Tips to improve performance of MS Reporting service reports (SSRS).

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A lot of times I got questions from people how to improve SSRS reports. Of course every report is different, but some tips can be applied to every report. Assume we have a report which takes X seconds to display all data on your screen. The total time to generate a SSRS reports can be split into 2 main parts:

1. Time to executed all queries on the SQL Server. Use the SQL profiler to measure the duration of all executed queries. (Y seconds)
2. Time to generated the report on the reporting server, based on the result set of the executed queries. (Z seconds)

Because we know the total time to execute the report and the total duration of all executed queries, you can calculate the time to generate the report (Z seconds). (X = Y + Z). After you know the values for X, Y and Z, you can start focusing on the biggest part.

• Use the SQL Profiler to see which queries are executed when the report is generated. Sometimes you will see more queries being executed than you expected. Every dataset in the report will be executed. A lot of times new datasets are added during building of reports. Check if all datasets are still being used. For instance, datasets for available parameter values. Remove all datasets which are not used anymore.
• A dataset contains more columns than used in the Tablix\list. A lot of times you will see datasets with next syntax:
  
  SELECT * FROM TableX WHERE Column1 = 'Something'.
  
  This is easy when start building the report. It will retrieve all columns of the table. However all columns are not useful and creates a lot of overhead. Assume you uses 3 columns in the tablix\list. Change the syntax of the dataset to only these 3 columns. This can save bookmark lookups and it will save disk I/O on the SQL Server. So you get a dataset with next syntax:
  
  SELECT Column1, Column5, Column 8 FROM TableX WHERE Column1 = 'Something'
• ORDER BY in the dataset differs from the ORDER BY in the Tablix\list. You need to decide where the data will be sorted. It can be done within SQL Server with an ORDER BY clause in the dataset or in by the Reporting server engine. It is not useful to do it on both sites. If an index is available use the ORDER BY in your dataset.
• Use the SQL Profiler to measure the performance of all datasets (Reads, CPU and Duration). Use the SQL Server Management Studio (SSMS) to analyze the execution plan of every dataset.
• Avoid datasets with result sets with a lot of records like more than 250 records. Greater result sets are more like a data export (dump). A lot of times data is GROUPED in the report without an Drill down option. In that scenario do the group by already in your dataset. This will save a lot of data transfer to the SQL Server and it will save the reporting server engine to group the resultset.
• Rendering of the report can take a while if the resultset is very big. Look very critical if such a big resultset is necessary. If details are used in only 5 % of the situations, create another report to display the details. This will avoid the retrieval of all details in 95 % of the situations.
• Use the database documentation of your applications to understand how to retrieve information from the database. For Exact Globe click here to find the database documentation. For Exact Synergy Enterprise click here to find the database documentattion.

Enjoy building high performing reports.

Index statistics and suggestions of a table in one query.

To optimize the index structure of tables in your database, you need to get information how these indexes are used. On the other hand you want to know if new indexes can improve the performance of your database. Index usage statistics and index suggestions are stored by the SQL Server engine as of SQL 2005.  With next query you can combine the index usages statistics and suggestions in one query. It will help you to improve the performance of your database.

Be aware to look very critical to all index suggestions. Suggestions have no relation to each other. Therefor do not add all index suggestions at the same. Add one index and analyze the results after a while and re-execute the query.

To use this script specify the table you want to analyze in the second line. In this example the table GBKMUT is analyzed.  If the table you specified does not exist, it will return all statistics and suggestions of all table in your database. A lot of success with improving your database.

DECLARE @ObjectID int

SELECT @ObjectID = OBJECT_ID('GBKMUT')

;WITH preIndexAnalysis
AS (
SELECT
OBJECT_SCHEMA_NAME(t.object_id) as schema_name
,t.name as table_name
,COALESCE(i.name, 'N/A') as index_name
,CASE WHEN i.is_unique = 1 THEN 'UNIQUE ' ELSE '' END + i.type_desc as type_desc
,NULL as impact
,ROW_NUMBER()
OVER (PARTITION BY i.object_id ORDER BY i.is_primary_key desc, ius.user_seeks + ius.user_scans + ius.user_lookups desc) as ranking
,ius.user_seeks + ius.user_scans + ius.user_lookups as user_total
,COALESCE(CAST(100 * (ius.user_seeks + ius.user_scans + ius.user_lookups)
/(NULLIF(SUM(ius.user_seeks + ius.user_scans + ius.user_lookups)
OVER(PARTITION BY i.object_id), 0) * 1.) as decimal(6,2)),0) as user_total_pct
,ius.user_seeks
,ius.user_scans
,ius.user_lookups
,STUFF((SELECT ', ' + QUOTENAME(c.name)
FROM sys.index_columns ic
INNER JOIN sys.columns c ON ic.object_id = c.object_id AND ic.column_id = c.column_id
WHERE i.object_id = ic.object_id
AND i.index_id = ic.index_id
AND is_included_column = 0
ORDER BY index_column_id ASC
FOR XML PATH('')), 1, 2, '') AS indexed_columns
,STUFF((SELECT ', ' + QUOTENAME(c.name)
FROM sys.index_columns ic
INNER JOIN sys.columns c ON ic.object_id = c.object_id AND ic.column_id = c.column_id
WHERE i.object_id = ic.object_id
AND i.index_id = ic.index_id
AND is_included_column = 1
ORDER BY index_column_id ASC
FOR XML PATH('')), 1, 2, '') AS included_columns
,i.object_id
,i.index_id
,STUFF((SELECT ', ' + QUOTENAME(ic.column_id,'(')
FROM sys.index_columns ic
WHERE i.object_id = ic.object_id
AND i.index_id = ic.index_id
AND is_included_column = 0
ORDER BY index_column_id ASC
FOR XML PATH('')), 1, 2, '') AS indexed_columns_compare
,COALESCE(STUFF((SELECT ', ' + QUOTENAME(ic.column_id, '(')
FROM sys.index_columns ic
WHERE i.object_id = ic.object_id
AND i.index_id = ic.index_id
AND is_included_column = 1
ORDER BY index_column_id ASC
FOR XML PATH('')), 1, 2, ''), SPACE(0)) AS included_columns_compare
FROM sys.tables t
INNER JOIN sys.indexes i ON t.object_id = i.object_id
LEFT OUTER JOIN sys.dm_db_index_usage_stats ius ON i.object_id = ius.object_id AND i.index_id = ius.index_id AND ius.database_id = db_id()
WHERE t.object_id = @ObjectID OR @ObjectID IS NULL
UNION ALL
SELECT
OBJECT_SCHEMA_NAME(mid.object_id) as schema_name
,OBJECT_NAME(mid.object_id) as table_name
,'--MISSING--'
,'--NONCLUSTERED--'
,(migs.user_seeks + migs.user_scans) * migs.avg_user_impact as impact
,0 as ranking
,migs.user_seeks + migs.user_scans as user_total
,NULL as user_total_pct
,migs.user_seeks
,migs.user_scans
,0 as user_lookups
,COALESCE(equality_columns + ', ', SPACE(0)) + COALESCE(inequality_columns, SPACE(0)) as indexed_columns
,included_columns
,mid.object_id
,NULL
,NULL
,NULL
FROM sys.dm_db_missing_index_details mid
INNER JOIN sys.dm_db_missing_index_groups mig ON mid.index_handle = mig.index_handle
INNER JOIN sys.dm_db_missing_index_group_stats migs ON mig.index_group_handle = migs.group_handle
WHERE database_id = db_id()
AND mid.object_id = @ObjectID OR @ObjectID IS NULL
)
SELECT schema_name
,table_name
,index_name
,type_desc
,impact
,user_total
,user_total_pct
,CAST(100 * (user_seeks + user_scans + user_lookups)
/(NULLIF(SUM(user_seeks + user_scans + user_lookups)
OVER(PARTITION BY schema_name, table_name), 0) * 1.) as decimal(6,2)) as estimated_percent
,user_seeks
,user_scans
,user_lookups
,indexed_columns
,included_columns
,STUFF((SELECT ', ' + index_name AS [data()]
FROM preIndexAnalysis iia
WHERE ia.object_id = iia.object_id
AND ia.index_id <> iia.index_id
AND ia.indexed_columns_compare = iia.indexed_columns_compare
AND ia.included_columns_compare = iia.included_columns_compare
FOR XML PATH('')), 1, 2, '') AS duplicate_indexes
,STUFF((SELECT ', ' + index_name AS [data()]
FROM preIndexAnalysis iia
WHERE ia.object_id = iia.object_id
AND ia.index_id <> iia.index_id
AND (ia.indexed_columns_compare LIKE iia.indexed_columns_compare + '%'
OR iia.indexed_columns_compare LIKE ia.indexed_columns_compare + '%')
AND ia.indexed_columns_compare <> iia.indexed_columns_compare
FOR XML PATH('')), 1, 2, '') AS overlapping_indexes
FROM preIndexAnalysis ia
ORDER BY schema_name, table_name, ROW_NUMBER() OVER (PARTITION BY schema_name, table_name ORDER BY user_total desc, ranking), index_name