What are Statistics?
There are multiple paths a database can use to answer a query, some of them being faster and more efficient than others. It is the job of the query optimizer to evaluate and choose the best path, or execution plan, for a given query. Using the available indexes may not always be the most efficient plan. For example, if 95% of the values for a column are the same, an index scan will probably be more efficient than using the index on that column. Statistics are SQL Server objects which contain metrics on the data count and distribution within a column or columns used by the optimizer to help it make that choice. They are used to estimate the count of rows.
Index statistics: Created automatically when an index (both clustered and non-clustered) is created. These will have the same name as the index and will exist as long as the index exists.
Column statistics: Created manually by the DBA using the ‘CREATE STATISTICS’ command, or automatically if the “Auto Create Statistics” option is set to “True”. Column statistics can be created, modified and dropped at will.
Statistics contain two different types of information about the data; density and distribution. Density is simply the inverse of the count of distinct values for the column or columns. The distribution is a representation of the data contained in the first column of the statistic. This information is stored in a histogram; the histogram contains up to 200 steps with a lower and upper limit and contains the count of values that fall between both limits. To view this histogram, go to the details tab of the statistic’s properties or use the command DBCC SHOW_STATISTICS. The screenshot below shows the histogram of an index statistic; the RANGE_HI_KEY is the upper limit of the step, the RANGE_HI_KEY of the previous step + 1 is the lower limit, and the RANGE_ROWS is the count of rows between the limits.
Statistics Maintenance and Best Practices
When the data in the database changes the statistics become stale and outdated. When examining a query execution plan, a large discrepancy between the Actual Number of Rows and the Estimated Number of Rows is an indication of outdated stats. Outdated statistics can lead the optimizer in choosing inefficient execution plan and can dramatically affect overall performance. Steps must therefore be taken in order to keep statistics up to date.
Keep Auto Create Statistics enabled: This database property allows SQL Server to automatically create stats for a single non-indexed column if they are missing when it is used in a where or join condition. This ensures the optimizer will have the necessary information to choose a plan. The statistics automatically created by SQL Server will start with _WA_ in their name.
Keep Auto Update Statistics enabled: This database property allows SQL Server to automatically update the statistics when they are deemed outdated. The update occurs before executing a query if certain conditions are met, or after the query is executed if Auto Update Statistics Asynchronously is used instead. The three conditions that will trigger an update if one is met are:
-Table had 0 rows and increases to one or more rows.
-Table had less than 500 rows and there is an increase of 500 rows or more since the last update
-Table has over 500 rows and there is an increase of 500 + 20% of the table size since the last update
Maintenance plan: You can also proactively update the statistics yourself using TSQL (sp_updatestats for all stats in a database or UPDATE STATISTICS for a single one) or a maintenance plan task. Scheduling the statistics maintenance during off hours will help reduce the need to update statistics during peak times. The need and frequency of this proactive maintenance will depend on your environment; frequent data changes causes the statistics to become outdated more quickly. You can also specify the sample size used to update the statistic;
UPDATE STATISTICS TableName(StatsName) WITH FULLSCAN: Costs more time and resources but will ensure that statistics are accurate.
UPDATE STATISTICS TableName(StatsName) WITH SAMPLE 50 PERCENT: Will only use half the rows and extrapolate the rest, meaning the updating will be faster, but the statistics may not be accurate.
Rebuilding an index will also update index statistics with full scan (column stats will not be updated, and an index reorg will do the update). Note however that updating statistics forces queries to recompile; you must therefore decide when the cost of the overhead for the recompiles is worth having the latest statistics.
Unused Statistics: Statistics comes with a cost, and just as with indexes, too many of them can lead to issues like increasing the cost of statistics maintenance, and can make the optimizer’s job more difficult. Updating statistics for a large database can easily take hours, even days, to complete. When Auto Create Statistics is enabled, stats can be created even for a one time query. A table could end up having a large number of statistics that serve no purpose. It is wise to review and clean up the statistics as part of general maintenance. Identifying unused statistics can be difficult since, unlike indexes, SQL Server does not record statistics usage. However you can identify the statistics that satisfy one of the thresholds for the automatic update above but still hasn’t been updated; this is a good indication of unused statistics.
In addition to unused stats, you may find overlapping stats which are covered by other statistics. The following script from Kendal Van Dyke will identify all single column statistics that are covered by an existing index statistic (share the same leading column) in a database and generates the TSQL commands to drop them.
WITH autostats ( object_id, stats_id, name, column_id ) AS ( SELECT sys.stats.object_id , sys.stats.stats_id , sys.stats.name , sys.stats_columns.column_id FROM sys.stats INNER JOIN sys.stats_columns ON sys.stats.object_id = sys.stats_columns.object_id AND sys.stats.stats_id = sys.stats_columns.stats_id WHERE sys.stats.auto_created = 1 AND sys.stats_columns.stats_column_id = 1 ) SELECT OBJECT_NAME(sys.stats.object_id) AS [Table] , sys.columns.name AS [Column] , sys.stats.name AS [Overlapped] , autostats.name AS [Overlapping] , 'DROP STATISTICS [' + OBJECT_SCHEMA_NAME(sys.stats.object_id) + '].[' + OBJECT_NAME(sys.stats.object_id) + '].[' + autostats.name + ']' FROM sys.stats INNER JOIN sys.stats_columns ON sys.stats.object_id = sys.stats_columns.object_id AND sys.stats.stats_id = sys.stats_columns.stats_id INNER JOIN autostats ON sys.stats_columns.object_id = autostats.object_id AND sys.stats_columns.column_id = autostats.column_id INNER JOIN sys.columns ON sys.stats.object_id = sys.columns.object_id AND sys.stats_columns.column_id = sys.columns.column_id WHERE sys.stats.auto_created = 0 AND sys.stats_columns.stats_column_id = 1 AND sys.stats_columns.stats_id != autostats.stats_id AND OBJECTPROPERTY(sys.stats.object_id, 'IsMsShipped') = 0
Statistics update after Index Rebuild: As mentioned previously, the index rebuild (not reorg) will also update index statistics using full scan. Scheduling stats maintenance after the index maintenance will cause duplicate work. In addition, if the stats maintenance is using a small sample size, the new updated stats will overwrite the ones that were just updated with full scan, meaning their values will be less accurate. Scheduling it after an index reorg however is fine.
Relying on Auto Update: As seen above, the threshold which triggers the auto update is around 20% of the total row count. This is fine for small tables, but larger tables require a lot of data changes before the update is triggered, during which the stats can become outdated.
Not specifying the sample size: While updating, choosing the right sample size is important to keep statistics accurate. While the cost of using full scan is higher, in some situations it is required, especially for very large databases. Running EXEC sp_updatestats @resample = ‘resample’ will update all statistics using the last sample used. If you do not specify the resample, it will update them using the default sample. The default sample is determined by SQL server and is a fraction of the total row count in a table. We have recently run into an issue where a DBA executed “EXEC sp_updatestats” on a 1 terabyte database, which caused all statistics to be updated with the default sample. Due to the size of the database, the default sample is simply not enough to represent the data distribution in the database and caused all queries to use bad execution plans which caused major performance issues. Only a full scan update of the statistics provided accurate statistics for this database, but it takes a very long time to run. Luckily there was a QA server where the database was restored before the stats update and with almost identical data. We were able to script the statistics from the QA server and recreate them on production using their binary representation (see WITH STATS_STREAM). This solution is not recommended and was only used as a last resort. This incident shows the importance of statistics and implementing proper maintenance appropriate for the environment.
Updating too often: Not only is there a cost in updating statistics, remember that it also causes queries to recompile. Updating statistics should be done only as required, and a schedule appropriate for your environment should be used. The frequency depends on the amount of data changes in the database, more changes require more frequent stats update.
Statistics are a crucial element in the overall performance of a database and require proper maintenance and attention. In addition, each environment is unique and has different needs regarding statistics maintenance. For more information regarding statistics, see https://technet.microsoft.com/en-us/library/ms190397.aspx.
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