ClickHouse/tests/integration/test_parallel_replicas_over_distributed/test.py
Azat Khuzhin c25d6cd624
Rename directory monitor concept into background INSERT (#55978)
* Limit log frequence for "Skipping send data over distributed table" message

After SYSTEM STOP DISTRIBUTED SENDS it will constantly print this
message.

Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>

* Rename directory monitor concept into async INSERT

Rename the following query settings (with preserving backward
compatiblity, by keeping old name as an alias):
- distributed_directory_monitor_sleep_time_ms -> distributed_async_insert_sleep_time_ms
- distributed_directory_monitor_max_sleep_time_ms -> distributed_async_insert_max_sleep_time_ms
- distributed_directory_monitor_batch -> distributed_async_insert_batch_inserts
- distributed_directory_monitor_split_batch_on_failure -> distributed_async_insert_split_batch_on_failure

Rename the following table settings (with preserving backward
compatiblity, by keeping old name as an alias):
- monitor_batch_inserts -> async_insert_batch
- monitor_split_batch_on_failure -> async_insert_split_batch_on_failure
- directory_monitor_sleep_time_ms -> async_insert_sleep_time_ms
- directory_monitor_max_sleep_time_ms -> async_insert_max_sleep_time_ms

And also update all the references:

    $ gg -e directory_monitor_ -e monitor_ tests docs | cut -d: -f1 | sort -u | xargs sed -e 's/distributed_directory_monitor_sleep_time_ms/distributed_async_insert_sleep_time_ms/g' -e 's/distributed_directory_monitor_max_sleep_time_ms/distributed_async_insert_max_sleep_time_ms/g' -e 's/distributed_directory_monitor_batch_inserts/distributed_async_insert_batch/g' -e 's/distributed_directory_monitor_split_batch_on_failure/distributed_async_insert_split_batch_on_failure/g' -e 's/monitor_batch_inserts/async_insert_batch/g' -e 's/monitor_split_batch_on_failure/async_insert_split_batch_on_failure/g' -e 's/monitor_sleep_time_ms/async_insert_sleep_time_ms/g' -e 's/monitor_max_sleep_time_ms/async_insert_max_sleep_time_ms/g' -i

Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>

* Rename async_insert for Distributed into background_insert

This will avoid amigibuity between general async INSERT's and INSERT
into Distributed, which are indeed background, so new term express it
even better.

Mostly done with:

    $ git di HEAD^ --name-only | xargs sed -i -e 's/distributed_async_insert/distributed_background_insert/g' -e 's/async_insert_batch/background_insert_batch/g' -e 's/async_insert_split_batch_on_failure/background_insert_split_batch_on_failure/g' -e 's/async_insert_sleep_time_ms/background_insert_sleep_time_ms/g' -e 's/async_insert_max_sleep_time_ms/background_insert_max_sleep_time_ms/g'

Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>

* Mark 02417_opentelemetry_insert_on_distributed_table as long

CI: https://s3.amazonaws.com/clickhouse-test-reports/55978/7a6abb03a0b507e29e999cb7e04f246a119c6f28/stateless_tests_flaky_check__asan_.html
Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>

---------

Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>
2023-11-01 15:09:39 +01:00

154 lines
6.2 KiB
Python

import pytest
from helpers.cluster import ClickHouseCluster
cluster = ClickHouseCluster(__file__)
nodes = [
cluster.add_instance(
f"n{i}", main_configs=["configs/remote_servers.xml"], with_zookeeper=True
)
for i in (1, 2, 3, 4, 5, 6)
]
@pytest.fixture(scope="module", autouse=True)
def start_cluster():
try:
cluster.start()
yield cluster
finally:
cluster.shutdown()
def create_tables(cluster, table_name):
# create replicated tables
for node in nodes:
node.query(f"DROP TABLE IF EXISTS {table_name} SYNC")
if cluster == "test_single_shard_multiple_replicas":
nodes[0].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r1') ORDER BY (key)"
)
nodes[1].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r2') ORDER BY (key)"
)
nodes[2].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r3') ORDER BY (key)"
)
nodes[3].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r4') ORDER BY (key)"
)
elif cluster == "test_multiple_shards_multiple_replicas":
# shard 1
nodes[0].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r1') ORDER BY (key)"
)
nodes[1].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r2') ORDER BY (key)"
)
nodes[2].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard1/{table_name}', 'r3') ORDER BY (key)"
)
# shard 2
nodes[3].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard2/{table_name}', 'r1') ORDER BY (key)"
)
nodes[4].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard2/{table_name}', 'r2') ORDER BY (key)"
)
nodes[5].query(
f"CREATE TABLE IF NOT EXISTS {table_name} (key Int64, value String) Engine=ReplicatedMergeTree('/test_parallel_replicas/shard2/{table_name}', 'r3') ORDER BY (key)"
)
else:
raise Exception(f"Unexpected cluster: {cluster}")
# create distributed table
nodes[0].query(f"DROP TABLE IF EXISTS {table_name}_d SYNC")
nodes[0].query(
f"""
CREATE TABLE {table_name}_d AS {table_name}
Engine=Distributed(
{cluster},
currentDatabase(),
{table_name},
key
)
"""
)
# populate data
nodes[0].query(
f"INSERT INTO {table_name}_d SELECT number, number FROM numbers(1000)",
settings={"distributed_foreground_insert": 1},
)
nodes[0].query(
f"INSERT INTO {table_name}_d SELECT number, number FROM numbers(2000)",
settings={"distributed_foreground_insert": 1},
)
nodes[0].query(
f"INSERT INTO {table_name}_d SELECT -number, -number FROM numbers(1000)",
settings={"distributed_foreground_insert": 1},
)
nodes[0].query(
f"INSERT INTO {table_name}_d SELECT -number, -number FROM numbers(2000)",
settings={"distributed_foreground_insert": 1},
)
nodes[0].query(
f"INSERT INTO {table_name}_d SELECT number, number FROM numbers(3)",
settings={"distributed_foreground_insert": 1},
)
@pytest.mark.parametrize(
"cluster,max_parallel_replicas,prefer_localhost_replica",
[
pytest.param("test_single_shard_multiple_replicas", 2, 0),
pytest.param("test_single_shard_multiple_replicas", 3, 0),
pytest.param("test_single_shard_multiple_replicas", 4, 0),
pytest.param("test_single_shard_multiple_replicas", 10, 0),
pytest.param("test_single_shard_multiple_replicas", 2, 1),
pytest.param("test_single_shard_multiple_replicas", 3, 1),
pytest.param("test_single_shard_multiple_replicas", 4, 1),
pytest.param("test_single_shard_multiple_replicas", 10, 1),
pytest.param("test_multiple_shards_multiple_replicas", 2, 0),
pytest.param("test_multiple_shards_multiple_replicas", 3, 0),
pytest.param("test_multiple_shards_multiple_replicas", 4, 0),
pytest.param("test_multiple_shards_multiple_replicas", 10, 0),
pytest.param("test_multiple_shards_multiple_replicas", 2, 1),
pytest.param("test_multiple_shards_multiple_replicas", 3, 1),
pytest.param("test_multiple_shards_multiple_replicas", 4, 1),
pytest.param("test_multiple_shards_multiple_replicas", 10, 1),
],
)
def test_parallel_replicas_over_distributed(
start_cluster, cluster, max_parallel_replicas, prefer_localhost_replica
):
table_name = "test_table"
create_tables(cluster, table_name)
node = nodes[0]
expected_result = f"6003\t-1999\t1999\t3\n"
# parallel replicas
assert (
node.query(
f"SELECT count(), min(key), max(key), sum(key) FROM {table_name}_d",
settings={
"allow_experimental_parallel_reading_from_replicas": 2,
"prefer_localhost_replica": prefer_localhost_replica,
"max_parallel_replicas": max_parallel_replicas,
"use_hedged_requests": 0,
},
)
== expected_result
)
# sync all replicas to get consistent result by next distributed query
node.query(f"SYSTEM SYNC REPLICA ON CLUSTER {cluster} {table_name}")
# w/o parallel replicas
assert (
node.query(f"SELECT count(), min(key), max(key), sum(key) FROM {table_name}_d")
== expected_result
)