mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-11-23 08:02:02 +00:00
921 lines
27 KiB
Python
921 lines
27 KiB
Python
import io
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import logging
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import os
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import random
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import time
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import pytest
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from helpers.client import QueryRuntimeException
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from helpers.cluster import ClickHouseCluster, ClickHouseInstance
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import json
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"""
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export CLICKHOUSE_TESTS_SERVER_BIN_PATH=/home/sergey/vkr/ClickHouse/build/programs/clickhouse-server
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export CLICKHOUSE_TESTS_CLIENT_BIN_PATH=/home/sergey/vkr/ClickHouse/build/programs/clickhouse-client
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export CLICKHOUSE_TESTS_ODBC_BRIDGE_BIN_PATH=/home/sergey/vkr/ClickHouse/build/programs/clickhouse-odbc-bridge
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export CLICKHOUSE_TESTS_BASE_CONFIG_DIR=/home/sergey/vkr/ClickHouse/programs/server
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"""
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MINIO_INTERNAL_PORT = 9001
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AVAILABLE_MODES = ["unordered", "ordered"]
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AUTH = "'minio','minio123',"
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SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
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def prepare_s3_bucket(started_cluster):
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# Allows read-write access for bucket without authorization.
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bucket_read_write_policy = {
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"Version": "2012-10-17",
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"Statement": [
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{
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"Sid": "",
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"Effect": "Allow",
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"Principal": {"AWS": "*"},
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"Action": "s3:GetBucketLocation",
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"Resource": "arn:aws:s3:::root",
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},
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{
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"Sid": "",
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"Effect": "Allow",
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"Principal": {"AWS": "*"},
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"Action": "s3:ListBucket",
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"Resource": "arn:aws:s3:::root",
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},
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{
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"Sid": "",
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"Effect": "Allow",
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"Principal": {"AWS": "*"},
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"Action": "s3:GetObject",
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"Resource": "arn:aws:s3:::root/*",
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},
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{
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"Sid": "",
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"Effect": "Allow",
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"Principal": {"AWS": "*"},
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"Action": "s3:PutObject",
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"Resource": "arn:aws:s3:::root/*",
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},
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{
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"Sid": "",
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"Effect": "Allow",
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"Principal": {"AWS": "*"},
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"Action": "s3:DeleteObject",
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"Resource": "arn:aws:s3:::root/*",
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},
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],
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}
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minio_client = started_cluster.minio_client
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minio_client.set_bucket_policy(
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started_cluster.minio_bucket, json.dumps(bucket_read_write_policy)
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)
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started_cluster.minio_restricted_bucket = "{}-with-auth".format(
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started_cluster.minio_bucket
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)
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if minio_client.bucket_exists(started_cluster.minio_restricted_bucket):
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minio_client.remove_bucket(started_cluster.minio_restricted_bucket)
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minio_client.make_bucket(started_cluster.minio_restricted_bucket)
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@pytest.fixture(autouse=True)
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def s3_queue_setup_teardown(started_cluster):
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instance = started_cluster.instances["instance"]
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instance_2 = started_cluster.instances["instance2"]
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instance.query("DROP DATABASE IF EXISTS test; CREATE DATABASE test;")
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instance_2.query("DROP DATABASE IF EXISTS test; CREATE DATABASE test;")
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minio = started_cluster.minio_client
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objects = list(
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minio.list_objects(started_cluster.minio_restricted_bucket, recursive=True)
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)
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for obj in objects:
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minio.remove_object(started_cluster.minio_restricted_bucket, obj.object_name)
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yield # run test
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@pytest.fixture(scope="module")
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def started_cluster():
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try:
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cluster = ClickHouseCluster(__file__)
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cluster.add_instance(
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"instance",
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user_configs=["configs/users.xml"],
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with_minio=True,
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with_zookeeper=True,
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main_configs=[
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"configs/defaultS3.xml",
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"configs/named_collections.xml",
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"configs/zookeeper.xml",
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"configs/s3queue_log.xml",
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],
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)
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cluster.add_instance(
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"instance2",
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user_configs=["configs/users.xml"],
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with_minio=True,
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with_zookeeper=True,
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main_configs=[
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"configs/defaultS3.xml",
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"configs/named_collections.xml",
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"configs/s3queue_log.xml",
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],
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)
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logging.info("Starting cluster...")
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cluster.start()
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logging.info("Cluster started")
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prepare_s3_bucket(cluster)
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yield cluster
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finally:
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cluster.shutdown()
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def run_query(instance, query, stdin=None, settings=None):
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# type: (ClickHouseInstance, str, object, dict) -> str
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logging.info("Running query '{}'...".format(query))
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result = instance.query(query, stdin=stdin, settings=settings)
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logging.info("Query finished")
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return result
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def generate_random_files(
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started_cluster, files_path, count, column_num=3, row_num=10, start_ind=0
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):
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files = [
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(f"{files_path}/test_{i}.csv", i) for i in range(start_ind, start_ind + count)
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]
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files.sort(key=lambda x: x[0])
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print(f"Generating files: {files}")
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total_values = []
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for filename, i in files:
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rand_values = [
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[random.randint(0, 1000) for _ in range(column_num)] for _ in range(row_num)
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]
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total_values += rand_values
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values_csv = (
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"\n".join((",".join(map(str, row)) for row in rand_values)) + "\n"
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).encode()
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put_s3_file_content(started_cluster, filename, values_csv)
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return total_values
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def put_s3_file_content(started_cluster, filename, data):
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buf = io.BytesIO(data)
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started_cluster.minio_client.put_object(
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started_cluster.minio_bucket, filename, buf, len(data)
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)
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def get_s3_file_content(started_cluster, bucket, filename, decode=True):
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# type: (ClickHouseCluster, str, str, bool) -> str
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# Returns content of given S3 file as string.
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data = started_cluster.minio_client.get_object(bucket, filename)
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data_str = b""
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for chunk in data.stream():
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data_str += chunk
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if decode:
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return data_str.decode()
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return data_str
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def create_table(
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started_cluster,
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node,
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table_name,
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mode,
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files_path,
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format="column1 UInt32, column2 UInt32, column3 UInt32",
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additional_settings={},
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file_format="CSV",
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):
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settings = {
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"s3queue_loading_retries": 0,
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"after_processing": "keep",
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"keeper_path": f"/clickhouse/test_{table_name}",
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"mode": f"{mode}",
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}
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settings.update(additional_settings)
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url = f"http://{started_cluster.minio_host}:{started_cluster.minio_port}/{started_cluster.minio_bucket}/{files_path}/"
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node.query(f"DROP TABLE IF EXISTS {table_name}")
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create_query = f"""
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CREATE TABLE {table_name} ({format})
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ENGINE = S3Queue('{url}', {AUTH}'{file_format}')
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SETTINGS {",".join((k+"="+repr(v) for k, v in settings.items()))}
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"""
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node.query(create_query)
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def create_mv(
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node,
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src_table_name,
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dst_table_name,
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format="column1 UInt32, column2 UInt32, column3 UInt32",
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):
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mv_name = f"{dst_table_name}_mv"
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node.query(
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f"""
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DROP TABLE IF EXISTS {dst_table_name};
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DROP TABLE IF EXISTS {mv_name};
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CREATE TABLE {dst_table_name} ({format}, _path String)
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ENGINE = MergeTree()
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ORDER BY column1;
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CREATE MATERIALIZED VIEW {mv_name} TO {dst_table_name} AS SELECT *, _path FROM {src_table_name};
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"""
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)
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@pytest.mark.parametrize("mode", AVAILABLE_MODES)
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def test_delete_after_processing(started_cluster, mode):
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node = started_cluster.instances["instance"]
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table_name = f"test.delete_after_processing_{mode}"
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dst_table_name = f"{table_name}_dst"
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files_path = f"{table_name}_data"
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files_num = 5
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row_num = 10
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total_values = generate_random_files(
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started_cluster, files_path, files_num, row_num=row_num
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)
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create_table(
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started_cluster,
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node,
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table_name,
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mode,
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files_path,
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additional_settings={"after_processing": "delete"},
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)
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create_mv(node, table_name, dst_table_name)
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expected_count = files_num * row_num
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for _ in range(100):
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count = int(node.query(f"SELECT count() FROM {dst_table_name}"))
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print(f"{count}/{expected_count}")
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if count == expected_count:
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break
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time.sleep(1)
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assert int(node.query(f"SELECT count() FROM {dst_table_name}")) == expected_count
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assert int(node.query(f"SELECT uniq(_path) FROM {dst_table_name}")) == files_num
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assert [
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list(map(int, l.split()))
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for l in node.query(
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f"SELECT column1, column2, column3 FROM {dst_table_name} ORDER BY column1, column2, column3"
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).splitlines()
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] == sorted(total_values, key=lambda x: (x[0], x[1], x[2]))
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minio = started_cluster.minio_client
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objects = list(minio.list_objects(started_cluster.minio_bucket, recursive=True))
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assert len(objects) == 0
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@pytest.mark.parametrize("mode", AVAILABLE_MODES)
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def test_failed_retry(started_cluster, mode):
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node = started_cluster.instances["instance"]
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table_name = f"test.failed_retry_{mode}"
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dst_table_name = f"{table_name}_dst"
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files_path = f"{table_name}_data"
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file_path = f"{files_path}/trash_test.csv"
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keeper_path = f"/clickhouse/test_{table_name}"
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retries_num = 3
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values = [
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["failed", 1, 1],
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]
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values_csv = (
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"\n".join((",".join(map(str, row)) for row in values)) + "\n"
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).encode()
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put_s3_file_content(started_cluster, file_path, values_csv)
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create_table(
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started_cluster,
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node,
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table_name,
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mode,
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files_path,
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additional_settings={
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"s3queue_loading_retries": retries_num,
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"keeper_path": keeper_path,
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},
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)
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create_mv(node, table_name, dst_table_name)
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failed_node_path = ""
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for _ in range(20):
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zk = started_cluster.get_kazoo_client("zoo1")
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failed_nodes = zk.get_children(f"{keeper_path}/failed/")
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if len(failed_nodes) > 0:
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assert len(failed_nodes) == 1
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failed_node_path = f"{keeper_path}/failed/{failed_nodes[0]}"
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time.sleep(1)
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assert failed_node_path != ""
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retries = 0
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for _ in range(20):
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data, stat = zk.get(failed_node_path)
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json_data = json.loads(data)
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print(f"Failed node metadata: {json_data}")
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assert json_data["file_path"] == file_path
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retries = int(json_data["retries"])
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if retries == retries_num:
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break
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time.sleep(1)
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assert retries == retries_num
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assert 0 == int(node.query(f"SELECT count() FROM {dst_table_name}"))
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@pytest.mark.parametrize("mode", AVAILABLE_MODES)
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def test_direct_select_file(started_cluster, mode):
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node = started_cluster.instances["instance"]
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table_name = f"test.direct_select_file_{mode}"
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keeper_path = f"/clickhouse/test_{table_name}"
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files_path = f"{table_name}_data"
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file_path = f"{files_path}/test.csv"
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values = [
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[12549, 2463, 19893],
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[64021, 38652, 66703],
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[81611, 39650, 83516],
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]
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values_csv = (
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"\n".join((",".join(map(str, row)) for row in values)) + "\n"
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).encode()
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put_s3_file_content(started_cluster, file_path, values_csv)
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for i in range(3):
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create_table(
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started_cluster,
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node,
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f"{table_name}_{i + 1}",
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mode,
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files_path,
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additional_settings={
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"keeper_path": keeper_path,
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},
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)
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_1").splitlines()
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] == values
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_2").splitlines()
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] == []
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_3").splitlines()
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] == []
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# New table with same zookeeper path
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create_table(
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started_cluster,
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node,
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f"{table_name}_4",
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mode,
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files_path,
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additional_settings={
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"keeper_path": keeper_path,
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},
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)
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
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] == []
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# New table with different zookeeper path
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keeper_path = f"/clickhouse/test_{table_name}_{mode}_2"
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create_table(
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started_cluster,
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node,
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f"{table_name}_4",
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mode,
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files_path,
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additional_settings={
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"keeper_path": keeper_path,
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},
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)
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
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] == values
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values = [
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[1, 1, 1],
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]
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values_csv = (
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"\n".join((",".join(map(str, row)) for row in values)) + "\n"
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).encode()
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file_path = f"{files_path}/t.csv"
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put_s3_file_content(started_cluster, file_path, values_csv)
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|
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if mode == "unordered":
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
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] == values
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elif mode == "ordered":
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}_4").splitlines()
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] == []
|
|
|
|
|
|
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
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def test_direct_select_multiple_files(started_cluster, mode):
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node = started_cluster.instances["instance"]
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table_name = f"direct_select_multiple_files_{mode}"
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files_path = f"{table_name}_data"
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|
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create_table(started_cluster, node, table_name, mode, files_path)
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for i in range(5):
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rand_values = [[random.randint(0, 50) for _ in range(3)] for _ in range(10)]
|
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values_csv = (
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"\n".join((",".join(map(str, row)) for row in rand_values)) + "\n"
|
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).encode()
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|
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file_path = f"{files_path}/test_{i}.csv"
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put_s3_file_content(started_cluster, file_path, values_csv)
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assert [
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list(map(int, l.split()))
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for l in node.query(f"SELECT * FROM {table_name}").splitlines()
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] == rand_values
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total_values = generate_random_files(started_cluster, files_path, 4, start_ind=5)
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assert {
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tuple(map(int, l.split()))
|
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for l in node.query(f"SELECT * FROM {table_name}").splitlines()
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} == set([tuple(i) for i in total_values])
|
|
|
|
|
|
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
|
|
def test_streaming_to_view_(started_cluster, mode):
|
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node = started_cluster.instances["instance"]
|
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table_name = f"streaming_to_view_{mode}"
|
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dst_table_name = f"{table_name}_dst"
|
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files_path = f"{table_name}_data"
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|
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total_values = generate_random_files(started_cluster, files_path, 10)
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create_table(started_cluster, node, table_name, mode, files_path)
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create_mv(node, table_name, dst_table_name)
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|
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expected_values = set([tuple(i) for i in total_values])
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for i in range(10):
|
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selected_values = {
|
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tuple(map(int, l.split()))
|
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for l in node.query(
|
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f"SELECT column1, column2, column3 FROM {dst_table_name}"
|
|
).splitlines()
|
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}
|
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if selected_values == expected_values:
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break
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time.sleep(1)
|
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assert selected_values == expected_values
|
|
|
|
|
|
@pytest.mark.parametrize("mode", AVAILABLE_MODES)
|
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def test_streaming_to_many_views(started_cluster, mode):
|
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node = started_cluster.instances["instance"]
|
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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(
|
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started_cluster,
|
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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=50
|
|
)
|
|
|
|
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"
|
|
)
|