statistics are up to date, but estimate is incorrect When I do dbcc show_statistics ('Reports_Documents', PK_Reports_Documents) I get the following result for Report ID 18698: 



For this query:

SELECT * 
FROM Reports_Documents 
WHERE ReportID = 18698 option (recompile)


I get a query plan that makes a Clustered Index Seek on PK_Reports_Documents as expected. 

But what baffles me is the incorrect value for Estimated Number of Rows:



According to this:


  When the sample query WHERE clause value is equal to a histogram
  RANGE_HI_KEY value, SQL Server will use the EQ_ROWS column in the
  histogram to determine the number of rows that are equal to 


This is also the way I would expect it to be, however it seems not to be the case in real life. I also tried some other RANGE_HI_KEY values that were present in the histogram provided by show_statistics and experienced the same. This issue in my case seems to cause some queries to use very unoptimal execution plans resulting in an execution time of a few minutes whereas I can get it to run in 1 sec with a query hint.

All in all: Can someone explain me why is EQ_ROWS from the histogram not being used for the Estimated Number of Rows and where does the incorrect estimate come from?

A bit more (possibly helpful) info: 


Auto create statistics is on and all the statistics are up to date.
The table being queried has about 80 million rows.
PK_Reports_Documents is a combination PK consisting of ReportID INT and DocumentID CHAR(8)


The query seems to load a total of 5 different statistics objects, all of which contain ReportID + some other columns from the table. They have all been freshly updated. RANGE_HI_KEY in the table below is the highest upper bound column value in the histogram.

+-------------------------------------------------------------------------+----------+--------------+--------------+---------------------+--------------+------------+----------+---------------------+----------------+
|                                  name                                   | stats_id | auto_created | user_created | Leading column Type | RANGE_HI_KEY | RANGE_ROWS | EQ_ROWS  | DISTINCT_RANGE_ROWS | AVG_RANGE_ROWS |
+-------------------------------------------------------------------------+----------+--------------+--------------+---------------------+--------------+------------+----------+---------------------+----------------+
| PK_Reports_Documents                                                    |        1 |            0 |            0 | Stationary          |        18722 | 0          | 2228,526 |                   0 | 1              |
| _dta_index_Reports_Documents_42_1629248859__K1_K63_K14_K13_K22_K23_72_6 |       62 |            0 |            0 | Stationary          |        18698 | 0          | 2228,526 |                   0 | 1              |
| _dta_stat_1629248859_1_1_59                                             |       76 |            0 |            1 | Stationary          |        18686 | 50,56393   | 1        |                   0 | 13397,04       |
| _dta_stat_1629248859_1_22_14_18_12_6                                    |       95 |            0 |            1 | Stationary          |        18698 | 0          | 2228,526 |                   0 | 1              |
| _dta_stat_1629248859_1_7_14_4_23_62                                     |       96 |            0 |            1 | Stationary          |        18698 | 56,63327   | 21641,5  |                   0 | 14526,44       |
+-------------------------------------------------------------------------+----------+--------------+--------------+---------------------+--------------+------------+----------+---------------------+----------------+


sp_updatestats is scheduled to run every night to update stats.
There is a simple solution to this:

Drop all of the _dta_... statistics and stop blindly applying DTA recommendations.

More information

The particular problem was that there were multiple sets of statistics for the column in question. The extra dta statistics were created by sampling the data (the default behaviour for statistics not associated with an index).

As is often the case with sampled statistics, the resulting histograms did not cover the full range of the unerlying data. The query in the question happened to choose a value that was outside the histogram, resulting in a 1-row estimate.

The exact behaviour of the query optimizer when multiple sets of statistics exist for the same column is not fully documented. It does tend to prefer 'full scan' statistics over sampled, but it also prefers more recently-updated statistics to older ones.