mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-17 21:24:28 +00:00
684 lines
21 KiB
Python
684 lines
21 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 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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main_configs=['configs/kafka.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 test.kafka')
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# Tests
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@pytest.mark.timeout(60)
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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(60)
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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(60)
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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(60)
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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(60)
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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(60)
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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(60)
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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(60)
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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(60)
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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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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)
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if kafka_check_result(result, False, 'test_kafka_virtual1.reference'):
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break
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kafka_check_result(result, True, 'test_kafka_virtual1.reference')
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@pytest.mark.timeout(60)
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def test_kafka_virtual_columns_with_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 = 'virt2',
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kafka_group_name = 'virt2',
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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, kafka_key String, topic String, offset UInt64, partition UInt64, timestamp Nullable(DateTime))
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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 *, _key as kafka_key, _topic as topic, _offset as offset, _partition as partition, _timestamp as timestamp 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('virt2', messages, 0)
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while True:
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result = instance.query('SELECT kafka_key, key, topic, value, offset, partition, timestamp FROM test.view')
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if kafka_check_result(result, False, 'test_kafka_virtual2.reference'):
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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, 'test_kafka_virtual2.reference')
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@pytest.mark.timeout(60)
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def test_kafka_insert(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 = '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(60)
|
|
def test_kafka_produce_consume(kafka_cluster):
|
|
instance.query('''
|
|
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';
|
|
''')
|
|
|
|
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()
|
|
|
|
instance.query('''
|
|
DROP TABLE IF EXISTS test.view;
|
|
DROP TABLE IF EXISTS test.consumer;
|
|
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;
|
|
''')
|
|
|
|
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!'
|
|
|
|
|
|
if __name__ == '__main__':
|
|
cluster.start()
|
|
raw_input("Cluster created, press any key to destroy...")
|
|
cluster.shutdown()
|