logging.debug("kafka is available - running test")
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 = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
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 = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
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 = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
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 = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
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_delimeters(
kafka_cluster, "pb_no_delimiter", 0, 20
)
kafka_produce_protobuf_messages_no_delimeters(
kafka_cluster, "pb_no_delimiter", 20, 1
)
kafka_produce_protobuf_messages_no_delimeters(
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)
def test_kafka_materialized_view(kafka_cluster):
instance.query(
"""
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 = 'mv',
kafka_group_name = 'mv',
kafka_format = 'JSONEachRow',
kafka_row_delimiter = '\\n';
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, "mv", messages)
while True:
result = instance.query("SELECT * FROM test.view")
if kafka_check_result(result):
break
instance.query(
"""
DROP TABLE test.consumer;
DROP TABLE test.view;
"""
)
kafka_check_result(result, True)
def test_kafka_recreate_kafka_table(kafka_cluster):
"""
Checks that materialized view work properly after dropping and recreating the Kafka table.
"""
# line for backporting:
# admin_client = KafkaAdminClient(bootstrap_servers="localhost:9092")
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "recreate_kafka_table"
kafka_create_topic(admin_client, topic_name, num_partitions=6)
instance.query(
"""
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 = 'recreate_kafka_table',
kafka_group_name = 'recreate_kafka_table_group',
kafka_format = 'JSONEachRow',
kafka_num_consumers = 6,
kafka_flush_interval_ms = 1000,
kafka_skip_broken_messages = 1048577;
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(
"kafka.*Committed offset [0-9]+.*recreate_kafka_table",
repetitions=6,
look_behind_lines=100,
)
instance.query(
"""
DROP TABLE test.kafka;
"""
)
kafka_produce(kafka_cluster, "recreate_kafka_table", messages)
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'recreate_kafka_table',
kafka_group_name = 'recreate_kafka_table_group',
kafka_format = 'JSONEachRow',
kafka_num_consumers = 6,
kafka_flush_interval_ms = 1000,
kafka_skip_broken_messages = 1048577;
"""
)
instance.wait_for_log_line(
"kafka.*Committed offset [0-9]+.*recreate_kafka_table",
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("SELECT count() FROM test.view")) == 240
instance.query(
"""
DROP TABLE test.consumer;
DROP TABLE test.view;
"""
)
kafka_delete_topic(admin_client, topic_name)
def test_librdkafka_compression(kafka_cluster):
"""
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)
for compression_type in supported_compression_types:
logging.debug(("Check compression {}".format(compression_type)))
topic_name = "test_librdkafka_compression_{}".format(compression_type)
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
kafka_create_topic(
admin_client, topic_name, config={"compression.type": compression_type}
)
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value String)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = '{topic_name}',
kafka_group_name = '{topic_name}_group',
kafka_format = 'JSONEachRow',
kafka_flush_interval_ms = 1000;
CREATE MATERIALIZED VIEW test.consumer Engine=Log AS
SELECT * FROM test.kafka;
""".format(
topic_name=topic_name
)
)
kafka_produce(kafka_cluster, topic_name, messages)
instance.wait_for_log_line("Committed offset {}".format(number_of_messages))
result = instance.query("SELECT * FROM test.consumer")
assert TSV(result) == TSV(expected)
instance.query("DROP TABLE test.kafka SYNC")
instance.query("DROP TABLE test.consumer SYNC")
kafka_delete_topic(admin_client, topic_name)
def test_kafka_materialized_view_with_subquery(kafka_cluster):
instance.query(
"""
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 = 'mvsq',
kafka_group_name = 'mvsq',
kafka_format = 'JSONEachRow',
kafka_row_delimiter = '\\n';
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, "mvsq", messages)
while True:
result = instance.query("SELECT * FROM test.view")
if kafka_check_result(result):
break
instance.query(
"""
DROP TABLE test.consumer;
DROP TABLE test.view;
"""
)
kafka_check_result(result, True)
def test_kafka_many_materialized_views(kafka_cluster):
instance.query(
"""
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 TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'mmv',
kafka_group_name = 'mmv',
kafka_format = 'JSONEachRow',
kafka_row_delimiter = '\\n';
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, "mmv", messages)
while True:
result1 = instance.query("SELECT * FROM test.view1")
result2 = instance.query("SELECT * FROM test.view2")
if kafka_check_result(result1) and kafka_check_result(result2):
break
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)
def test_kafka_flush_on_big_message(kafka_cluster):
# Create batchs of messages of size ~100Kb
kafka_messages = 1000
batch_messages = 1000
messages = [
json.dumps({"key": i, "value": "x" * 100}) * batch_messages
for i in range(kafka_messages)
]
kafka_produce(kafka_cluster, "flush", messages)
instance.query(
"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.consumer;
CREATE TABLE test.kafka (key UInt64, value String)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'flush',
kafka_group_name = 'flush',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 10;
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;
"""
)
client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
received = False
while not received:
try:
offsets = client.list_consumer_group_offsets("flush")
for topic, offset in list(offsets.items()):
if topic.topic == "flush" 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):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_config = {
# default retention, since predefined timestamp_ms is used.
"retention.ms": "-1",
}
kafka_create_topic(admin_client, "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")
def test_kafka_virtual_columns_with_materialized_view(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_config = {
# default retention, since predefined timestamp_ms is used.
"retention.ms": "-1",
}
kafka_create_topic(admin_client, "virt2", config=topic_config)
instance.query(
"""
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 = 'virt2',
kafka_group_name = 'virt2',
kafka_format = 'JSONEachRow',
kafka_row_delimiter = '\\n';
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, "virt2", messages, 0)
sql = "SELECT kafka_key, key, topic, value, offset, partition, timestamp FROM test.view ORDER BY kafka_key, key"
result = instance.query(sql)
iterations = 0
while (
not kafka_check_result(result, False, "test_kafka_virtual2.reference")
and iterations < 10
):
time.sleep(3)
iterations += 1
result = instance.query(sql)
kafka_check_result(result, True, "test_kafka_virtual2.reference")
instance.query(
"""
DROP TABLE test.consumer;
DROP TABLE test.view;
"""
)
def test_kafka_insert(kafka_cluster):
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'insert1',
kafka_group_name = 'insert1',
kafka_format = 'TSV',
kafka_commit_on_select = 1,
kafka_row_delimiter = '\\n';
"""
)
values = []
for i in range(50):
values.append("({i}, {i})".format(i=i))
values = ",".join(values)
while True:
try:
instance.query("INSERT INTO test.kafka VALUES {}".format(values))
break
except QueryRuntimeException as e:
if "Local: Timed out." in str(e):
continue
else:
raise
messages = []
while True:
messages.extend(kafka_consume(kafka_cluster, "insert1"))
if len(messages) == 50:
break
result = "\n".join(messages)
kafka_check_result(result, True)
def test_kafka_produce_consume(kafka_cluster):
instance.query(
"""
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 = 'insert2',
kafka_group_name = 'insert2',
kafka_format = 'TSV',
kafka_row_delimiter = '\\n';
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)
while True:
try:
instance.query("INSERT INTO test.kafka VALUES {}".format(values))
break
except QueryRuntimeException as e:
if "Local: Timed out." in str(e):
continue
else:
raise
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()
while True:
result = instance.query("SELECT count() FROM test.view")
time.sleep(1)
if int(result) == messages_num * threads_num:
break
instance.query(
"""
DROP TABLE test.consumer;
DROP TABLE test.view;
"""
)
for thread in threads:
thread.join()
assert (
int(result) == messages_num * threads_num
), "ClickHouse lost some messages: {}".format(result)
def test_kafka_commit_on_block_write(kafka_cluster):
instance.query(
"""
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 = 'block',
kafka_group_name = 'block',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 100,
kafka_row_delimiter = '\\n';
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()
i = [0]
def produce():
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, "block", messages)
kafka_thread = threading.Thread(target=produce)
kafka_thread.start()
while int(instance.query("SELECT count() FROM test.view")) == 0:
time.sleep(1)
cancel.set()
instance.query(
"""
DROP TABLE test.kafka;
"""
)
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'block',
kafka_group_name = 'block',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 100,
kafka_row_delimiter = '\\n';
"""
)
while int(instance.query("SELECT uniqExact(key) FROM test.view")) < i[0]:
time.sleep(1)
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!"
def test_kafka_virtual_columns2(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_config = {
# default retention, since predefined timestamp_ms is used.
"retention.ms": "-1",
}
kafka_create_topic(admin_client, "virt2_0", num_partitions=2, config=topic_config)
kafka_create_topic(admin_client, "virt2_1", num_partitions=2, config=topic_config)
instance.query(
"""
CREATE TABLE test.kafka (value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'virt2_0,virt2_1',
kafka_group_name = 'virt2',
kafka_num_consumers = 2,
kafka_format = 'JSONEachRow';
CREATE MATERIALIZED VIEW test.view Engine=Log 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="virt2_0",
value=json.dumps({"value": 1}),
partition=0,
key="k1",
timestamp_ms=1577836801001,
headers=[("content-encoding", b"base64")],
)
producer.send(
topic="virt2_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="virt2_0",
value=json.dumps({"value": 3}),
partition=1,
key="k3",
timestamp_ms=1577836803003,
headers=[("b", b"b"), ("a", b"a")],
)
producer.send(
topic="virt2_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="virt2_1",
value=json.dumps({"value": 5}),
partition=0,
key="k5",
timestamp_ms=1577836805005,
)
producer.send(
topic="virt2_1",
value=json.dumps({"value": 6}),
partition=0,
key="k6",
timestamp_ms=1577836806006,
)
producer.flush()
producer.send(
topic="virt2_1",
value=json.dumps({"value": 7}),
partition=1,
key="k7",
timestamp_ms=1577836807007,
)
producer.send(
topic="virt2_1",
value=json.dumps({"value": 8}),
partition=1,
key="k8",
timestamp_ms=1577836808008,
)
producer.flush()
instance.wait_for_log_line(
"kafka.*Committed offset 2.*virt2_[01]", repetitions=4, look_behind_lines=6000
)
members = describe_consumer_group(kafka_cluster, "virt2")
# 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 = """\
1 k1 virt2_0 0 0 1577836801 1577836801001 ['content-encoding'] ['base64']
2 k2 virt2_0 0 1 1577836802 1577836802002 ['empty_value','','','repetition','repetition'] ['','empty name','','1','2']
3 k3 virt2_0 1 0 1577836803 1577836803003 ['b','a'] ['b','a']
4 k4 virt2_0 1 1 1577836804 1577836804004 ['a','b'] ['a','b']
5 k5 virt2_1 0 0 1577836805 1577836805005 [] []
6 k6 virt2_1 0 1 1577836806 1577836806006 [] []
7 k7 virt2_1 1 0 1577836807 1577836807007 [] []
8 k8 virt2_1 1 1 1577836808 1577836808008 [] []
"""
assert TSV(result) == TSV(expected)
instance.query(
"""
DROP TABLE test.kafka;
DROP TABLE test.view;
"""
)
kafka_delete_topic(admin_client, "virt2_0")
kafka_delete_topic(admin_client, "virt2_1")
instance.rotate_logs()
def test_kafka_produce_key_timestamp(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "insert3"
topic_config = {
# default retention, since predefined timestamp_ms is used.
"retention.ms": "-1",
}
kafka_create_topic(admin_client, topic_name, config=topic_config)
instance.query(
"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.consumer;
CREATE TABLE test.kafka_writer (key UInt64, value UInt64, _key String, _timestamp DateTime('UTC'))
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'insert3',
kafka_group_name = 'insert3',
kafka_format = 'TSV',
kafka_row_delimiter = '\\n';
CREATE TABLE test.kafka (key UInt64, value UInt64, inserted_key String, inserted_timestamp DateTime('UTC'))
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'insert3',
kafka_group_name = 'insert3',
kafka_format = 'TSV',
kafka_row_delimiter = '\\n';
CREATE MATERIALIZED VIEW test.view Engine=Log 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("Committed offset 5")
result = instance.query("SELECT * FROM test.view ORDER BY value", ignore_error=True)
# logging.debug(result)
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
"""
assert TSV(result) == TSV(expected)
kafka_delete_topic(admin_client, topic_name)
def test_kafka_insert_avro(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_config = {
# default retention, since predefined timestamp_ms is used.
"retention.ms": "-1",
}
kafka_create_topic(admin_client, "avro1", config=topic_config)
instance.query(
"""
DROP TABLE IF EXISTS test.kafka;
CREATE TABLE test.kafka (key UInt64, value UInt64, _timestamp DateTime('UTC'))
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'avro1',
kafka_group_name = 'avro1',
kafka_commit_on_select = 1,
kafka_format = 'Avro';
"""
)
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'"
)
messages = []
while True:
messages.extend(
kafka_consume(
kafka_cluster, "avro1", needDecode=False, timestamp=1636505534
)
)
if len(messages) == 2:
break
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
def test_kafka_produce_consume_avro(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "insert_avro"
kafka_create_topic(admin_client, topic_name)
num_rows = 75
instance.query(
"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.kafka;
DROP TABLE IF EXISTS test.kafka_writer;
CREATE TABLE test.kafka_writer (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'avro',
kafka_group_name = 'avro',
kafka_format = 'Avro';
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'avro',
kafka_group_name = 'avro',
kafka_format = 'Avro';
CREATE MATERIALIZED VIEW test.view Engine=Log 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
kafka_delete_topic(admin_client, topic_name)
def test_kafka_flush_by_time(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "flush_by_time"
kafka_create_topic(admin_client, topic_name)
instance.query(
"""
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 = 'flush_by_time',
kafka_group_name = 'flush_by_time',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 100,
kafka_row_delimiter = '\\n';
SELECT * FROM test.kafka;
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 = []
messages.append(json.dumps({"key": 0, "value": 0}))
kafka_produce(kafka_cluster, "flush_by_time", 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;
"""
)
time.sleep(18)
result = instance.query("SELECT uniqExact(ts) = 2, count() >= 15 FROM test.view")
cancel.set()
kafka_thread.join()
# kafka_cluster.open_bash_shell('instance')
instance.query(
"""
DROP TABLE test.consumer;
DROP TABLE test.view;
"""
)
assert TSV(result) == TSV("1 1")
kafka_delete_topic(admin_client, topic_name)
def test_kafka_flush_by_block_size(kafka_cluster):
cancel = threading.Event()
def produce():
while not cancel.is_set():
messages = []
messages.append(json.dumps({"key": 0, "value": 0}))
kafka_produce(kafka_cluster, "flush_by_block_size", messages)
kafka_thread = threading.Thread(target=produce)
kafka_thread.start()
instance.query(
"""
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 = 'flush_by_block_size',
kafka_group_name = 'flush_by_block_size',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 100,
kafka_poll_max_batch_size = 1,
kafka_flush_interval_ms = 120000, /* should not flush by time during test */
kafka_row_delimiter = '\\n';
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!"
def test_kafka_lot_of_partitions_partial_commit_of_bulk(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "topic_with_multiple_partitions2"
kafka_create_topic(admin_client, topic_name, num_partitions=10)
instance.query(
"""
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_with_multiple_partitions2',
kafka_group_name = 'topic_with_multiple_partitions2',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 211,
kafka_flush_interval_ms = 500;
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_with_multiple_partitions2", 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;
"""
)
kafka_delete_topic(admin_client, topic_name)
def test_kafka_rebalance(kafka_cluster):
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;
"""
)
# kafka_cluster.open_bash_shell('instance')
# time.sleep(2)
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "topic_with_multiple_partitions"
kafka_create_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_with_multiple_partitions", messages)
kafka_thread = threading.Thread(target=produce)
kafka_thread.start()
for consumer_index in range(NUMBER_OF_CONSURRENT_CONSUMERS):
table_name = "kafka_consumer{}".format(consumer_index)
logging.debug(("Setting up {}".format(table_name)))
instance.query(
"""
DROP TABLE IF EXISTS test.{0};
DROP TABLE IF EXISTS test.{0}_mv;
CREATE TABLE test.{0} (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',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 33,
kafka_flush_interval_ms = 500;
CREATE MATERIALIZED VIEW test.{0}_mv TO test.destination AS
SELECT
key,
value,
_topic,
_key,
_offset,
_partition,
_timestamp,
'{0}' as _consumed_by
FROM test.{0};
""".format(
table_name
)
)
# kafka_cluster.open_bash_shell('instance')
# Waiting for test.kafka_consumerX to start consume ...
instance.wait_for_log_line(
"kafka_consumer{}.*Polled offset [0-9]+".format(consumer_index)
)
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!"
kafka_delete_topic(admin_client, topic_name)
def test_kafka_no_holes_when_write_suffix_failed(kafka_cluster):
messages = [json.dumps({"key": j + 1, "value": "x" * 300}) for j in range(22)]
kafka_produce(kafka_cluster, "no_holes_when_write_suffix_failed", messages)
instance.query(
"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.consumer;
CREATE TABLE test.kafka (key UInt64, value String)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'no_holes_when_write_suffix_failed',
kafka_group_name = 'no_holes_when_write_suffix_failed',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 20,
kafka_flush_interval_ms = 2000;
CREATE TABLE test.view (key UInt64, value String)
ENGINE = ReplicatedMergeTree('/clickhouse/kafkatest/tables/no_holes_when_write_suffix_failed', '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.*(session has been expired|Connection loss).*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;
"""
)
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")
def test_commits_of_unprocessed_messages_on_drop(kafka_cluster):
messages = [json.dumps({"key": j + 1, "value": j + 1}) for j in range(1)]
kafka_produce(kafka_cluster, "commits_of_unprocessed_messages_on_drop", messages)
instance.query(
"""
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 TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'commits_of_unprocessed_messages_on_drop',
kafka_group_name = 'commits_of_unprocessed_messages_on_drop_test_group',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 1000,
kafka_flush_interval_ms = 1000;
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, "commits_of_unprocessed_messages_on_drop", messages
)
time.sleep(0.5)
kafka_thread = threading.Thread(target=produce)
kafka_thread.start()
time.sleep(4)
instance.query(
"""
DROP TABLE test.kafka SYNC;
"""
)
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'commits_of_unprocessed_messages_on_drop',
kafka_group_name = 'commits_of_unprocessed_messages_on_drop_test_group',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 10000,
kafka_flush_interval_ms = 1000;
"""
)
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!"
def test_bad_reschedule(kafka_cluster):
messages = [json.dumps({"key": j + 1, "value": j + 1}) for j in range(20000)]
kafka_produce(kafka_cluster, "test_bad_reschedule", messages)
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'test_bad_reschedule',
kafka_group_name = 'test_bad_reschedule',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 1000,
kafka_flush_interval_ms = 1000;
CREATE MATERIALIZED VIEW test.destination Engine=Log 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 quesionable - 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
def test_premature_flush_on_eof(kafka_cluster):
instance.query(
"""
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'premature_flush_on_eof',
kafka_group_name = 'premature_flush_on_eof',
kafka_format = 'JSONEachRow';
SELECT * FROM test.kafka LIMIT 1;
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 immedeately after MV creation
# reaching topic EOF.
# But we should not do flush immedeately 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": j + 1, "value": j + 1}) for j in range(1)]
kafka_produce(kafka_cluster, "premature_flush_on_eof", 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, "premature_flush_on_eof", 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;
"""
)
def test_kafka_unavailable(kafka_cluster):
messages = [json.dumps({"key": j + 1, "value": j + 1}) for j in range(20000)]
kafka_produce(kafka_cluster, "test_bad_reschedule", messages)
kafka_cluster.pause_container("kafka1")
instance.query(
"""
CREATE TABLE test.test_bad_reschedule (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'test_bad_reschedule',
kafka_group_name = 'test_bad_reschedule',
kafka_format = 'JSONEachRow',
kafka_commit_on_select = 1,
kafka_max_block_size = 1000;
CREATE MATERIALIZED VIEW test.destination_unavailable Engine=Log AS
SELECT
key,
now() as consume_ts,
value,
_topic,
_key,
_offset,
_partition,
_timestamp
FROM test.test_bad_reschedule;
"""
)
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")
while (
int(instance.query("SELECT count() FROM test.destination_unavailable")) < 20000
):
print("Waiting for consume")
time.sleep(1)
def test_kafka_issue14202(kafka_cluster):
"""
INSERT INTO Kafka Engine from an empty SELECT sub query was leading to failure
"""
instance.query(
"""
CREATE TABLE test.empty_table (
dt Date,
some_string String
)
ENGINE = MergeTree()
PARTITION BY toYYYYMM(dt)
ORDER BY some_string;
CREATE TABLE test.kafka_q (t UInt64, `some_string` String)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'issue14202',
kafka_group_name = 'issue14202',
kafka_format = 'JSONEachRow';
"""
)
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))
def test_kafka_engine_put_errors_to_stream(kafka_cluster):
instance.query(
"""
DROP TABLE IF EXISTS test.kafka;
DROP TABLE IF EXISTS test.kafka_data;
DROP TABLE IF EXISTS test.kafka_errors;
CREATE TABLE test.kafka (i Int64, s String)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'kafka_engine_put_errors_to_stream',
kafka_group_name = 'kafka_engine_put_errors_to_stream',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 128,
kafka_handle_error_mode = 'stream';
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, "kafka_engine_put_errors_to_stream", messages)
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()
def test_kafka_engine_put_errors_to_stream_with_random_malformed_json(kafka_cluster):
instance.query(
"""
DROP TABLE IF EXISTS test.kafka;
DROP TABLE IF EXISTS test.kafka_data;
DROP TABLE IF EXISTS test.kafka_errors;
CREATE TABLE test.kafka (i Int64, s String)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'kafka_engine_put_errors_to_stream_with_random_malformed_json',
kafka_group_name = 'kafka_engine_put_errors_to_stream_with_random_malformed_json',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 100,
kafka_poll_max_batch_size = 1,
kafka_handle_error_mode = 'stream';
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,
"kafka_engine_put_errors_to_stream_with_random_malformed_json",
messages,
)
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;
"""
)
def test_kafka_formats_with_broken_message(kafka_cluster):
# 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": r"""{"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 convert: String to 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": {
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# broken message
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],
"expected": r"""{"raw_message":"4F52430A0B0A030000001204080150000A150A050000000000120C0801120608001000180050000A120A06000000000000120808014202080650000A120A06000000000000120808014202080450000A290A0400000000122108011A1B09000000000000E03F11000000000000E03F19000000000000E03F50000A150A050000000000120C080112060802100218025000FF80FF80FF00FF80FF03424144FF80FF02414DFF800000003FFF80FF010A0608061000180D0A060806100118170A060806100218140A060806100318140A0608061004182B0A060806100518170A060800100018020A060800100118020A060801100118020A060800100218020A060802100218020A060801100218030A060800100318020A060802100318020A060801100318020A060800100418020A060801100418040A060800100518020A060801100518021204080010001204080010001204080010001204080010001204080010001204080010001A03474D540A590A04080150000A0C0801120608001000180050000A0808014202080650000A0808014202080450000A2108011A1B09000000000000E03F11000000000000E03F19000000000000E03F50000A0C080112060802100218025000080310EC021A0C0803108E01181D20C1012801222E080C120501020304051A0269641A07626C6F636B4E6F1A0476616C311A0476616C321A0476616C33200028003000220808042000280030002208080820002800300022080808200028003000220808052000280030002208080120002800300030013A04080150003A0C0801120608001000180050003A0808014202080650003A0808014202080450003A2108011A1B09000000000000E03F11000000000000E03F19000000000000E03F50003A0C08011206080210021802500040904E480108D5011000188080042202000B285B300682F403034F524318","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_"
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}"
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)
instance.query(
"""
DROP TABLE IF EXISTS test.kafka_{format_name};
CREATE TABLE test.kafka_{format_name} (
id Int64,
blockNo UInt16,
val1 String,
val2 Float32,
val3 UInt8
) ENGINE = Kafka()
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = '{topic_name}',
kafka_group_name = '{topic_name}',
kafka_format = '{format_name}',
kafka_handle_error_mode = 'stream',
kafka_flush_interval_ms = 1000 {extra_settings};
DROP TABLE IF EXISTS test.kafka_data_{format_name}_mv;
CREATE MATERIALIZED VIEW test.kafka_data_{format_name}_mv Engine=Log 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=Log 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;
""".format(
topic_name=topic_name,
format_name=format_name,
raw_message=raw_message,
extra_settings=format_opts.get("extra_settings") or "",
)
)
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")
instance.query_with_retry(
f"SELECT * FROM test.kafka_data_{list(all_formats.keys())[-1]}_mv;",
retry_count=30,
sleep_time=1,
check_callback=lambda res: res.count("\n") == expected_rows_count,
)
for format_name, format_opts in list(all_formats.items()):
logging.debug(f"Checking {format_name}")
topic_name = f"{topic_name_prefix}{format_name}"
# 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 = ast.literal_eval(
instance.query(
"SELECT raw_message, error FROM test.kafka_errors_{format_name}_mv format JSONEachRow".format(
format_name=format_name
)
)
)
errors_expected = ast.literal_eval(format_opts["expected"])
# print(errors_result.strip())
# print(errors_expected.strip())
assert (
errors_result["raw_message"] == errors_expected["raw_message"]
), "Proper raw_message for format: {}".format(format_name)
# Errors text can change, just checking prefixes
assert (
errors_expected["error"] in errors_result["error"]
), "Proper error for format: {}".format(format_name)
kafka_delete_topic(admin_client, topic_name)
def wait_for_new_data(table_name, prev_count=0, max_retries=120):
retries = 0
while True:
new_count = int(instance.query("SELECT count() FROM {}".format(table_name)))
print(new_count)
if new_count > prev_count:
return new_count
else:
retries += 1
time.sleep(0.5)
if retries > max_retries:
raise Exception("No new data :(")
def test_kafka_consumer_failover(kafka_cluster):
# for backporting:
# admin_client = KafkaAdminClient(bootstrap_servers="localhost:9092")
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic_name = "kafka_consumer_failover"
kafka_create_topic(admin_client, topic_name, num_partitions=2)
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 = 'kafka_consumer_failover',
kafka_group_name = 'kafka_consumer_failover_group',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 1,
kafka_poll_timeout_ms = 200;
CREATE TABLE test.kafka2 (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'kafka_consumer_failover',
kafka_group_name = 'kafka_consumer_failover_group',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 1,
kafka_poll_timeout_ms = 200;
CREATE TABLE test.kafka3 (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'kafka_consumer_failover',
kafka_group_name = 'kafka_consumer_failover_group',
kafka_format = 'JSONEachRow',
kafka_max_block_size = 1,
kafka_poll_timeout_ms = 200;
CREATE TABLE test.destination (
key UInt64,
value UInt64,
_consumed_by LowCardinality(String)
)
ENGINE = MergeTree()
ORDER BY key;
CREATE MATERIALIZED VIEW test.kafka_mv TO test.destination AS
SELECT key, value, 'kafka' as _consumed_by
FROM test.kafka;
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="kafka_consumer_failover",
value=json.dumps({"key": 1, "value": 1}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 1, "value": 1}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination")
## 2 attached, 2 working
instance.query("DETACH TABLE test.kafka")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 2, "value": 2}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 2, "value": 2}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
## 1 attached, 1 working
instance.query("DETACH TABLE test.kafka2")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 3, "value": 3}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 3, "value": 3}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
## 2 attached, 2 working
instance.query("ATTACH TABLE test.kafka")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 4, "value": 4}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 4, "value": 4}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
## 1 attached, 1 working
instance.query("DETACH TABLE test.kafka3")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 5, "value": 5}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 5, "value": 5}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
## 2 attached, 2 working
instance.query("ATTACH TABLE test.kafka2")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 6, "value": 6}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 6, "value": 6}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
## 3 attached, 2 working
instance.query("ATTACH TABLE test.kafka3")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 7, "value": 7}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 7, "value": 7}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
## 2 attached, same 2 working
instance.query("DETACH TABLE test.kafka3")
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 8, "value": 8}),
partition=0,
)
producer.send(
topic="kafka_consumer_failover",
value=json.dumps({"key": 8, "value": 8}),
partition=1,
)
producer.flush()
prev_count = wait_for_new_data("test.destination", prev_count)
kafka_delete_topic(admin_client, topic_name)
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
def test_issue26643(kafka_cluster):
# for backporting:
# admin_client = KafkaAdminClient(bootstrap_servers="localhost:9092")
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
producer = KafkaProducer(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port),
value_serializer=producer_serializer,
)
topic_list = []
topic_list.append(
NewTopic(name="test_issue26643", num_partitions=4, replication_factor=1)
)
admin_client.create_topics(new_topics=topic_list, validate_only=False)
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="test_issue26643", value=data)
data = _VarintBytes(len(serialized_msg)) + serialized_msg
producer.send(topic="test_issue26643", value=data)
producer.flush()
instance.query(
"""
CREATE TABLE IF NOT EXISTS test.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
)
ENGINE = Kafka
SETTINGS
kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'test_issue26643',
kafka_group_name = 'test_issue26643_group',
kafka_format = 'Protobuf',
kafka_schema = 'message_with_repeated.proto:Message',
kafka_num_consumers = 4,
kafka_skip_broken_messages = 10000;
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)
# kafka_cluster.open_bash_shell('instance')
def test_num_consumers_limit(kafka_cluster):
instance.query("DROP TABLE IF EXISTS test.kafka")
error = instance.query_and_get_error(
"""
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', '', 100)
SETTINGS kafka_commit_on_select = 1;
"""
)
assert "BAD_ARGUMENTS" in error
instance.query(
"""
SET kafka_disable_num_consumers_limit = 1;
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', '', 100)
SETTINGS kafka_commit_on_select = 1;
"""
)
instance.query("DROP TABLE test.kafka")
def test_format_with_prefix_and_suffix(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
kafka_create_topic(admin_client, "custom")
instance.query(
"""
DROP TABLE IF EXISTS test.kafka;
CREATE TABLE test.kafka (key UInt64, value UInt64)
ENGINE = Kafka
SETTINGS kafka_broker_list = 'kafka1:19092',
kafka_topic_list = 'custom',
kafka_group_name = 'custom',
kafka_format = 'CustomSeparated';
"""
)
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'"
)
messages = []
attempt = 0
while attempt < 100:
messages.extend(kafka_consume(kafka_cluster, "custom"))
if len(messages) == 2:
break
attempt += 1
assert len(messages) == 2
assert (
"".join(messages) == "<prefix>\n0\t0\n<suffix>\n<prefix>\n10\t100\n<suffix>\n"
)
kafka_delete_topic(admin_client, "custom")
def test_max_rows_per_message(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic = "custom_max_rows_per_message"
kafka_create_topic(admin_client, topic)
num_rows = 5
instance.query(
f"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.kafka;
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_format = 'CustomSeparated',
format_custom_result_before_delimiter = '<prefix>\n',
format_custom_result_after_delimiter = '<suffix>\n',
kafka_max_rows_per_message = 3;
CREATE MATERIALIZED VIEW test.view Engine=Log 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'"
)
messages = []
attempt = 0
while attempt < 500:
messages.extend(kafka_consume(kafka_cluster, topic))
if len(messages) == 2:
break
attempt += 1
assert len(messages) == 2
assert (
"".join(messages)
== "<prefix>\n0\t0\n10\t100\n20\t200\n<suffix>\n<prefix>\n30\t300\n40\t400\n<suffix>\n"
)
attempt = 0
rows = 0
while attempt < 500:
rows = int(instance.query("SELECT count() FROM test.view"))
if rows == num_rows:
break
attempt += 1
assert rows == num_rows
result = instance.query("SELECT * FROM test.view")
assert result == "0\t0\n10\t100\n20\t200\n30\t300\n40\t400\n"
kafka_delete_topic(admin_client, topic)
def test_row_based_formats(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
for format_name in [
"TSV",
"TSVWithNamesAndTypes",
"TSKV",
"CSV",
"CSVWithNamesAndTypes",
"CustomSeparatedWithNamesAndTypes",
"Values",
"JSON",
"JSONEachRow",
"JSONCompactEachRow",
"JSONCompactEachRowWithNamesAndTypes",
"JSONObjectEachRow",
"Avro",
"RowBinary",
"RowBinaryWithNamesAndTypes",
"MsgPack",
]:
print(format_name)
kafka_create_topic(admin_client, format_name)
num_rows = 10
instance.query(
f"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.kafka;
CREATE TABLE test.kafka (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;
CREATE MATERIALIZED VIEW test.view Engine=Log AS
SELECT key, value FROM test.kafka;
INSERT INTO test.kafka SELECT number * 10 as key, number * 100 as value FROM numbers({num_rows});
"""
)
messages = []
attempt = 0
while attempt < 500:
messages.extend(kafka_consume(kafka_cluster, format_name, needDecode=False))
if len(messages) == 2:
break
attempt += 1
assert len(messages) == 2
attempt = 0
rows = 0
while attempt < 500:
rows = int(instance.query("SELECT count() FROM test.view"))
if rows == num_rows:
break
attempt += 1
assert rows == 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
kafka_delete_topic(admin_client, format_name)
def test_block_based_formats_1(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
topic = "pretty_space"
kafka_create_topic(admin_client, topic)
instance.query(
f"""
DROP TABLE IF EXISTS test.kafka;
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_format = 'PrettySpace';
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;
"""
)
messages = []
attempt = 0
while attempt < 500:
messages.extend(kafka_consume(kafka_cluster, topic))
if len(messages) == 3:
break
attempt += 1
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"],
]
kafka_delete_topic(admin_client, topic)
def test_block_based_formats_2(kafka_cluster):
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:{}".format(kafka_cluster.kafka_port)
)
num_rows = 100
for format_name in [
"JSONColumns",
"Native",
"Arrow",
"Parquet",
"ORC",
"JSONCompactColumns",
]:
kafka_create_topic(admin_client, format_name)
instance.query(
f"""
DROP TABLE IF EXISTS test.view;
DROP TABLE IF EXISTS test.kafka;
CREATE TABLE test.kafka (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}';
CREATE MATERIALIZED VIEW test.view Engine=Log AS
SELECT key, value FROM test.kafka;
INSERT INTO test.kafka SELECT number * 10 as key, number * 100 as value FROM numbers({num_rows}) settings max_block_size=12, optimize_trivial_insert_select=0;
"""
)
messages = []
attempt = 0
while attempt < 500:
messages.extend(kafka_consume(kafka_cluster, format_name, needDecode=False))
if len(messages) == 9:
break
attempt += 1
assert len(messages) == 9
attempt = 0
rows = 0
while attempt < 500:
rows = int(instance.query("SELECT count() FROM test.view"))
if rows == num_rows:
break
attempt += 1
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
kafka_delete_topic(admin_client, format_name)
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_, 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 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
num_messages_read: 4
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
num_messages_read: 1
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)
if __name__ == "__main__":
cluster.start()
input("Cluster created, press any key to destroy...")
cluster.shutdown()