SELECT
table,
formatReadableSize(size) AS size,
rows,
days,
formatReadableSize(avgDaySize) AS avgDaySize
FROM
(
SELECT
table,
sum(bytes) AS size,
sum(rows) AS rows,
min(min_date) AS min_date,
max(max_date) AS max_date,
max_date - min_date AS days,
size / (max_date - min_date) AS avgDaySize
FROM system.parts
WHERE active
GROUP BY table
ORDER BY rows DESC
)
Compression columns percentage as well as the size of primary index in memory
You can see how compressed your data is by column. This query also returns the size of your primary indexes in memory - useful to know because primary indexes must fit in memory.
SELECT
parts.*,
columns.compressed_size,
columns.uncompressed_size,
columns.compression_ratio,
columns.compression_percentage
FROM
(
SELECT
table,
formatReadableSize(sum(data_uncompressed_bytes)) AS uncompressed_size,
formatReadableSize(sum(data_compressed_bytes)) AS compressed_size,
round(sum(data_compressed_bytes) / sum(data_uncompressed_bytes), 3) AS compression_ratio,
round(100 - ((sum(data_compressed_bytes) * 100) / sum(data_uncompressed_bytes)), 3) AS compression_percentage
FROM system.columns
GROUP BY table
) AS columns
RIGHT JOIN
(
SELECT
table,
sum(rows) AS rows,
max(modification_time) AS latest_modification,
formatReadableSize(sum(bytes)) AS disk_size,
formatReadableSize(sum(primary_key_bytes_in_memory)) AS primary_keys_size,
any(engine) AS engine,
sum(bytes) AS bytes_size
FROM system.parts
WHERE active
GROUP BY
database,
table
) AS parts ON columns.table = parts.table
ORDER BY parts.bytes_size DESC
Number of queries sent by client in the last 10 minutes
Feel free to increase or decrease the time interval in the toIntervalMinute(10) function:
SELECT
client_name,
count(),
query_kind,
toStartOfMinute(event_time) AS event_time_m
FROM system.query_log
WHERE (type = 'QueryStart') AND (event_time > (now() - toIntervalMinute(10)))
GROUP BY
event_time_m,
client_name,
query_kind
ORDER BY
event_time_m DESC,
count() ASC
Top 10 queries that are using the most CPU and memory
SELECT
type,
event_time,
initial_query_id,
formatReadableSize(memory_usage) AS memory,
`ProfileEvents.Values`[indexOf(`ProfileEvents.Names`, 'UserTimeMicroseconds')] AS userCPU,
`ProfileEvents.Values`[indexOf(`ProfileEvents.Names`, 'SystemTimeMicroseconds')] AS systemCPU,
normalizedQueryHash(query) AS normalized_query_hash
FROM system.query_log
ORDER BY memory_usage DESC
LIMIT 10
SELECT
name,
parent_name,
formatReadableSize(bytes_on_disk) AS bytes,
formatReadableSize(parent_bytes_on_disk) AS parent_bytes,
bytes_on_disk / parent_bytes_on_disk AS ratio
FROM system.projection_parts
Show disk storage, number of parts, number of rows in system.parts and marks across databases
SELECT
database,
table,
partition,
count() AS parts,
formatReadableSize(sum(bytes_on_disk)) AS bytes_on_disk,
formatReadableQuantity(sum(rows)) AS rows,
sum(marks) AS marks
FROM system.parts
WHERE (database != 'system') AND active
GROUP BY
database,
table,
partition
ORDER BY database ASC
The details include when they got created, how large they are, how many rows, and more:
SELECT
modification_time,
rows,
formatReadableSize(bytes_on_disk),
*
FROM clusterAllReplicas(default, system.parts)
WHERE (database = 'default') AND active AND (level = 0)
ORDER BY modification_time DESC
LIMIT 100
The following queries are useful for monitoring ClickHouse clusters. They use clusterAllReplicas() to aggregate data across all nodes.
Примечание
These queries assume your cluster is named default. If your cluster has a different name, replace 'default' and default with your cluster's actual name.
Average new parts created per minute and second (last hour)
WITH
PER_MINUTE AS
(
SELECT
toStartOfInterval(modification_time, toIntervalMinute(1)) AS t,
count() AS new_part_count
FROM
clusterAllReplicas(default, merge(system, '^parts'))
WHERE
(database = 'default') AND
(table = 'your_table') AND
(active = true) AND
(level = 0) AND
(modification_time >= (now() - toIntervalHour(1)))
GROUP BY
t
ORDER BY
t ASC
SETTINGS skip_unavailable_shards = 1
)
SELECT
AVG(new_part_count) AS new_parts_per_minute,
new_parts_per_minute / 60 AS new_parts_per_second
FROM
PER_MINUTE
Replace 'your_table' with the actual table name you want to monitor.
SELECT
type,
event_time,
initial_query_id,
formatReadableSize(memory_usage) AS memory,
`ProfileEvents.Values`[indexOf(`ProfileEvents.Names`, 'UserTimeMicroseconds')] AS userCPU,
`ProfileEvents.Values`[indexOf(`ProfileEvents.Names`, 'SystemTimeMicroseconds')] AS systemCPU,
normalizedQueryHash(query) AS normalized_query_hash
FROM clusterAllReplicas(default, merge(system, '^query_log'))
ORDER BY memory_usage DESC
LIMIT 10
Find the most frequently executed queries (useful for identifying which queries to optimize):
SELECT
normalizedQueryHash(query) AS query_hash,
count() AS execution_count,
any(query) AS example_query
FROM clusterAllReplicas(default, merge(system, '^query_log'))
WHERE event_date >= today() - 1
GROUP BY normalizedQueryHash(query)
ORDER BY execution_count DESC
LIMIT 20
SELECT
event_date,
event_type,
table,
error,
COUNT() AS error_count
FROM clusterAllReplicas(default, merge(system, '^part_log'))
WHERE database = 'default'
GROUP BY
event_date,
event_type,
error,
table
ORDER BY
event_date DESC,
error_count DESC
SELECT
hostName() AS host,
count() AS table_count
FROM clusterAllReplicas('default', merge(system, '^tables'))
WHERE database = 'default'
GROUP BY hostName()
ORDER BY table_count DESC
SELECT
event_date,
count() AS total_count,
sum(if(query LIKE '%async%', 1, 0)) AS async_count,
sum(if(query LIKE '%INSERT%', 1, 0)) AS insert_count
FROM clusterAllReplicas(default, merge(system, '^query_log'))
WHERE event_date >= today() - 7
GROUP BY event_date
ORDER BY event_date DESC
See the number of active parts per table across the cluster:
SELECT
database,
table,
count() AS part_count,
formatReadableSize(sum(bytes_on_disk)) AS total_size
FROM clusterAllReplicas(default, system.parts)
WHERE active = 1 AND database = 'default'
GROUP BY database, table
ORDER BY part_count DESC
Find partitions that may have too many parts (which can impact query performance):
SELECT
database,
table,
partition,
count() AS part_count,
formatReadableSize(sum(bytes_on_disk)) AS total_size
FROM clusterAllReplicas(default, system.parts)
WHERE active = 1
GROUP BY database, table, partition
HAVING part_count > 100
ORDER BY part_count DESC
Check for detached parts that might need investigation:
SELECT
database,
table,
partition_id,
name,
reason,
count()
FROM clusterAllReplicas(default, system.detached_parts)
GROUP BY database, table, partition_id, name, reason
ORDER BY database, table
SELECT
hostName() AS host,
formatReadableSize(max(memory_usage)) AS peak_memory,
formatReadableSize(avg(memory_usage)) AS avg_memory,
formatReadableSize(min(memory_usage)) AS min_memory
FROM clusterAllReplicas(default, merge(system, '^query_log'))
WHERE event_date >= today() - 1
GROUP BY hostName()
ORDER BY peak_memory DESC
SELECT
hostName() AS host,
initial_user,
query_id,
elapsed,
read_rows,
formatReadableSize(memory_usage) AS memory_usage,
normalizedQueryHash(query) AS query_hash
FROM clusterAllReplicas(default, system.processes)
ORDER BY elapsed DESC
For replicated tables, check the replication queue:
SELECT
hostName() AS host,
database,
table,
count() AS queue_size,
sum(if(is_currently_executing = 1, 1, 0)) AS executing_count
FROM clusterAllReplicas(default, system.replication_queue)
GROUP BY hostName(), database, table
HAVING queue_size > 0
ORDER BY queue_size DESC
