Table statistics for dedicated SQL pool in Azure Synapse Analytics

In this article, you'll find recommendations and examples for creating and updating query-optimization statistics on tables in dedicated SQL pool.

Why use statistics

The more dedicated SQL pool knows about your data, the faster it can execute queries against it. After loading data into dedicated SQL pool, collecting statistics on your data is one of the most important things you can do to optimize your queries.

The dedicated SQL pool query optimizer is a cost-based optimizer. It compares the cost of various query plans, and then chooses the plan with the lowest cost. In most cases, it chooses the plan that will execute the fastest.

For example, if the optimizer estimates that the date your query is filtering on will return one row it will choose one plan. If it estimates that the selected date will return 1 million rows, it will return a different plan.

Automatic creation of statistic

When the database AUTO_CREATE_STATISTICS option is on, dedicated SQL pool analyzes incoming user queries for missing statistics.

If statistics are missing, the query optimizer creates statistics on individual columns in the query predicate or join condition to improve cardinality estimates for the query plan.


Automatic creation of statistics is currently turned on by default.

You can check if your dedicated SQL pool has AUTO_CREATE_STATISTICS configured by running the following command:

SELECT name, is_auto_create_stats_on
FROM sys.databases

If your dedicated SQL pool doesn't have AUTO_CREATE_STATISTICS configured, we recommend you enable this property by running the following command:

ALTER DATABASE <yourdatawarehousename>

These statements will trigger automatic creation of statistics:

  • CTAS
  • EXPLAIN when containing a join or the presence of a predicate is detected


Automatic creation of statistics are not created on temporary or external tables.

Automatic creation of statistics is done synchronously so you may incur slightly degraded query performance if your columns are missing statistics. The time to create statistics for a single column depends on the size of the table.

To avoid measurable performance degradation, you should ensure stats have been created first by executing the benchmark workload before profiling the system.


The creation of stats will be logged in sys.dm_pdw_exec_requests under a different user context.

When automatic statistics are created, they will take the form: WA_Sys<8 digit column id in Hex>_<8 digit table id in Hex>. You can view stats that have already been created by running the DBCC SHOW_STATISTICS command:

DBCC SHOW_STATISTICS (<table_name>, <target>)

The table_name is the name of the table that contains the statistics to display. This table can't be an external table. The target is the name of the target index, statistics, or column for which to display statistics information.

Update statistics

One best practice is to update statistics on date columns each day as new dates are added. Each time new rows are loaded into the dedicated SQL pool, new load dates or transaction dates are added. These additions change the data distribution and make the statistics out of date.

Statistics on a country/region column in a customer table might never need to be updated since the distribution of values doesn't generally change. Assuming the distribution is constant between customers, adding new rows to the table variation isn't going to change the data distribution.

However, if your dedicated SQL pool only contains one country/region, and you bring in data from a new country/region, resulting in data from multiple countries/regions being stored, then you need to update statistics on the country/region column.

The following are recommendations updating statistics:

Statistics attribute Recommendation
Frequency of stats updates Conservative: Daily
After loading or transforming your data
Sampling Less than 1 billion rows, use default sampling (20 percent).
With more than 1 billion rows, use sampling of two percent.

One of the first questions to ask when you're troubleshooting a query is, "Are the statistics up to date?"

This question isn't one that can be answered by the age of the data. An up-to-date statistics object might be old if there's been no material change to the underlying data. When the number of rows has changed substantially, or there is a material change in the distribution of values for a column, then it's time to update statistics.

There is no dynamic management view to determine if data within the table has changed since the last time statistics were updated. The following two queries can help you determine whether your statistics are stale.

Query 1: Find out the difference between the row count from the statistics (stats_row_count) and the actual row count (actual_row_count).

row_count_difference = CASE
    WHEN actualRowCounts.actual_row_count >= statsRowCounts.stats_row_count THEN actualRowCounts.actual_row_count - statsRowCounts.stats_row_count
    ELSE statsRowCounts.stats_row_count - actualRowCounts.actual_row_count
percent_deviation_from_actual = CASE
    WHEN actualRowCounts.actual_row_count = 0 THEN statsRowCounts.stats_row_count
    WHEN statsRowCounts.stats_row_count = 0 THEN actualRowCounts.actual_row_count
    WHEN actualRowCounts.actual_row_count >= statsRowCounts.stats_row_count THEN CONVERT(NUMERIC(18, 0), CONVERT(NUMERIC(18, 2), (actualRowCounts.actual_row_count - statsRowCounts.stats_row_count)) / CONVERT(NUMERIC(18, 2), actualRowCounts.actual_row_count) * 100)
    ELSE CONVERT(NUMERIC(18, 0), CONVERT(NUMERIC(18, 2), (statsRowCounts.stats_row_count - actualRowCounts.actual_row_count)) / CONVERT(NUMERIC(18, 2), actualRowCounts.actual_row_count) * 100)
    select distinct object_id from sys.stats where stats_id > 1
) objIdsWithStats
left join
    select object_id, sum(rows) as stats_row_count from sys.partitions group by object_id
) statsRowCounts
on objIdsWithStats.object_id = statsRowCounts.object_id 
left join
    SELECT [schema] , logical_table_name ,
        tb.object_id object_id ,
        SUM(rg.row_count) actual_row_count
    FROM sys.schemas sm
         INNER JOIN sys.tables tb ON sm.schema_id = tb.schema_id
         INNER JOIN sys.pdw_table_mappings mp ON tb.object_id = mp.object_id
         INNER JOIN sys.pdw_nodes_tables nt ON = mp.physical_name
         INNER JOIN sys.dm_pdw_nodes_db_partition_stats rg     ON rg.object_id = nt.object_id
            AND rg.pdw_node_id = nt.pdw_node_id
            AND rg.distribution_id = nt.distribution_id
    WHERE rg.index_id = 1
    GROUP BY,, tb.object_id
) actualRowCounts
on objIdsWithStats.object_id = actualRowCounts.object_id

Query 2: Find out the age of your statistics by checking the last time your statistics were updated on each table.


If there is a material change in the distribution of values for a column, you should update statistics regardless of the last time they were updated.

    sm.[name] AS [schema_name],
    tb.[name] AS [table_name],
    co.[name] AS [stats_column_name],
    st.[name] AS [stats_name],
    STATS_DATE(st.[object_id],st.[stats_id]) AS [stats_last_updated_date]
    sys.objects ob
    JOIN sys.stats st
        ON  ob.[object_id] = st.[object_id]
    JOIN sys.stats_columns sc
        ON  st.[stats_id] = sc.[stats_id]
        AND st.[object_id] = sc.[object_id]
    JOIN sys.columns co
        ON  sc.[column_id] = co.[column_id]
        AND sc.[object_id] = co.[object_id]
    JOIN sys.types  ty
        ON  co.[user_type_id] = ty.[user_type_id]
    JOIN sys.tables tb
        ON  co.[object_id] = tb.[object_id]
    JOIN sys.schemas sm
        ON  tb.[schema_id] = sm.[schema_id]
    st.[user_created] = 1;

Date columns in a dedicated SQL pool, for example, usually need frequent statistics updates. Each time new rows are loaded into the dedicated SQL pool, new load dates or transaction dates are added. These additions change the data distribution and make the statistics out of date.

Conversely, statistics on a gender column in a customer table might never need to be updated. Assuming the distribution is constant between customers, adding new rows to the table variation isn't going to change the data distribution.

If your dedicated SQL pool contains only one gender and a new requirement results in multiple genders, then you need to update statistics on the gender column.

For more information, see general guidance for Statistics.

Implementing statistics management

It is often a good idea to extend your data-loading process to ensure that statistics are updated at the end of the load to avoid/minimize blocking or resource contention between concurrent queries.

The data load is when tables most frequently change their size and/or their distribution of values. Data-loading is a logical place to implement some management processes.

The following guiding principles are provided for updating your statistics:

  • Ensure that each loaded table has at least one statistics object updated. This updates the table size (row count and page count) information as part of the statistics update.
  • Focus on columns participating in JOIN, GROUP BY, ORDER BY, and DISTINCT clauses.
  • Consider updating "ascending key" columns such as transaction dates more frequently, because these values will not be included in the statistics histogram.
  • Consider updating static distribution columns less frequently.
  • Remember, each statistic object is updated in sequence. Simply implementing UPDATE STATISTICS <TABLE_NAME> isn't always ideal, especially for wide tables with lots of statistics objects.

For more information, see Cardinality Estimation.

Examples: Create statistics

These examples show how to use various options for creating statistics. The options that you use for each column depend on the characteristics of your data and how the column will be used in queries.

Create single-column statistics with default options

To create statistics on a column, provide a name for the statistics object and the name of the column.

This syntax uses all of the default options. By default, 20 percent of the table is sampled when creating statistics.

CREATE STATISTICS [statistics_name] ON [schema_name].[table_name]([column_name]);

For example:

CREATE STATISTICS col1_stats ON dbo.table1 (col1);

Create single-column statistics by examining every row

The default sampling rate of 20 percent is sufficient for most situations. However, you can adjust the sampling rate.

To sample the full table, use this syntax:

CREATE STATISTICS [statistics_name] ON [schema_name].[table_name]([column_name]) WITH FULLSCAN;

For example:

CREATE STATISTICS col1_stats ON dbo.table1 (col1) WITH FULLSCAN;

Create single-column statistics by specifying the sample size

Alternatively, you can specify the sample size as a percent:

CREATE STATISTICS col1_stats ON dbo.table1 (col1) WITH SAMPLE = 50 PERCENT;

Create single-column statistics on only some of the rows

You can also create statistics on a portion of the rows in your table. This is called a filtered statistic.

For example, you can use filtered statistics when you plan to query a specific partition of a large partitioned table. By creating statistics on only the partition values, the accuracy of the statistics will improve, and therefore improve query performance.

This example creates statistics on a range of values. The values can easily be defined to match the range of values in a partition.

CREATE STATISTICS stats_col1 ON table1(col1) WHERE col1 > '2000101' AND col1 < '20001231';


For the query optimizer to consider using filtered statistics when it chooses the distributed query plan, the query must fit inside the definition of the statistics object. Using the previous example, the query's WHERE clause needs to specify col1 values between 2000101 and 20001231.

Create single-column statistics with all the options

You can also combine the options together. The following example creates a filtered statistics object with a custom sample size:

CREATE STATISTICS stats_col1 ON table1 (col1) WHERE col1 > '2000101' AND col1 < '20001231' WITH SAMPLE = 50 PERCENT;

For the full reference, see CREATE STATISTICS.

Create multi-column statistics

To create a multi-column statistics object, use the previous examples, but specify more columns.


The histogram, which is used to estimate the number of rows in the query result, is only available for the first column listed in the statistics object definition.

In this example, the histogram is on product_category. Cross-column statistics are calculated on product_category and product_sub_category:

CREATE STATISTICS stats_2cols ON table1 (product_category, product_sub_category) WHERE product_category > '2000101' AND product_category < '20001231' WITH SAMPLE = 50 PERCENT;

Because there is a correlation between product_category and product_sub_category, a multi-column statistics object can be useful if these columns are accessed at the same time.

Create statistics on all columns in a table

One way to create statistics is to issue CREATE STATISTICS commands after creating the table:

CREATE TABLE dbo.table1
   col1 int
,  col2 int
,  col3 int

CREATE STATISTICS stats_col1 on dbo.table1 (col1);
CREATE STATISTICS stats_col2 on dbo.table2 (col2);
CREATE STATISTICS stats_col3 on dbo.table3 (col3);

Use a stored procedure to create statistics on all columns in a SQL pool

Dedicated SQL pool does not have a system stored procedure equivalent to sp_create_stats in SQL Server. This stored procedure creates a single column statistics object on every column in a SQL pool that doesn't already have statistics.

The following example will help you get started with your SQL pool design. Feel free to adapt it to your needs.

CREATE PROCEDURE    [dbo].[prc_sqldw_create_stats]
(   @create_type    tinyint -- 1 default 2 Fullscan 3 Sample
,   @sample_pct     tinyint

IF @create_type IS NULL
    SET @create_type = 1;

IF @create_type NOT IN (1,2,3)
    THROW 151000,'Invalid value for @stats_type parameter. Valid range 1 (default), 2 (fullscan) or 3 (sample).',1;

IF @sample_pct IS NULL
    SET @sample_pct = 20;

IF OBJECT_ID('tempdb..#stats_ddl') IS NOT NULL
    DROP TABLE #stats_ddl;

CREATE TABLE #stats_ddl
WITH    (   DISTRIBUTION    = HASH([seq_nmbr])
        ,   LOCATION        = USER_DB
SELECT      t.[name]                        AS [table_name]
,           s.[name]                        AS [table_schema_name]
,           c.[name]                        AS [column_name]
,           c.[column_id]                   AS [column_id]
,           t.[object_id]                   AS [object_id]
,           ROW_NUMBER()
            OVER(ORDER BY (SELECT NULL))    AS [seq_nmbr]
FROM        sys.[tables] t
JOIN        sys.[schemas] s         ON  t.[schema_id]       = s.[schema_id]
JOIN        sys.[columns] c         ON  t.[object_id]       = c.[object_id]
LEFT JOIN   sys.[stats_columns] l   ON  l.[object_id]       = c.[object_id]
                                    AND l.[column_id]       = c.[column_id]
                                    AND l.[stats_column_id] = 1
LEFT JOIN    sys.[external_tables] e    ON    e.[object_id]        = t.[object_id]
WHERE       l.[object_id] IS NULL
AND            e.[object_id] IS NULL -- not an external table
SELECT  [table_schema_name]
,       [table_name]
,       [column_name]
,       [column_id]
,       [object_id]
,       [seq_nmbr]
,       CASE @create_type
        WHEN 1
        THEN    CAST('CREATE STATISTICS '+QUOTENAME('stat_'+table_schema_name+ '_' + table_name + '_'+column_name)+' ON '+QUOTENAME(table_schema_name)+'.'+QUOTENAME(table_name)+'('+QUOTENAME(column_name)+')' AS VARCHAR(8000))
        WHEN 2
        THEN    CAST('CREATE STATISTICS '+QUOTENAME('stat_'+table_schema_name+ '_' + table_name + '_'+column_name)+' ON '+QUOTENAME(table_schema_name)+'.'+QUOTENAME(table_name)+'('+QUOTENAME(column_name)+') WITH FULLSCAN' AS VARCHAR(8000))
        WHEN 3
        THEN    CAST('CREATE STATISTICS '+QUOTENAME('stat_'+table_schema_name+ '_' + table_name + '_'+column_name)+' ON '+QUOTENAME(table_schema_name)+'.'+QUOTENAME(table_name)+'('+QUOTENAME(column_name)+') WITH SAMPLE '+CONVERT(varchar(4),@sample_pct)+' PERCENT' AS VARCHAR(8000))
        END AS create_stat_ddl

DECLARE @i INT              = 1
,       @t INT              = (SELECT COUNT(*) FROM #stats_ddl)
,       @s NVARCHAR(4000)   = N''

WHILE @i <= @t
    SET @s=(SELECT create_stat_ddl FROM #stats_ddl WHERE seq_nmbr = @i);

    PRINT @s
    EXEC sp_executesql @s
    SET @i+=1;

DROP TABLE #stats_ddl;

To create statistics on all columns in the table using the defaults, execute the stored procedure.

EXEC [dbo].[prc_sqldw_create_stats] 1, NULL;

To create statistics on all columns in the table using a fullscan, call this procedure.

EXEC [dbo].[prc_sqldw_create_stats] 2, NULL;

To create sampled statistics on all columns in the table, enter 3, and the sample percent. This procedure uses a 20 percent sample rate.

EXEC [dbo].[prc_sqldw_create_stats] 3, 20;

Examples: Update statistics

To update statistics, you can:

  • Update one statistics object. Specify the name of the statistics object you want to update.
  • Update all statistics objects on a table. Specify the name of the table instead of one specific statistics object.

Update one specific statistics object

Use the following syntax to update a specific statistics object:

UPDATE STATISTICS [schema_name].[table_name]([stat_name]);

For example:

UPDATE STATISTICS [dbo].[table1] ([stats_col1]);

By updating specific statistics objects, you can minimize the time and resources required to manage statistics. Doing so requires some thought to choose the best statistics objects to update.

Update all statistics on a table

A simple method for updating all the statistics objects on a table is:

UPDATE STATISTICS [schema_name].[table_name];

For example:


The UPDATE STATISTICS statement is easy to use. Just remember that it updates all statistics on the table, and therefore might perform more work than is necessary. If performance is not an issue, this is the easiest and most complete way to guarantee that statistics are up to date.


When updating all statistics on a table, dedicated SQL pool does a scan to sample the table for each statistics object. If the table is large and has many columns and many statistics, it might be more efficient to update individual statistics based on need.

For an implementation of an UPDATE STATISTICS procedure, see Temporary Tables. The implementation method is slightly different from the preceding CREATE STATISTICS procedure, but the result is the same.

For the full syntax, see Update Statistics.

Statistics metadata

There are several system views and functions that you can use to find information about statistics. For example, you can see if a statistics object might be out of date by using the stats-date function to see when statistics were last created or updated.

Catalog views for statistics

These system views provide information about statistics:

Catalog view Description
sys.columns One row for each column.
sys.objects One row for each object in the database.
sys.schemas One row for each schema in the database.
sys.stats One row for each statistics object.
sys.stats_columns One row for each column in the statistics object. Links back to sys.columns.
sys.tables One row for each table (includes external tables).
sys.table_types One row for each data type.

System functions for statistics

These system functions are useful for working with statistics:

System function Description
STATS_DATE Date the statistics object was last updated.
DBCC SHOW_STATISTICS Summary level and detailed information about the distribution of values as understood by the statistics object.

Combine statistics columns and functions into one view

This view brings columns that relate to statistics and results from the STATS_DATE() function together.

CREATE VIEW dbo.vstats_columns
        sm.[name]                           AS [schema_name]
,       tb.[name]                           AS [table_name]
,       st.[name]                           AS [stats_name]
,       st.[filter_definition]              AS [stats_filter_definition]
,       st.[has_filter]                     AS [stats_is_filtered]
,       STATS_DATE(st.[object_id],st.[stats_id])
                                            AS [stats_last_updated_date]
,       co.[name]                           AS [stats_column_name]
,       ty.[name]                           AS [column_type]
,       co.[max_length]                     AS [column_max_length]
,       co.[precision]                      AS [column_precision]
,       co.[scale]                          AS [column_scale]
,       co.[is_nullable]                    AS [column_is_nullable]
,       co.[collation_name]                 AS [column_collation_name]
,       QUOTENAME(sm.[name])+'.'+QUOTENAME(tb.[name])
                                            AS two_part_name
,       QUOTENAME(DB_NAME())+'.'+QUOTENAME(sm.[name])+'.'+QUOTENAME(tb.[name])
                                            AS three_part_name
FROM    sys.objects                         AS ob
JOIN    sys.stats           AS st ON    ob.[object_id]      = st.[object_id]
JOIN    sys.stats_columns   AS sc ON    st.[stats_id]       = sc.[stats_id]
                            AND         st.[object_id]      = sc.[object_id]
JOIN    sys.columns         AS co ON    sc.[column_id]      = co.[column_id]
                            AND         sc.[object_id]      = co.[object_id]
JOIN    sys.types           AS ty ON    co.[user_type_id]   = ty.[user_type_id]
JOIN    sys.tables          AS tb ON  co.[object_id]        = tb.[object_id]
JOIN    sys.schemas         AS sm ON  tb.[schema_id]        = sm.[schema_id]
WHERE   1=1
AND     st.[user_created] = 1


DBCC SHOW_STATISTICS() shows the data held within a statistics object. This data comes in three parts:

  • Header
  • Density vector
  • Histogram

The header metadata about the statistics. The histogram displays the distribution of values in the first key column of the statistics object. The density vector measures cross-column correlation.


Dedicated SQL pool computes cardinality estimates with any of the data in the statistics object.

Show header, density, and histogram

This simple example shows all three parts of a statistics object:

DBCC SHOW_STATISTICS([<schema_name>.<table_name>],<stats_name>)

For example:

DBCC SHOW_STATISTICS (dbo.table1, stats_col1);

Show one or more parts of DBCC SHOW_STATISTICS()

If you're only interested in viewing specific parts, use the WITH clause and specify which parts you want to see:

DBCC SHOW_STATISTICS([<schema_name>.<table_name>],<stats_name>) WITH stat_header, histogram, density_vector

For example:

DBCC SHOW_STATISTICS (dbo.table1, stats_col1) WITH histogram, density_vector


DBCC SHOW_STATISTICS() is more strictly implemented in dedicated SQL pool compared to SQL Server:

  • Undocumented features are not supported.
  • Cannot use Stats_stream.
  • Cannot join results for specific subsets of statistics data. For example, STAT_HEADER JOIN DENSITY_VECTOR.
  • NO_INFOMSGS cannot be set for message suppression.
  • Square brackets around statistics names cannot be used.
  • Cannot use column names to identify statistics objects.
  • Custom error 2767 is not supported.

Next steps

For further improve query performance, see Monitor your workload