queries.yaml

pg_replication:
  query: "SELECT CASE WHEN NOT pg_is_in_recovery() THEN 0 ELSE GREATEST (0, EXTRACT(EPOCH FROM (now() - pg_last_xact_replay_timestamp()))) END AS lag"
  master: true
  metrics:
    - lag:
        usage: "GAUGE"
        description: "Replication lag behind master in seconds"

pg_postmaster:
  query: "SELECT pg_postmaster_start_time as start_time_seconds from pg_postmaster_start_time()"
  master: true
  metrics:
    - start_time_seconds:
        usage: "GAUGE"
        description: "Time at which postmaster started"

pg_stat_user_tables:
  query: |
   SELECT
     current_database() datname,
     schemaname,
     relname,
     seq_scan,
     seq_tup_read,
     idx_scan,
     idx_tup_fetch,
     n_tup_ins,
     n_tup_upd,
     n_tup_del,
     n_tup_hot_upd,
     n_live_tup,
     n_dead_tup,
     n_mod_since_analyze,
     COALESCE(last_vacuum, '1970-01-01Z') as last_vacuum,
     COALESCE(last_autovacuum, '1970-01-01Z') as last_autovacuum,
     COALESCE(last_analyze, '1970-01-01Z') as last_analyze,
     COALESCE(last_autoanalyze, '1970-01-01Z') as last_autoanalyze,
     vacuum_count,
     autovacuum_count,
     analyze_count,
     autoanalyze_count
   FROM
     pg_stat_user_tables
  metrics:
    - datname:
        usage: "LABEL"
        description: "Name of current database"
    - schemaname:
        usage: "LABEL"
        description: "Name of the schema that this table is in"
    - relname:
        usage: "LABEL"
        description: "Name of this table"
    - seq_scan:
        usage: "COUNTER"
        description: "Number of sequential scans initiated on this table"
    - seq_tup_read:
        usage: "COUNTER"
        description: "Number of live rows fetched by sequential scans"
    - idx_scan:
        usage: "COUNTER"
        description: "Number of index scans initiated on this table"
    - idx_tup_fetch:
        usage: "COUNTER"
        description: "Number of live rows fetched by index scans"
    - n_tup_ins:
        usage: "COUNTER"
        description: "Number of rows inserted"
    - n_tup_upd:
        usage: "COUNTER"
        description: "Number of rows updated"
    - n_tup_del:
        usage: "COUNTER"
        description: "Number of rows deleted"
    - n_tup_hot_upd:
        usage: "COUNTER"
        description: "Number of rows HOT updated (i.e., with no separate index update required)"
    - n_live_tup:
        usage: "GAUGE"
        description: "Estimated number of live rows"
    - n_dead_tup:
        usage: "GAUGE"
        description: "Estimated number of dead rows"
    - n_mod_since_analyze:
        usage: "GAUGE"
        description: "Estimated number of rows changed since last analyze"
    - last_vacuum:
        usage: "GAUGE"
        description: "Last time at which this table was manually vacuumed (not counting VACUUM FULL)"
    - last_autovacuum:
        usage: "GAUGE"
        description: "Last time at which this table was vacuumed by the autovacuum daemon"
    - last_analyze:
        usage: "GAUGE"
        description: "Last time at which this table was manually analyzed"
    - last_autoanalyze:
        usage: "GAUGE"
        description: "Last time at which this table was analyzed by the autovacuum daemon"
    - vacuum_count:
        usage: "COUNTER"
        description: "Number of times this table has been manually vacuumed (not counting VACUUM FULL)"
    - autovacuum_count:
        usage: "COUNTER"
        description: "Number of times this table has been vacuumed by the autovacuum daemon"
    - analyze_count:
        usage: "COUNTER"
        description: "Number of times this table has been manually analyzed"
    - autoanalyze_count:
        usage: "COUNTER"
        description: "Number of times this table has been analyzed by the autovacuum daemon"

pg_statio_user_tables:
  query: "SELECT current_database() datname, schemaname, relname, heap_blks_read, heap_blks_hit, idx_blks_read, idx_blks_hit, toast_blks_read, toast_blks_hit, tidx_blks_read, tidx_blks_hit FROM pg_statio_user_tables"
  metrics:
    - datname:
        usage: "LABEL"
        description: "Name of current database"
    - schemaname:
        usage: "LABEL"
        description: "Name of the schema that this table is in"
    - relname:
        usage: "LABEL"
        description: "Name of this table"
    - heap_blks_read:
        usage: "COUNTER"
        description: "Number of disk blocks read from this table"
    - heap_blks_hit:
        usage: "COUNTER"
        description: "Number of buffer hits in this table"
    - idx_blks_read:
        usage: "COUNTER"
        description: "Number of disk blocks read from all indexes on this table"
    - idx_blks_hit:
        usage: "COUNTER"
        description: "Number of buffer hits in all indexes on this table"
    - toast_blks_read:
        usage: "COUNTER"
        description: "Number of disk blocks read from this table's TOAST table (if any)"
    - toast_blks_hit:
        usage: "COUNTER"
        description: "Number of buffer hits in this table's TOAST table (if any)"
    - tidx_blks_read:
        usage: "COUNTER"
        description: "Number of disk blocks read from this table's TOAST table indexes (if any)"
    - tidx_blks_hit:
        usage: "COUNTER"
        description: "Number of buffer hits in this table's TOAST table indexes (if any)"

#
# WARNING: 
#   This set of metrics can be very expensive on a busy server as every
#   unique query executed will create an additional time series
#
# pg_stat_statements:
#   query: |
#     SELECT
#       pg_get_userbyid(userid) as user,
#       pg_database.datname,
#       pg_stat_statements.queryid,
#       pg_stat_statements.calls as calls_total,
#       pg_stat_statements.total_time / 1000.0 as seconds_total,
#       pg_stat_statements.rows as rows_total,
#       pg_stat_statements.blk_read_time / 1000.0 as block_read_seconds_total,
#       pg_stat_statements.blk_write_time / 1000.0 as block_write_seconds_total
#       FROM pg_stat_statements
#       JOIN pg_database
#         ON pg_database.oid = pg_stat_statements.dbid
#       WHERE
#         total_time > (
#           SELECT percentile_cont(0.1)
#             WITHIN GROUP (ORDER BY total_time)
#             FROM pg_stat_statements
#         )
#       ORDER BY seconds_total DESC
#       LIMIT 100
#   metrics:
#     - user:
#         usage: "LABEL"
#         description: "The user who executed the statement"
#     - datname:
#         usage: "LABEL"
#         description: "The database in which the statement was executed"
#     - queryid:
#         usage: "LABEL"
#         description: "Internal hash code, computed from the statement's parse tree"
#     - calls_total:
#         usage: "COUNTER"
#         description: "Number of times executed"
#     - seconds_total:
#         usage: "COUNTER"
#         description: "Total time spent in the statement, in seconds"
#     - rows_total:
#         usage: "COUNTER"
#         description: "Total number of rows retrieved or affected by the statement"
#     - block_read_seconds_total:
#         usage: "COUNTER"
#         description: "Total time the statement spent reading blocks, in seconds"
#     - block_write_seconds_total:
#         usage: "COUNTER"
#         description: "Total time the statement spent writing blocks, in seconds"

pg_process_idle:
  query: |
    WITH
      metrics AS (
        SELECT
          application_name,
          SUM(EXTRACT(EPOCH FROM (CURRENT_TIMESTAMP - state_change))::bigint)::float AS process_idle_seconds_sum,
          COUNT(*) AS process_idle_seconds_count
        FROM pg_stat_activity
        WHERE state = 'idle'
        GROUP BY application_name
      ),
      buckets AS (
        SELECT
          application_name,
          le,
          SUM(
            CASE WHEN EXTRACT(EPOCH FROM (CURRENT_TIMESTAMP - state_change)) <= le
              THEN 1
              ELSE 0
            END
          )::bigint AS bucket
        FROM
          pg_stat_activity,
          UNNEST(ARRAY[1, 2, 5, 15, 30, 60, 90, 120, 300]) AS le
        GROUP BY application_name, le
        ORDER BY application_name, le
      )
    SELECT
      application_name,
      process_idle_seconds_sum as seconds_sum,
      process_idle_seconds_count as seconds_count,
      ARRAY_AGG(le) AS seconds,
      ARRAY_AGG(bucket) AS seconds_bucket
    FROM metrics JOIN buckets USING (application_name)
    GROUP BY 1, 2, 3
  metrics:
    - application_name:
        usage: "LABEL"
        description: "Application Name"
    - seconds:
        usage: "HISTOGRAM"
        description: "Idle time of server processes"