Difference between auto update statistics and auto update statistics asynchronously

Dear readers,

Please find the interview question and its answer based on statistics in SQL Server.

How to find auto update statistics and auto update statistics asynchronously options in SSMS:

Right click on your database–> Go to Properties…> options

The query optimizer uses statistics to create query plans that improve query performance.

AUTO_UPDATE_STATISTICS Option

As from snapshot above, by default its value is true.

When the automatic update statistics option, AUTO_UPDATE_STATISTICS, is on, the query optimizer determines when statistics might be out-of-date and then updates them when they are used by a query. Statistics become out-of-date after insert, update, delete, or merge operations change the data distribution in the table or indexed view. The query optimizer determines when statistics might be out-of-date by counting the number of data modifications since the last statistics update and comparing the number of modifications to a threshold. The threshold is based on the number of rows in the table or indexed view.

The query optimizer checks for out-of-date statistics before compiling a query and before executing a cached query plan. Before compiling a query, the query optimizer uses the columns, tables, and indexed views in the query predicate to determine which statistics might be out-of-date. Before executing a cached query plan, the Database Engine verifies that the query plan references up-to-date statistics.

The AUTO_UPDATE_STATISTICS option applies to statistics objects created for indexes, single-columns in query predicates, and statistics created with the CREATE STATISTICS statement. This option also applies to filtered statistics.

Auto Update Statistics Asynchronously 

The default setting for this option is disabled.

The asynchronous statistics update option, AUTO_UPDATE_STATISTICS_ASYNC, determines whether the query optimizer uses synchronous or asynchronous statistics updates. By default, the asynchronous statistics update option is off, and the query optimizer updates statistics synchronously. The AUTO_UPDATE_STATISTICS_ASYNC option applies to statistics objects created for indexes, single columns in query predicates, and statistics created with the CREATE STATISTICS statement.

Statistics updates can be either synchronous (the default) or asynchronous. With synchronous statistics updates, queries always compile and execute with up-to-date statistics; when statistics are out-of-date, the query optimizer waits for updated statistics before compiling and executing the query. With asynchronous statistics updates, queries compile with existing statistics even if the existing statistics are out-of-date; the query optimizer could choose a suboptimal query plan if statistics are out-of-date when the query compiles. Queries that compile after the asynchronous updates have completed will benefit from using the updated statistics.

Consider using synchronous statistics when you perform operations that change the distribution of data, such as truncating a table or performing a bulk update of a large percentage of the rows. If you do not update the statistics after completing the operation, using synchronous statistics will ensure statistics are up-to-date before executing queries on the changed data.

Consider using asynchronous statistics to achieve more predictable query response times for the following scenarios:

• Your application frequently executes the same query, similar queries, or similar cached query plans. Your query response times might be more predictable with asynchronous statistics updates than with synchronous statistics updates because the query optimizer can execute incoming queries without waiting for up-to-date statistics. This avoids delaying some queries and not others.
• Your application has experienced client request time outs caused by one or more queries waiting for updated statistics. In some cases, waiting for synchronous statistics could cause applications with aggressive time outs to fail.

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