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Adding tests.

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Vitaliy Zakaznikov 2020-05-07 15:50:42 +02:00
parent 90e52e7fea
commit abe28968f4
3 changed files with 409 additions and 0 deletions
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0
tests/integration/test_rename_column/__init__.py Normal file
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tests/integration/test_rename_column/configs/remote_servers.xml Normal file
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<yandex>
<remote_servers>
<test_cluster>
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>node1</host>
<port>9000</port>
</replica>
<replica>
<host>node2</host>
<port>9000</port>
</replica>
</shard>
<shard>
<internal_replication>true</internal_replication>
<replica>
<host>node3</host>
<port>9000</port>
</replica>
<replica>
<host>node4</host>
<port>9000</port>
</replica>
</shard>
</test_cluster>
</remote_servers>
</yandex>

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tests/integration/test_rename_column/test.py Normal file
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from __future__ import print_function
import time
import pytest
from multiprocessing.dummy import Pool
from helpers.cluster import ClickHouseCluster
from helpers.client import QueryRuntimeException
from helpers.network import PartitionManager
from helpers.test_tools import TSV
main_configs=['configs/remote_servers.xml']
cluster = ClickHouseCluster(__file__)
node1 = cluster.add_instance('node1', with_zookeeper=True, macros={"shard": 0, "replica": 1}, main_configs=main_configs )
node2 = cluster.add_instance('node2', with_zookeeper=True, macros={"shard": 0, "replica": 2}, main_configs=main_configs )
node3 = cluster.add_instance('node3', with_zookeeper=True, macros={"shard": 1, "replica": 1}, main_configs=main_configs )
node4 = cluster.add_instance('node4', with_zookeeper=True, macros={"shard": 1, "replica": 2}, main_configs=main_configs )
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))
time.sleep(1)
def create_table(nodes, table_name):
for node in nodes:
sql = """
CREATE TABLE {table_name}
(
num UInt32,
num2 UInt32 DEFAULT num + 1
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/test/{table_name}', '{replica}')
ORDER BY num PARTITION BY num % 100;
""".format(table_name=table_name, replica=node.name)
node.query(sql)
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".format(table_name))
node.query("DROP TABLE IF EXISTS {}_replicated ON CLUSTER test_cluster".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):
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 = 64")
if 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 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)
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:
create_table(nodes, table_name)
for i in range(20):
insert(node1, table_name, 100, ["num","num2"], 1, False, False, True, offset=i*100)
def merge_parts(node, table_name, iterations=1):
for i in range(iterations):
node.query("OPTIMIZE TABLE %s FINAL" % table_name)
p = Pool(15)
tasks = []
for i in range(1):
tasks.append(p.apply_async(rename_column, (node1, table_name, "num2", "foo2", 25, True)))
tasks.append(p.apply_async(rename_column, (node2, table_name, "foo2", "foo3", 25, True)))
tasks.append(p.apply_async(rename_column, (node3, table_name, "foo3", "num2", 25, True)))
tasks.append(p.apply_async(merge_parts, (node1, table_name, 15)))
tasks.append(p.apply_async(merge_parts, (node2, table_name, 15)))
tasks.append(p.apply_async(merge_parts, (node3, table_name, 15)))
for task in tasks:
task.get(timeout=240)
# 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)
# check that select still works
select(node1, table_name, "num2", "1998\n")
select(node2, table_name, "num2", "1998\n")
select(node3, table_name, "num2", "1998\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_slow_select(started_cluster):
table_name = "test_rename_with_parallel_slow_select"
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(select, (node1, table_name, "num2", "999\n", 1, True, True)))
time.sleep(0.25)
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", "1099\n")
select(node2, table_name, "num2", "1099\n", poll=30)
select(node3, table_name, "num2", "1099\n", poll=30)
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', 5, True)))
tasks.append(p.apply_async(rename_column_on_cluster, (node1, '%s_replicated' % table_name, 'num2', 'foo2', 5, True)))
tasks.append(p.apply_async(rename_column_on_cluster, (node1, table_name, 'foo2', 'foo3', 5, True)))
tasks.append(p.apply_async(rename_column_on_cluster, (node1, '%s_replicated' % table_name, 'foo2', 'foo3', 5, True)))
tasks.append(p.apply_async(rename_column_on_cluster, (node1, table_name, 'foo3', 'num2', 5, True)))
tasks.append(p.apply_async(rename_column_on_cluster, (node1, '%s_replicated' % 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)))
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)