1. 2012 © Trivadis BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MÜNCHEN STUTTGART WIEN Welcome November 2012 Columnstore Indexes and Partition Improvements 1 SQL Server 2012 Columnstore Indexes and Table Partitioning Improvements November 2012 Meinrad Weiss

2. 2012 © Trivadis Column Store: Data Warehouse Query Performance Columnstore indexes provide an easy way to significantly improve data warehouse and decision support query performance against very large data sets  Ideal candidates include queries against star schemas that use filtering, aggregations and grouping against very large fact tables Performance improvements for “typical” data warehouse queries from 10x to 100x 2 November 2012 Columnstore Indexes and Partition Improvements

3. 2012 © Trivadis DW Queries in SQL Server 2008 and SQL Server 2012 You need to execute high performance DW queries against very large data sets?  In SQL Server 2008 and SQL Server 2008 R2  OLAP (SSAS) MDX solution  ROLAP and T-SQL + intermediate summary tables, indexed views and aggregate tables -(Inherently inflexible)  In SQL Server 2012  You can create a columnstore index on a very large fact table referencing all columns with supporting data types -Utilizing T-SQL and core Database Engine functionality -Minimal query refactoring or intervention 3 November 2012 Columnstore Indexes and Partition Improvements SQL MDX - Dimensions - Key Figures - Aggregates (Speed) - Link to Excel - Data Mining

4. 2012 © Trivadis Column vs. Row Store November 2012 Columnstore Indexes and Partition Improvements 4 Row Store (Heap / B-Tree) ProductIDOrderDateCost 310200107012’171.29 311200107011’912.15 312200107022’171.29 data page “1000” data page “1001” ProductIDOrderDateCost 313200107014’171.20 314200107041’812.25 315200107021’171.30 ProductID 310 311 312 313 314 315 OrderDate 20010701 20010702 20010704 Cost 2’171.29 1’912.15 2’171.29 4’171.20 1’812.25 1’171.30 data page “2000” data page “2001” data page “2003” Column Store (values compressed)

5. 2012 © Trivadis Creating a columnstore index 5 T-SQL SSMS November 2012 Columnstore Indexes and Partition Improvements

6. 2012 © Trivadis Good Candidates for Columnstore Indexing Table candidates:  Very large fact tables (for example – billions of rows)  use more or less all attributes -Adding additional columns will only have an effect at creation time  (Larger dimension tables (millions of rows) with compression friendly column data)  Update of rows may get quite complex  If unsure, it is easy to create a columnstore index and test the impact on your query workload 6 November 2012 Columnstore Indexes and Partition Improvements Fact Table Many rows Few attributes Fact Table Column Store Index

7. 2012 © Trivadis Supported Data Types Supported data types  Char / nchar / varchar / nvarchar  (max) types, legacy LOB types and FILESTREAM are NOT supported  Decimal/numeric  Precision greater than 18 digits NOT supported  Tinyint, smallint, int, bigint  Float/real  Bit  Money, smallmoney  Date and time data types  Datetimeoffset with scale > 2 NOT supported 7 November 2012 Columnstore Indexes and Partition Improvements

8. 2012 © Trivadis Maintaining Data in a Columnstore Index Once built, the table becomes “read-only” and INSERT/UPDATE/DELETE/MERGE is no longer allowed ALTER INDEX REBUILD / REORGANIZE not allowed Other options are still supported:  Partition switches (IN and OUT)  Drop columnstore index / make modifications / add columnstore index  UNION ALL (but be sure to validate performance) 8 November 2012 Columnstore Indexes and Partition Improvements

9. 2012 © Trivadis Working with Partitions SQL Server 2012 supports up to 15’000 partitions per table Nice new Wizard November 2012 Columnstore Indexes and Partition Improvements 9 Partitioned Table (read only) Range 2012_08 Range 2012_09 Range 2012_10 Range 2012_11 Table Partitioned Table (read only) Switch In ETL Column Store Index Read-only Table Create Column Store index Create Column Store index

10. 2012 © Trivadis BASEL BERN LAUSANNE ZÜRICH DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. HAMBURG MÜNCHEN STUTTGART WIEN Let‘s go. November 2012 Columnstore Indexes and Partition Improvements 10 Wettbewerb