import io import json import logging import random import string import time import uuid import pytest from helpers.client import QueryRuntimeException from helpers.cluster import ClickHouseCluster, ClickHouseInstance AVAILABLE_MODES = ["unordered", "ordered"] DEFAULT_AUTH = ["'minio'", "'minio123'"] NO_AUTH = ["NOSIGN"] def prepare_public_s3_bucket(started_cluster): def create_bucket(client, bucket_name, policy): if client.bucket_exists(bucket_name): client.remove_bucket(bucket_name) client.make_bucket(bucket_name) client.set_bucket_policy(bucket_name, json.dumps(policy)) def get_policy_with_public_access(bucket_name): return { "Version": "2012-10-17", "Statement": [ { "Sid": "", "Effect": "Allow", "Principal": "*", "Action": [ "s3:GetBucketLocation", "s3:ListBucket", ], "Resource": f"arn:aws:s3:::{bucket_name}", }, { "Sid": "", "Effect": "Allow", "Principal": "*", "Action": [ "s3:GetObject", "s3:PutObject", "s3:DeleteObject", ], "Resource": f"arn:aws:s3:::{bucket_name}/*", }, ], } minio_client = started_cluster.minio_client started_cluster.minio_public_bucket = f"{started_cluster.minio_bucket}-public" create_bucket( minio_client, started_cluster.minio_public_bucket, get_policy_with_public_access(started_cluster.minio_public_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 default; CREATE DATABASE default;") instance_2.query("DROP DATABASE IF EXISTS default; CREATE DATABASE default;") minio = started_cluster.minio_client objects = list(minio.list_objects(started_cluster.minio_bucket, recursive=True)) for obj in objects: minio.remove_object(started_cluster.minio_bucket, obj.object_name) container_client = started_cluster.blob_service_client.get_container_client( started_cluster.azurite_container ) if container_client.exists(): blob_names = [b.name for b in container_client.list_blobs()] logging.debug(f"Deleting blobs: {blob_names}") for b in blob_names: container_client.delete_blob(b) 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_azurite=True, with_zookeeper=True, main_configs=[ "configs/zookeeper.xml", "configs/s3queue_log.xml", ], stay_alive=True, ) cluster.add_instance( "instance2", user_configs=["configs/users.xml"], with_minio=True, with_zookeeper=True, main_configs=[ "configs/s3queue_log.xml", ], stay_alive=True, ) cluster.add_instance( "old_instance", with_zookeeper=True, image="clickhouse/clickhouse-server", tag="23.12", stay_alive=True, with_installed_binary=True, use_old_analyzer=True, ) cluster.add_instance( "node1", with_zookeeper=True, stay_alive=True, main_configs=[ "configs/zookeeper.xml", "configs/s3queue_log.xml", "configs/remote_servers.xml", ], ) cluster.add_instance( "node2", with_zookeeper=True, stay_alive=True, main_configs=[ "configs/zookeeper.xml", "configs/s3queue_log.xml", "configs/remote_servers.xml", ], ) cluster.add_instance( "instance_too_many_parts", user_configs=["configs/users.xml"], with_minio=True, with_zookeeper=True, main_configs=[ "configs/s3queue_log.xml", "configs/merge_tree.xml", ], stay_alive=True, ) cluster.add_instance( "instance_24.5", with_zookeeper=True, image="clickhouse/clickhouse-server", tag="24.5", stay_alive=True, user_configs=[ "configs/users.xml", ], with_installed_binary=True, use_old_analyzer=True, ) cluster.add_instance( "node_cloud_mode", with_zookeeper=True, stay_alive=True, main_configs=[ "configs/zookeeper.xml", "configs/s3queue_log.xml", ], user_configs=["configs/cloud_mode.xml"], ) logging.info("Starting cluster...") cluster.start() logging.info("Cluster started") 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, storage="s3", column_num=3, row_num=10, start_ind=0, bucket=None, ): 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() if storage == "s3": put_s3_file_content(started_cluster, filename, values_csv, bucket) else: put_azure_file_content(started_cluster, filename, values_csv, bucket) return total_values def put_s3_file_content(started_cluster, filename, data, bucket=None): bucket = started_cluster.minio_bucket if bucket is None else bucket buf = io.BytesIO(data) started_cluster.minio_client.put_object(bucket, filename, buf, len(data)) def put_azure_file_content(started_cluster, filename, data, bucket=None): client = started_cluster.blob_service_client.get_blob_client( started_cluster.azurite_container, filename ) buf = io.BytesIO(data) client.upload_blob(buf, "BlockBlob", len(data)) def create_table( started_cluster, node, table_name, mode, files_path, engine_name="S3Queue", format="column1 UInt32, column2 UInt32, column3 UInt32", additional_settings={}, file_format="CSV", auth=DEFAULT_AUTH, bucket=None, expect_error=False, database_name="default", ): auth_params = ",".join(auth) bucket = started_cluster.minio_bucket if bucket is None else bucket settings = { "s3queue_loading_retries": 0, "after_processing": "keep", "keeper_path": f"/clickhouse/test_{table_name}", "mode": f"{mode}", } settings.update(additional_settings) engine_def = None if engine_name == "S3Queue": url = f"http://{started_cluster.minio_host}:{started_cluster.minio_port}/{bucket}/{files_path}/" engine_def = f"{engine_name}('{url}', {auth_params}, {file_format})" else: engine_def = f"{engine_name}('{started_cluster.env_variables['AZURITE_CONNECTION_STRING']}', '{started_cluster.azurite_container}', '{files_path}/', 'CSV')" node.query(f"DROP TABLE IF EXISTS {table_name}") create_query = f""" CREATE TABLE {database_name}.{table_name} ({format}) ENGINE = {engine_def} SETTINGS {",".join((k+"="+repr(v) for k, v in settings.items()))} """ if expect_error: return node.query_and_get_error(create_query) 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}; """ ) def generate_random_string(length=6): return "".join(random.choice(string.ascii_lowercase) for i in range(length)) @pytest.mark.parametrize("mode", ["unordered", "ordered"]) @pytest.mark.parametrize("engine_name", ["S3Queue", "AzureQueue"]) def test_delete_after_processing(started_cluster, mode, engine_name): node = started_cluster.instances["instance"] table_name = f"delete_after_processing_{mode}_{engine_name}" dst_table_name = f"{table_name}_dst" files_path = f"{table_name}_data" files_num = 5 row_num = 10 # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" if engine_name == "S3Queue": storage = "s3" else: storage = "azure" total_values = generate_random_files( started_cluster, files_path, files_num, row_num=row_num, storage=storage ) create_table( started_cluster, node, table_name, mode, files_path, additional_settings={"after_processing": "delete", "keeper_path": keeper_path}, engine_name=engine_name, ) 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])) if engine_name == "S3Queue": minio = started_cluster.minio_client objects = list(minio.list_objects(started_cluster.minio_bucket, recursive=True)) assert len(objects) == 0 else: client = started_cluster.blob_service_client.get_container_client( started_cluster.azurite_container ) objects_iterator = client.list_blobs(files_path) for objects in objects_iterator: assert False @pytest.mark.parametrize("mode", ["unordered", "ordered"]) @pytest.mark.parametrize("engine_name", ["S3Queue", "AzureQueue"]) def test_failed_retry(started_cluster, mode, engine_name): node = started_cluster.instances["instance"] table_name = f"failed_retry_{mode}_{engine_name}" dst_table_name = f"{table_name}_dst" files_path = f"{table_name}_data" file_path = f"{files_path}/trash_test.csv" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" retries_num = 3 values = [ ["failed", 1, 1], ] values_csv = ( "\n".join((",".join(map(str, row)) for row in values)) + "\n" ).encode() if engine_name == "S3Queue": put_s3_file_content(started_cluster, file_path, values_csv) else: put_azure_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, }, engine_name=engine_name, ) 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"direct_select_file_{mode}" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{mode}_{generate_random_string()}" 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, "s3queue_processing_threads_num": 1, }, ) 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, "s3queue_processing_threads_num": 1, }, ) 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"{keeper_path}_2" create_table( started_cluster, node, f"{table_name}_4", mode, files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": 1, }, ) 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" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" create_table( started_cluster, node, table_name, mode, files_path, additional_settings={"keeper_path": keeper_path, "processing_threads_num": 3}, ) 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" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" total_values = generate_random_files(started_cluster, files_path, 10) create_table( started_cluster, node, table_name, mode, files_path, additional_settings={"keeper_path": keeper_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" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" 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" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" 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 "Existing table metadata in ZooKeeper differs in engine mode" 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 "Existing table metadata in ZooKeeper differs in columns" 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" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" 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"] # A unique table name is necessary for repeatable tests table_name = ( f"multiple_tables_streaming_sync_distributed_{mode}_{generate_random_string()}" ) dst_table_name = f"{table_name}_dst" keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 300 row_num = 50 total_rows = row_num * files_to_generate for instance in [node, node_2]: create_table( started_cluster, instance, table_name, mode, files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_buckets": 2, **({"s3queue_processing_threads_num": 1} if mode == "ordered" else {}), }, ) 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=row_num ) 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) ) == total_rows: break time.sleep(1) if ( get_count(node, dst_table_name) + get_count(node_2, dst_table_name) ) != total_rows: 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() ] logging.debug( f"res1 size: {len(res1)}, res2 size: {len(res2)}, total_rows: {total_rows}" ) assert len(res1) + len(res2) == total_rows # 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) ) == total_rows def test_max_set_age(started_cluster): node = started_cluster.instances["instance"] table_name = "max_set_age" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" max_age = 20 files_to_generate = 10 create_table( started_cluster, node, table_name, "unordered", files_path, additional_settings={ "keeper_path": keeper_path, "tracked_file_ttl_sec": max_age, "cleanup_interval_min_ms": max_age / 3, "cleanup_interval_max_ms": max_age / 3, "loading_retries": 0, "processing_threads_num": 1, "loading_retries": 0, }, ) create_mv(node, table_name, dst_table_name) _ = generate_random_files(started_cluster, files_path, files_to_generate, row_num=1) expected_rows = files_to_generate 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}")) def wait_for_condition(check_function, max_wait_time=1.5 * max_age): before = time.time() while time.time() - before < max_wait_time: if check_function(): return time.sleep(0.25) assert False wait_for_condition(lambda: get_count() == expected_rows) assert files_to_generate == int( node.query(f"SELECT uniq(_path) from {dst_table_name}") ) expected_rows *= 2 wait_for_condition(lambda: get_count() == expected_rows) assert files_to_generate == 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 files_to_generate == len(paths_count) for path_count in paths_count: assert 2 == path_count def get_object_storage_failures(): return int( node.query( "SELECT value FROM system.events WHERE name = 'ObjectStorageQueueFailedFiles' SETTINGS system_events_show_zero_values=1" ) ) failed_count = get_object_storage_failures() values = [ ["failed", 1, 1], ] values_csv = ( "\n".join((",".join(map(str, row)) for row in values)) + "\n" ).encode() # use a different filename for each test to allow running a bunch of them sequentially with --count file_with_error = f"max_set_age_fail_{uuid.uuid4().hex[:8]}.csv" put_s3_file_content(started_cluster, f"{files_path}/{file_with_error}", values_csv) wait_for_condition(lambda: failed_count + 1 == get_object_storage_failures()) node.query("SYSTEM FLUSH LOGS") assert "Cannot parse input" in node.query( f"SELECT exception FROM system.s3queue WHERE file_name ilike '%{file_with_error}'" ) assert 1 == int( node.query( f"SELECT count() FROM system.s3queue_log WHERE file_name ilike '%{file_with_error}' AND notEmpty(exception)" ) ) wait_for_condition(lambda: failed_count + 2 == get_object_storage_failures()) node.query("SYSTEM FLUSH LOGS") assert "Cannot parse input" in node.query( f"SELECT exception FROM system.s3queue WHERE file_name ilike '%{file_with_error}' ORDER BY processing_end_time DESC LIMIT 1" ) assert 1 < int( node.query( f"SELECT count() FROM system.s3queue_log WHERE file_name ilike '%{file_with_error}' AND notEmpty(exception)" ) ) node.restart_clickhouse() expected_rows *= 2 wait_for_condition(lambda: get_count() == expected_rows) assert files_to_generate == int( node.query(f"SELECT uniq(_path) from {dst_table_name}") ) def test_max_set_size(started_cluster): node = started_cluster.instances["instance"] table_name = f"max_set_size" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" 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" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" 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"rows from file: test_drop_data") node.query(f"DROP TABLE {table_name} SYNC") assert node.contains_in_log( f"StorageS3Queue (default.{table_name}): Table is being dropped" ) or node.contains_in_log( f"StorageS3Queue (default.{table_name}): Shutdown was called, stopping sync" ) def test_s3_client_reused(started_cluster): node = started_cluster.instances["instance"] table_name = f"test_s3_client_reused" dst_table_name = f"{table_name}_dst" files_path = f"{table_name}_data" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" row_num = 10 def get_created_s3_clients_count(): value = node.query( f"SELECT value FROM system.events WHERE event='S3Clients'" ).strip() return int(value) if value != "" else 0 def wait_all_processed(files_num): 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 ) prepare_public_s3_bucket(started_cluster) s3_clients_before = get_created_s3_clients_count() create_table( started_cluster, node, table_name, "ordered", files_path, additional_settings={ "after_processing": "delete", "s3queue_processing_threads_num": 1, "keeper_path": keeper_path, }, auth=NO_AUTH, bucket=started_cluster.minio_public_bucket, ) s3_clients_after = get_created_s3_clients_count() assert s3_clients_before + 1 == s3_clients_after create_mv(node, table_name, dst_table_name) for i in range(0, 10): s3_clients_before = get_created_s3_clients_count() generate_random_files( started_cluster, files_path, count=1, start_ind=i, row_num=row_num, bucket=started_cluster.minio_public_bucket, ) wait_all_processed(i + 1) s3_clients_after = get_created_s3_clients_count() assert s3_clients_before == s3_clients_after def get_processed_files(node, table_name): return ( node.query( f""" select splitByChar('/', file_name)[-1] as file from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' order by file """ ) .strip() .split("\n") ) def get_unprocessed_files(node, table_name): return node.query( f""" select concat('test_', toString(number), '.csv') as file from numbers(300) where file not in (select splitByChar('/', file_name)[-1] from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed') """ ) @pytest.mark.parametrize("mode", ["unordered", "ordered"]) def test_processing_threads(started_cluster, mode): node = started_cluster.instances["instance"] table_name = f"processing_threads_{mode}" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" files_to_generate = 300 processing_threads = 32 create_table( started_cluster, node, table_name, mode, files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": processing_threads, }, ) create_mv(node, table_name, dst_table_name) 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(50): if (get_count(f"{dst_table_name}")) == files_to_generate: break time.sleep(1) if get_count(dst_table_name) != files_to_generate: processed_files = get_processed_files(node, table_name) unprocessed_files = get_unprocessed_files(node, table_name) logging.debug( f"Processed files: {len(processed_files)}/{files_to_generate}, unprocessed files: {unprocessed_files}, count: {get_count(dst_table_name)}" ) assert False res = [ list(map(int, l.split())) for l in node.query( f"SELECT column1, column2, column3 FROM {dst_table_name}" ).splitlines() ] assert {tuple(v) for v in res} == set([tuple(i) for i in total_values]) if mode == "ordered": zk = started_cluster.get_kazoo_client("zoo1") nodes = zk.get_children(f"{keeper_path}") print(f"Metadata nodes: {nodes}") processed_nodes = zk.get_children(f"{keeper_path}/buckets/") assert len(processed_nodes) == processing_threads @pytest.mark.parametrize( "mode, processing_threads", [ pytest.param("unordered", 1), pytest.param("unordered", 8), pytest.param("ordered", 1), pytest.param("ordered", 8), ], ) def test_shards(started_cluster, mode, processing_threads): node = started_cluster.instances["instance"] table_name = f"test_shards_{mode}_{processing_threads}" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" files_to_generate = 300 shards_num = 3 for i in range(shards_num): 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, "s3queue_processing_threads_num": processing_threads, "s3queue_buckets": shards_num, }, ) 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(30): count = ( get_count(f"{dst_table_name}_1") + get_count(f"{dst_table_name}_2") + get_count(f"{dst_table_name}_3") ) if count == files_to_generate: break print(f"Current {count}/{files_to_generate}") 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: processed_files = ( node.query( f""" select splitByChar('/', file_name)[-1] as file from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0 order by file """ ) .strip() .split("\n") ) logging.debug( f"Processed files: {len(processed_files)}/{files_to_generate}: {processed_files}" ) count = ( get_count(f"{dst_table_name}_1") + get_count(f"{dst_table_name}_2") + get_count(f"{dst_table_name}_3") ) logging.debug(f"Processed rows: {count}/{files_to_generate}") info = node.query( f""" select concat('test_', toString(number), '.csv') as file from numbers(300) where file not in (select splitByChar('/', file_name)[-1] from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0) """ ) logging.debug(f"Unprocessed files: {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 if mode == "ordered": zk = started_cluster.get_kazoo_client("zoo1") processed_nodes = zk.get_children(f"{keeper_path}/buckets/") assert len(processed_nodes) == shards_num @pytest.mark.parametrize( "mode, processing_threads", [ pytest.param("unordered", 1), pytest.param("unordered", 8), pytest.param("ordered", 1), pytest.param("ordered", 2), ], ) def test_shards_distributed(started_cluster, mode, processing_threads): node = started_cluster.instances["instance"] node_2 = started_cluster.instances["instance2"] table_name = f"test_shards_distributed_{mode}_{processing_threads}" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" files_to_generate = 300 row_num = 300 total_rows = row_num * files_to_generate shards_num = 2 i = 0 for instance in [node, node_2]: create_table( started_cluster, instance, table_name, mode, files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": processing_threads, "s3queue_buckets": shards_num, }, ) i += 1 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=row_num ) def get_count(node, table_name): return int(run_query(node, f"SELECT count() FROM {table_name}")) def print_debug_info(): processed_files = ( node.query( f""" select splitByChar('/', file_name)[-1] as file from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0 order by file """ ) .strip() .split("\n") ) logging.debug( f"Processed files by node 1: {len(processed_files)}/{files_to_generate}" ) processed_files = ( node_2.query( f""" select splitByChar('/', file_name)[-1] as file from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0 order by file """ ) .strip() .split("\n") ) logging.debug( f"Processed files by node 2: {len(processed_files)}/{files_to_generate}" ) count = get_count(node, dst_table_name) + get_count(node_2, dst_table_name) logging.debug(f"Processed rows: {count}/{total_rows}") info = node.query( f""" select concat('test_', toString(number), '.csv') as file from numbers(300) where file not in (select splitByChar('/', file_name)[-1] from clusterAllReplicas(default, system.s3queue) where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0) """ ) logging.debug(f"Unprocessed files: {info}") files1 = ( node.query( f""" select splitByChar('/', file_name)[-1] from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0 """ ) .strip() .split("\n") ) files2 = ( node_2.query( f""" select splitByChar('/', file_name)[-1] from system.s3queue where zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0 """ ) .strip() .split("\n") ) def intersection(list_a, list_b): return [e for e in list_a if e in list_b] logging.debug(f"Intersecting files: {intersection(files1, files2)}") for _ in range(30): if ( get_count(node, dst_table_name) + get_count(node_2, dst_table_name) ) == total_rows: break time.sleep(1) if ( get_count(node, dst_table_name) + get_count(node_2, dst_table_name) ) != total_rows: print_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() ] if len(res1) + len(res2) != total_rows or len(res1) <= 0 or len(res2) <= 0 or True: logging.debug( f"res1 size: {len(res1)}, res2 size: {len(res2)}, total_rows: {total_rows}" ) print_debug_info() assert len(res1) + len(res2) == total_rows # 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) ) == total_rows if mode == "ordered": zk = started_cluster.get_kazoo_client("zoo1") processed_nodes = zk.get_children(f"{keeper_path}/buckets/") assert len(processed_nodes) == shards_num node.restart_clickhouse() time.sleep(10) assert ( get_count(node, dst_table_name) + get_count(node_2, dst_table_name) ) == total_rows def test_settings_check(started_cluster): node = started_cluster.instances["instance"] node_2 = started_cluster.instances["instance2"] table_name = f"test_settings_check" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" mode = "ordered" create_table( started_cluster, node, table_name, mode, files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": 5, "s3queue_buckets": 2, }, ) assert ( "Existing table metadata in ZooKeeper differs in buckets setting. Stored in ZooKeeper: 2, local: 3" in create_table( started_cluster, node_2, table_name, mode, files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": 5, "s3queue_buckets": 3, }, expect_error=True, ) ) node.query(f"DROP TABLE {table_name} SYNC") @pytest.mark.parametrize("processing_threads", [1, 5]) def test_processed_file_setting(started_cluster, processing_threads): node = started_cluster.instances["instance"] table_name = f"test_processed_file_setting_{processing_threads}" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = ( f"/clickhouse/test_{table_name}_{processing_threads}_{generate_random_string()}" ) files_path = f"{table_name}_data" files_to_generate = 10 create_table( started_cluster, node, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": processing_threads, "s3queue_last_processed_path": f"{files_path}/test_5.csv", }, ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) create_mv(node, table_name, dst_table_name) def get_count(): return int(node.query(f"SELECT count() FROM {dst_table_name}")) expected_rows = 4 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() node.restart_clickhouse() time.sleep(10) expected_rows = 4 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() @pytest.mark.parametrize("processing_threads", [1, 5]) def test_processed_file_setting_distributed(started_cluster, processing_threads): node = started_cluster.instances["instance"] node_2 = started_cluster.instances["instance2"] table_name = f"test_processed_file_setting_distributed_{processing_threads}" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = ( f"/clickhouse/test_{table_name}_{processing_threads}_{generate_random_string()}" ) files_path = f"{table_name}_data" files_to_generate = 10 for instance in [node, node_2]: create_table( started_cluster, instance, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": processing_threads, "s3queue_last_processed_path": f"{files_path}/test_5.csv", "s3queue_buckets": 2, }, ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) for instance in [node, node_2]: create_mv(instance, table_name, dst_table_name) def get_count(): query = f"SELECT count() FROM {dst_table_name}" return int(node.query(query)) + int(node_2.query(query)) expected_rows = 4 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() for instance in [node, node_2]: instance.restart_clickhouse() time.sleep(10) expected_rows = 4 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() def test_upgrade(started_cluster): node = started_cluster.instances["old_instance"] table_name = f"test_upgrade" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}_{generate_random_string()}" files_path = f"{table_name}_data" files_to_generate = 10 create_table( started_cluster, node, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, }, ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) create_mv(node, table_name, dst_table_name) def get_count(): return int(node.query(f"SELECT count() FROM {dst_table_name}")) expected_rows = 10 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() node.restart_with_latest_version() assert expected_rows == get_count() def test_exception_during_insert(started_cluster): node = started_cluster.instances["instance_too_many_parts"] # A unique table name is necessary for repeatable tests table_name = f"test_exception_during_insert_{generate_random_string()}" dst_table_name = f"{table_name}_dst" keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 10 create_table( started_cluster, node, table_name, "unordered", files_path, additional_settings={ "keeper_path": keeper_path, }, ) node.rotate_logs() total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) create_mv(node, table_name, dst_table_name) node.wait_for_log_line( "Failed to process data: Code: 252. DB::Exception: Too many parts" ) time.sleep(2) exception = node.query( f"SELECT exception FROM system.s3queue WHERE zookeeper_path ilike '%{table_name}%' and notEmpty(exception)" ) assert "Too many parts" in exception original_parts_to_throw_insert = 0 modified_parts_to_throw_insert = 10 node.replace_in_config( "/etc/clickhouse-server/config.d/merge_tree.xml", f"parts_to_throw_insert>{original_parts_to_throw_insert}", f"parts_to_throw_insert>{modified_parts_to_throw_insert}", ) try: node.restart_clickhouse() def get_count(): return int(node.query(f"SELECT count() FROM {dst_table_name}")) expected_rows = 10 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() finally: node.replace_in_config( "/etc/clickhouse-server/config.d/merge_tree.xml", f"parts_to_throw_insert>{modified_parts_to_throw_insert}", f"parts_to_throw_insert>{original_parts_to_throw_insert}", ) node.restart_clickhouse() def test_commit_on_limit(started_cluster): node = started_cluster.instances["instance"] # A unique table name is necessary for repeatable tests table_name = f"test_commit_on_limit_{generate_random_string()}" dst_table_name = f"{table_name}_dst" keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 10 failed_files_event_before = int( node.query( "SELECT value FROM system.events WHERE name = 'ObjectStorageQueueFailedFiles' SETTINGS system_events_show_zero_values=1" ) ) create_table( started_cluster, node, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_processing_threads_num": 1, "s3queue_loading_retries": 0, "s3queue_max_processed_files_before_commit": 10, }, ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) incorrect_values = [ ["failed", 1, 1], ] incorrect_values_csv = ( "\n".join((",".join(map(str, row)) for row in incorrect_values)) + "\n" ).encode() correct_values = [ [1, 1, 1], ] correct_values_csv = ( "\n".join((",".join(map(str, row)) for row in correct_values)) + "\n" ).encode() put_s3_file_content( started_cluster, f"{files_path}/test_99.csv", correct_values_csv ) put_s3_file_content( started_cluster, f"{files_path}/test_999.csv", correct_values_csv ) put_s3_file_content( started_cluster, f"{files_path}/test_9999.csv", incorrect_values_csv ) put_s3_file_content( started_cluster, f"{files_path}/test_99999.csv", correct_values_csv ) put_s3_file_content( started_cluster, f"{files_path}/test_999999.csv", correct_values_csv ) create_mv(node, table_name, dst_table_name) def get_processed_files(): return ( node.query( f"SELECT file_name FROM system.s3queue WHERE zookeeper_path ilike '%{table_name}%' and status = 'Processed' and rows_processed > 0 " ) .strip() .split("\n") ) def get_failed_files(): return ( node.query( f"SELECT file_name FROM system.s3queue WHERE zookeeper_path ilike '%{table_name}%' and status = 'Failed'" ) .strip() .split("\n") ) for _ in range(30): if "test_999999.csv" in get_processed_files(): break time.sleep(1) assert "test_999999.csv" in get_processed_files() assert 1 == int( node.count_in_log(f"Setting file {files_path}/test_9999.csv as failed") ) assert failed_files_event_before + 1 == int( node.query( "SELECT value FROM system.events WHERE name = 'ObjectStorageQueueFailedFiles' SETTINGS system_events_show_zero_values=1" ) ) expected_processed = ["test_" + str(i) + ".csv" for i in range(files_to_generate)] processed = get_processed_files() for value in expected_processed: assert value in processed expected_failed = ["test_9999.csv"] failed = get_failed_files() for value in expected_failed: assert value not in processed assert value in failed def test_upgrade_2(started_cluster): node = started_cluster.instances["instance_24.5"] table_name = f"test_upgrade_2_{uuid.uuid4().hex[:8]}" dst_table_name = f"{table_name}_dst" # A unique path is necessary for repeatable tests keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 10 create_table( started_cluster, node, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, "s3queue_current_shard_num": 0, "s3queue_processing_threads_num": 2, }, ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) create_mv(node, table_name, dst_table_name) def get_count(): return int(node.query(f"SELECT count() FROM {dst_table_name}")) expected_rows = 10 for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() node.restart_with_latest_version() assert table_name in node.query("SHOW TABLES") def test_replicated(started_cluster): node1 = started_cluster.instances["node1"] node2 = started_cluster.instances["node2"] table_name = f"test_replicated_{uuid.uuid4().hex[:8]}" dst_table_name = f"{table_name}_dst" keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 1000 node1.query("DROP DATABASE IF EXISTS r") node2.query("DROP DATABASE IF EXISTS r") node1.query( "CREATE DATABASE r ENGINE=Replicated('/clickhouse/databases/replicateddb', 'shard1', 'node1')" ) node2.query( "CREATE DATABASE r ENGINE=Replicated('/clickhouse/databases/replicateddb', 'shard1', 'node2')" ) create_table( started_cluster, node1, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, }, database_name="r", ) assert '"processing_threads_num":16' in node1.query( f"SELECT * FROM system.zookeeper WHERE path = '{keeper_path}'" ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) create_mv(node1, f"r.{table_name}", dst_table_name) create_mv(node2, f"r.{table_name}", dst_table_name) def get_count(): return int( node1.query( f"SELECT count() FROM clusterAllReplicas(cluster, default.{dst_table_name})" ) ) expected_rows = files_to_generate for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() def test_bad_settings(started_cluster): node = started_cluster.instances["node_cloud_mode"] table_name = f"test_bad_settings_{uuid.uuid4().hex[:8]}" dst_table_name = f"{table_name}_dst" keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 10 try: create_table( started_cluster, node, table_name, "ordered", files_path, additional_settings={ "keeper_path": keeper_path, "processing_threads_num": 1, "buckets": 0, }, ) assert False except Exception as e: assert "Ordered mode in cloud without either" in str(e) def test_alter_settings(started_cluster): node1 = started_cluster.instances["node1"] node2 = started_cluster.instances["node2"] table_name = f"test_alter_settings_{uuid.uuid4().hex[:8]}" dst_table_name = f"{table_name}_dst" keeper_path = f"/clickhouse/test_{table_name}" files_path = f"{table_name}_data" files_to_generate = 1000 node1.query("DROP DATABASE IF EXISTS r") node2.query("DROP DATABASE IF EXISTS r") node1.query( f"CREATE DATABASE r ENGINE=Replicated('/clickhouse/databases/{table_name}', 'shard1', 'node1')" ) node2.query( f"CREATE DATABASE r ENGINE=Replicated('/clickhouse/databases/{table_name}', 'shard1', 'node2')" ) create_table( started_cluster, node1, table_name, "unordered", files_path, additional_settings={"keeper_path": keeper_path, "processing_threads_num": 10}, database_name="r", ) assert '"processing_threads_num":10' in node1.query( f"SELECT * FROM system.zookeeper WHERE path = '{keeper_path}'" ) total_values = generate_random_files( started_cluster, files_path, files_to_generate, start_ind=0, row_num=1 ) create_mv(node1, f"r.{table_name}", dst_table_name) create_mv(node2, f"r.{table_name}", dst_table_name) def get_count(): return int( node1.query( f"SELECT count() FROM clusterAllReplicas(cluster, default.{dst_table_name})" ) ) expected_rows = files_to_generate for _ in range(20): if expected_rows == get_count(): break time.sleep(1) assert expected_rows == get_count() node1.query(f"ALTER TABLE r.{table_name} MODIFY SETTING processing_threads_num=5") assert '"processing_threads_num":5' in node1.query( f"SELECT * FROM system.zookeeper WHERE path = '{keeper_path}'" )