mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-24 08:32:02 +00:00
1115 lines
37 KiB
Python
1115 lines
37 KiB
Python
import os.path as p
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import random
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import threading
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import time
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import pytest
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from helpers.cluster import ClickHouseCluster
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from helpers.test_tools import TSV
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from helpers.client import QueryRuntimeException
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import json
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import subprocess
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import kafka.errors
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from kafka import KafkaAdminClient, KafkaProducer, KafkaConsumer
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from kafka.admin import NewTopic
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from google.protobuf.internal.encoder import _VarintBytes
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"""
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protoc --version
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libprotoc 3.0.0
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# to create kafka_pb2.py
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protoc --python_out=. kafka.proto
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"""
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import kafka_pb2
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# TODO: add test for run-time offset update in CH, if we manually update it on Kafka side.
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# TODO: add test for SELECT LIMIT is working.
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# TODO: modify tests to respect `skip_broken_messages` setting.
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cluster = ClickHouseCluster(__file__)
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instance = cluster.add_instance('instance',
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config_dir='configs',
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main_configs=['configs/kafka.xml', 'configs/log_conf.xml' ],
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with_kafka=True,
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clickhouse_path_dir='clickhouse_path')
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kafka_id = ''
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# Helpers
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def check_kafka_is_available():
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p = subprocess.Popen(('docker',
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'exec',
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'-i',
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kafka_id,
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'/usr/bin/kafka-broker-api-versions',
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'--bootstrap-server',
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'INSIDE://localhost:9092'),
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stdout=subprocess.PIPE)
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p.communicate()
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return p.returncode == 0
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def wait_kafka_is_available(max_retries=50):
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retries = 0
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while True:
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if check_kafka_is_available():
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break
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else:
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retries += 1
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if retries > max_retries:
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raise "Kafka is not available"
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print("Waiting for Kafka to start up")
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time.sleep(1)
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def kafka_produce(topic, messages, timestamp=None):
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producer = KafkaProducer(bootstrap_servers="localhost:9092")
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for message in messages:
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producer.send(topic=topic, value=message, timestamp_ms=timestamp)
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producer.flush()
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# print ("Produced {} messages for topic {}".format(len(messages), topic))
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def kafka_consume(topic):
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consumer = KafkaConsumer(bootstrap_servers="localhost:9092", auto_offset_reset="earliest")
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consumer.subscribe(topics=(topic))
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for toppar, messages in consumer.poll(5000).items():
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if toppar.topic == topic:
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for message in messages:
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yield message.value
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consumer.unsubscribe()
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consumer.close()
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def kafka_produce_protobuf_messages(topic, start_index, num_messages):
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data = ''
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for i in range(start_index, start_index + num_messages):
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msg = kafka_pb2.KeyValuePair()
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msg.key = i
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msg.value = str(i)
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serialized_msg = msg.SerializeToString()
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data = data + _VarintBytes(len(serialized_msg)) + serialized_msg
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producer = KafkaProducer(bootstrap_servers="localhost:9092")
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producer.send(topic=topic, value=data)
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producer.flush()
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print("Produced {} messages for topic {}".format(num_messages, topic))
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# Since everything is async and shaky when receiving messages from Kafka,
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# we may want to try and check results multiple times in a loop.
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def kafka_check_result(result, check=False, ref_file='test_kafka_json.reference'):
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fpath = p.join(p.dirname(__file__), ref_file)
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with open(fpath) as reference:
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if check:
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assert TSV(result) == TSV(reference)
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else:
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return TSV(result) == TSV(reference)
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# Fixtures
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@pytest.fixture(scope="module")
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def kafka_cluster():
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try:
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global kafka_id
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cluster.start()
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kafka_id = instance.cluster.kafka_docker_id
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print("kafka_id is {}".format(kafka_id))
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instance.query('CREATE DATABASE test')
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yield cluster
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finally:
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cluster.shutdown()
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@pytest.fixture(autouse=True)
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def kafka_setup_teardown():
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instance.query('DROP TABLE IF EXISTS test.kafka')
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wait_kafka_is_available()
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print("kafka is available - running test")
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yield # run test
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instance.query('DROP TABLE IF EXISTS test.kafka')
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# Tests
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@pytest.mark.timeout(180)
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def test_kafka_settings_old_syntax(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka('kafka1:19092', 'old', 'old', 'JSONEachRow', '\\n');
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''')
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# Don't insert malformed messages since old settings syntax
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# doesn't support skipping of broken messages.
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messages = []
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for i in range(50):
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messages.append(json.dumps({'key': i, 'value': i}))
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kafka_produce('old', messages)
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result = ''
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while True:
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result += instance.query('SELECT * FROM test.kafka', ignore_error=True)
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if kafka_check_result(result):
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break
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_settings_new_syntax(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'new',
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kafka_group_name = 'new',
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kafka_format = 'JSONEachRow',
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kafka_row_delimiter = '\\n',
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kafka_skip_broken_messages = 1;
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''')
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messages = []
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for i in range(25):
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messages.append(json.dumps({'key': i, 'value': i}))
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kafka_produce('new', messages)
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# Insert couple of malformed messages.
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kafka_produce('new', ['}{very_broken_message,'])
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kafka_produce('new', ['}another{very_broken_message,'])
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messages = []
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for i in range(25, 50):
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messages.append(json.dumps({'key': i, 'value': i}))
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kafka_produce('new', messages)
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result = ''
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while True:
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result += instance.query('SELECT * FROM test.kafka', ignore_error=True)
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if kafka_check_result(result):
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break
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_csv_with_delimiter(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'csv',
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kafka_group_name = 'csv',
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kafka_format = 'CSV',
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kafka_row_delimiter = '\\n';
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''')
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messages = []
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for i in range(50):
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messages.append('{i}, {i}'.format(i=i))
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kafka_produce('csv', messages)
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result = ''
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while True:
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result += instance.query('SELECT * FROM test.kafka', ignore_error=True)
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if kafka_check_result(result):
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break
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_tsv_with_delimiter(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'tsv',
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kafka_group_name = 'tsv',
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kafka_format = 'TSV',
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kafka_row_delimiter = '\\n';
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''')
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messages = []
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for i in range(50):
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messages.append('{i}\t{i}'.format(i=i))
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kafka_produce('tsv', messages)
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result = ''
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while True:
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result += instance.query('SELECT * FROM test.kafka', ignore_error=True)
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if kafka_check_result(result):
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break
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_select_empty(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'empty',
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kafka_group_name = 'empty',
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kafka_format = 'TSV',
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kafka_row_delimiter = '\\n';
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''')
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assert int(instance.query('SELECT count() FROM test.kafka')) == 0
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@pytest.mark.timeout(180)
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def test_kafka_json_without_delimiter(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'json',
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kafka_group_name = 'json',
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kafka_format = 'JSONEachRow';
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''')
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messages = ''
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for i in range(25):
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messages += json.dumps({'key': i, 'value': i}) + '\n'
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kafka_produce('json', [messages])
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messages = ''
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for i in range(25, 50):
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messages += json.dumps({'key': i, 'value': i}) + '\n'
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kafka_produce('json', [messages])
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result = ''
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while True:
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result += instance.query('SELECT * FROM test.kafka', ignore_error=True)
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if kafka_check_result(result):
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break
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_protobuf(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value String)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'pb',
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kafka_group_name = 'pb',
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kafka_format = 'Protobuf',
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kafka_schema = 'kafka.proto:KeyValuePair';
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''')
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kafka_produce_protobuf_messages('pb', 0, 20)
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kafka_produce_protobuf_messages('pb', 20, 1)
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kafka_produce_protobuf_messages('pb', 21, 29)
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result = ''
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while True:
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result += instance.query('SELECT * FROM test.kafka', ignore_error=True)
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if kafka_check_result(result):
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break
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_materialized_view(kafka_cluster):
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instance.query('''
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DROP TABLE IF EXISTS test.view;
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DROP TABLE IF EXISTS test.consumer;
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'mv',
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kafka_group_name = 'mv',
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kafka_format = 'JSONEachRow',
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kafka_row_delimiter = '\\n';
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CREATE TABLE test.view (key UInt64, value UInt64)
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ENGINE = MergeTree()
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ORDER BY key;
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CREATE MATERIALIZED VIEW test.consumer TO test.view AS
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SELECT * FROM test.kafka;
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''')
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messages = []
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for i in range(50):
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messages.append(json.dumps({'key': i, 'value': i}))
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kafka_produce('mv', messages)
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while True:
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result = instance.query('SELECT * FROM test.view')
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if kafka_check_result(result):
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break
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instance.query('''
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DROP TABLE test.consumer;
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DROP TABLE test.view;
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''')
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_materialized_view_with_subquery(kafka_cluster):
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instance.query('''
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DROP TABLE IF EXISTS test.view;
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DROP TABLE IF EXISTS test.consumer;
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'mvsq',
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kafka_group_name = 'mvsq',
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kafka_format = 'JSONEachRow',
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kafka_row_delimiter = '\\n';
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CREATE TABLE test.view (key UInt64, value UInt64)
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ENGINE = MergeTree()
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ORDER BY key;
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CREATE MATERIALIZED VIEW test.consumer TO test.view AS
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SELECT * FROM (SELECT * FROM test.kafka);
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''')
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messages = []
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for i in range(50):
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messages.append(json.dumps({'key': i, 'value': i}))
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kafka_produce('mvsq', messages)
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while True:
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result = instance.query('SELECT * FROM test.view')
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if kafka_check_result(result):
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break
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instance.query('''
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DROP TABLE test.consumer;
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DROP TABLE test.view;
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''')
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kafka_check_result(result, True)
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@pytest.mark.timeout(180)
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def test_kafka_many_materialized_views(kafka_cluster):
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instance.query('''
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DROP TABLE IF EXISTS test.view1;
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DROP TABLE IF EXISTS test.view2;
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DROP TABLE IF EXISTS test.consumer1;
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DROP TABLE IF EXISTS test.consumer2;
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'mmv',
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kafka_group_name = 'mmv',
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kafka_format = 'JSONEachRow',
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kafka_row_delimiter = '\\n';
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CREATE TABLE test.view1 (key UInt64, value UInt64)
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ENGINE = MergeTree()
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ORDER BY key;
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CREATE TABLE test.view2 (key UInt64, value UInt64)
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ENGINE = MergeTree()
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ORDER BY key;
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CREATE MATERIALIZED VIEW test.consumer1 TO test.view1 AS
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SELECT * FROM test.kafka;
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CREATE MATERIALIZED VIEW test.consumer2 TO test.view2 AS
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SELECT * FROM test.kafka;
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''')
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messages = []
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for i in range(50):
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messages.append(json.dumps({'key': i, 'value': i}))
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kafka_produce('mmv', messages)
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while True:
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result1 = instance.query('SELECT * FROM test.view1')
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result2 = instance.query('SELECT * FROM test.view2')
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if kafka_check_result(result1) and kafka_check_result(result2):
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break
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instance.query('''
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DROP TABLE test.consumer1;
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DROP TABLE test.consumer2;
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DROP TABLE test.view1;
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DROP TABLE test.view2;
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''')
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kafka_check_result(result1, True)
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kafka_check_result(result2, True)
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@pytest.mark.timeout(300)
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def test_kafka_flush_on_big_message(kafka_cluster):
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# Create batchs of messages of size ~100Kb
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kafka_messages = 1000
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batch_messages = 1000
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messages = [json.dumps({'key': i, 'value': 'x' * 100}) * batch_messages for i in range(kafka_messages)]
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kafka_produce('flush', messages)
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instance.query('''
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DROP TABLE IF EXISTS test.view;
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DROP TABLE IF EXISTS test.consumer;
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CREATE TABLE test.kafka (key UInt64, value String)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'flush',
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kafka_group_name = 'flush',
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kafka_format = 'JSONEachRow',
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kafka_max_block_size = 10;
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CREATE TABLE test.view (key UInt64, value String)
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ENGINE = MergeTree
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ORDER BY key;
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CREATE MATERIALIZED VIEW test.consumer TO test.view AS
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SELECT * FROM test.kafka;
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''')
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client = KafkaAdminClient(bootstrap_servers="localhost:9092")
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received = False
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while not received:
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try:
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offsets = client.list_consumer_group_offsets('flush')
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for topic, offset in offsets.items():
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if topic.topic == 'flush' and offset.offset == kafka_messages:
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received = True
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break
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except kafka.errors.GroupCoordinatorNotAvailableError:
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continue
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while True:
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result = instance.query('SELECT count() FROM test.view')
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if int(result) == kafka_messages*batch_messages:
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break
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instance.query('''
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DROP TABLE test.consumer;
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DROP TABLE test.view;
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''')
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assert int(result) == kafka_messages*batch_messages, 'ClickHouse lost some messages: {}'.format(result)
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@pytest.mark.timeout(180)
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def test_kafka_virtual_columns(kafka_cluster):
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instance.query('''
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CREATE TABLE test.kafka (key UInt64, value UInt64)
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ENGINE = Kafka
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SETTINGS kafka_broker_list = 'kafka1:19092',
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kafka_topic_list = 'virt1',
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kafka_group_name = 'virt1',
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kafka_format = 'JSONEachRow';
|
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''')
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|
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messages = ''
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for i in range(25):
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messages += json.dumps({'key': i, 'value': i}) + '\n'
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kafka_produce('virt1', [messages], 0)
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messages = ''
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for i in range(25, 50):
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messages += json.dumps({'key': i, 'value': i}) + '\n'
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kafka_produce('virt1', [messages], 0)
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result = ''
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while True:
|
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result += instance.query('SELECT _key, key, _topic, value, _offset, _partition, _timestamp FROM test.kafka', ignore_error=True)
|
|
if kafka_check_result(result, False, 'test_kafka_virtual1.reference'):
|
|
break
|
|
|
|
kafka_check_result(result, True, 'test_kafka_virtual1.reference')
|
|
|
|
|
|
@pytest.mark.timeout(180)
|
|
def test_kafka_virtual_columns_with_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 = '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))
|
|
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 as timestamp FROM test.kafka;
|
|
''')
|
|
|
|
messages = []
|
|
for i in range(50):
|
|
messages.append(json.dumps({'key': i, 'value': i}))
|
|
kafka_produce('virt2', messages, 0)
|
|
|
|
while True:
|
|
result = instance.query('SELECT kafka_key, key, topic, value, offset, partition, timestamp FROM test.view')
|
|
if kafka_check_result(result, False, 'test_kafka_virtual2.reference'):
|
|
break
|
|
|
|
instance.query('''
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
''')
|
|
|
|
kafka_check_result(result, True, 'test_kafka_virtual2.reference')
|
|
|
|
|
|
@pytest.mark.timeout(180)
|
|
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_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('insert1'))
|
|
if len(messages) == 50:
|
|
break
|
|
|
|
result = '\n'.join(messages)
|
|
kafka_check_result(result, True)
|
|
|
|
|
|
@pytest.mark.timeout(240)
|
|
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)
|
|
|
|
|
|
@pytest.mark.timeout(300)
|
|
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('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;
|
|
''')
|
|
|
|
while int(instance.query("SELECT count() FROM system.tables WHERE database='test' AND name='kafka'")) == 1:
|
|
time.sleep(1)
|
|
|
|
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!'
|
|
|
|
|
|
@pytest.mark.timeout(180)
|
|
def test_kafka_virtual_columns2(kafka_cluster):
|
|
|
|
admin_client = KafkaAdminClient(bootstrap_servers="localhost:9092")
|
|
topic_list = []
|
|
topic_list.append(NewTopic(name="virt2_0", num_partitions=2, replication_factor=1))
|
|
topic_list.append(NewTopic(name="virt2_1", num_partitions=2, replication_factor=1))
|
|
|
|
admin_client.create_topics(new_topics=topic_list, validate_only=False)
|
|
|
|
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_format = 'JSONEachRow';
|
|
|
|
CREATE MATERIALIZED VIEW test.view Engine=Log AS
|
|
SELECT value, _key, _topic, _partition, _offset, toUnixTimestamp(_timestamp) FROM test.kafka;
|
|
''')
|
|
|
|
producer = KafkaProducer(bootstrap_servers="localhost:9092")
|
|
|
|
producer.send(topic='virt2_0', value=json.dumps({'value': 1}), partition=0, key='k1', timestamp_ms=1577836801000)
|
|
producer.send(topic='virt2_0', value=json.dumps({'value': 2}), partition=0, key='k2', timestamp_ms=1577836802000)
|
|
producer.flush()
|
|
time.sleep(1)
|
|
|
|
producer.send(topic='virt2_0', value=json.dumps({'value': 3}), partition=1, key='k3', timestamp_ms=1577836803000)
|
|
producer.send(topic='virt2_0', value=json.dumps({'value': 4}), partition=1, key='k4', timestamp_ms=1577836804000)
|
|
producer.flush()
|
|
time.sleep(1)
|
|
|
|
producer.send(topic='virt2_1', value=json.dumps({'value': 5}), partition=0, key='k5', timestamp_ms=1577836805000)
|
|
producer.send(topic='virt2_1', value=json.dumps({'value': 6}), partition=0, key='k6', timestamp_ms=1577836806000)
|
|
producer.flush()
|
|
time.sleep(1)
|
|
|
|
producer.send(topic='virt2_1', value=json.dumps({'value': 7}), partition=1, key='k7', timestamp_ms=1577836807000)
|
|
producer.send(topic='virt2_1', value=json.dumps({'value': 8}), partition=1, key='k8', timestamp_ms=1577836808000)
|
|
producer.flush()
|
|
|
|
time.sleep(10)
|
|
|
|
result = instance.query("SELECT * FROM test.view ORDER BY value", ignore_error=True)
|
|
|
|
expected = '''\
|
|
1 k1 virt2_0 0 0 1577836801
|
|
2 k2 virt2_0 0 1 1577836802
|
|
3 k3 virt2_0 1 0 1577836803
|
|
4 k4 virt2_0 1 1 1577836804
|
|
5 k5 virt2_1 0 0 1577836805
|
|
6 k6 virt2_1 0 1 1577836806
|
|
7 k7 virt2_1 1 0 1577836807
|
|
8 k8 virt2_1 1 1 1577836808
|
|
'''
|
|
|
|
assert TSV(result) == TSV(expected)
|
|
|
|
|
|
|
|
@pytest.mark.timeout(240)
|
|
def test_kafka_produce_key_timestamp(kafka_cluster):
|
|
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)
|
|
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)
|
|
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))
|
|
|
|
time.sleep(10)
|
|
|
|
result = instance.query("SELECT * FROM test.view ORDER BY value", ignore_error=True)
|
|
|
|
# print(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)
|
|
|
|
|
|
|
|
@pytest.mark.timeout(600)
|
|
def test_kafka_flush_by_time(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 = 'flush_by_time',
|
|
kafka_group_name = 'flush_by_time',
|
|
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()
|
|
|
|
def produce():
|
|
while not cancel.is_set():
|
|
messages = []
|
|
messages.append(json.dumps({'key': 0, 'value': 0}))
|
|
kafka_produce('flush_by_time', messages)
|
|
time.sleep(1)
|
|
|
|
kafka_thread = threading.Thread(target=produce)
|
|
kafka_thread.start()
|
|
|
|
time.sleep(18)
|
|
|
|
result = instance.query('SELECT count() FROM test.view')
|
|
|
|
print(result)
|
|
cancel.set()
|
|
kafka_thread.join()
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
|
|
instance.query('''
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
''')
|
|
|
|
# 40 = 2 flushes (7.5 sec), 15 polls each, about 1 mgs per 1.5 sec
|
|
assert int(result) > 12, 'Messages from kafka should be flushed at least every stream_flush_interval_ms!'
|
|
|
|
|
|
@pytest.mark.timeout(600)
|
|
def test_kafka_flush_by_block_size(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 = 'flush_by_block_size',
|
|
kafka_group_name = 'flush_by_block_size',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_max_block_size = 100,
|
|
kafka_row_delimiter = '\\n';
|
|
|
|
SELECT * FROM test.kafka;
|
|
|
|
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 _ in range(101):
|
|
messages.append(json.dumps({'key': 0, 'value': 0}))
|
|
kafka_produce('flush_by_block_size', messages)
|
|
|
|
time.sleep(1)
|
|
|
|
result = instance.query('SELECT count() FROM test.view')
|
|
# print(result)
|
|
|
|
# kafka_cluster.open_bash_shell('instance')
|
|
|
|
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 at least every stream_flush_interval_ms!'
|
|
|
|
|
|
@pytest.mark.timeout(600)
|
|
def test_kafka_lot_of_partitions_partial_commit_of_bulk(kafka_cluster):
|
|
admin_client = KafkaAdminClient(bootstrap_servers="localhost:9092")
|
|
|
|
topic_list = []
|
|
topic_list.append(NewTopic(name="topic_with_multiple_partitions2", num_partitions=10, replication_factor=1))
|
|
admin_client.create_topics(new_topics=topic_list, validate_only=False)
|
|
|
|
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;
|
|
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('topic_with_multiple_partitions2', messages)
|
|
|
|
time.sleep(30)
|
|
|
|
result = instance.query('SELECT count(), uniqExact(key), max(key) FROM test.view')
|
|
print(result)
|
|
assert TSV(result) == TSV('{0}\t{0}\t{0}'.format(count) )
|
|
|
|
instance.query('''
|
|
DROP TABLE test.consumer;
|
|
DROP TABLE test.view;
|
|
''')
|
|
|
|
@pytest.mark.timeout(1200)
|
|
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),
|
|
_consumed_by LowCardinality(String)
|
|
)
|
|
ENGINE = MergeTree()
|
|
ORDER BY key;
|
|
''')
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# kafka_cluster.open_bash_shell('instance')
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#time.sleep(2)
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admin_client = KafkaAdminClient(bootstrap_servers="localhost:9092")
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topic_list = []
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topic_list.append(NewTopic(name="topic_with_multiple_partitions", num_partitions=11, replication_factor=1))
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admin_client.create_topics(new_topics=topic_list, validate_only=False)
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cancel = threading.Event()
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|
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msg_index = [0]
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def produce():
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while not cancel.is_set():
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messages = []
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for _ in range(59):
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messages.append(json.dumps({'key': msg_index[0], 'value': msg_index[0]}))
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msg_index[0] += 1
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kafka_produce('topic_with_multiple_partitions', messages)
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|
|
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kafka_thread = threading.Thread(target=produce)
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kafka_thread.start()
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|
|
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for consumer_index in range(NUMBER_OF_CONSURRENT_CONSUMERS):
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|
table_name = 'kafka_consumer{}'.format(consumer_index)
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print("Setting up {}".format(table_name))
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|
|
|
instance.query('''
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|
DROP TABLE IF EXISTS test.{0};
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|
DROP TABLE IF EXISTS test.{0}_mv;
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|
CREATE TABLE test.{0} (key UInt64, value UInt64)
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|
ENGINE = Kafka
|
|
SETTINGS kafka_broker_list = 'kafka1:19092',
|
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kafka_topic_list = 'topic_with_multiple_partitions',
|
|
kafka_group_name = 'rebalance_test_group',
|
|
kafka_format = 'JSONEachRow',
|
|
kafka_max_block_size = 33;
|
|
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')
|
|
while int(instance.query("SELECT count() FROM test.destination WHERE _consumed_by='{}'".format(table_name))) == 0:
|
|
print("Waiting for test.kafka_consumer{} to start consume".format(consumer_index))
|
|
time.sleep(1)
|
|
|
|
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):
|
|
print("Dropping test.kafka_consumer{}".format(consumer_index))
|
|
instance.query('DROP TABLE IF EXISTS test.kafka_consumer{}'.format(consumer_index))
|
|
while int(instance.query("SELECT count() FROM system.tables WHERE database='test' AND name='kafka_consumer{}'".format(consumer_index))) == 1:
|
|
time.sleep(1)
|
|
|
|
# print(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)
|
|
print("Waiting for finishing consuming (have {}, should be {})".format(messages_consumed,msg_index[0]))
|
|
|
|
print(instance.query('SELECT count(), uniqExact(key), max(key) + 1 FROM test.destination'))
|
|
|
|
# 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) 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) 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;
|
|
|
|
result = int(instance.query('SELECT count() == uniqExact(key) FROM test.destination'))
|
|
|
|
for consumer_index in range(NUMBER_OF_CONSURRENT_CONSUMERS):
|
|
print("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!'
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
cluster.start()
|
|
raw_input("Cluster created, press any key to destroy...")
|
|
cluster.shutdown()
|