Auto update statistics option

An index on the VIN is more selective than an index on the manufacturer, because VIN has lower density than manufacturer. A maximum frequency of 1 can be found in columns with unique values. The density vector contains one density for each prefix of columns in the statistics object. For example, if a statistics object has the key columns CustomerId , ItemId and Price , density is calculated on each of the following column prefixes.

Filtered statistics can improve query performance for queries that select from well-defined subsets of data. Filtered statistics use a filter predicate to select the subset of data that is included in the statistics.

Well-designed filtered statistics can improve the query execution plan compared with full-table statistics. For more information about when to create filtered statistics, see the When to Create Statistics section in this article. There are three options that affect when and how statistics are created and updated. These options are configurable at the database level only.

These single-column statistics are created on columns that do not already have a histogram in an existing statistics object. This option also does not generate filtered statistics.

It applies strictly to single-column statistics for the full table. You can use the following query to determine if the Query Optimizer has created statistics for a query predicate column. This action is also known as statistics recompilation. Statistics become out-of-date after modifications from insert, update, delete, or merge operations change the data distribution in the table or indexed view.

The Query Optimizer determines when statistics might be out-of-date by counting the number of row modifications since the last statistics update and comparing the number of row modifications to a threshold.

The threshold is based on the table cardinality, which can be defined as the number of rows in the table or indexed view. Up to SQL Server The threshold is different whether a table is temporary or permanent. Starting with SQL Server With this change, statistics on large tables will be updated more frequently. However, if a database has a compatibility level below , then the SQL Server This means the statistics will be updated every 44, modifications. While recommended for all scenarios, enabling the trace flag is optional.

However, you can use the following guidance for enabling the trace flag in your pre-SQL Server 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. This option also applies to filtered statistics. You can use the sys. By default, the asynchronous statistics update option is OFF, and the Query Optimizer updates statistics synchronously.

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.

Statistics are typically updated soon thereafter. Queries that compile after the stats updates complete 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 manually 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. Asynchronous statistics update is performed by a background request. When the request is ready to write updated statistics to the database, it attempts to acquire a schema modification lock on the statistics metadata object.

If a different session is already holding a lock on the same object, asynchronous statistics update is blocked until the schema modification lock can be acquired. Similarly, sessions that need to acquire a schema stability Sch-S lock on the statistics metadata object to compile a query may be blocked by the asynchronous statistics update background session, which is already holding or waiting to acquire the schema modification lock.

Therefore, for workloads with very frequent query compilations and frequent statistics updates, using asynchronous statistics may increase the likelihood of concurrency issues due to lock blocking.

With this configuration enabled, the background request will wait to acquire the schema modification Sch-M lock and persist the updated statistics on a separate low-priority queue, allowing other requests to continue compiling queries with existing statistics.

Once no other session is holding a lock on the statistics metadata object, the background request will acquire its schema modification lock and update statistics. In the unlikely event that the background request cannot acquire the lock within a timeout period of several minutes, the asynchronous statistics update will be aborted, and the statistics will not be updated until another automatic statistics update is triggered, or until statistics are updated manually.

The default is OFF. When new partitions are added to a large table, statistics should be updated to include the new partitions. Also, scanning the entire table isn't necessary because only the statistics on the new partitions might be needed.

The incremental option creates and stores statistics on a per partition basis, and when updated, only refreshes statistics on those partitions that need new statistics. If per partition statistics are not supported the option is ignored and a warning is generated.

Incremental stats are not supported for following statistics types:. The Query Optimizer creates statistics for indexes on tables or views when the index is created. These statistics are created on the key columns of the index. If the index is a filtered index, the Query Optimizer creates filtered statistics on the same subset of rows specified for the filtered index. Instead, the Query Optimizer uses the default sampling algorithm to generate statistics.

This option can be useful in OLTP environments while it can have negative effects in data warehouses. You can find additional details about this option in this tip. In certain rare cases you might have to disable this useful feature.

The auto update statistics feature can be turned off at different levels:. Please note that if you disable the auto update statistics option on the database level then there will be no statistics updates regardless of the individual table, index or statistics object settings. One answer is to create statistics whenever the Database Engine Tuning Advisor suggests creating statistics. Another reason for creating statistics is that you can see missing statistics warnings a yellow triangle with a black exclamation point or red table name in SQL Server on the Graphical Query Execution Plan as shown in the screenshot below.

You should also consider creating statistics when your query selects from a subset of data or the query predicate contains multiple correlated columns. If your queries are executing slower, then it is time to update the statistics. It is recommended to update your statistics after you insert a larger amount of data into ascending or descending key columns because in such cases the statistics histogram might not have any information about the newly inserted values.

It is also highly recommended to update the statistics after maintenance except index maintenance the data distribution does not change if you rebuild, defragment or reorganize an index. At a minimum I generally recommend updating statistics daily if the data changes frequently in your database. Generally speaking, you can update that statistics less frequently with data warehouses storing historical data where the refreshes are weekly or monthly data loads.

Thanks for the post. At the end of this page you say "At a minimum I generally recommend updating statistics daily Related Articles. How to get index usage information in SQL Server.

Heap Tables. It depends on the specifics of your installation, on the table sizes and number of indexes, the frequency of data change, the queries run, etc You should weigh the pros and cons of this option before changing your current settings. The benefits and disadvantages can be unpredictable if your server mixes OLTP and data warehousing functions. Also, I recommend always running tests before you change something on your production environment. Related Articles. How to get index usage information in SQL Server.

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