Query system data
InfluxDB Clustered stores data related to queries, tables, partitions, and compaction in system tables within your cluster. System tables contain time series data used by and generated from the InfluxDB Clustered internal monitoring system. You can query the cluster system tables for information about your cluster.
May impact cluster performance
Querying InfluxDB 3 system tables may impact write and query performance of your InfluxDB cluster. Use filters to optimize queries to reduce impact to your cluster.
System tables are subject to change
System tables are not part of InfluxDB’s stable API and may change with new releases. The provided schema information and query examples are valid as of September 18, 2024. If you detect a schema change or a non-functioning query example, please submit an issue.
Query system tables
Querying system tables with influxctl requires influxctl v2.8.0 or newer.
Use the influxctl query command
and SQL to query system tables.
Provide the following:
- Enable system tables with the - --enable-system-tablescommand flag.
- Database token: A database token with read permissions on the specified database. Uses the - tokensetting from the- influxctlconnection profile or the- --tokencommand flag.
- Database name: The name of the database to query information about. Uses the - databasesetting from the- influxctlconnection profile or the- --databasecommand flag.
- SQL query: The SQL query to execute. - Pass the query in one of the following ways: - a string on the command line
- a path to a file that contains the query
- a single dash (-) to read the query from stdin
 
influxctl query \
  --enable-system-tables \
  --database DATABASE_NAME \
  --token DATABASE_TOKEN \
  "SQL_QUERY"influxctl query \
  --enable-system-tables \
  --database DATABASE_NAME \
  --token DATABASE_TOKEN \
  /path/to/query.sqlcat ./query.sql | influxctl query \
  --enable-system-tables \
  --database DATABASE_NAME \
  --token DATABASE_TOKEN \
  - Replace the following:
- DATABASE_TOKEN: A database token with read access to the specified database
- DATABASE_NAME: The name of the database to query information about.
- SQL_QUERY: The SQL query to execute. For examples, see System query examples.
When prompted, enter y to acknowledge the potential impact querying system
tables may have on your cluster.
Optimize queries to reduce impact to your cluster
Querying InfluxDB 3 system tables may impact the performance of your InfluxDB cluster. As you write data to a cluster, the number of partitions and Parquet files can increase to a point that impacts system table performance. Queries that took milliseconds with fewer files and partitions might take 10 seconds or longer as files and partitions increase.
Use the following filters to optimize your system table queries and reduce the impact on your cluster’s performance.
In your queries, replace the following:
- TABLE_NAME: the table to retrieve partitions for
- PARTITION_ID: a partition ID (int64)
- PARTITION_KEY: a partition key derived from the table’s partition template. The default format is- %Y-%m-%d(for example,- 2024-01-01).
Filter by table name
When querying the system.tables, system.partitions, or system.compactor tables, use the
WHERE clause to filter by table_name .
SELECT * FROM system.partitions WHERE table_name = 'TABLE_NAME'Filter by partition key
When querying the system.partitions or system.compactor tables, use the WHERE clause to
filter by partition_key.
SELECT * FROM system.partitions WHERE partition_key = 'PARTITION_KEY'To further improve performance, use AND to pair partition_key with table_name–for example:
SELECT * 
FROM system.partitions 
WHERE
  table_name = 'TABLE_NAME' 
    AND partition_key = 'PARTITION_KEY';SELECT * 
FROM system.compactor
WHERE
  table_name = 'TABLE_NAME' 
    AND partition_key = 'PARTITION_KEY';Filter by partition ID
When querying the system.partitions or system.compactor table, use the WHERE clause to
filter by partition_id .
SELECT * FROM system.partitions WHERE partition_id = PARTITION_IDFor the most optimized approach, use AND to pair partition_id with table_name–for example:
SELECT * 
FROM system.partitions 
WHERE
  table_name = 'TABLE_NAME' 
    AND partition_id = PARTITION_ID;Although you don’t need to pair partition_id with table_name (because a partition ID is unique within a cluster),
it’s the most optimized approach, especially when you have many tables in a database.
Retrieve a partition ID
To retrieve a partition ID, query system.partitions for a table_name and partition_key pair–for example:
SELECT
  table_name,
  partition_key,
  partition_id 
FROM system.partitions
WHERE
  table_name = 'TABLE_NAME'
    AND partition_key = 'PARTITION_KEY';The result contains the partition_id:
| table_name | partition_key | partition_id | 
|---|---|---|
| weather | 43 | 2020-05-27 | 1362 | 
Combine filters for performance improvement
Use the AND, OR, or IN keywords to combine filters in your query.
- Use - ORor- INconditions when filtering for different values in the same column–for example:- WHERE partition_id = 1 OR partition_id = 2- Use - INto make multiple- ORconditions more readable–for example:- WHERE table_name IN ('foo', 'bar', 'baz')
- Avoid mixing different columns in - ORconditions, as this won’t improve performance–for example:- WHERE table_name = 'foo' OR partition_id = 2 -- This will not improve performance
System tables
System tables are subject to change.
Understanding system table data distribution
Data in system.tables, system.partitions, and system.compactor includes
data for all InfluxDB Queriers in your cluster.
The data comes from the catalog, and because all the queriers share one catalog,
the results from these three tables derive from the same source data,
regardless of which querier you connect to.
However, the system.queries table is different–data is local to each Querier.
system.queries contains a non-persisted log of queries run against the current
querier to which your query is routed.
The query log is specific to the current Querier and isn’t shared across
queriers in your cluster.
Logs are scoped to the specified database.
system.queries
The system.queries table stores log entries for queries executed for the provided namespace (database) on the node that is currently handling queries.
system.queries reflects a process-local, in-memory, namespace-scoped query log.
While this table may be useful for debugging and monitoring queries, keep the following in mind:
- Records stored in system.queriesare transient and volatile- InfluxDB deletes system.queriesrecords during pod restarts.
- Queries for one namespace can evict records from another namespace.
 
- InfluxDB deletes 
- Data reflects the state of a specific pod answering queries for the namespace.- Data isn’t shared across queriers in your cluster.
- A query for records in system.queriescan return different results depending on the pod the request was routed to.
 
When listing measurements (tables) available within a namespace,
some clients and query tools may include the queries table in the list of
namespace tables.
system.tables
The system.tables table contains information about tables in the specified database.
system.partitions
The system.partitions table contains information about partitions associated
with the specified database.
system.compactor
The system.compactor table contains information about compacted partition Parquet
files associated with the specified database.
System query examples
May impact cluster performance
Querying InfluxDB 3 system tables may impact write and query performance of your InfluxDB cluster.
The examples in this section include WHERE filters to optimize queries and reduce impact to your cluster.
In the examples below, replace TABLE_NAME
with the name of the table you want to query information about.
Query logs
View all stored query logs
SELECT * FROM system.queriesView query logs for queries with end-to-end durations above a threshold
The following returns query logs for queries with an end-to-end duration greater than 50 milliseconds.
SELECT *
FROM
  system.queries
WHERE
  end2end_duration::BIGINT > (50 * 1000000)View query logs for a specific query within a time interval
SELECT *
FROM system.queries
WHERE issue_time >= now() - INTERVAL '1 day'
  AND query_text LIKE '%select * from home%'from influxdb_client_3 import InfluxDBClient3
client = InfluxDBClient3(token = DATABASE_TOKEN,
                          host = HOSTNAME,
                          org = '',
                          database=DATABASE_NAME)
client.query('select * from home')
reader = client.query('''
                      SELECT *
                      FROM system.queries
                      WHERE issue_time >= now() - INTERVAL '1 day'
                      AND query_text LIKE '%select * from home%'
                      ''',
                    language='sql',
                    headers=[(b"iox-debug", b"true")],
                    mode="reader")Partitions
View the partition template of a specific table
SELECT *
FROM
  system.tables
WHERE
  table_name = 'TABLE_NAME'View all partitions for a table
SELECT *
FROM
  system.partitions
WHERE
  table_name = 'TABLE_NAME'View the number of partitions per table
SELECT
  table_name,
  COUNT(*) AS partition_count
FROM
  system.partitions
WHERE
  table_name IN ('foo', 'bar', 'baz')
GROUP BY
  table_nameView the number of partitions for a specific table
SELECT
  COUNT(*) AS partition_count
FROM
  system.partitions
WHERE
  table_name = 'TABLE_NAME'Storage usage
View the size in megabytes of a specific table
SELECT
  SUM(total_size_mb) AS total_size_mb
FROM
  system.partitions
WHERE
  table_name = 'TABLE_NAME'View the size in megabytes per table
SELECT
  table_name,
  SUM(total_size_mb) AS total_size_mb
FROM
  system.partitions
WHERE
  table_name IN ('foo', 'bar', 'baz')
GROUP BY
  table_nameView the total size in bytes of compacted partitions per table
SELECT
  table_name,
  SUM(total_l0_bytes) + SUM(total_l1_bytes) + SUM(total_l2_bytes) AS total_bytes
FROM
  system.compactor
WHERE
  table_name IN ('foo', 'bar', 'baz')
GROUP BY
  table_nameView the total size in bytes of compacted partitions for a specific table
SELECT
  SUM(total_l0_bytes) + SUM(total_l1_bytes) + SUM(total_l2_bytes) AS total_bytes
FROM
  system.compactor
WHERE
  table_name = 'TABLE_NAME'Compaction
View compaction totals for each table
SELECT
  table_name,
  SUM(total_l0_files) AS total_l0_files,
  SUM(total_l1_files) AS total_l1_files,
  SUM(total_l2_files) AS total_l2_files,
  SUM(total_l0_bytes) AS total_l0_bytes,
  SUM(total_l1_bytes) AS total_l1_bytes,
  SUM(total_l2_bytes) AS total_l2_bytes
FROM
  system.compactor
WHERE
  table_name IN ('foo', 'bar', 'baz')
GROUP BY
  table_nameView compaction totals for a specific table
SELECT
  SUM(total_l0_files) AS total_l0_files,
  SUM(total_l1_files) AS total_l1_files,
  SUM(total_l2_files) AS total_l2_files,
  SUM(total_l0_bytes) AS total_l0_bytes,
  SUM(total_l1_bytes) AS total_l1_bytes,
  SUM(total_l2_bytes) AS total_l2_bytes
FROM
  system.compactor
WHERE
  table_name = 'TABLE_NAME'Was this page helpful?
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