Package: pg-extras
Python PG ExtrasPython port ofHeroku PG Extraswith several additions and improvements. The goal of this project is to provide powerful insights into the PostgreSQL database for Python apps that are not using the Heroku PostgreSQL plugin.Queries can be used to obtain information about a Postgres instance, that may be useful when analyzing performance issues. This includes information about locks, index usage, buffer cache hit ratios and vacuum statistics. Python API enables developers to easily integrate the tool into e.g. automatic monitoring tasks.You can check out this blog post for detailed step by step tutorial on how tooptimize PostgreSQL using PG Extras library.Alternative versions:RubyRuby on RailsNodeJSElixirHaskellInstallationpipinstallpg-extrasSome of the queries (e.g.,callsandoutliers) requirepg_stat_statementsextension enabled.You can check if it is enabled in your database by running:PGExtras.query('extensions')You should see the similar line in the output:|pg_stat_statements|1.7|1.7|trackexecutionstatisticsofallSQLstatementsexecuted|UsageGem expects theos.environ['DATABASE_URL']value in the following format:"postgresql://postgres:secret@localhost:5432/database_name"Alternatively you can pass it directly to the method:PGExtras.query('cache_hit',database_url="postgresql://postgres:secret@localhost:5432/database_name")You can run queries using a simple python API:frompg_extrasimportPGExtrasPGExtras.query('cache_hit')+----------------+------------------------+|Indexandtablehitrate|+----------------+------------------------+|name|ratio|+----------------+------------------------+|indexhitrate|0.97796610169491525424||tablehitrate|0.96724294813466787989|+----------------+------------------------+By default the ASCII table is displayed. Alternatively you can return the raw query object:result=PGExtras.query('cache_hit',output='raw')type(result)# => <class 'sqlalchemy.engine.result.ResultProxy'>result.keys()# => ['name', 'ratio']result.fetchall()# => [('index hit rate', Decimal('0.939...')), ('table hit rate', Decimal('0.986...'))]Available methodscache_hitPGExtras.query('cache_hit')name|ratio----------------+------------------------indexhitrate|0.99957765013541945832tablehitrate|1.00(2rows)This command provides information on the efficiency of the buffer cache, for both index reads (index hit rate) as well as table reads (table hit rate). A low buffer cache hit ratio can be a sign that the Postgres instance is too small for the workload.index_cache_hitPGExtras.query('index_cache_hit')|name|buffer_hits|block_reads|total_read|ratio|+-----------------------+-------------+-------------+------------+-------------------+|teams|187665|109|187774|0.999419514948821||subscriptions|5160|6|5166|0.99883855981417||plans|5718|9|5727|0.998428496595076|(truncatedresultsforbrevity)The same ascache_hitwith each table's indexes cache hit info displayed separately.table_cache_hitPGExtras.query('table_cache_hit')|name|buffer_hits|block_reads|total_read|ratio|+-----------------------+-------------+-------------+------------+-------------------+|plans|32123|2|32125|0.999937743190662||subscriptions|95021|8|95029|0.999915815172211||teams|171637|200|171837|0.99883610631005|(truncatedresultsforbrevity)The same ascache_hitwith each table's cache hit info displayed seperately.index_usagePGExtras.query('index_usage')relname|percent_of_times_index_used|rows_in_table---------------------+-----------------------------+---------------events|65|1217347app_infos|74|314057app_infos_user_info|0|198848user_info|5|94545delayed_jobs|27|0(5rows)This command provides information on the efficiency of indexes, represented as what percentage of total scans were index scans. A low percentage can indicate under indexing, or wrong data being indexed.locksPGExtras.query('locks')procpid|relname|transactionid|granted|query_snippet|mode|age---------+---------+---------------+---------+-----------------------+-------------------------------------31776|||t|<IDLE>intransaction|ExclusiveLock|00:19:29.83789831776||1294|t|<IDLE>intransaction|RowExclusiveLock|00:19:29.83789831912|||t|select*fromhello;|ExclusiveLock|00:19:17.942593443|||t|+|ExclusiveLock|00:00:00||||select+||||||pg_stat_activi||(4rows)This command displays queries that have taken out an exclusive lock on a relation. Exclusive locks typically prevent other operations on that relation from taking place, and can be a cause of "hung" queries that are waiting for a lock to be granted.all_locksPGExtras.query('all_locks')This command displays all the current locks, regardless of their type.outliersPGExtras.query('outliers')qry|exec_time|prop_exec_time|ncalls|sync_io_time-----------------------------------------+------------------+----------------+-------------+--------------SELECT*FROMarchivable_usage_events..|154:39:26.431466|72.2%|34,211,877|00:00:00COPYpublic.archivable_usage_events(..|50:38:33.198418|23.6%|13|13:34:21.00108COPYpublic.usage_events(id,reporte..|02:32:16.335233|1.2%|13|00:34:19.784318INSERTINTOusage_events(id,retaine..|01:42:59.436532|0.8%|12,328,187|00:00:00SELECT*FROMusage_eventsWHERE(alp..|01:18:10.754354|0.6%|102,114,301|00:00:00UPDATEusage_eventsSETreporter_id=..|00:52:35.683254|0.4%|23,786,348|00:00:00INSERTINTOusage_events(id,retaine..|00:49:24.952561|0.4%|21,988,201|00:00:00(truncatedresultsforbrevity)This command displays statements, obtained frompg_stat_statements, ordered by the amount of time to execute in aggregate. This includes the statement itself, the total execution time for that statement, the proportion of total execution time for all statements that statement has taken up, the number of times that statement has been called, and the amount of time that statement spent on synchronous I/O (reading/writing from the file system).Typically, an efficient query will have an appropriate ratio of calls to total execution time, with as little time spent on I/O as possible. Queries that have a high total execution time but low call count should be investigated to improve their performance. Queries that have a high proportion of execution time being spent on synchronous I/O should also be investigated.callsPGExtras.query('calls')qry|exec_time|prop_exec_time|ncalls|sync_io_time-----------------------------------------+------------------+----------------+-------------+--------------SELECT*FROMusage_eventsWHERE(alp..|01:18:11.073333|0.6%|102,120,780|00:00:00BEGIN|00:00:51.285988|0.0%|47,288,662|00:00:00COMMIT|00:00:52.31724|0.0%|47,288,615|00:00:00SELECT*FROMarchivable_usage_event..|154:39:26.431466|72.2%|34,211,877|00:00:00UPDATEusage_eventsSETreporter_id=..|00:52:35.986167|0.4%|23,788,388|00:00:00INSERTINTOusage_events(id,retaine..|00:49:25.260245|0.4%|21,990,326|00:00:00INSERTINTOusage_events(id,retaine..|01:42:59.436532|0.8%|12,328,187|00:00:00(truncatedresultsforbrevity)This command is much likepg:outliers, but ordered by the number of times a statement has been called.blockingPGExtras.query('blocking')blocked_pid|blocking_statement|blocking_duration|blocking_pid|blocked_statement|blocked_duration-------------+--------------------------+-------------------+--------------+------------------------------------------------------------------------------------+------------------461|selectcount(*)fromapp|00:00:03.838314|15682|UPDATE"app"SET"updated_at"='2013-03-04 15:07:04.746688'WHERE"id"=12823149|00:00:03.821826(1row)This command displays statements that are currently holding locks that other statements are waiting to be released. This can be used in conjunction withpg:locksto determine which statements need to be terminated in order to resolve lock contention.total_index_sizePGExtras.query('total_index_size')size-------28194MB(1row)This command displays the total size of all indexes on the database, in MB. It is calculated by taking the number of pages (reported inrelpages) and multiplying it by the page size (8192 bytes).index_sizePGExtras.query('index_size')name|size---------------------------------------------------------------+---------idx_activity_attemptable_and_type_lesson_enrollment|5196MBindex_enrollment_attemptables_by_attempt_and_last_in_group|4045MBindex_attempts_on_student_id|2611MBenrollment_activity_attemptables_pkey|2513MBindex_attempts_on_student_id_final_attemptable_type|2466MBattempts_pkey|2466MBindex_attempts_on_response_id|2404MBindex_attempts_on_enrollment_id|1957MBindex_enrollment_attemptables_by_enrollment_activity_id|1789MBenrollment_activities_pkey|458MB(truncatedresultsforbrevity)This command displays the size of each each index in the database, in MB. It is calculated by taking the number of pages (reported inrelpages) and multiplying it by the page size (8192 bytes).table_sizePGExtras.query('table_size')name|size---------------------------------------------------------------+---------learning_coaches|196MBstates|145MBgrade_levels|111MBcharities_customers|73MBcharities|66MB(truncatedresultsforbrevity)This command displays the size of each table and materialized view in the database, in MB. It is calculated by using the system administration functionpg_table_size(), which includes the size of the main data fork, free space map, visibility map and TOAST data.table_indexes_sizePGExtras.query('table_indexes_size')table|indexes_size---------------------------------------------------------------+--------------learning_coaches|153MBstates|125MBcharities_customers|93MBcharities|16MBgrade_levels|11MB(truncatedresultsforbrevity)This command displays the total size of indexes for each table and materialized view, in MB. It is calculated by using the system administration functionpg_indexes_size().total_table_sizePGExtras.query('total_table_size')name|size---------------------------------------------------------------+---------learning_coaches|349MBstates|270MBcharities_customers|166MBgrade_levels|122MBcharities|82MB(truncatedresultsforbrevity)This command displays the total size of each table and materialized view in the database, in MB. It is calculated by using the system administration functionpg_total_relation_size(), which includes table size, total index size and TOAST data.unused_indexesPGExtras.query('unused_indexes')table|index|index_size|index_scans---------------------+--------------------------------------------+------------+-------------public.grade_levels|index_placement_attempts_on_grade_level_id|97MB|0public.observations|observations_attrs_grade_resources|33MB|0public.messages|user_resource_id_idx|12MB|0(3rows)This command displays indexes that have < 50 scans recorded against them, and are greater than 5 pages in size, ordered by size relative to the number of index scans. This command is generally useful for eliminating indexes that are unused, which can impact write performance, as well as read performance should they occupy space in memory.null_indexesPGExtras.query('null_indexes')oid|index|index_size|unique|indexed_column|null_frac|expected_saving---------+--------------------+------------+--------+----------------+-----------+-----------------183764|users_reset_token|1445MB|t|reset_token|97.00%|1401MB88732|plan_cancelled_at|539MB|f|cancelled_at|8.30%|44MB9827345|users_email|18MB|t|email|28.67%|5160kBThis command displays indexes that containNULLvalues. A high ratio ofNULLvalues means that using a partial index excluding them will be beneficial in case they are not used for searching.seq_scansPGExtras.query('seq_scans')name|count-----------------------------------+----------learning_coaches|44820063states|36794975grade_levels|13972293charities_customers|8615277charities|4316276messages|3922247contests_customers|2915972classroom_goals|2142014(truncatedresultsforbrevity)This command displays the number of sequential scans recorded against all tables, descending by count of sequential scans. Tables that have very high numbers of sequential scans may be under-indexed, and it may be worth investigating queries that read from these tables.long_running_queriesPGExtras.query('long_running_queries')pid|duration|query-------+-----------------+---------------------------------------------------------------------------------------19578|02:29:11.200129|EXPLAINSELECT"students".*FROM"students"WHERE"students"."id"=1450645LIMIT119465|02:26:05.542653|EXPLAINSELECT"students".*FROM"students"WHERE"students"."id"=1889881LIMIT119632|02:24:46.962818|EXPLAINSELECT"students".*FROM"students"WHERE"students"."id"=1581884LIMIT1(truncatedresultsforbrevity)This command displays currently running queries, that have been running for longer than 5 minutes, descending by duration. Very long running queries can be a source of multiple issues, such as preventing DDL statements completing or vacuum being unable to updaterelfrozenxid.records_rankPGExtras.query('records_rank')name|estimated_count-----------------------------------+-----------------tastypie_apiaccess|568891notifications_event|381227core_todo|178614core_comment|123969notifications_notification|102101django_session|68078(truncatedresultsforbrevity)This command displays an estimated count of rows per table, descending by estimated count. The estimated count is derived fromn_live_tup, which is updated by vacuum operations. Due to the wayn_live_tupis populated, sparse vs. dense pages can result in estimations that are significantly out from the real count of rows.bloatPGExtras.query('bloat')type|schemaname|object_name|bloat|waste-------+------------+-------------------------------+-------+----------table|public|bloated_table|1.1|98MBtable|public|other_bloated_table|1.1|58MBindex|public|bloated_table::bloated_index|3.7|34MBtable|public|clean_table|0.2|3808kBtable|public|other_clean_table|0.3|1576kB(truncatedresultsforbrevity)This command displays an estimation of table "bloat" – space allocated to a relation that is full of dead tuples, that has yet to be reclaimed. Tables that have a high bloat ratio, typically 10 or greater, should be investigated to see if vacuuming is aggressive enough, and can be a sign of high table churn.vacuum_statsPGExtras.query('vacuum_stats')schema|table|last_vacuum|last_autovacuum|rowcount|dead_rowcount|autovacuum_threshold|expect_autovacuum--------+-----------------------+-------------+------------------+----------------+----------------+----------------------+-------------------public|log_table||2013-04-2617:37|18,030|0|3,656|public|data_table||2013-04-2613:09|79|28|66|public|other_table||2013-04-2611:41|41|47|58|public|queue_table||2013-04-2617:39|12|8,228|52|yespublic|picnic_table|||13|0|53|(truncatedresultsforbrevity)This command displays statistics related to vacuum operations for each table, including an estimation of dead rows, last autovacuum and the current autovacuum threshold. This command can be useful when determining if current vacuum thresholds require adjustments, and to determine when the table was last vacuumed.kill_allPGExtras.query('kill_all')This commands kills all the currently active connections to the database. It can be useful as a last resort when your database is stuck in a deadlock.extensionsPGExtras.query('extensions')This command lists all the currently installed and available PostgreSQL extensions.mandelbrotPGExtras.query('mandelbrot')This command outputs the Mandelbrot set, calculated through SQL.