En esta sesión revisaremos de que se trata el CE en SQL Server 2014, cómo nos beneficia, y consideraciones a tomar en cuanto en una migración a esta versión.

1. Cardinality Estimator en SQL Server 2014. ¿Qué es? Y
cómo nos beneficia?
11 de Marzo 2015 (12 pm GMT -5)
Percy Reyes
Resumen:
En esta sesión revisaremos de que se trata el
CE en SQL Server 2014, cómo nos beneficia,
y consideraciones a tomar en cuanto en una
migración a esta versión.
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7. Cardinality Estimator en SQL Server 2014.
¿Qué es? Y cómo nos beneficia?
11 de Marzo de 2015
Percy Reyes
Microsoft SQL Server MVP
Sr. SQL DBA with over 10 years
Author at MSSQLTips.com | SQL PASS Peru Chapter Leader
MCITP DBA, MCITP Dev, MCTS, MCP
www.percyreyes.com
Moderador: José L. Rivera

8. Agenda
What inputs is used by the Query Optimizer
What is CE?
The importance of CE
New deployments vs upgrade
Validating a Query’s Cardinality Estimator Version
Why can query plans change with the new CE?
How to control new cardinality estimator
Recommendations
Guidelines on query performance troubleshooting with new CE

9. What inputs is used by the Query Optimizer
- The SQL Query and/or Stored Procedure
- If the query or stored procedure is parameterized, then the value of the parameters
- Knowledge about the index structures of table(s) to be accessed
- Statistics of index(es) and columns of the table(s) to be accessed
- Hints assigned to the query
- Global max degree of parallelism setting
- Hardware Settings (How many CPUs, How much RAM, Disk Subsystem configuration)

10. What is CE?
- Cardinality estimations are predictions of final row count and row counts of intermediate results (such as joins, filtering and aggregation. The
component which does cardinality estimation is called Cardinality Estimator (CE) .
- Prior to SQL Server 2014, cardinality estimator was largely based on SQL Server 7.0 code base.
- The cardinality Estimator has been redesigned.

11. The importance of CE
- Under estimating rows can lead to:
- The selection of serial plan when parallelism would have been more optimal.
- Inappropriate join strategies.
- Inefficient index selection and navigation strategies.
- Memory spills to disk, for example, where not enough memory was requested for sort or
hash operations
- Inversely, over estimating rows can lead to:
- Selection of a parallel plan when a serial plan might be more optimal.
- Inappropriate join strategy selection.
- Inefficient index navigation strategies (scan versus seek).
- Inflated memory grants.
- Wasted memory and unnecessarily throttled concurrency.
So, improving the accuracy of row estimates can improve the quality of the query execution
plan and, as a result, improve the performance of the query.

12. New deployments vs upgrade
- SQL Server 2014 uses database compatibility level to determine if new cardinality estimator
will be used
- You will continue to use old cardinality estimator in upgrade and restore situations by
default unless you have manually changed the compatibility level to be 120.
- You will use cardinality estimator based on current database under the query is compiled
(even though the query references temp table)
- Regarding upgrade of system databases:
- model, msdb and tempdb will be changed to 120
- master system database retains the compatibility level it had before upgrade

13. Validating a Query’s Cardinality Estimator Version
In the SQL 2014 XML plan, check the new attribute in StmtSimple called CardinalityEstimationModelVersion
- Capturing a new SQL Server 2014 XEvent called query_optimizer_estimate_cardinality

14. Why can query plans change with the new CE?
1. The new CE is calculating combined filter density/selectivity differently
The way how the CE calculates the selectivity of a combination of filters submitted with a query
- With Old CE:
- Treating the selectivity/density of each filter/column independently
- Old calculation formula: d1 * d2* d3* d4* … dn
- Row Estimated=# Total of rows / (1/combined density)
- With NEW CE:
- Combinations of values of different columns are not as independent.
- New CE works based on a new calculation formula to calculate combined density of filters.
- The NEW calculation formula now would d1 * d2^(1/2) * d3^(1/4) * d4^(1/8)
- Row Estimated=# Total of rows / (1/combined density)

15. Why can query plans change with the new CE?
2. The new CE is treating ascending/descending key scenarios differently
What if we would add a new value out of the range values of an statistics?
- An update statistics with FULLSCAN was performed and after a new value is added, which would be
out of the range of the column statistics, then the new CE would estimate 1 row. The same behavior is
for old CE.
- An update statistics performed in the default sampling and after a new value is added, which would
be out of the range of the column statistics, then the new CE also will now report an estimate of
around 1000 rows. The old CE would estimate 1 row.
- An update statistics performed in the default sampling or with FULLSCAN and after several NEW
values are added, which would be out of the range of the column statistics, then the new CE also will
now report an estimate of around 1000 rows.
IMPORTANT: The # of rows estimated which are found outside the boundaries of the statistics will
be majorly impacted by the # of values and their occurrence in the column according to the
statistics.
- What if we would add a new value within the range values of an statistics?
- The behavior here is not too much different between the old and the new CE
- The new as well as the old CE would return an estimate of 1 row only

16. How to control new cardinality estimator
Trace flag at query level
- You use QUERYTRACEON hint
- Example: SELECT* FROM Product where ProductId= 4672 OPTION(QUERYTRACEON 2312)
Trace flags at server level
- Flag 2312 is used to force new cardinality estimator
- Flag 9481 is used to force old cardinality estimator
- If you enable both trace flags, neither will be used. Instead, database compatibility level will determine
which version of cardinality estimator to be used
Trace flag at database level
- Via database compatibility level
Order of Precedente

17. Recommendations
- Before changing to the new CE in production, test all critical workloads using representative data in a
production-like environment.
- If you cannot change or fully test the existing application, you can still migrate to SQL Server 2014.
However, the database compatibility level should remain below 120 until you can perform thorough
testing.
- To leverage new SQL Server 2014 features without activating the new CE, change to the latest database
compatibility level and enable trace flag 9481 at the server level. Use DBCC TRACEON with the -1
argument to enable the trace flag globally. As an alternative, you can use the –T startup option to enable
the trace flag during SQL Server startup.
- If creating a new database for a new application, use database compatibility level 120 by default.

18. Guidelines on query performance troubleshooting
with new CE
- Statistics
- Make sure you enable auto update and auto create statistics for the database
- If you have large tables, you may need to schedule jobs to manually update statistics.
- Tune your indexes
- XML Plan will display missing index warning for a query
- Missing index DMVs
- Database Tuning Advisor (DTA) can be used to help you tune a specific query
- Analyze the execution plans to detect and fix any index performance issue
- Constructs not significantly addressed by the new cardinality estimator
- Table variables. You will continue to get low estimate (1) for table variables.
- Multi-statement table valued function (TVF): Multi-statement TVF will continue to get estimate of
100 instead of 1 in earlier version. But this can still cause issues if your TVF returns many rows.
- Behaviors of Table valued parameter (TVP) and local variables are unchanged. The number of rows
of TVP at compile time will be used for cardinality estimate regardless if the rows will change for
future executions. Local variables will continued to be optimized for unknown.

19. Thank You: Q&A
PERCY REYES
• Twitter: @percyreyes
• Blog: mssqlinternals.com
• percy.reyes@live.com
• Website: www.percyreyes.com
sqlpassperu.com

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Resúmen:
Power Query es una nueva herramienta de la familia Power BI que se
encarga del proceso de extracción y transformación de datos. Ha sido
catalogada como una de las mejores herramientas para Excel en salir al
mercado por parte de Microsoft en los últimos años y en esta sesión
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