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https://github.com/ClickHouse/ClickHouse.git
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d030e08d05
By comparing only megabytes in the memory changes, instead of bytes as before, since it may be tricky at least due to max_untracked_memory and how thread pool handle it. It should be safe, since originally it was written in #16121 which fixes issue #15932, which has ~4MB consumption of memory per request.
106 lines
3.4 KiB
Python
106 lines
3.4 KiB
Python
# pylint: disable=unused-argument
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# pylint: disable=redefined-outer-name
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# pylint: disable=line-too-long
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# This test verifies that memory tracking does not have significant drift,
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# in other words, every allocation should be taken into account at the global
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# memory tracker.
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#
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# So we are running some queries with GROUP BY to make some allocations,
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# and after we are checking MemoryTracking metric from system.metrics,
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# and check that it does not changes too frequently.
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#
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# Also note, that syncing MemoryTracking with RSS had been disabled in
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# asynchronous_metrics_update_period_s.xml.
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import logging
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import pytest
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from helpers.cluster import ClickHouseCluster
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cluster = ClickHouseCluster(__file__)
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node = cluster.add_instance('node', main_configs=[
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'configs/no_system_log.xml',
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'configs/asynchronous_metrics_update_period_s.xml',
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], user_configs=[
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'configs/users.d/overrides.xml',
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])
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@pytest.fixture(scope='module', autouse=True)
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def start_cluster():
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try:
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cluster.start()
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yield cluster
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finally:
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cluster.shutdown()
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query_settings = {
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'max_threads': 1,
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'log_queries': 0,
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}
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sample_query = "SELECT groupArray(repeat('a', 1000)) FROM numbers(10000) GROUP BY number%10 FORMAT JSON"
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def query(*args, **kwargs):
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if 'settings' not in kwargs:
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kwargs['settings'] = query_settings
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else:
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kwargs['settings'].update(query_settings)
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return node.query(*args, **kwargs)
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def http_query(*args, **kwargs):
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if 'params' not in kwargs:
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kwargs['params'] = query_settings
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else:
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kwargs['params'].update(query_settings)
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return node.http_query(*args, **kwargs)
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def get_MemoryTracking():
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return int(http_query("SELECT value FROM system.metrics WHERE metric = 'MemoryTracking'"))
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def check_memory(memory):
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# bytes -> megabytes
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memory = [*map(lambda x: int(int(x)/1024/1024), memory)]
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# 3 changes to MemoryTracking is minimum, since:
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# - this is not that high to not detect inacuracy
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# - memory can go like X/X+N due to some background allocations
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# - memory can go like X/X+N/X, so at least 2 changes
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changes_allowed = 3
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# if number of samples is large enough, use 10% from them
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# (actually most of the time there will be only few changes, it was made 10% to avoid flackiness)
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changes_allowed_auto=int(len(memory) * 0.1)
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changes_allowed = max(changes_allowed_auto, changes_allowed)
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changed=len(set(memory))
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logging.info('Changes: allowed=%s, actual=%s, sample=%s',
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changes_allowed, changed, len(memory))
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assert changed < changes_allowed
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def test_http():
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memory = []
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memory.append(get_MemoryTracking())
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for _ in range(100):
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http_query(sample_query)
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memory.append(get_MemoryTracking())
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check_memory(memory)
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def test_tcp_multiple_sessions():
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memory = []
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memory.append(get_MemoryTracking())
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for _ in range(100):
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query(sample_query)
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memory.append(get_MemoryTracking())
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check_memory(memory)
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def test_tcp_single_session():
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memory = []
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memory.append(get_MemoryTracking())
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sample_queries = [
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sample_query,
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"SELECT metric, value FROM system.metrics WHERE metric = 'MemoryTracking'",
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] * 100
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rows = query(';'.join(sample_queries))
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memory = rows.split('\n')
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memory = filter(lambda x: x.startswith('MemoryTracking'), memory)
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memory = map(lambda x: x.split('\t')[1], memory)
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memory = [*memory]
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check_memory(memory)
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