1. Updating your Database Management Skills to Microsoft® SQL Server® 2014 Jump Start
Graeme Malcolm | Data Technology Specialist, Content Master
Pete Harris | Learning Product Planner, Microsoft

2. Graeme Malcolm | ‏@graeme_malcolm
Microsoft Data Platform Specialist
Consultant, trainer, and author since SQL Server 4.2
One of the world’s first MCSEs in SQL Server 2012 BI
(Fairly) regular blogger at
Longstanding partner with Microsoft
Lead author for Microsoft Official Curriculum SQL Server 2014 courses
Contributing author of Patterns and Practices Guide to Big Data
Author of numerous training courses and Microsoft Press titles since SQL Server 7.0

3. Pete Harris | @SQLPete Learning Product Planner
Various roles at Microsoft since 1995

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5. Course Topics
Updating your Database Management Skills to Microsoft® SQL Server® 2014
01 | Making the Most of Memory
04 | Always On High Availability
02 | Mastering Your Data
05 | Managing Security
03 | Managing Data Quality
06 | SQL Server and the Cloud

6. Setting Expectations Target Audience
Database professionals familiar with SQL Server 2008
Suggested Prerequisites/Supporting Material
Experience managing SQL Server 2008 databases
Familiarity with Transact-SQL

7. The Road to SQL Server 2014 SQL Server 2014 2008 2010 2012 2014
Audit
Compression
Change Data Capture
Data Collector
Resource Governor
Policy-Based Management
PowerShell provider
Spatial Data
Filestream Data
SQL Server 2008 R2
Multi-Server Admin
Data-Tier Applications
PowerPivot
Report Builder 2.0
Master Data Services
Prepared Instances
StreamInsight
SQL Server 2012
AlwaysOn High Availability
Columnstore Indexes
Contained databases
User-Defined Server Roles
Data Quality Services
SSAS Tabular Mode
SSIS Catalog
SSRS Power View
SSRS Data Alerts
Deploy to SQL Azure
SQL Server 2014
Windows Server 2008
Windows Server 2012
Windows Server 2012 R2 OS
Windows Server 2008 R2
System Center 2007
System Center 2012
System Center 2012 R2
SQL Database Services (REST)
SQL Azure
Windows Azure SQL Database
Azure
Marketplace Data Market
SQL Server in VMs
Windows Azure HDInsight
Office 2007
Data Mining Add-Ins (Excel)
Office 2010
PowerPivot (Excel/SP)
Office 2013
Power View(Excel)
O365 Power BI
Office
Power Query
Power Map
Shared Queries
Q&A
MDS Add-in (Excel)

8. 01 | Making the Most of Memory
Graeme Malcolm | Data Technology Specialist, Content Master
Pete Harris | Learning Product Planner, Microsoft

9. Module Overview The Buffer Pool Extension Columnstore Indexes
Memory-Optimized Tables

10. Buffer Pool Extension Extends buffer cache to non- volatile storage
Improves performance for read- heavy OLTP workloads
SSD devices are often more cost- effective than adding physical memory
Simple configuration with no changes to existing applications.
Data files
(Disk)
Buffer cache
(RAM)
Buffer pool extension
(SSD)
Pages
Clean Pages

11. Demo: The Buffer Pool Extension
In this demonstration, you will see how to:
Enable the Buffer Pool Extension
Verify Buffer Pool Extension Configuration
Disable the Buffer Pool Extension

12. Columnstore Indexes
In-memory, compressed data in pages based on columns instead of rows
Row Store
Column Store
ProductID
OrderDate
Cost
310
311
312
313
413.14
ProductID
310
311
312
313
314
315
316
317
318
319
320
321
OrderDate …
Cost
413.14
333.42
641.22
24.95
64.32
Data page 1000
ProductID
OrderDate
Cost
314
333.42
315
316
317
641.22
Data page 1001
Data page 2000
Data page 2001
Data page 2002

13. Types of Columnstore Index
Clustered Columnstore Indexes
SQL Server 2014 Enterprise, Developer, and Evaluation Edition Only
Includes all columns in the table
Only index on the table
Optimizes storage for compression and performance
Updatable
Non-Clustered Columnstore Indexes
Includes some or all columns in the table
Can be combined with other indexes
Read-Only

14. Updating Clustered Columnstores
ProductID
310
311
312
313
OrderDate
Cost
413.14
Deltastore
ProductID
OrderDate
Cost
314
311
316
403.34
Columnstore
A row-based deltastore stores interim changes
New rows are inserted into the deltastore until the minimum rowgroup size is reached.
Deleted rows in the deltastore are physically deleted. Columnstore data is marked as deleted, and space is reclaimed when the index is rebuilt.
Updated rows in the deltastore are modified. Columnstore data is marked as deleted and a new row is added to the deltastore.

15. Updating Nonclustered Columnstores
Drop and recreate columnstore indexes
Partition the table and switch in new rows
Switched table must have a matching columnstore index
Use Trickle Updating:
Store only static data in the columnstore table
Create a matching delta table for dynamic data rows
Use UNION or Common Table Expressions to retrieve data
Periodically move stabilized rows from the delta table to the columnstore table using one of the above techniques

16. Demo: Columnstore Indexes
In this demonstration, you will see how to:
View Logical Reads for a Query
Create a Non-Clustered Columnstore Index
Create a Clustered Columnstore Index
View Columnstore Index Metadata
View Logical Reads for a Query
If you did not perform the previous demonstrations in this module, start the MIA-DC and MIA-SQL virtual machines, and log on to MIA-SQL as ADVENTUREWORKS\Student with the password XXXXXXXXXXXXX. Then in the D:\Demofiles\Mod03 folder, right-click Setup.cmd and click Run as administrator. When prompted, click Yes.
If it is not already open, start SQL Server Management Studio and connect to the MIA-SQL instance of SQL Server using Windows authentication.
Open DWQuery.sql from the D:\Demofiles\Mod03 folder. Note that this script performs the following actions:
Runs a query so that the required data is cached for future executions.
Sets statistics options on so that details of the query execution can be retrieved.
Runs the query again to retrieve the statistics.
Sets the statistics options off again.
Execute the script, and then wait until execution is complete and two results sets are displayed.
On the Messages tab, note the elapsed time in the last line of the statistics report.
Create a Non-Clustered Columnstore Index
Open ColumnStoreIndex.sql from the D:\Demofiles\Mod03 folder.
Select the code under the comment Create a non-clustered columnstore index and click Execute. That this script creates a non-clustered columnstore index on the FactProductInventory table.
Return to the DWQuery.sql tab. Then execute the script, and wait until execution is complete and two results sets are displayed.
On the Messages tab, note the elapsed time in the last line of the statistics report. This should be significantly lower than the previous execution.
Return to the ColumnStoreIndex.sql tab and select the code under the comment Try to insert a row. Then click Execute.
Note that an error occurs because you cannot modify a table on which a non-clustered columnstore index has been created.
Create a Clustered Columnstore Index
Select the code under the comment Drop the non-clustered columnstore index, existing clustered index, and foreign keys, and then click Execute. This drops all of the existing indexes on the table.
Select the code under the comment Create a clustered columnstore index and click Execute. This creates a clustered columnstore index on the FactProductInventory table.
On the Messages tab, note the elapsed time in the last line of the statistics report. This should still be significantly lower than the first execution.
Return to the ColumnStoreIndex.sql tab and select the code under the comment Insert a row. Then click Execute.
Note that you can insert data into a clustered columnstore index.
View Columnstore Index Metadata
Select the code under the comment View row groups and click Execute.
Note that this code retrieves information about the columnstore index, and shows that the row you inserted is in a deltastore rowgroup, while the previously existing rows are all compressed in the columnstore.

17. Memory-Optimized Tables
Defined as C structs, compiled into DLLs, and loaded
into memory
Can be persisted as filestreams, or non-durable
Do not apply any locking semantics
Can be indexed using hash indexes
Can co-exist with disk-based tables
Can be queried using Transact-SQL
Cannot include some data types, including text, image, and nvarchar(max)
Do not support identity columns or foreign key constraints

18. Memory-Optimized Table Scenarios
Optimistic concurrency optimizes latch-bound workloads:
Multiple concurrent transactions modify large numbers of rows
A table contains “hot” pages
Applications should handle conflict errors:
Write conflicts
Repeatable read validation failures
Serializable validation failures
Commit dependency failures

19. Creating Memory-Optimized Tables
Add a filegroup for memory-optimized data
Create a memory-optimized table
ALTER DATABASE MyDB
ADD FILEGROUP mem_data CONTAINS MEMORY_OPTIMIZED_DATA; GO
ADD FILE (NAME = 'MemData' FILENAME = 'D:\Data\MyDB_MemData.ndf')
TO FILEGROUP mem_data;
CREATE TABLE dbo.MemoryTable
(OrderId INTEGER NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 1000),
OrderDate DATETIME NOT NULL,
ProductCode INTEGER NULL,
Quantity INTEGER NULL)
WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA);

20. Memory-Optimized Indexes
Hash Indexes
Rows assigned to buckets based on hashed key
Multiple rows in the same bucket form a linked list
Effective for equality predicates
Query results are not sorted
Range Indexes
Latch free, in-memory B-Tree structure
Effective for range scans, equality predicates, and inequality predicates
CREATE TABLE tab1
(col1 INT NOT NULL INDEX h_idx NONCLUSTERED HASH
WITH (BUCKET_COUNT = 100))
WITH (MEMORY_OPTIMIZED = ON,
DURABILITY = SCHEMA_ONLY)
CREATE TABLE tab2
(col1 INT NOT NULL INDEX r_idx NONCLUSTERED)
WITH (MEMORY_OPTIMIZED = ON,
DURABILITY = SCHEMA_ONLY)

21. Querying Memory-Optimized Tables
Query Interop
Interpreted Transact-SQL
Enables queries that combine memory-optimized and disk- based tables
Native Compilation
Stored procedure converted to C and compiled
Access to memory-optimized tables only
Native Compilation
CREATE PROCEDURE…
#define __in
HRESULT hkp_(…
Transact-SQL
SELECT t1.col1, t3.col2
FROM Tab1 t1
JOIN Tab2 t2
ON t1.Col1 = t2.col1;
Translate to C
Compile to DLL
Query Interop
Memory-Optimized Tables
Disk-Based
Tables
Tab1
Tab2
Tab3
Tab4

22. Creating Native Stored Procedures
Use the CREATE PROCEDURE statement
NATIVE_COMPILATION option
SCHEMABINDING option
EXECUTE AS option
BEGIN ATOMIC clause (isolation level and language)
CREATE PROCEDURE INT
WITH NATIVE_COMPILATION, SCHEMABINDING, EXECUTE AS OWNER AS
BEGIN ATOMIC WITH
(TRANSACTION ISOLATION LEVEL = SNAPSHOT;
LANGUAGE = 'us_English')
DELETE dbo.OpenOrders WHERE CustomerID
DELETE dbo.Customer WHERE CustomerID
END;

23. Demo: Memory-Optimized Tables
In this demonstration, you will see how to:
Enable Memory-Optimized Tables in a Database
Create a Memory-Optimized Table
Query Memory-Optimized Tables
Create a Natively Compiled Stored Procedure
View Memory-Optimized Table Statistics

24. Module Summary Make the most of memory
Use solid state storage to extend the buffer pool
Use columnstore indexes for data warehouse workloads
Use memory-optimized tables and native stored procedures for latch- bound workloads