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Important

Azure Database for PostgreSQL - Single Server is on the retirement path. We strongly recommend for you to upgrade to Azure Database for PostgreSQL - Flexible Server. For more information about migrating to Azure Database for PostgreSQL - Flexible Server, see What's happening to Azure Database for PostgreSQL Single Server ?

The Query Store feature in Azure Database for PostgreSQL provides a way to track query performance over time. Query Store simplifies performance troubleshooting by helping you quickly find the longest running and most resource-intensive queries. Query Store automatically captures a history of queries and runtime statistics, and it retains them for your review. It separates data by time windows so that you can see database usage patterns. Data for all users, databases, and queries is stored in a database named azure_sys in the Azure Database for PostgreSQL instance.

Important

Do not modify the azure_sys database or its schemas. Doing so will prevent Query Store and related performance features from functioning correctly.

Enabling Query Store

Query Store is an opt-in feature, so it isn't active by default on a server. The store is enabled or disabled globally for all the databases on a given server and cannot be turned on or off per database.

Enable Query Store using the Azure portal

To enable wait statistics in your Query Store:

Alternatively you can set these parameters using the Azure CLI.

az postgres server configuration set --name pg_qs.query_capture_mode --resource-group myresourcegroup --server mydemoserver --value TOP
az postgres server configuration set --name pgms_wait_sampling.query_capture_mode --resource-group myresourcegroup --server mydemoserver --value ALL
Allow up to 20 minutes for the first batch of data to persist in the azure_sys database.
Information in Query Store
Query Store has two stores:
A runtime stats store for persisting the query execution statistics information.
A wait stats store for persisting wait statistics information.
Common scenarios for using Query Store include:
Determining the number of times a query was executed in a given time window
Comparing the average execution time of a query across time windows to see large deltas
Identifying longest running queries in the past X hours
Identifying top N queries that are waiting on resources
Understanding wait nature for a particular query
To minimize space usage, the runtime execution statistics in the runtime stats store are aggregated over a fixed, configurable time window. The information in these stores is visible by querying the query store views.
Access Query Store information
Query Store data is stored in the azure_sys database on your Postgres server.
The following query returns information about queries in Query Store:
SELECT * FROM query_store.qs_view; 
Or this query for wait stats:
SELECT * FROM query_store.pgms_wait_sampling_view;
Finding wait queries
Wait event types combine different wait events into buckets by similarity. Query Store provides the wait event type, specific wait event name, and the query in question. Being able to correlate this wait information with the query runtime statistics means you can gain a deeper understanding of what contributes to query performance characteristics.
Here are some examples of how you can gain more insights into your workload using the wait statistics in Query Store:
Observation
Action
High Lock waits
Check the query texts for the affected queries and identify the target entities. Look in Query Store for other queries modifying the same entity, which is executed frequently and/or have high duration. After identifying these queries, consider changing the application logic to improve concurrency, or use a less restrictive isolation level.
High Buffer IO waits
Find the queries with a high number of physical reads in Query Store. If they match the queries with high IO waits, consider introducing an index on the underlying entity, in order to do seeks instead of scans. This would minimize the IO overhead of the queries. Check the Performance Recommendations for your server in the portal to see if there are index recommendations for this server that would optimize the queries.
High Memory waits
Find the top memory consuming queries in Query Store. These queries are probably delaying further progress of the affected queries. Check the Performance Recommendations for your server in the portal to see if there are index recommendations that would optimize these queries.
Configuration options
When Query Store is enabled it saves data in 15-minute aggregation windows, up to 500 distinct queries per window.
The following options are available for configuring Query Store parameters.
Parameter
Description
Default
Range
pg_qs.max_query_text_length
Sets the maximum query length that can be saved. Longer queries will be truncated.
100 - 10K
pg_qs.retention_period_in_days
Sets the retention period.
1 - 30
pg_qs.track_utility
Sets whether utility commands are tracked
on, off
The following options apply specifically to wait statistics.
Parameter
Description
Default
Range
pgms_wait_sampling.query_capture_mode
Sets which statements are tracked for wait stats.
none, all
Pgms_wait_sampling.history_period
Set the frequency, in milliseconds, at which wait events are sampled.
1-600000
pg_qs.query_capture_mode supersedes pgms_wait_sampling.query_capture_mode. If pg_qs.query_capture_mode is NONE, the pgms_wait_sampling.query_capture_mode setting has no effect.
Use the Azure portal or Azure CLI to get or set a different value for a parameter.
Views and functions
View and manage Query Store using the following views and functions. Anyone in the PostgreSQL public role can use these views to see the data in Query Store. These views are only available in the azure_sys database.
Queries are normalized by looking at their structure after removing literals and constants. If two queries are identical except for literal values, they will have the same hash.
query_store.qs_view
This view returns query text data in Query Store. There is one row for each distinct query_text. The data isn't available via the Intelligent Performance section in the portal, APIs, or the CLI - but It can be found by connecting to azure_sys and querying 'query_store.query_texts_view'.
References
Description
Varchar(10000)
Text of a representative statement. Different queries with the same structure are clustered together; this text is the text for the first of the queries in the cluster.
plan_id
bigint
ID of the plan corresponding to this query, not available yet
start_time
timestamp
Queries are aggregated by time buckets - the time span of a bucket is 15 minutes by default. This is the start time corresponding to the time bucket for this entry.
end_time
timestamp
End time corresponding to the time bucket for this entry.
calls
bigint
Number of times the query executed
total_time
double precision
Total query execution time, in milliseconds
min_time
double precision
Minimum query execution time, in milliseconds
max_time
double precision
Maximum query execution time, in milliseconds
mean_time
double precision
Mean query execution time, in milliseconds
stddev_time
double precision
Standard deviation of the query execution time, in milliseconds
bigint
Total number of rows retrieved or affected by the statement
shared_blks_hit
bigint
Total number of shared block cache hits by the statement
shared_blks_read
bigint
Total number of shared blocks read by the statement
shared_blks_dirtied
bigint
Total number of shared blocks dirtied by the statement
shared_blks_written
bigint
Total number of shared blocks written by the statement
local_blks_hit
bigint
Total number of local block cache hits by the statement
local_blks_read
bigint
Total number of local blocks read by the statement
local_blks_dirtied
bigint
Total number of local blocks dirtied by the statement
local_blks_written
bigint
Total number of local blocks written by the statement
temp_blks_read
bigint
Total number of temp blocks read by the statement
temp_blks_written
bigint
Total number of temp blocks written by the statement
blk_read_time
double precision
Total time the statement spent reading blocks, in milliseconds (if track_io_timing is enabled, otherwise zero)
blk_write_time
double precision
Total time the statement spent writing blocks, in milliseconds (if track_io_timing is enabled, otherwise zero)
query_store.query_texts_view
This view returns query text data in Query Store. There is one row for each distinct query_text.
Description
Functions
Query_store.qs_reset() returns void
qs_reset discards all statistics gathered so far by Query Store. This function can only be executed by the server admin role.
Query_store.staging_data_reset() returns void
staging_data_reset discards all statistics gathered in memory by Query Store (that is, the data in memory that has not been flushed yet to the database). This function can only be executed by the server admin role.
Azure Monitor
Azure Database for PostgreSQL is integrated with Azure Monitor diagnostic settings. Diagnostic settings allows you to send your Postgres logs in JSON format to Azure Monitor Logs for analytics and alerting, Event Hubs for streaming, and Azure Storage for archiving.
Important
This diagnostic feature for is only available in the General Purpose and Memory Optimized pricing tiers.
Configure diagnostic settings
You can enable diagnostic settings for your Postgres server using the Azure portal, CLI, REST API, and PowerShell. The log categories to configure are QueryStoreRuntimeStatistics and QueryStoreWaitStatistics.
To enable resource logs using the Azure portal:
In the portal, go to Diagnostic Settings in the navigation menu of your Postgres server.
Select Add Diagnostic Setting.
Name this setting.
Select your preferred endpoint (storage account, event hub, log analytics).
Select the log types QueryStoreRuntimeStatistics and QueryStoreWaitStatistics.
Save your setting.
To enable this setting using PowerShell, CLI, or REST API, visit the diagnostic settings article.
JSON log format
The following tables describes the fields for the two log types. Depending on the output endpoint you choose, the fields included and the order in which they appear may vary.
QueryStoreRuntimeStatistics
Field
Description
Limitations and known issues
If a PostgreSQL server has the parameter default_transaction_read_only on, Query Store cannot capture data.
Query Store functionality can be interrupted if it encounters long Unicode queries (>= 6000 bytes).
Read replicas replicate Query Store data from the primary server. This means that a read replica's Query Store does not provide statistics about queries run on the read replica.
Next steps
Learn more about scenarios where Query Store can be especially helpful.
Learn more about best practices for using Query Store.