memgraph/tests/e2e/streams/streams_tests.py

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#!/usr/bin/python3
# To run these test locally a running Kafka sever is necessery. The test tries
# to connect on localhost:9092.
# All tests are implemented in this file, because using the same test fixtures
# in multiple files is not possible in a straightforward way
import sys
import pytest
import mgclient
import time
from multiprocessing import Process, Value
from kafka import KafkaProducer
from kafka.admin import KafkaAdminClient, NewTopic
# These are the indices of the different values in the result of SHOW STREAM
# query
NAME = 0
TOPICS = 1
CONSUMER_GROUP = 2
BATCH_INTERVAL = 3
BATCH_SIZE = 4
TRANSFORM = 5
IS_RUNNING = 6
# These are the indices of the query and parameters in the result of CHECK
# STREAM query
QUERY = 0
PARAMS = 1
TRANSFORMATIONS_TO_CHECK = [
"transform.simple", "transform.with_parameters"]
SIMPLE_MSG = b'message'
def execute_and_fetch_all(cursor, query):
cursor.execute(query)
return cursor.fetchall()
def connect():
connection = mgclient.connect(host="localhost", port=7687)
connection.autocommit = True
return connection
@pytest.fixture(autouse=True)
def connection():
connection = connect()
yield connection
cursor = connection.cursor()
execute_and_fetch_all(cursor, "MATCH (n) DETACH DELETE n")
stream_infos = execute_and_fetch_all(cursor, "SHOW STREAMS")
for stream_info in stream_infos:
execute_and_fetch_all(cursor, f"DROP STREAM {stream_info[NAME]}")
@pytest.fixture(scope="function")
def topics():
admin_client = KafkaAdminClient(
bootstrap_servers="localhost:9092", client_id='test')
topics = []
topics_to_create = []
for index in range(3):
topic = f"topic_{index}"
topics.append(topic)
topics_to_create.append(NewTopic(name=topic,
num_partitions=1, replication_factor=1))
admin_client.create_topics(new_topics=topics_to_create, timeout_ms=5000)
yield topics
admin_client.delete_topics(topics=topics, timeout_ms=5000)
@pytest.fixture(scope="function")
def producer():
yield KafkaProducer(bootstrap_servers="localhost:9092")
def timed_wait(fun):
start_time = time.time()
seconds = 10
while True:
current_time = time.time()
elapsed_time = current_time - start_time
if elapsed_time > seconds:
return False
if fun():
return True
def check_one_result_row(cursor, query):
start_time = time.time()
seconds = 10
while True:
current_time = time.time()
elapsed_time = current_time - start_time
if elapsed_time > seconds:
return False
cursor.execute(query)
results = cursor.fetchall()
if len(results) < 1:
time.sleep(0.1)
continue
return len(results) == 1
def check_vertex_exists_with_topic_and_payload(cursor, topic, payload_bytes):
assert check_one_result_row(cursor,
"MATCH (n: MESSAGE {"
f"payload: '{payload_bytes.decode('utf-8')}',"
f"topic: '{topic}'"
"}) RETURN n")
def get_stream_info(cursor, stream_name):
stream_infos = execute_and_fetch_all(cursor, "SHOW STREAMS")
for stream_info in stream_infos:
if (stream_info[NAME] == stream_name):
return stream_info
return None
def get_is_running(cursor, stream_name):
stream_info = get_stream_info(cursor, stream_name)
assert stream_info
return stream_info[IS_RUNNING]
def start_stream(cursor, stream_name):
execute_and_fetch_all(cursor, f"START STREAM {stream_name}")
assert get_is_running(cursor, stream_name)
def stop_stream(cursor, stream_name):
execute_and_fetch_all(cursor, f"STOP STREAM {stream_name}")
assert not get_is_running(cursor, stream_name)
def drop_stream(cursor, stream_name):
execute_and_fetch_all(cursor, f"DROP STREAM {stream_name}")
assert get_stream_info(cursor, stream_name) is None
def check_stream_info(cursor, stream_name, expected_stream_info):
stream_info = get_stream_info(cursor, stream_name)
assert len(stream_info) == len(expected_stream_info)
for info, expected_info in zip(stream_info, expected_stream_info):
assert info == expected_info
##############################################
# Tests
##############################################
@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
def test_simple(producer, topics, connection, transformation):
assert len(topics) > 0
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM test "
f"TOPICS {','.join(topics)} "
f"TRANSFORM {transformation}")
start_stream(cursor, "test")
time.sleep(5)
for topic in topics:
producer.send(topic, SIMPLE_MSG).get(timeout=60)
for topic in topics:
check_vertex_exists_with_topic_and_payload(
cursor, topic, SIMPLE_MSG)
@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
def test_separate_consumers(producer, topics, connection, transformation):
assert len(topics) > 0
cursor = connection.cursor()
stream_names = []
for topic in topics:
stream_name = "stream_" + topic
stream_names.append(stream_name)
execute_and_fetch_all(cursor,
f"CREATE STREAM {stream_name} "
f"TOPICS {topic} "
f"TRANSFORM {transformation}")
for stream_name in stream_names:
start_stream(cursor, stream_name)
time.sleep(5)
for topic in topics:
producer.send(topic, SIMPLE_MSG).get(timeout=60)
for topic in topics:
check_vertex_exists_with_topic_and_payload(
cursor, topic, SIMPLE_MSG)
def test_start_from_last_committed_offset(producer, topics, connection):
# This test creates a stream, consumes a message to have a committed
# offset, then destroys the stream. A new message is sent before the
# stream is recreated and then restarted. This simulates when Memgraph is
# stopped (stream is destroyed) and then restarted (stream is recreated).
# This is of course not as good as restarting memgraph would be, but
# restarting Memgraph during a single workload cannot be done currently.
assert len(topics) > 0
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM test "
f"TOPICS {topics[0]} "
"TRANSFORM transform.simple")
start_stream(cursor, "test")
time.sleep(1)
producer.send(topics[0], SIMPLE_MSG).get(timeout=60)
check_vertex_exists_with_topic_and_payload(
cursor, topics[0], SIMPLE_MSG)
stop_stream(cursor, "test")
drop_stream(cursor, "test")
messages = [b"second message", b"third message"]
for message in messages:
producer.send(topics[0], message).get(timeout=60)
for message in messages:
vertices_with_msg = execute_and_fetch_all(cursor,
"MATCH (n: MESSAGE {"
f"payload: '{message.decode('utf-8')}'"
"}) RETURN n")
assert len(vertices_with_msg) == 0
execute_and_fetch_all(cursor,
"CREATE STREAM test "
f"TOPICS {topics[0]} "
"TRANSFORM transform.simple")
start_stream(cursor, "test")
for message in messages:
check_vertex_exists_with_topic_and_payload(
cursor, topics[0], message)
@pytest.mark.parametrize("transformation", TRANSFORMATIONS_TO_CHECK)
def test_check_stream(producer, topics, connection, transformation):
assert len(topics) > 0
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM test "
f"TOPICS {topics[0]} "
f"TRANSFORM {transformation} "
"BATCH_SIZE 1")
start_stream(cursor, "test")
time.sleep(1)
producer.send(topics[0], SIMPLE_MSG).get(timeout=60)
stop_stream(cursor, "test")
messages = [b"first message", b"second message", b"third message"]
for message in messages:
producer.send(topics[0], message).get(timeout=60)
def check_check_stream(batch_limit):
assert transformation == "transform.simple" \
or transformation == "transform.with_parameters"
test_results = execute_and_fetch_all(
cursor, f"CHECK STREAM test BATCH_LIMIT {batch_limit}")
assert len(test_results) == batch_limit
for i in range(batch_limit):
message_as_str = messages[i].decode('utf-8')
if transformation == "transform.simple":
assert f"payload: '{message_as_str}'" in \
test_results[i][QUERY]
assert test_results[i][PARAMS] is None
else:
assert test_results[i][QUERY] == ("CREATE (n:MESSAGE "
"{timestamp: $timestamp, "
"payload: $payload, "
"topic: $topic})")
parameters = test_results[i][PARAMS]
# this is not a very sofisticated test, but checks if
# timestamp has some kind of value
assert parameters["timestamp"] > 1000000000000
assert parameters["topic"] == topics[0]
assert parameters["payload"] == message_as_str
check_check_stream(1)
check_check_stream(2)
check_check_stream(3)
start_stream(cursor, "test")
for message in messages:
check_vertex_exists_with_topic_and_payload(
cursor, topics[0], message)
def test_show_streams(producer, topics, connection):
assert len(topics) > 1
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM default_values "
f"TOPICS {topics[0]} "
f"TRANSFORM transform.simple")
consumer_group = "my_special_consumer_group"
batch_interval = 42
batch_size = 3
execute_and_fetch_all(cursor,
"CREATE STREAM complex_values "
f"TOPICS {','.join(topics)} "
f"TRANSFORM transform.with_parameters "
f"CONSUMER_GROUP {consumer_group} "
f"BATCH_INTERVAL {batch_interval} "
f"BATCH_SIZE {batch_size} ")
assert len(execute_and_fetch_all(cursor, "SHOW STREAMS")) == 2
check_stream_info(cursor, "default_values", ("default_values", [
topics[0]], "mg_consumer", None, None,
"transform.simple", False))
check_stream_info(cursor, "complex_values", ("complex_values", topics,
consumer_group, batch_interval, batch_size,
"transform.with_parameters",
False))
@pytest.mark.parametrize("operation", ["START", "STOP"])
def test_start_and_stop_during_check(producer, topics, connection, operation):
# This test is quite complex. The goal is to call START/STOP queries
# while a CHECK query is waiting for its result. Because the Global
# Interpreter Lock, running queries on multiple threads is not useful,
# because only one of them can call Cursor::execute at a time. Therefore
# multiple processes are used to execute the queries, because different
# processes have different GILs.
# The counter variables are thread- and process-safe variables to
# synchronize between the different processes. Each value represents a
# specific phase of the execution of the processes.
assert len(topics) > 1
assert operation == "START" or operation == "STOP"
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM test_stream "
f"TOPICS {topics[0]} "
f"TRANSFORM transform.simple")
check_counter = Value('i', 0)
check_result_len = Value('i', 0)
operation_counter = Value('i', 0)
CHECK_BEFORE_EXECUTE = 1
CHECK_AFTER_FETCHALL = 2
CHECK_CORRECT_RESULT = 3
CHECK_INCORRECT_RESULT = 4
def call_check(counter, result_len):
# This process will call the CHECK query and increment the counter
# based on its progress and expected behavior
connection = connect()
cursor = connection.cursor()
counter.value = CHECK_BEFORE_EXECUTE
result = execute_and_fetch_all(cursor, "CHECK STREAM test_stream")
result_len.value = len(result)
counter.value = CHECK_AFTER_FETCHALL
if len(result) > 0 and "payload: 'message'" in result[0][QUERY]:
counter.value = CHECK_CORRECT_RESULT
else:
counter.value = CHECK_INCORRECT_RESULT
OP_BEFORE_EXECUTE = 1
OP_AFTER_FETCHALL = 2
OP_ALREADY_STOPPED_EXCEPTION = 3
OP_INCORRECT_ALREADY_STOPPED_EXCEPTION = 4
OP_UNEXPECTED_EXCEPTION = 5
def call_operation(counter):
# This porcess will call the query with the specified operation and
# increment the counter based on its progress and expected behavior
connection = connect()
cursor = connection.cursor()
counter.value = OP_BEFORE_EXECUTE
try:
execute_and_fetch_all(cursor, f"{operation} STREAM test_stream")
counter.value = OP_AFTER_FETCHALL
except mgclient.DatabaseError as e:
if "Kafka consumer test_stream is already stopped" in str(e):
counter.value = OP_ALREADY_STOPPED_EXCEPTION
else:
counter.value = OP_INCORRECT_ALREADY_STOPPED_EXCEPTION
except Exception:
counter.value = OP_UNEXPECTED_EXCEPTION
check_stream_proc = Process(
target=call_check, daemon=True, args=(check_counter, check_result_len))
operation_proc = Process(target=call_operation,
daemon=True, args=(operation_counter,))
try:
check_stream_proc.start()
time.sleep(0.5)
assert timed_wait(lambda: check_counter.value == CHECK_BEFORE_EXECUTE)
assert timed_wait(lambda: get_is_running(cursor, "test_stream"))
assert check_counter.value == CHECK_BEFORE_EXECUTE, "SHOW STREAMS " \
"was blocked until the end of CHECK STREAM"
operation_proc.start()
assert timed_wait(lambda: operation_counter.value == OP_BEFORE_EXECUTE)
producer.send(topics[0], SIMPLE_MSG).get(timeout=60)
assert timed_wait(lambda: check_counter.value > CHECK_AFTER_FETCHALL)
assert check_counter.value == CHECK_CORRECT_RESULT
assert check_result_len.value == 1
check_stream_proc.join()
operation_proc.join()
if operation == "START":
assert operation_counter.value == OP_AFTER_FETCHALL
assert get_is_running(cursor, "test_stream")
else:
assert operation_counter.value == OP_ALREADY_STOPPED_EXCEPTION
assert not get_is_running(cursor, "test_stream")
finally:
# to make sure CHECK STREAM finishes
producer.send(topics[0], SIMPLE_MSG).get(timeout=60)
if check_stream_proc.is_alive():
check_stream_proc.terminate()
if operation_proc.is_alive():
operation_proc.terminate()
def test_check_already_started_stream(topics, connection):
assert len(topics) > 0
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM started_stream "
f"TOPICS {topics[0]} "
f"TRANSFORM transform.simple")
start_stream(cursor, "started_stream")
with pytest.raises(mgclient.DatabaseError):
execute_and_fetch_all(cursor, "CHECK STREAM started_stream")
def test_start_checked_stream_after_timeout(topics, connection):
cursor = connection.cursor()
execute_and_fetch_all(cursor,
"CREATE STREAM test_stream "
f"TOPICS {topics[0]} "
f"TRANSFORM transform.simple")
timeout_ms = 2000
def call_check():
execute_and_fetch_all(
connect().cursor(),
f"CHECK STREAM test_stream TIMEOUT {timeout_ms}")
check_stream_proc = Process(target=call_check, daemon=True)
start = time.time()
check_stream_proc.start()
assert timed_wait(lambda: get_is_running(cursor, "test_stream"))
start_stream(cursor, "test_stream")
end = time.time()
assert (end - start) < 1.3 * \
timeout_ms, "The START STREAM was blocked too long"
assert get_is_running(cursor, "test_stream")
stop_stream(cursor, "test_stream")
if __name__ == "__main__":
sys.exit(pytest.main([__file__, "-rA"]))