ClickHouse/tests/integration/test_rename_column/test.py
2023-07-04 21:19:30 +02:00

803 lines
25 KiB
Python

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 {} SYNC".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}) SETTINGS function_sleep_max_microseconds_per_block = 0".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) SETTINGS function_sleep_max_microseconds_per_block = 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
):
i = 0
while True:
i += 1
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 "Coordination::Exception" in str(ex):
continue
if not ignore_exception:
raise
if i >= iterations:
break
def rename_column_on_cluster(
node, table_name, name, new_name, iterations=1, ignore_exception=False
):
i = 0
while True:
i += 1
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 "Coordination::Exception" in str(ex):
continue
if not ignore_exception:
raise
if i >= iterations:
break
def alter_move(node, table_name, iterations=1, ignore_exception=False):
i = 0
while True:
i += 1
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 "Coordination::Exception" in str(ex):
continue
if not ignore_exception:
raise
if i >= iterations:
break
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)