456 lines
15 KiB
Python
Executable File
456 lines
15 KiB
Python
Executable File
#!/usr/bin/python3
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# Copyright 2021 Memgraph Ltd.
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#
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# Use of this software is governed by the Business Source License
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# included in the file licenses/BSL.txt; by using this file, you agree to be bound by the terms of the Business Source
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# License, and you may not use this file except in compliance with the Business Source License.
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#
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# As of the Change Date specified in that file, in accordance with
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# the Business Source License, use of this software will be governed
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# by the Apache License, Version 2.0, included in the file
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# licenses/APL.txt.
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import sys
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import pytest
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import mgclient
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import time
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from multiprocessing import Process, Value
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import common
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TRANSFORMATIONS_TO_CHECK = [
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"kafka_transform.simple",
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"kafka_transform.with_parameters"]
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@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
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def test_simple(kafka_producer, kafka_topics, connection, transformation):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM test "
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f"TOPICS {','.join(kafka_topics)} "
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f"TRANSFORM {transformation}",
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)
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common.start_stream(cursor, "test")
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time.sleep(5)
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for topic in kafka_topics:
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kafka_producer.send(topic, common.SIMPLE_MSG).get(timeout=60)
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for topic in kafka_topics:
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common.kafka_check_vertex_exists_with_topic_and_payload(
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cursor, topic, common.SIMPLE_MSG)
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@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
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def test_separate_consumers(
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kafka_producer,
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kafka_topics,
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connection,
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transformation):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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stream_names = []
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for topic in kafka_topics:
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stream_name = "stream_" + topic
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stream_names.append(stream_name)
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common.execute_and_fetch_all(
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cursor,
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f"CREATE KAFKA STREAM {stream_name} "
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f"TOPICS {topic} "
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f"TRANSFORM {transformation}",
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)
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for stream_name in stream_names:
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common.start_stream(cursor, stream_name)
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time.sleep(5)
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for topic in kafka_topics:
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kafka_producer.send(topic, common.SIMPLE_MSG).get(timeout=60)
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for topic in kafka_topics:
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common.kafka_check_vertex_exists_with_topic_and_payload(
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cursor, topic, common.SIMPLE_MSG)
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def test_start_from_last_committed_offset(
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kafka_producer, kafka_topics, connection):
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# This test creates a stream, consumes a message to have a committed
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# offset, then destroys the stream. A new message is sent before the
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# stream is recreated and then restarted. This simulates when Memgraph is
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# stopped (stream is destroyed) and then restarted (stream is recreated).
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# This is of course not as good as restarting memgraph would be, but
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# restarting Memgraph during a single workload cannot be done currently.
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor, "CREATE KAFKA STREAM test "
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f"TOPICS {kafka_topics[0]} "
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"TRANSFORM kafka_transform.simple", )
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common.start_stream(cursor, "test")
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time.sleep(1)
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kafka_producer.send(kafka_topics[0], common.SIMPLE_MSG).get(timeout=60)
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common.kafka_check_vertex_exists_with_topic_and_payload(
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cursor, kafka_topics[0], common.SIMPLE_MSG)
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common.stop_stream(cursor, "test")
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common.drop_stream(cursor, "test")
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messages = [b"second message", b"third message"]
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for message in messages:
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kafka_producer.send(kafka_topics[0], message).get(timeout=60)
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for message in messages:
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vertices_with_msg = common.execute_and_fetch_all(
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cursor,
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"MATCH (n: MESSAGE {" f"payload: '{message.decode('utf-8')}'" "}) RETURN n",
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)
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assert len(vertices_with_msg) == 0
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common.execute_and_fetch_all(
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cursor, "CREATE KAFKA STREAM test "
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f"TOPICS {kafka_topics[0]} "
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"TRANSFORM kafka_transform.simple", )
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common.start_stream(cursor, "test")
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for message in messages:
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common.kafka_check_vertex_exists_with_topic_and_payload(
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cursor, kafka_topics[0], message)
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@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
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def test_check_stream(
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kafka_producer,
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kafka_topics,
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connection,
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transformation):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM test "
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f"TOPICS {kafka_topics[0]} "
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f"TRANSFORM {transformation} "
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"BATCH_SIZE 1",
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)
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common.start_stream(cursor, "test")
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time.sleep(1)
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kafka_producer.send(kafka_topics[0], common.SIMPLE_MSG).get(timeout=60)
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common.stop_stream(cursor, "test")
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messages = [b"first message", b"second message", b"third message"]
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for message in messages:
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kafka_producer.send(kafka_topics[0], message).get(timeout=60)
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def check_check_stream(batch_limit):
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assert (
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transformation == "kafka_transform.simple"
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or transformation == "kafka_transform.with_parameters"
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)
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test_results = common.execute_and_fetch_all(
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cursor, f"CHECK STREAM test BATCH_LIMIT {batch_limit}"
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)
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assert len(test_results) == batch_limit
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for i in range(batch_limit):
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message_as_str = messages[i].decode("utf-8")
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if transformation == "kafka_transform.simple":
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assert f"payload: '{message_as_str}'" in test_results[i][common.QUERY]
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assert test_results[i][common.PARAMS] is None
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else:
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assert f"payload: $payload" in test_results[i][
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common.QUERY] and f"topic: $topic" in test_results[i][common.QUERY]
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parameters = test_results[i][common.PARAMS]
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# this is not a very sofisticated test, but checks if
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# timestamp has some kind of value
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assert parameters["timestamp"] > 1000000000000
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assert parameters["topic"] == kafka_topics[0]
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assert parameters["payload"] == message_as_str
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check_check_stream(1)
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check_check_stream(2)
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check_check_stream(3)
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common.start_stream(cursor, "test")
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for message in messages:
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common.kafka_check_vertex_exists_with_topic_and_payload(
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cursor, kafka_topics[0], message)
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def test_show_streams(kafka_producer, kafka_topics, connection):
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assert len(kafka_topics) > 1
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM default_values "
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f"TOPICS {kafka_topics[0]} "
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f"TRANSFORM kafka_transform.simple "
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f"BOOTSTRAP_SERVERS 'localhost:9092'",
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)
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consumer_group = "my_special_consumer_group"
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batch_interval = 42
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batch_size = 3
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM complex_values "
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f"TOPICS {','.join(kafka_topics)} "
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f"TRANSFORM kafka_transform.with_parameters "
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f"CONSUMER_GROUP {consumer_group} "
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f"BATCH_INTERVAL {batch_interval} "
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f"BATCH_SIZE {batch_size} ",
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)
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assert len(common.execute_and_fetch_all(cursor, "SHOW STREAMS")) == 2
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common.check_stream_info(
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cursor,
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"default_values",
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("default_values",
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"kafka",
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100,
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1000,
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"kafka_transform.simple",
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None,
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False),
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)
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common.check_stream_info(
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cursor,
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"complex_values",
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(
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"complex_values",
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"kafka",
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batch_interval,
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batch_size,
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"kafka_transform.with_parameters",
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None,
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False,
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),
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)
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@pytest.mark.parametrize("operation", ["START", "STOP"])
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def test_start_and_stop_during_check(
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kafka_producer,
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kafka_topics,
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connection,
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operation):
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assert len(kafka_topics) > 1
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def stream_creator(stream_name):
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return f"CREATE KAFKA STREAM {stream_name} TOPICS {kafka_topics[0]} TRANSFORM kafka_transform.simple"
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def message_sender(msg):
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kafka_producer.send(kafka_topics[0], msg).get(timeout=60)
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common.test_start_and_stop_during_check(
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operation,
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connection,
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stream_creator,
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message_sender,
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"Kafka consumer test_stream is already stopped")
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def test_check_already_started_stream(kafka_topics, connection):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM started_stream "
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f"TOPICS {kafka_topics[0]} "
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f"TRANSFORM kafka_transform.simple",
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)
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common.start_stream(cursor, "started_stream")
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with pytest.raises(mgclient.DatabaseError):
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common.execute_and_fetch_all(cursor, "CHECK STREAM started_stream")
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def test_start_checked_stream_after_timeout(kafka_topics, connection):
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def stream_creator(stream_name):
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return f"CREATE KAFKA STREAM {stream_name} TOPICS {kafka_topics[0]} TRANSFORM kafka_transform.simple"
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common.test_start_checked_stream_after_timeout(connection, stream_creator)
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def test_restart_after_error(kafka_producer, kafka_topics, connection):
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM test_stream "
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f"TOPICS {kafka_topics[0]} "
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f"TRANSFORM kafka_transform.query",
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)
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common.start_stream(cursor, "test_stream")
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time.sleep(1)
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kafka_producer.send(kafka_topics[0], common.SIMPLE_MSG).get(timeout=60)
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assert common.timed_wait(
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lambda: not common.get_is_running(
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cursor, "test_stream"))
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common.start_stream(cursor, "test_stream")
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time.sleep(1)
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kafka_producer.send(kafka_topics[0], b"CREATE (n:VERTEX { id : 42 })")
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assert common.check_one_result_row(
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cursor, "MATCH (n:VERTEX { id : 42 }) RETURN n")
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@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
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def test_bootstrap_server(
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kafka_producer,
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kafka_topics,
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connection,
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transformation):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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local = "localhost:9092"
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM test "
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f"TOPICS {','.join(kafka_topics)} "
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f"TRANSFORM {transformation} "
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f"BOOTSTRAP_SERVERS '{local}'",
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)
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common.start_stream(cursor, "test")
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time.sleep(5)
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for topic in kafka_topics:
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kafka_producer.send(topic, common.SIMPLE_MSG).get(timeout=60)
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for topic in kafka_topics:
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common.kafka_check_vertex_exists_with_topic_and_payload(
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cursor, topic, common.SIMPLE_MSG)
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@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
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def test_bootstrap_server_empty(
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kafka_producer,
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kafka_topics,
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connection,
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transformation):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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with pytest.raises(mgclient.DatabaseError):
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM test "
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f"TOPICS {','.join(kafka_topics)} "
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f"TRANSFORM {transformation} "
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"BOOTSTRAP_SERVERS ''",
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)
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@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
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def test_set_offset(kafka_producer, kafka_topics, connection, transformation):
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assert len(kafka_topics) > 0
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cursor = connection.cursor()
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common.execute_and_fetch_all(
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cursor,
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"CREATE KAFKA STREAM test "
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f"TOPICS {kafka_topics[0]} "
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f"TRANSFORM {transformation} "
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"BATCH_SIZE 1",
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)
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messages = [f"{i} message" for i in range(1, 21)]
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for message in messages:
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kafka_producer.send(kafka_topics[0], message.encode()).get(timeout=60)
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def consume(expected_msgs):
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common.start_stream(cursor, "test")
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if len(expected_msgs) == 0:
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time.sleep(2)
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else:
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assert common.check_one_result_row(
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cursor,
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(
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f"MATCH (n: MESSAGE {{payload: '{expected_msgs[-1]}'}})"
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"RETURN n"
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),
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)
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common.stop_stream(cursor, "test")
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res = common.execute_and_fetch_all(
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cursor, "MATCH (n) RETURN n.payload"
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)
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return res
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def execute_set_offset_and_consume(id, expected_msgs):
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common.execute_and_fetch_all(
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cursor, f"CALL mg.kafka_set_stream_offset('test', {id})"
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)
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return consume(expected_msgs)
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with pytest.raises(mgclient.DatabaseError):
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res = common.execute_and_fetch_all(
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cursor, "CALL mg.kafka_set_stream_offset('foo', 10)"
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)
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def comparison_check(a, b):
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return a == str(b).strip("'(,)")
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res = execute_set_offset_and_consume(10, messages[10:])
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assert len(res) == 10
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assert all([comparison_check(a, b) for a, b in zip(messages[10:], res)])
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common.execute_and_fetch_all(cursor, "MATCH (n) DETACH DELETE n")
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res = execute_set_offset_and_consume(-1, messages)
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assert len(res) == len(messages)
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assert all([comparison_check(a, b) for a, b in zip(messages, res)])
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res = common.execute_and_fetch_all(cursor, "MATCH (n) return n.offset")
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assert all([comparison_check(str(i), res[i]) for i in range(1, 20)])
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res = common.execute_and_fetch_all(cursor, "MATCH (n) DETACH DELETE n")
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res = execute_set_offset_and_consume(-2, [])
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assert len(res) == 0
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last_msg = "Final Message"
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kafka_producer.send(kafka_topics[0], last_msg.encode()).get(timeout=60)
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res = consume([last_msg])
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assert len(res) == 1
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assert comparison_check("Final Message", res[0])
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common.execute_and_fetch_all(cursor, "MATCH (n) DETACH DELETE n")
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def test_info_procedure(kafka_topics, connection):
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cursor = connection.cursor()
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stream_name = 'test_stream'
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configs = {"sasl.username": "michael.scott"}
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local = "localhost:9092"
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credentials = {"sasl.password": "S3cr3tP4ssw0rd"}
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consumer_group = "ConsumerGr"
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common.execute_and_fetch_all(
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cursor,
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f"CREATE KAFKA STREAM {stream_name} "
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f"TOPICS {','.join(kafka_topics)} "
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f"TRANSFORM pulsar_transform.simple "
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f"CONSUMER_GROUP {consumer_group} "
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f"BOOTSTRAP_SERVERS '{local}' "
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f"CONFIGS {configs} "
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f"CREDENTIALS {credentials}"
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)
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stream_info = common.execute_and_fetch_all(
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cursor, f"CALL mg.kafka_stream_info('{stream_name}') YIELD *")
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reducted_credentials = {key: "<REDUCTED>" for
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key in credentials.keys()}
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expected_stream_info = [
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(local, configs, consumer_group, reducted_credentials, kafka_topics)]
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common.validate_info(stream_info, expected_stream_info)
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if __name__ == "__main__":
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sys.exit(pytest.main([__file__, "-rA"]))
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