import random import time from multiprocessing.dummy import Pool import datetime import pytest from helpers.client import QueryRuntimeException from helpers.cluster import ClickHouseCluster node_options = dict( with_zookeeper=True, main_configs=[ "configs/remote_servers.xml", "configs/config.d/instant_moves.xml", "configs/config.d/part_log.xml", "configs/config.d/zookeeper_session_timeout.xml", "configs/config.d/storage_configuration.xml", ], tmpfs=["/external:size=200M", "/internal:size=1M"], ) cluster = ClickHouseCluster(__file__) node1 = cluster.add_instance("node1", macros={"shard": 0, "replica": 1}, **node_options) node2 = cluster.add_instance("node2", macros={"shard": 0, "replica": 2}, **node_options) node3 = cluster.add_instance("node3", macros={"shard": 1, "replica": 1}, **node_options) node4 = cluster.add_instance("node4", macros={"shard": 1, "replica": 2}, **node_options) nodes = [node1, node2, node3, node4] @pytest.fixture(scope="module") def started_cluster(): try: cluster.start() yield cluster except Exception as ex: print(ex) finally: cluster.shutdown() def drop_table(nodes, table_name): for node in nodes: node.query("DROP TABLE IF EXISTS {} NO DELAY".format(table_name)) def create_table( nodes, table_name, with_storage_policy=False, with_time_column=False, with_ttl_move=False, with_ttl_delete=False, ): extra_columns = "" settings = [] for node in nodes: sql = """ CREATE TABLE {table_name} ( num UInt32, num2 UInt32 DEFAULT num + 1{extra_columns} ) ENGINE = ReplicatedMergeTree('/clickhouse/tables/test/{table_name}', '{replica}') ORDER BY num PARTITION BY num % 100 """ if with_ttl_move: sql += """ TTL time + INTERVAL (num2 % 1) SECOND TO DISK 'external' """ if with_ttl_delete: sql += """ TTL time + INTERVAL (num2 % 1) SECOND DELETE """ settings.append("merge_with_ttl_timeout = 1") if with_storage_policy: settings.append("storage_policy='default_with_external'") if settings: sql += """ SETTINGS {} """.format( ", ".join(settings) ) if with_time_column: extra_columns = """, time DateTime """ node.query( sql.format( table_name=table_name, replica=node.name, extra_columns=extra_columns ) ) def create_distributed_table(node, table_name): sql = """ CREATE TABLE %(table_name)s_replicated ON CLUSTER test_cluster ( num UInt32, num2 UInt32 DEFAULT num + 1 ) ENGINE = ReplicatedMergeTree('/clickhouse/tables/test/{shard}/%(table_name)s_replicated', '{replica}') ORDER BY num PARTITION BY num %% 100; """ % dict( table_name=table_name ) node.query(sql) sql = """ CREATE TABLE %(table_name)s ON CLUSTER test_cluster AS %(table_name)s_replicated ENGINE = Distributed(test_cluster, default, %(table_name)s_replicated, rand()) """ % dict( table_name=table_name ) node.query(sql) def drop_distributed_table(node, table_name): node.query( "DROP TABLE IF EXISTS {} ON CLUSTER test_cluster SYNC".format(table_name) ) node.query( "DROP TABLE IF EXISTS {}_replicated ON CLUSTER test_cluster SYNC".format( table_name ) ) time.sleep(1) def insert( node, table_name, chunk=1000, col_names=None, iterations=1, ignore_exception=False, slow=False, with_many_parts=False, offset=0, with_time_column=False, ): if col_names is None: col_names = ["num", "num2"] for i in range(iterations): try: query = ["SET max_partitions_per_insert_block = 10000000"] if with_many_parts: query.append("SET max_insert_block_size = 256") if with_time_column: query.append( "INSERT INTO {table_name} ({col0}, {col1}, time) SELECT number AS {col0}, number + 1 AS {col1}, now() + 10 AS time FROM numbers_mt({chunk})".format( table_name=table_name, chunk=chunk, col0=col_names[0], col1=col_names[1], ) ) elif slow: query.append( "INSERT INTO {table_name} ({col0}, {col1}) SELECT number + sleepEachRow(0.001) AS {col0}, number + 1 AS {col1} FROM numbers_mt({chunk})".format( table_name=table_name, chunk=chunk, col0=col_names[0], col1=col_names[1], ) ) else: query.append( "INSERT INTO {table_name} ({col0},{col1}) SELECT number + {offset} AS {col0}, number + 1 + {offset} AS {col1} FROM numbers_mt({chunk})".format( table_name=table_name, chunk=chunk, col0=col_names[0], col1=col_names[1], offset=str(offset), ) ) node.query(";\n".join(query)) except QueryRuntimeException as ex: if not ignore_exception: raise def select( node, table_name, col_name="num", expected_result=None, iterations=1, ignore_exception=False, slow=False, poll=None, ): for i in range(iterations): start_time = time.time() while True: try: if slow: r = node.query( "SELECT count() FROM (SELECT num2, sleepEachRow(0.5) FROM {} WHERE {} % 1000 > 0)".format( table_name, col_name ) ) else: r = node.query( "SELECT count() FROM {} WHERE {} % 1000 > 0".format( table_name, col_name ) ) if expected_result: if ( r != expected_result and poll and time.time() - start_time < poll ): continue assert r == expected_result except QueryRuntimeException as ex: if not ignore_exception: raise break def rename_column( node, table_name, name, new_name, iterations=1, ignore_exception=False ): for i in range(iterations): try: node.query( "ALTER TABLE {table_name} RENAME COLUMN {name} to {new_name}".format( table_name=table_name, name=name, new_name=new_name ) ) except QueryRuntimeException as ex: if not ignore_exception: raise def rename_column_on_cluster( node, table_name, name, new_name, iterations=1, ignore_exception=False ): for i in range(iterations): try: node.query( "ALTER TABLE {table_name} ON CLUSTER test_cluster RENAME COLUMN {name} to {new_name}".format( table_name=table_name, name=name, new_name=new_name ) ) except QueryRuntimeException as ex: if not ignore_exception: raise def alter_move(node, table_name, iterations=1, ignore_exception=False): for i in range(iterations): move_part = random.randint(0, 99) move_volume = "external" try: node.query( "ALTER TABLE {table_name} MOVE PARTITION '{move_part}' TO VOLUME '{move_volume}'".format( table_name=table_name, move_part=move_part, move_volume=move_volume ) ) except QueryRuntimeException as ex: if not ignore_exception: raise def test_rename_parallel_same_node(started_cluster): table_name = "test_rename_parallel_same_node" drop_table(nodes, table_name) try: create_table(nodes, table_name) insert(node1, table_name, 1000) p = Pool(15) tasks = [] for i in range(1): tasks.append( p.apply_async( rename_column, (node1, table_name, "num2", "foo2", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node1, table_name, "foo2", "foo3", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node1, table_name, "foo3", "num2", 5, True) ) ) for task in tasks: task.get(timeout=240) # rename column back to original rename_column(node1, table_name, "foo3", "num2", 1, True) rename_column(node1, table_name, "foo2", "num2", 1, True) # check that select still works select(node1, table_name, "num2", "999\n") finally: drop_table(nodes, table_name) def test_rename_parallel(started_cluster): table_name = "test_rename_parallel" drop_table(nodes, table_name) try: create_table(nodes, table_name) insert(node1, table_name, 1000) p = Pool(15) tasks = [] for i in range(1): tasks.append( p.apply_async( rename_column, (node1, table_name, "num2", "foo2", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node2, table_name, "foo2", "foo3", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node3, table_name, "foo3", "num2", 5, True) ) ) for task in tasks: task.get(timeout=240) # rename column back to original rename_column(node1, table_name, "foo3", "num2", 1, True) rename_column(node1, table_name, "foo2", "num2", 1, True) # check that select still works select(node1, table_name, "num2", "999\n") finally: drop_table(nodes, table_name) def test_rename_with_parallel_select(started_cluster): table_name = "test_rename_with_parallel_select" drop_table(nodes, table_name) try: create_table(nodes, table_name) insert(node1, table_name, 1000) select(node1, table_name, "num2", "999\n", poll=30) select(node2, table_name, "num2", "999\n", poll=30) select(node3, table_name, "num2", "999\n", poll=30) p = Pool(15) tasks = [] for i in range(1): tasks.append( p.apply_async( rename_column, (node1, table_name, "num2", "foo2", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node2, table_name, "foo2", "foo3", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node3, table_name, "foo3", "num2", 5, True) ) ) tasks.append( p.apply_async(select, (node1, table_name, "foo3", "999\n", 5, True)) ) tasks.append( p.apply_async(select, (node2, table_name, "num2", "999\n", 5, True)) ) tasks.append( p.apply_async(select, (node3, table_name, "foo2", "999\n", 5, True)) ) for task in tasks: task.get(timeout=240) # rename column back to original name rename_column(node1, table_name, "foo3", "num2", 1, True) rename_column(node1, table_name, "foo2", "num2", 1, True) # check that select still works select(node1, table_name, "num2", "999\n") finally: drop_table(nodes, table_name) def test_rename_with_parallel_insert(started_cluster): table_name = "test_rename_with_parallel_insert" drop_table(nodes, table_name) try: create_table(nodes, table_name) insert(node1, table_name, 1000) p = Pool(15) tasks = [] for i in range(1): tasks.append( p.apply_async( rename_column, (node1, table_name, "num2", "foo2", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node2, table_name, "foo2", "foo3", 5, True) ) ) tasks.append( p.apply_async( rename_column, (node3, table_name, "foo3", "num2", 5, True) ) ) tasks.append( p.apply_async( insert, (node1, table_name, 100, ["num", "foo3"], 5, True) ) ) tasks.append( p.apply_async( insert, (node2, table_name, 100, ["num", "num2"], 5, True) ) ) tasks.append( p.apply_async( insert, (node3, table_name, 100, ["num", "foo2"], 5, True) ) ) for task in tasks: task.get(timeout=240) # rename column back to original rename_column(node1, table_name, "foo3", "num2", 1, True) rename_column(node1, table_name, "foo2", "num2", 1, True) # check that select still works select(node1, table_name, "num2") finally: drop_table(nodes, table_name) def test_rename_with_parallel_merges(started_cluster): table_name = "test_rename_with_parallel_merges" drop_table(nodes, table_name) try: print("Creating tables", datetime.datetime.now()) create_table(nodes, table_name) for i in range(5): insert( node1, table_name, 100, ["num", "num2"], 1, False, False, True, offset=i * 100, ) print("Data inserted", datetime.datetime.now()) def merge_parts(node, table_name, iterations=1): for _ in range(iterations): try: node.query("OPTIMIZE TABLE %s FINAL" % table_name) except Exception as ex: print("Got an exception while optimizing table", ex) print("Creating pool") p = Pool(15) tasks = [] tasks.append( p.apply_async(rename_column, (node1, table_name, "num2", "foo2", 2, True)) ) tasks.append( p.apply_async(rename_column, (node2, table_name, "foo2", "foo3", 2, True)) ) tasks.append( p.apply_async(rename_column, (node3, table_name, "foo3", "num2", 2, True)) ) tasks.append(p.apply_async(merge_parts, (node1, table_name, 2))) tasks.append(p.apply_async(merge_parts, (node2, table_name, 2))) tasks.append(p.apply_async(merge_parts, (node3, table_name, 2))) print("Waiting for tasks", datetime.datetime.now()) for task in tasks: task.get(timeout=240) print("Finished waiting", datetime.datetime.now()) print("Renaming columns", datetime.datetime.now()) # rename column back to the original name rename_column(node1, table_name, "foo3", "num2", 1, True) rename_column(node1, table_name, "foo2", "num2", 1, True) print("Finished renaming", datetime.datetime.now()) # check that select still works select(node1, table_name, "num2", "500\n") select(node2, table_name, "num2", "500\n") select(node3, table_name, "num2", "500\n") finally: drop_table(nodes, table_name) def test_rename_with_parallel_slow_insert(started_cluster): table_name = "test_rename_with_parallel_slow_insert" drop_table(nodes, table_name) try: create_table(nodes, table_name) insert(node1, table_name, 1000) p = Pool(15) tasks = [] tasks.append( p.apply_async( insert, (node1, table_name, 10000, ["num", "num2"], 1, False, True) ) ) tasks.append( p.apply_async( insert, (node1, table_name, 10000, ["num", "num2"], 1, True, True) ) ) # deduplicated time.sleep(0.5) tasks.append(p.apply_async(rename_column, (node1, table_name, "num2", "foo2"))) for task in tasks: task.get(timeout=240) insert(node1, table_name, 100, ["num", "foo2"]) # rename column back to original rename_column(node1, table_name, "foo2", "num2") # check that select still works select(node1, table_name, "num2", "11089\n") select(node2, table_name, "num2", "11089\n", poll=30) select(node3, table_name, "num2", "11089\n", poll=30) finally: drop_table(nodes, table_name) def test_rename_with_parallel_ttl_move(started_cluster): table_name = "test_rename_with_parallel_ttl_move" try: create_table( nodes, table_name, with_storage_policy=True, with_time_column=True, with_ttl_move=True, ) rename_column(node1, table_name, "time", "time2", 1, False) rename_column(node1, table_name, "time2", "time", 1, False) p = Pool(15) tasks = [] tasks.append( p.apply_async( insert, ( node1, table_name, 10000, ["num", "num2"], 1, False, False, True, 0, True, ), ) ) time.sleep(5) rename_column(node1, table_name, "time", "time2", 1, False) time.sleep(4) tasks.append( p.apply_async(rename_column, (node1, table_name, "num2", "foo2", 5, True)) ) tasks.append( p.apply_async(rename_column, (node2, table_name, "foo2", "foo3", 5, True)) ) tasks.append( p.apply_async(rename_column, (node3, table_name, "num3", "num2", 5, True)) ) for task in tasks: task.get(timeout=240) # check some parts got moved assert "external" in set( node1.query( "SELECT disk_name FROM system.parts WHERE table == '{}' AND active=1 ORDER BY modification_time".format( table_name ) ) .strip() .splitlines() ) # rename column back to original rename_column(node1, table_name, "foo2", "num2", 1, True) rename_column(node1, table_name, "foo3", "num2", 1, True) # check that select still works select(node1, table_name, "num2", "9990\n") finally: drop_table(nodes, table_name) def test_rename_with_parallel_ttl_delete(started_cluster): table_name = "test_rename_with_parallel_ttl_delete" try: create_table(nodes, table_name, with_time_column=True, with_ttl_delete=True) rename_column(node1, table_name, "time", "time2", 1, False) rename_column(node1, table_name, "time2", "time", 1, False) def merge_parts(node, table_name, iterations=1): for i in range(iterations): node.query("OPTIMIZE TABLE {}".format(table_name)) p = Pool(15) tasks = [] tasks.append( p.apply_async( insert, ( node1, table_name, 10000, ["num", "num2"], 1, False, False, True, 0, True, ), ) ) time.sleep(15) tasks.append( p.apply_async(rename_column, (node1, table_name, "num2", "foo2", 5, True)) ) tasks.append( p.apply_async(rename_column, (node2, table_name, "foo2", "foo3", 5, True)) ) tasks.append( p.apply_async(rename_column, (node3, table_name, "num3", "num2", 5, True)) ) tasks.append(p.apply_async(merge_parts, (node1, table_name, 3))) tasks.append(p.apply_async(merge_parts, (node2, table_name, 3))) tasks.append(p.apply_async(merge_parts, (node3, table_name, 3))) for task in tasks: task.get(timeout=240) # rename column back to original rename_column(node1, table_name, "foo2", "num2", 1, True) rename_column(node1, table_name, "foo3", "num2", 1, True) assert ( int(node1.query("SELECT count() FROM {}".format(table_name)).strip()) < 10000 ) finally: drop_table(nodes, table_name) def test_rename_distributed(started_cluster): table_name = "test_rename_distributed" try: create_distributed_table(node1, table_name) insert(node1, table_name, 1000) rename_column_on_cluster(node1, table_name, "num2", "foo2") rename_column_on_cluster(node1, "%s_replicated" % table_name, "num2", "foo2") insert(node1, table_name, 1000, col_names=["num", "foo2"]) select(node1, table_name, "foo2", "1998\n", poll=30) finally: drop_distributed_table(node1, table_name) def test_rename_distributed_parallel_insert_and_select(started_cluster): table_name = "test_rename_distributed_parallel_insert_and_select" try: create_distributed_table(node1, table_name) insert(node1, table_name, 1000) p = Pool(15) tasks = [] for i in range(1): tasks.append( p.apply_async( rename_column_on_cluster, (node1, table_name, "num2", "foo2", 3, True), ) ) tasks.append( p.apply_async( rename_column_on_cluster, (node1, "%s_replicated" % table_name, "num2", "foo2", 3, True), ) ) tasks.append( p.apply_async( rename_column_on_cluster, (node1, table_name, "foo2", "foo3", 3, True), ) ) tasks.append( p.apply_async( rename_column_on_cluster, (node1, "%s_replicated" % table_name, "foo2", "foo3", 3, True), ) ) tasks.append( p.apply_async( rename_column_on_cluster, (node1, table_name, "foo3", "num2", 3, True), ) ) tasks.append( p.apply_async( rename_column_on_cluster, (node1, "%s_replicated" % table_name, "foo3", "num2", 3, True), ) ) tasks.append( p.apply_async(insert, (node1, table_name, 10, ["num", "foo3"], 5, True)) ) tasks.append( p.apply_async(insert, (node2, table_name, 10, ["num", "num2"], 5, True)) ) tasks.append( p.apply_async(insert, (node3, table_name, 10, ["num", "foo2"], 5, True)) ) tasks.append( p.apply_async(select, (node1, table_name, "foo2", None, 5, True)) ) tasks.append( p.apply_async(select, (node2, table_name, "foo3", None, 5, True)) ) tasks.append( p.apply_async(select, (node3, table_name, "num2", None, 5, True)) ) for task in tasks: task.get(timeout=240) rename_column_on_cluster(node1, table_name, "foo2", "num2", 1, True) rename_column_on_cluster( node1, "%s_replicated" % table_name, "foo2", "num2", 1, True ) rename_column_on_cluster(node1, table_name, "foo3", "num2", 1, True) rename_column_on_cluster( node1, "%s_replicated" % table_name, "foo3", "num2", 1, True ) insert(node1, table_name, 1000, col_names=["num", "num2"]) select(node1, table_name, "num2") select(node2, table_name, "num2") select(node3, table_name, "num2") select(node4, table_name, "num2") finally: drop_distributed_table(node1, table_name)