1. SQL Server 2014 - Optimizing Query Plans
Pooja Harjani | Senior Program Manager, SQL Server

2. Meet Pooja Harjani | ‏@pvaswani
Senior Program Manager, SQL Server
Worked on features in Query Processing area in SQL Server 2012 and in In-Memory OLTP technology in SQL Server 2014
Release Manager for SQL Server 2014
Currently working on Query Processing area and In-Memory OLTP technology in SQL Server
Contributed to white papers on partitioning and In-Memory OLTP in SQL Server

3. Course Topics SQL Server 2014 - Optimizing Query Plans
01 | Background on SQL Server Query Optimizer (QO)
02 | New Cardinality Estimator (CE)
03 | Incremental Statistics

4. Setting Expectations Target Audience
DBAs with a background in on-premises SQL Server
Developers with a background in developing for SQL Server
Suggested Prerequisites/Supporting Material
Suggested Reading:
Optimizing your query plans with SQL Server 2014 Cardinality Estimator -

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6. Pooja Harjani | Senior Program Manager, SQL Server
01 | Background on SQL Server Query Optimizer (QO)
Pooja Harjani | Senior Program Manager, SQL Server

7. Module Overview About Query Optimizer (QO) Cardinality Estimation (CE)
Statistics

8. About Query Optimizer (QO)
The QO takes a user query and returns a query plan
Rule-based optimizer
Estimates cost using estimates of the size of a given sub-result (Cardinality Estimates)
First bullet supporting points:
Rearranges the order of operations
Chooses logical and physical operators
Maintains query semantics (many plans have the same semantics)

9. Cardinality Estimation
Estimates the number of rows returned by each operation
Relies on
Basic assumptions (independence, uniformity, etc)
Statistics

10. Statistics
Basic information about the distribution of the data in the table
Used extensively by Cardinality Estimator (CE)
Freshness matters

11. Basic Statistics Terms
Density = 1 / Distinct Value Count
Frequency = Row Count * Density
Selectivity of P= Row Count satisfying P/ Row Count