27.2. The Cumulative Statistics System (original) (raw)

PostgreSQL's cumulative statistics system supports collection and reporting of information about server activity. Presently, accesses to tables and indexes in both disk-block and individual-row terms are counted. The total number of rows in each table, and information about vacuum and analyze actions for each table are also counted. If enabled, calls to user-defined functions and the total time spent in each one are counted as well.

PostgreSQL also supports reporting dynamic information about exactly what is going on in the system right now, such as the exact command currently being executed by other server processes, and which other connections exist in the system. This facility is independent of the cumulative statistics system.

27.2.1. Statistics Collection Configuration #

Since collection of statistics adds some overhead to query execution, the system can be configured to collect or not collect information. This is controlled by configuration parameters that are normally set in postgresql.conf. (See Chapter 19 for details about setting configuration parameters.)

The parameter track_activities enables monitoring of the current command being executed by any server process.

The parameter track_counts controls whether cumulative statistics are collected about table and index accesses.

The parameter track_functions enables tracking of usage of user-defined functions.

The parameter track_io_timing enables monitoring of block read, write, extend, and fsync times.

The parameter track_wal_io_timing enables monitoring of WAL write and fsync times.

Normally these parameters are set in postgresql.conf so that they apply to all server processes, but it is possible to turn them on or off in individual sessions using the SET command. (To prevent ordinary users from hiding their activity from the administrator, only superusers are allowed to change these parameters with SET.)

Cumulative statistics are collected in shared memory. Every PostgreSQL process collects statistics locally, then updates the shared data at appropriate intervals. When a server, including a physical replica, shuts down cleanly, a permanent copy of the statistics data is stored in the pg_stat subdirectory, so that statistics can be retained across server restarts. In contrast, when starting from an unclean shutdown (e.g., after an immediate shutdown, a server crash, starting from a base backup, and point-in-time recovery), all statistics counters are reset.

27.2.2. Viewing Statistics #

Several predefined views, listed in Table 27.1, are available to show the current state of the system. There are also several other views, listed in Table 27.2, available to show the accumulated statistics. Alternatively, one can build custom views using the underlying cumulative statistics functions, as discussed in Section 27.2.26.

When using the cumulative statistics views and functions to monitor collected data, it is important to realize that the information does not update instantaneously. Each individual server process flushes out accumulated statistics to shared memory just before going idle, but not more frequently than once per PGSTAT_MIN_INTERVAL milliseconds (1 second unless altered while building the server); so a query or transaction still in progress does not affect the displayed totals and the displayed information lags behind actual activity. However, current-query information collected by track_activities is always up-to-date.

Another important point is that when a server process is asked to display any of the accumulated statistics, accessed values are cached until the end of its current transaction in the default configuration. So the statistics will show static information as long as you continue the current transaction. Similarly, information about the current queries of all sessions is collected when any such information is first requested within a transaction, and the same information will be displayed throughout the transaction. This is a feature, not a bug, because it allows you to perform several queries on the statistics and correlate the results without worrying that the numbers are changing underneath you. When analyzing statistics interactively, or with expensive queries, the time delta between accesses to individual statistics can lead to significant skew in the cached statistics. To minimize skew, stats_fetch_consistency can be set to snapshot, at the price of increased memory usage for caching not-needed statistics data. Conversely, if it's known that statistics are only accessed once, caching accessed statistics is unnecessary and can be avoided by setting stats_fetch_consistency to none. You can invoke pg_stat_clear_snapshot() to discard the current transaction's statistics snapshot or cached values (if any). The next use of statistical information will (when in snapshot mode) cause a new snapshot to be built or (when in cache mode) accessed statistics to be cached.

A transaction can also see its own statistics (not yet flushed out to the shared memory statistics) in the views pg_stat_xact_all_tables, pg_stat_xact_sys_tables, pg_stat_xact_user_tables, and pg_stat_xact_user_functions. These numbers do not act as stated above; instead they update continuously throughout the transaction.

Some of the information in the dynamic statistics views shown in Table 27.1 is security restricted. Ordinary users can only see all the information about their own sessions (sessions belonging to a role that they are a member of). In rows about other sessions, many columns will be null. Note, however, that the existence of a session and its general properties such as its sessions user and database are visible to all users. Superusers and roles with privileges of built-in role pg_read_all_stats (see also Section 21.5) can see all the information about all sessions.

Table 27.1. Dynamic Statistics Views

Table 27.2. Collected Statistics Views

The per-index statistics are particularly useful to determine which indexes are being used and how effective they are.

The pg_stat_io and pg_statio_ set of views are useful for determining the effectiveness of the buffer cache. They can be used to calculate a cache hit ratio. Note that while PostgreSQL's I/O statistics capture most instances in which the kernel was invoked in order to perform I/O, they do not differentiate between data which had to be fetched from disk and that which already resided in the kernel page cache. Users are advised to use the PostgreSQL statistics views in combination with operating system utilities for a more complete picture of their database's I/O performance.

27.2.3. pg_stat_activity #

The pg_stat_activity view will have one row per server process, showing information related to the current activity of that process.

Table 27.3. pg_stat_activity View

Note

The wait_event and state columns are independent. If a backend is in the active state, it may or may not be waiting on some event. If the state is active and wait_event is non-null, it means that a query is being executed, but is being blocked somewhere in the system.

Table 27.4. Wait Event Types

Table 27.5. Wait Events of Type Activity

Table 27.6. Wait Events of Type Bufferpin

Table 27.7. Wait Events of Type Client

Table 27.8. Wait Events of Type Extension

Table 27.9. Wait Events of Type Io

Table 27.10. Wait Events of Type Ipc

Table 27.11. Wait Events of Type Lock

Table 27.12. Wait Events of Type Lwlock

Table 27.13. Wait Events of Type Timeout

Here are examples of how wait events can be viewed:

SELECT pid, wait_event_type, wait_event FROM pg_stat_activity WHERE wait_event is NOT NULL; pid | wait_event_type | wait_event ------+-----------------+------------ 2540 | Lock | relation 6644 | LWLock | ProcArray (2 rows)

SELECT a.pid, a.wait_event, w.description FROM pg_stat_activity a JOIN pg_wait_events w ON (a.wait_event_type = w.type AND a.wait_event = w.name) WHERE a.wait_event is NOT NULL and a.state = 'active'; -[ RECORD 1 ]------------------------------------------------------​------------ pid | 686674 wait_event | WALInitSync description | Waiting for a newly initialized WAL file to reach durable storage

Note

Extensions can add Extension, InjectionPoint. and LWLock events to the lists shown in Table 27.8 and Table 27.12. In some cases, the name of an LWLock assigned by an extension will not be available in all server processes. It might be reported as just “extension” rather than the extension-assigned name.

27.2.4. pg_stat_replication #

The pg_stat_replication view will contain one row per WAL sender process, showing statistics about replication to that sender's connected standby server. Only directly connected standbys are listed; no information is available about downstream standby servers.

Table 27.14. pg_stat_replication View

The lag times reported in the pg_stat_replication view are measurements of the time taken for recent WAL to be written, flushed and replayed and for the sender to know about it. These times represent the commit delay that was (or would have been) introduced by each synchronous commit level, if the remote server was configured as a synchronous standby. For an asynchronous standby, the replay_lag column approximates the delay before recent transactions became visible to queries. If the standby server has entirely caught up with the sending server and there is no more WAL activity, the most recently measured lag times will continue to be displayed for a short time and then show NULL.

Lag times work automatically for physical replication. Logical decoding plugins may optionally emit tracking messages; if they do not, the tracking mechanism will simply display NULL lag.

Note

The reported lag times are not predictions of how long it will take for the standby to catch up with the sending server assuming the current rate of replay. Such a system would show similar times while new WAL is being generated, but would differ when the sender becomes idle. In particular, when the standby has caught up completely, pg_stat_replication shows the time taken to write, flush and replay the most recent reported WAL location rather than zero as some users might expect. This is consistent with the goal of measuring synchronous commit and transaction visibility delays for recent write transactions. To reduce confusion for users expecting a different model of lag, the lag columns revert to NULL after a short time on a fully replayed idle system. Monitoring systems should choose whether to represent this as missing data, zero or continue to display the last known value.

27.2.5. pg_stat_replication_slots #

The pg_stat_replication_slots view will contain one row per logical replication slot, showing statistics about its usage.

Table 27.15. pg_stat_replication_slots View

27.2.6. pg_stat_wal_receiver #

The pg_stat_wal_receiver view will contain only one row, showing statistics about the WAL receiver from that receiver's connected server.

Table 27.16. pg_stat_wal_receiver View

27.2.7. pg_stat_recovery_prefetch #

The pg_stat_recovery_prefetch view will contain only one row. The columns wal_distance, block_distance and io_depth show current values, and the other columns show cumulative counters that can be reset with the pg_stat_reset_shared function.

Table 27.17. pg_stat_recovery_prefetch View

27.2.8. pg_stat_subscription #

Table 27.18. pg_stat_subscription View

27.2.9. pg_stat_subscription_stats #

The pg_stat_subscription_stats view will contain one row per subscription.

Table 27.19. pg_stat_subscription_stats View

27.2.10. pg_stat_ssl #

The pg_stat_ssl view will contain one row per backend or WAL sender process, showing statistics about SSL usage on this connection. It can be joined to pg_stat_activity or pg_stat_replication on the pid column to get more details about the connection.

Table 27.20. pg_stat_ssl View

27.2.11. pg_stat_gssapi #

The pg_stat_gssapi view will contain one row per backend, showing information about GSSAPI usage on this connection. It can be joined to pg_stat_activity or pg_stat_replication on the pid column to get more details about the connection.

Table 27.21. pg_stat_gssapi View

27.2.12. pg_stat_archiver #

The pg_stat_archiver view will always have a single row, containing data about the archiver process of the cluster.

Table 27.22. pg_stat_archiver View

Normally, WAL files are archived in order, oldest to newest, but that is not guaranteed, and does not hold under special circumstances like when promoting a standby or after crash recovery. Therefore it is not safe to assume that all files older than last_archived_wal have also been successfully archived.

27.2.13. pg_stat_io #

The pg_stat_io view will contain one row for each combination of backend type, target I/O object, and I/O context, showing cluster-wide I/O statistics. Combinations which do not make sense are omitted.

Currently, I/O on relations (e.g. tables, indexes) is tracked. However, relation I/O which bypasses shared buffers (e.g. when moving a table from one tablespace to another) is currently not tracked.

Table 27.23. pg_stat_io View

Some backend types never perform I/O operations on some I/O objects and/or in some I/O contexts. These rows are omitted from the view. For example, the checkpointer does not checkpoint temporary tables, so there will be no rows for backend_type checkpointer and object temp relation.

In addition, some I/O operations will never be performed either by certain backend types or on certain I/O objects and/or in certain I/O contexts. These cells will be NULL. For example, temporary tables are not fsynced, so fsyncs will be NULL for object temp relation. Also, the background writer does not perform reads, so reads will be NULL in rows for backend_type background writer.

pg_stat_io can be used to inform database tuning. For example:

• A high evictions count can indicate that shared buffers should be increased.
• Client backends rely on the checkpointer to ensure data is persisted to permanent storage. Large numbers of fsyncs by client backends could indicate a misconfiguration of shared buffers or of the checkpointer. More information on configuring the checkpointer can be found in Section 28.5.
• Normally, client backends should be able to rely on auxiliary processes like the checkpointer and the background writer to write out dirty data as much as possible. Large numbers of writes by client backends could indicate a misconfiguration of shared buffers or of the checkpointer. More information on configuring the checkpointer can be found in Section 28.5.

Note

Columns tracking I/O time will only be non-zero when track_io_timing is enabled. The user should be careful when referencing these columns in combination with their corresponding I/O operations in case track_io_timing was not enabled for the entire time since the last stats reset.

27.2.14. pg_stat_bgwriter #

The pg_stat_bgwriter view will always have a single row, containing data about the background writer of the cluster.

Table 27.24. pg_stat_bgwriter View

27.2.15. pg_stat_checkpointer #

The pg_stat_checkpointer view will always have a single row, containing data about the checkpointer process of the cluster.

Table 27.25. pg_stat_checkpointer View

27.2.16. pg_stat_wal #

The pg_stat_wal view will always have a single row, containing data about WAL activity of the cluster.

Table 27.26. pg_stat_wal View

27.2.17. pg_stat_database #

The pg_stat_database view will contain one row for each database in the cluster, plus one for shared objects, showing database-wide statistics.

Table 27.27. pg_stat_database View

27.2.18. pg_stat_database_conflicts #

The pg_stat_database_conflicts view will contain one row per database, showing database-wide statistics about query cancels occurring due to conflicts with recovery on standby servers. This view will only contain information on standby servers, since conflicts do not occur on primary servers.

Table 27.28. pg_stat_database_conflicts View

27.2.19. pg_stat_all_tables #

The pg_stat_all_tables view will contain one row for each table in the current database (including TOAST tables), showing statistics about accesses to that specific table. The pg_stat_user_tables and pg_stat_sys_tables views contain the same information, but filtered to only show user and system tables respectively.

Table 27.29. pg_stat_all_tables View

27.2.20. pg_stat_all_indexes #

The pg_stat_all_indexes view will contain one row for each index in the current database, showing statistics about accesses to that specific index. The pg_stat_user_indexes and pg_stat_sys_indexes views contain the same information, but filtered to only show user and system indexes respectively.

Table 27.30. pg_stat_all_indexes View

Indexes can be used by simple index scans, “bitmap” index scans, and the optimizer. In a bitmap scan the output of several indexes can be combined via AND or OR rules, so it is difficult to associate individual heap row fetches with specific indexes when a bitmap scan is used. Therefore, a bitmap scan increments the pg_stat_all_indexes.idx_tup_read count(s) for the index(es) it uses, and it increments the pg_stat_all_tables.idx_tup_fetch count for the table, but it does not affect pg_stat_all_indexes.idx_tup_fetch. The optimizer also accesses indexes to check for supplied constants whose values are outside the recorded range of the optimizer statistics because the optimizer statistics might be stale.

Note

The idx_tup_read and idx_tup_fetch counts can be different even without any use of bitmap scans, because idx_tup_read counts index entries retrieved from the index while idx_tup_fetch counts live rows fetched from the table. The latter will be less if any dead or not-yet-committed rows are fetched using the index, or if any heap fetches are avoided by means of an index-only scan.

Note

Queries that use certain SQL constructs to search for rows matching any value out of a list or array of multiple scalar values (see Section 9.25) perform multiple “primitive” index scans (up to one primitive scan per scalar value) during query execution. Each internal primitive index scan increments pg_stat_all_indexes.idx_scan, so it's possible for the count of index scans to significantly exceed the total number of index scan executor node executions.

27.2.21. pg_statio_all_tables #

The pg_statio_all_tables view will contain one row for each table in the current database (including TOAST tables), showing statistics about I/O on that specific table. The pg_statio_user_tables and pg_statio_sys_tables views contain the same information, but filtered to only show user and system tables respectively.

Table 27.31. pg_statio_all_tables View

27.2.22. pg_statio_all_indexes #

The pg_statio_all_indexes view will contain one row for each index in the current database, showing statistics about I/O on that specific index. The pg_statio_user_indexes and pg_statio_sys_indexes views contain the same information, but filtered to only show user and system indexes respectively.

Table 27.32. pg_statio_all_indexes View

27.2.23. pg_statio_all_sequences #

The pg_statio_all_sequences view will contain one row for each sequence in the current database, showing statistics about I/O on that specific sequence.

Table 27.33. pg_statio_all_sequences View

27.2.24. pg_stat_user_functions #

The pg_stat_user_functions view will contain one row for each tracked function, showing statistics about executions of that function. The track_functions parameter controls exactly which functions are tracked.

Table 27.34. pg_stat_user_functions View

27.2.25. pg_stat_slru #

PostgreSQL accesses certain on-disk information via SLRU (simple least-recently-used) caches. The pg_stat_slru view will contain one row for each tracked SLRU cache, showing statistics about access to cached pages.

For each SLRU cache that's part of the core server, there is a configuration parameter that controls its size, with the suffix _buffers appended.

Table 27.35. pg_stat_slru View

27.2.26. Statistics Functions #

Other ways of looking at the statistics can be set up by writing queries that use the same underlying statistics access functions used by the standard views shown above. For details such as the functions' names, consult the definitions of the standard views. (For example, in psql you could issue \d+ pg_stat_activity.) The access functions for per-database statistics take a database OID as an argument to identify which database to report on. The per-table and per-index functions take a table or index OID. The functions for per-function statistics take a function OID. Note that only tables, indexes, and functions in the current database can be seen with these functions.

Additional functions related to the cumulative statistics system are listed in Table 27.36.

Table 27.36. Additional Statistics Functions

Warning

Using pg_stat_reset() also resets counters that autovacuum uses to determine when to trigger a vacuum or an analyze. Resetting these counters can cause autovacuum to not perform necessary work, which can cause problems such as table bloat or out-dated table statistics. A database-wide ANALYZE is recommended after the statistics have been reset.

pg_stat_get_activity, the underlying function of the pg_stat_activity view, returns a set of records containing all the available information about each backend process. Sometimes it may be more convenient to obtain just a subset of this information. In such cases, another set of per-backend statistics access functions can be used; these are shown in Table 27.37. These access functions use the session's backend ID number, which is a small integer (>= 0) that is distinct from the backend ID of any concurrent session, although a session's ID can be recycled as soon as it exits. The backend ID is used, among other things, to identify the session's temporary schema if it has one. The function pg_stat_get_backend_idset provides a convenient way to list all the active backends' ID numbers for invoking these functions. For example, to show the PIDs and current queries of all backends:

SELECT pg_stat_get_backend_pid(backendid) AS pid, pg_stat_get_backend_activity(backendid) AS query FROM pg_stat_get_backend_idset() AS backendid;

Table 27.37. Per-Backend Statistics Functions