ClickHouse/tests/integration/test_storage_s3_queue/test.py
2023-11-10 11:28:09 +01:00

921 lines
27 KiB
Python

import io
import logging
import os
import random
import time
import pytest
from helpers.client import QueryRuntimeException
from helpers.cluster import ClickHouseCluster, ClickHouseInstance
import json
"""
export CLICKHOUSE_TESTS_SERVER_BIN_PATH=/home/sergey/vkr/ClickHouse/build/programs/clickhouse-server
export CLICKHOUSE_TESTS_CLIENT_BIN_PATH=/home/sergey/vkr/ClickHouse/build/programs/clickhouse-client
export CLICKHOUSE_TESTS_ODBC_BRIDGE_BIN_PATH=/home/sergey/vkr/ClickHouse/build/programs/clickhouse-odbc-bridge
export CLICKHOUSE_TESTS_BASE_CONFIG_DIR=/home/sergey/vkr/ClickHouse/programs/server
"""
MINIO_INTERNAL_PORT = 9001
AVAILABLE_MODES = ["unordered", "ordered"]
AUTH = "'minio','minio123',"
SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
def prepare_s3_bucket(started_cluster):
# Allows read-write access for bucket without authorization.
bucket_read_write_policy = {
"Version": "2012-10-17",
"Statement": [
{
"Sid": "",
"Effect": "Allow",
"Principal": {"AWS": "*"},
"Action": "s3:GetBucketLocation",
"Resource": "arn:aws:s3:::root",
},
{
"Sid": "",
"Effect": "Allow",
"Principal": {"AWS": "*"},
"Action": "s3:ListBucket",
"Resource": "arn:aws:s3:::root",
},
{
"Sid": "",
"Effect": "Allow",
"Principal": {"AWS": "*"},
"Action": "s3:GetObject",
"Resource": "arn:aws:s3:::root/*",
},
{
"Sid": "",
"Effect": "Allow",
"Principal": {"AWS": "*"},
"Action": "s3:PutObject",
"Resource": "arn:aws:s3:::root/*",
},
{
"Sid": "",
"Effect": "Allow",
"Principal": {"AWS": "*"},
"Action": "s3:DeleteObject",
"Resource": "arn:aws:s3:::root/*",
},
],
}
minio_client = started_cluster.minio_client
minio_client.set_bucket_policy(
started_cluster.minio_bucket, json.dumps(bucket_read_write_policy)
)
started_cluster.minio_restricted_bucket = "{}-with-auth".format(
started_cluster.minio_bucket
)
if minio_client.bucket_exists(started_cluster.minio_restricted_bucket):
minio_client.remove_bucket(started_cluster.minio_restricted_bucket)
minio_client.make_bucket(started_cluster.minio_restricted_bucket)
@pytest.fixture(autouse=True)
def s3_queue_setup_teardown(started_cluster):
instance = started_cluster.instances["instance"]
instance_2 = started_cluster.instances["instance2"]
instance.query("DROP DATABASE IF EXISTS test; CREATE DATABASE test;")
instance_2.query("DROP DATABASE IF EXISTS test; CREATE DATABASE test;")
minio = started_cluster.minio_client
objects = list(
minio.list_objects(started_cluster.minio_restricted_bucket, recursive=True)
)
for obj in objects:
minio.remove_object(started_cluster.minio_restricted_bucket, obj.object_name)
yield # run test
@pytest.fixture(scope="module")
def started_cluster():
try:
cluster = ClickHouseCluster(__file__)
cluster.add_instance(
"instance",
user_configs=["configs/users.xml"],
with_minio=True,
with_zookeeper=True,
main_configs=[
"configs/defaultS3.xml",
"configs/named_collections.xml",
"configs/zookeeper.xml",
"configs/s3queue_log.xml",
],
)
cluster.add_instance(
"instance2",
user_configs=["configs/users.xml"],
with_minio=True,
with_zookeeper=True,
main_configs=[
"configs/defaultS3.xml",
"configs/named_collections.xml",
"configs/s3queue_log.xml",
],
)
logging.info("Starting cluster...")
cluster.start()
logging.info("Cluster started")
prepare_s3_bucket(cluster)
yield cluster
finally:
cluster.shutdown()
def run_query(instance, query, stdin=None, settings=None):
# type: (ClickHouseInstance, str, object, dict) -> str
logging.info("Running query '{}'...".format(query))
result = instance.query(query, stdin=stdin, settings=settings)
logging.info("Query finished")
return result
def generate_random_files(
started_cluster, files_path, count, column_num=3, row_num=10, start_ind=0
):
files = [
(f"{files_path}/test_{i}.csv", i) for i in range(start_ind, start_ind + count)
]
files.sort(key=lambda x: x[0])
print(f"Generating files: {files}")
total_values = []
for filename, i in files:
rand_values = [
[random.randint(0, 1000) for _ in range(column_num)] for _ in range(row_num)
]
total_values += rand_values
values_csv = (
"\n".join((",".join(map(str, row)) for row in rand_values)) + "\n"
).encode()
put_s3_file_content(started_cluster, filename, values_csv)
return total_values
def put_s3_file_content(started_cluster, filename, data):
buf = io.BytesIO(data)
started_cluster.minio_client.put_object(
started_cluster.minio_bucket, filename, buf, len(data)
)
def get_s3_file_content(started_cluster, bucket, filename, decode=True):
# type: (ClickHouseCluster, str, str, bool) -> str
# Returns content of given S3 file as string.
data = started_cluster.minio_client.get_object(bucket, filename)
data_str = b""
for chunk in data.stream():
data_str += chunk
if decode:
return data_str.decode()
return data_str
def create_table(
started_cluster,
node,
table_name,
mode,
files_path,
format="column1 UInt32, column2 UInt32, column3 UInt32",
additional_settings={},
file_format="CSV",
):
settings = {
"s3queue_loading_retries": 0,
"after_processing": "keep",
"keeper_path": f"/clickhouse/test_{table_name}",
"mode": f"{mode}",
}
settings.update(additional_settings)
url = f"http://{started_cluster.minio_host}:{started_cluster.minio_port}/{started_cluster.minio_bucket}/{files_path}/"
node.query(f"DROP TABLE IF EXISTS {table_name}")
create_query = f"""
CREATE TABLE {table_name} ({format})
ENGINE = S3Queue('{url}', {AUTH}'{file_format}')
SETTINGS {",".join((k+"="+repr(v) for k, v in settings.items()))}
"""
node.query(create_query)
def create_mv(
node,
src_table_name,
dst_table_name,
format="column1 UInt32, column2 UInt32, column3 UInt32",
):
mv_name = f"{dst_table_name}_mv"
node.query(
f"""
DROP TABLE IF EXISTS {dst_table_name};
DROP TABLE IF EXISTS {mv_name};
CREATE TABLE {dst_table_name} ({format}, _path String)
ENGINE = MergeTree()
ORDER BY column1;
CREATE MATERIALIZED VIEW {mv_name} TO {dst_table_name} AS SELECT *, _path FROM {src_table_name};
"""
)
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_delete_after_processing(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"test.delete_after_processing_{mode}"
dst_table_name = f"{table_name}_dst"
files_path = f"{table_name}_data"
files_num = 5
row_num = 10
total_values = generate_random_files(
started_cluster, files_path, files_num, row_num=row_num
)
create_table(
started_cluster,
node,
table_name,
mode,
files_path,
additional_settings={"after_processing": "delete"},
)
create_mv(node, table_name, dst_table_name)
expected_count = files_num * row_num
for _ in range(100):
count = int(node.query(f"SELECT count() FROM {dst_table_name}"))
print(f"{count}/{expected_count}")
if count == expected_count:
break
time.sleep(1)
assert int(node.query(f"SELECT count() FROM {dst_table_name}")) == expected_count
assert int(node.query(f"SELECT uniq(_path) FROM {dst_table_name}")) == files_num
assert [
list(map(int, l.split()))
for l in node.query(
f"SELECT column1, column2, column3 FROM {dst_table_name} ORDER BY column1, column2, column3"
).splitlines()
] == sorted(total_values, key=lambda x: (x[0], x[1], x[2]))
minio = started_cluster.minio_client
objects = list(minio.list_objects(started_cluster.minio_bucket, recursive=True))
assert len(objects) == 0
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_failed_retry(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"test.failed_retry_{mode}"
dst_table_name = f"{table_name}_dst"
files_path = f"{table_name}_data"
file_path = f"{files_path}/trash_test.csv"
keeper_path = f"/clickhouse/test_{table_name}"
retries_num = 3
values = [
["failed", 1, 1],
]
values_csv = (
"\n".join((",".join(map(str, row)) for row in values)) + "\n"
).encode()
put_s3_file_content(started_cluster, file_path, values_csv)
create_table(
started_cluster,
node,
table_name,
mode,
files_path,
additional_settings={
"s3queue_loading_retries": retries_num,
"keeper_path": keeper_path,
},
)
create_mv(node, table_name, dst_table_name)
failed_node_path = ""
for _ in range(20):
zk = started_cluster.get_kazoo_client("zoo1")
failed_nodes = zk.get_children(f"{keeper_path}/failed/")
if len(failed_nodes) > 0:
assert len(failed_nodes) == 1
failed_node_path = f"{keeper_path}/failed/{failed_nodes[0]}"
time.sleep(1)
assert failed_node_path != ""
retries = 0
for _ in range(20):
data, stat = zk.get(failed_node_path)
json_data = json.loads(data)
print(f"Failed node metadata: {json_data}")
assert json_data["file_path"] == file_path
retries = int(json_data["retries"])
if retries == retries_num:
break
time.sleep(1)
assert retries == retries_num
assert 0 == int(node.query(f"SELECT count() FROM {dst_table_name}"))
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_direct_select_file(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"test.direct_select_file_{mode}"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
file_path = f"{files_path}/test.csv"
values = [
[12549, 2463, 19893],
[64021, 38652, 66703],
[81611, 39650, 83516],
]
values_csv = (
"\n".join((",".join(map(str, row)) for row in values)) + "\n"
).encode()
put_s3_file_content(started_cluster, file_path, values_csv)
for i in range(3):
create_table(
started_cluster,
node,
f"{table_name}_{i + 1}",
mode,
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_1").splitlines()
] == values
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_2").splitlines()
] == []
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_3").splitlines()
] == []
# New table with same zookeeper path
create_table(
started_cluster,
node,
f"{table_name}_4",
mode,
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
] == []
# New table with different zookeeper path
keeper_path = f"/clickhouse/test_{table_name}_{mode}_2"
create_table(
started_cluster,
node,
f"{table_name}_4",
mode,
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
] == values
values = [
[1, 1, 1],
]
values_csv = (
"\n".join((",".join(map(str, row)) for row in values)) + "\n"
).encode()
file_path = f"{files_path}/t.csv"
put_s3_file_content(started_cluster, file_path, values_csv)
if mode == "unordered":
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
] == values
elif mode == "ordered":
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
] == []
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_direct_select_multiple_files(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"direct_select_multiple_files_{mode}"
files_path = f"{table_name}_data"
create_table(started_cluster, node, table_name, mode, files_path)
for i in range(5):
rand_values = [[random.randint(0, 50) for _ in range(3)] for _ in range(10)]
values_csv = (
"\n".join((",".join(map(str, row)) for row in rand_values)) + "\n"
).encode()
file_path = f"{files_path}/test_{i}.csv"
put_s3_file_content(started_cluster, file_path, values_csv)
assert [
list(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}").splitlines()
] == rand_values
total_values = generate_random_files(started_cluster, files_path, 4, start_ind=5)
assert {
tuple(map(int, l.split()))
for l in node.query(f"SELECT * FROM {table_name}").splitlines()
} == set([tuple(i) for i in total_values])
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_streaming_to_view_(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"streaming_to_view_{mode}"
dst_table_name = f"{table_name}_dst"
files_path = f"{table_name}_data"
total_values = generate_random_files(started_cluster, files_path, 10)
create_table(started_cluster, node, table_name, mode, files_path)
create_mv(node, table_name, dst_table_name)
expected_values = set([tuple(i) for i in total_values])
for i in range(10):
selected_values = {
tuple(map(int, l.split()))
for l in node.query(
f"SELECT column1, column2, column3 FROM {dst_table_name}"
).splitlines()
}
if selected_values == expected_values:
break
time.sleep(1)
assert selected_values == expected_values
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_streaming_to_many_views(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"streaming_to_many_views_{mode}"
dst_table_name = f"{table_name}_dst"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
for i in range(3):
table = f"{table_name}_{i + 1}"
create_table(
started_cluster,
node,
table,
mode,
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
create_mv(node, table, dst_table_name)
total_values = generate_random_files(started_cluster, files_path, 5)
expected_values = set([tuple(i) for i in total_values])
def select():
return {
tuple(map(int, l.split()))
for l in node.query(
f"SELECT column1, column2, column3 FROM {dst_table_name}"
).splitlines()
}
for _ in range(20):
if select() == expected_values:
break
time.sleep(1)
assert select() == expected_values
def test_multiple_tables_meta_mismatch(started_cluster):
node = started_cluster.instances["instance"]
table_name = f"multiple_tables_meta_mismatch"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
create_table(
started_cluster,
node,
table_name,
"ordered",
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
# check mode
failed = False
try:
create_table(
started_cluster,
node,
f"{table_name}_copy",
"unordered",
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
except QueryRuntimeException as e:
assert (
"Metadata with the same `s3queue_zookeeper_path` was already created but with different settings"
in str(e)
)
failed = True
assert failed is True
# check columns
try:
create_table(
started_cluster,
node,
f"{table_name}_copy",
"ordered",
files_path,
format="column1 UInt32, column2 UInt32, column3 UInt32, column4 UInt32",
additional_settings={
"keeper_path": keeper_path,
},
)
except QueryRuntimeException as e:
assert (
"Table columns structure in ZooKeeper is different from local table structure"
in str(e)
)
failed = True
assert failed is True
# check format
try:
create_table(
started_cluster,
node,
f"{table_name}_copy",
"ordered",
files_path,
format="column1 UInt32, column2 UInt32, column3 UInt32, column4 UInt32",
additional_settings={
"keeper_path": keeper_path,
},
file_format="TSV",
)
except QueryRuntimeException as e:
assert "Existing table metadata in ZooKeeper differs in format name" in str(e)
failed = True
assert failed is True
# create working engine
create_table(
started_cluster,
node,
f"{table_name}_copy",
"ordered",
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
# TODO: Update the modes for this test to include "ordered" once PR #55795 is finished.
@pytest.mark.parametrize("mode", ["unordered"])
def test_multiple_tables_streaming_sync(started_cluster, mode):
node = started_cluster.instances["instance"]
table_name = f"multiple_tables_streaming_sync_{mode}"
dst_table_name = f"{table_name}_dst"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
files_to_generate = 300
for i in range(3):
table = f"{table_name}_{i + 1}"
dst_table = f"{dst_table_name}_{i + 1}"
create_table(
started_cluster,
node,
table,
mode,
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
create_mv(node, table, dst_table)
total_values = generate_random_files(
started_cluster, files_path, files_to_generate, row_num=1
)
def get_count(table_name):
return int(run_query(node, f"SELECT count() FROM {table_name}"))
for _ in range(100):
if (
get_count(f"{dst_table_name}_1")
+ get_count(f"{dst_table_name}_2")
+ get_count(f"{dst_table_name}_3")
) == files_to_generate:
break
time.sleep(1)
if (
get_count(f"{dst_table_name}_1")
+ get_count(f"{dst_table_name}_2")
+ get_count(f"{dst_table_name}_3")
) != files_to_generate:
info = node.query(
f"SELECT * FROM system.s3queue WHERE zookeeper_path like '%{table_name}' ORDER BY file_name FORMAT Vertical"
)
logging.debug(info)
assert False
res1 = [
list(map(int, l.split()))
for l in node.query(
f"SELECT column1, column2, column3 FROM {dst_table_name}_1"
).splitlines()
]
res2 = [
list(map(int, l.split()))
for l in node.query(
f"SELECT column1, column2, column3 FROM {dst_table_name}_2"
).splitlines()
]
res3 = [
list(map(int, l.split()))
for l in node.query(
f"SELECT column1, column2, column3 FROM {dst_table_name}_3"
).splitlines()
]
assert {tuple(v) for v in res1 + res2 + res3} == set(
[tuple(i) for i in total_values]
)
# Checking that all files were processed only once
time.sleep(10)
assert (
get_count(f"{dst_table_name}_1")
+ get_count(f"{dst_table_name}_2")
+ get_count(f"{dst_table_name}_3")
) == files_to_generate
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
def test_multiple_tables_streaming_sync_distributed(started_cluster, mode):
node = started_cluster.instances["instance"]
node_2 = started_cluster.instances["instance2"]
table_name = f"multiple_tables_streaming_sync_distributed_{mode}"
dst_table_name = f"{table_name}_dst"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
files_to_generate = 300
for instance in [node, node_2]:
create_table(
started_cluster,
instance,
table_name,
mode,
files_path,
additional_settings={
"keeper_path": keeper_path,
},
)
for instance in [node, node_2]:
create_mv(instance, table_name, dst_table_name)
total_values = generate_random_files(
started_cluster, files_path, files_to_generate, row_num=1
)
def get_count(node, table_name):
return int(run_query(node, f"SELECT count() FROM {table_name}"))
for _ in range(150):
if (
get_count(node, dst_table_name) + get_count(node_2, dst_table_name)
) == files_to_generate:
break
time.sleep(1)
if (
get_count(node, dst_table_name) + get_count(node_2, dst_table_name)
) != files_to_generate:
info = node.query(
f"SELECT * FROM system.s3queue WHERE zookeeper_path like '%{table_name}' ORDER BY file_name FORMAT Vertical"
)
logging.debug(info)
assert False
get_query = f"SELECT column1, column2, column3 FROM {dst_table_name}"
res1 = [list(map(int, l.split())) for l in run_query(node, get_query).splitlines()]
res2 = [
list(map(int, l.split())) for l in run_query(node_2, get_query).splitlines()
]
assert len(res1) + len(res2) == files_to_generate
# Checking that all engines have made progress
assert len(res1) > 0
assert len(res2) > 0
assert {tuple(v) for v in res1 + res2} == set([tuple(i) for i in total_values])
# Checking that all files were processed only once
time.sleep(10)
assert (
get_count(node, dst_table_name) + get_count(node_2, dst_table_name)
) == files_to_generate
def test_max_set_age(started_cluster):
node = started_cluster.instances["instance"]
table_name = f"max_set_age"
dst_table_name = f"{table_name}_dst"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
max_age = 10
files_to_generate = 10
create_table(
started_cluster,
node,
table_name,
"unordered",
files_path,
additional_settings={
"keeper_path": keeper_path,
"s3queue_tracked_file_ttl_sec": max_age,
"s3queue_cleanup_interval_min_ms": 0,
"s3queue_cleanup_interval_max_ms": 0,
},
)
create_mv(node, table_name, dst_table_name)
total_values = generate_random_files(
started_cluster, files_path, files_to_generate, row_num=1
)
expected_rows = 10
node.wait_for_log_line("Checking node limits")
node.wait_for_log_line("Node limits check finished")
def get_count():
return int(node.query(f"SELECT count() FROM {dst_table_name}"))
for _ in range(20):
if expected_rows == get_count():
break
time.sleep(1)
assert expected_rows == get_count()
assert 10 == int(node.query(f"SELECT uniq(_path) from {dst_table_name}"))
time.sleep(max_age + 1)
expected_rows = 20
for _ in range(20):
if expected_rows == get_count():
break
time.sleep(1)
assert expected_rows == get_count()
assert 10 == int(node.query(f"SELECT uniq(_path) from {dst_table_name}"))
paths_count = [
int(x)
for x in node.query(
f"SELECT count() from {dst_table_name} GROUP BY _path"
).splitlines()
]
assert 10 == len(paths_count)
for path_count in paths_count:
assert 2 == path_count
def test_max_set_size(started_cluster):
node = started_cluster.instances["instance"]
table_name = f"max_set_size"
dst_table_name = f"{table_name}_dst"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
max_age = 10
files_to_generate = 10
create_table(
started_cluster,
node,
table_name,
"unordered",
files_path,
additional_settings={
"keeper_path": keeper_path,
"s3queue_tracked_files_limit": 9,
"s3queue_cleanup_interval_min_ms": 0,
"s3queue_cleanup_interval_max_ms": 0,
"s3queue_processing_threads_num": 1,
},
)
total_values = generate_random_files(
started_cluster, files_path, files_to_generate, start_ind=0, row_num=1
)
get_query = f"SELECT * FROM {table_name} ORDER BY column1, column2, column3"
res1 = [list(map(int, l.split())) for l in run_query(node, get_query).splitlines()]
assert res1 == sorted(total_values, key=lambda x: (x[0], x[1], x[2]))
print(total_values)
time.sleep(10)
zk = started_cluster.get_kazoo_client("zoo1")
processed_nodes = zk.get_children(f"{keeper_path}/processed/")
assert len(processed_nodes) == 9
res1 = [list(map(int, l.split())) for l in run_query(node, get_query).splitlines()]
assert res1 == [total_values[0]]
time.sleep(10)
res1 = [list(map(int, l.split())) for l in run_query(node, get_query).splitlines()]
assert res1 == [total_values[1]]
def test_drop_table(started_cluster):
node = started_cluster.instances["instance"]
table_name = f"test_drop"
dst_table_name = f"{table_name}_dst"
keeper_path = f"/clickhouse/test_{table_name}"
files_path = f"{table_name}_data"
files_to_generate = 300
create_table(
started_cluster,
node,
table_name,
"unordered",
files_path,
additional_settings={
"keeper_path": keeper_path,
"s3queue_processing_threads_num": 5,
},
)
total_values = generate_random_files(
started_cluster, files_path, files_to_generate, start_ind=0, row_num=100000
)
create_mv(node, table_name, dst_table_name)
node.wait_for_log_line(f"Reading from file: test_drop_data")
node.query(f"DROP TABLE {table_name} SYNC")
assert node.contains_in_log(
f"StorageS3Queue ({table_name}): Table is being dropped"
)