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Expensive queries by memory usage

· 2 min read

The following useful query shows which of your executed queries used the most memory. A couple of comments about this query:

  • the results are computed from the past day (now() - toIntervalDay(1))) but you can easily modify the time interval
  • it assumes you have a cluster named default, which is the name of your cluster in ClickHouse Cloud. Change default to the name of your cluster
  • if you do not have a cluster, see the query listed at the end of this article
SELECT
count() as nb_query,
user,
query,
sum(memory_usage) AS memory,
normalized_query_hash
FROM
clusterAllReplicas(default, system.query_log)
WHERE
(event_time >= (now() - toIntervalDay(1)))
AND query_kind = 'Select'
AND type = 'QueryFinish'
and user != 'monitoring-internal'
GROUP BY
normalized_query_hash,
query,
user
ORDER BY
memory DESC;

The response looks like:

┌─nb_query─┬─user────┬─query─────────────────────────────────────────────────────────┬───memory─┬─normalized_query_hash─┐
│ 11 │ default │ select version() │ 46178924 │ 7202516440347714159 │
│ 2 │ default │ SELECT * FROM "system"."table_functions" LIMIT 31 OFFSET 0 │ 8391544 │ 12830067173062987695 │
└──────────┴─────────┴───────────────────────────────────────────────────────────────┴──────────┴───────────────────────┘
note

If you do not have a system.query_log table, then you likely do not have query logging enabled. View the details of the query_log setting for details on how to enable it.

If you do not have a cluster, use can just query your one system.query_log table directly:

SELECT
count() as nb_query,
user,
query,
sum(memory_usage) AS memory,
normalized_query_hash
FROM
system.query_log
WHERE
(event_time >= (now() - toIntervalDay(1)))
AND query_kind = 'Select'
AND type = 'QueryFinish'
and user != 'monitoring-internal'
GROUP BY
normalized_query_hash,
query,
user
ORDER BY
memory DESC;