OPTIMIZED PRODUCTIVITY

Cloud On Your Terms

THE FANTASTIC 12 OF 2012

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BUILD IN A PRODUCTIVE DEV ENVIRONMENT SQL Server Data Tools (SSDT)

SQL SERVER DATA TOOLS

Declarative, model based database development

Integrated tools with modern language services

Connected and offline with local testing

Target SQL Server (2012, 2008 R2, 2008, 2005) and Azure SQL Database

Publish (Direct, via SQL script, or DACPAC)

Support for “Snapshots” - point-in-time representation of the schema

BUILD IN OPEN DEV ENVIRONMENTS Quickly build database applications with Visual Studio, Java, PHP, & Ruby

VISUAL STUDIO 2012

SQL Server database projects (*.sqlproj) are supported in all Visual Studio 2012 SKUs Supported in VS2010 Professional+, with exception of the Express editions

Replaces the Visual Studio 2010 database projects (*.dbproj)

Codebases will be maintained in sync (VS2010 and VS2012)

Project (*.sqplproj) system round trips between VS2010 and VS2012

Free VS2012 hosted SSDT version based on VS2012 Isolated Shell

CONNECTED DEVELOPMENT

PROJECT BASED DEVELOPMENT

SCHEMA DEPLOYMENT

SSDT SCHEMA COMPARE

INTRODUCING DATA TIER APPLICATIONS!

Self contained database entity used by an application Single unit of deployment and lifecycle management

DAC Packages (.dacpac/.bacpac) Authored alongside your application code

Extracted from existing database

Deployable to SQL Server and Windows Azure SQL Databases

Consistent story for database development, migration, and versioning across the SQL Server platform

PACKAGE ARTIFACTS

.dacpac Packaged schema representing the declarative model of the database

Not SQL, but a declarative Schema Model representation of the database

Compiled from source code or Extracted from existing databases

Deploy as new database or Upgrade an existing database

Supports all SQL Server database objects and types

.bacpac Packaged schema and data representing the state of the database

Composed of Schema Model with state-ful properties and Data streams

Exported from existing databases

Imported as a new database or populates an empty database

Supports most SQL Server database objects and types (Azure Parity)

DAC FRAMEWORK (DACFX)

Core SQL Server component providing modeling, reverse engineering, and deployment capabilities

A QUICK DAC HISTORY

DAC 1.0 SQL Server 2008 R2 Utility

VS 2010 SP1 DAC Project

DAC 1.1 – Upgrade in Place

DAC 2.0 – Object support for SQL Azure, BACPAC

DAC 3.0 SQL Server 2012/SQL Server Data Tools

Object support for SQL Server 2005-above, SQL Azure

SUPPORTED VERSIONS

DACFX OBJECT SUPPORT AND COMPAT

SQL Server 2012 DACFx (v3.0) supports full SQL Server database domain SQL Server 2005

SQL Server 2008/R2

SQL Server 2012

Windows Azure SQL Databases

DACFx (v3.0) backwards compatibility Back-compat for DACFx 1.0, 1.1, and 2.0

DAC IN SQL SERVER DATA TOOLS (SSDT)

Developer-focused toolset for authoring, building, and publishing DACPACs Experiences Enabled

Connected Imperative and Declarative Development

Project Based Development

Application Lifecycle & Tools

DACPAC Actions

Build/Snapshot

Compare

Import into Project

Publish

WHAT DOES IT DO?

SQL Server Data Tools/DACFx features include: Building a DACPAC from a set of T-SQL scripts

Extracting a DACPAC from a database

Deploying a DACPAC to a new database

Incrementally upgrading an existing database schema via DACPAC

Exporting a BACPAC from an existing database

Importing a BACPAC to a new/empty database

Schema comparison

Online Database Development Tools

WHAT'S THE POINT?

Provides services around SQL Server Database extraction and packaging

File formats are SQL Server version-independent

DAC features enable Managed database application lifecycle

Schema and data portability

WHAT PROBLEM DOES IT SOLVE?

Meant to simplify deployment across SQL Server release/version differences

Features, T-SQL dialect

SQL Azure vs. SQL Server

T-SQL dialect, other differences

Others…

Migrating database between instances On Prem => SQL Azure and back or between On Prem

DAC IN SQL SERVER MANAGEMENT STUDIO (SSMS)

DBA-focused tools for creating, deploying, and managing DAC packages

DACFX 3.0 IN SSMS 2012

On SQL Server or SQL Azure node in Object Explorer

Databases Folder Deploy (from DACPAC)

Import (from BACPAC)

Local file system or Windows Azure storage

Individual Databases/Tasks Extract

Migrate Database to Azure (using BACPAC)

Export (to BACPAC)

Local file system or Windows Azure storage

Register

Upgrade

Delete (Unregister)

DAC IN AZURE MANAGEMENT PORTAL

DBA-focused tools for creating, deploying, and managing DAC packages

DAC LIFECYCLE

DAC LIFECYCLE

DAC SCENARIOS

NEW QUERY & SCHEMA CONSTRUCTS

Support for Simplified Paging SELECT...

ORDER BY ...

OFFSET <expr> ROWS

FETCH NEXT <expr> ROWS ONLY

Support for UTF-16, introducing _SC collations Common Unicode characters occupy 16-bits each (NCHAR / NVARCHAR)

Rarer Unicode characters occupy 2 x 16-bits each

“Supplementary Characters”, “Surrogate Pairs”

Ancient scripts; Music Notation; Math Symbols etc.

SEQUENCES

New Sequence Object , similar to the IDENTITY property

Separates number-generation from column and table

ANSI standard compliant implementation

EXCEPTIONS & MESSAGES

Use cases: Send progress updates to the application

Log events

Raise & handle exceptions

Options: RAISERROR

xp_logevent

Logging table

NEW: THROW

NEW ERROR HANDLING WITH THROW

THROW <number>, <message>, <state>; Always aborts the batch

Batch aborts if not in SET XACT_ABORT ON where it

transaction-aborts

Does not automatically use sys.messages

Is even spelled correctly!

re-THROW BEGIN CATCH

…;

THROW;

END CATCH

CALCULATIONS & AGGREGATIONS

Use cases: Include aggregations in details

Cumulative sum, averages etc.

Reference other rows in a calculation

Finding gaps, trends, etc.

Options: Imperative programming patterns

Correlated sub queries

NEW: Window Functions

CALCULATIONS ACROSS ROWS

Referencing same row is simple: Transaction cost is $1.5/tran., what was

the total amount?

Amount + 1.5 AS TotalAmount

What about other rows? Current bank balance?

Current account balance?

Number of days since last tran.?

Amount of previous transaction?

WINDOW FUNCTIONS

Calculate the average amount of the last 3 transactions

WINDOW FUNCTIONS

Multiple partitions, e.g. for calculating the balance for different accounts

WINDOW FUNCTIONS

Aggregation AVG, CHECKSUM_AGG, COUNT, COUNT_BIG, MIN, MAX, SUM, STDEV, STDEVP, VAR, VARP

User-defined CLR Aggregates (excl. windowing)

Analytical ROW_NUMBER, NTILE, RANK, DENSE_RANK, CUME_DIST, PERCENT_RANK

Distribution PERCENTILE_CONT, PERCENTILE_DISC

Offset LAG, LEAD, FIRST_VALUE, LAST_VALUE

COMMON TASKS

Use cases: Transform data to and from strings

Constructing date instances

Handle conversion errors

Paging

Options: Write yourself

NEW: Additional scalar functions

ADDITIONAL SCALAR FUNCTIONS

New conversion functions for all types: TRY_CONVERT(data_type[(length)], [,style])

TRY_CAST(expression AS data_type[(length)])

New conversion functions to and from strings: FORMAT(value, format [,culture])

PARSE(string_value AS data_type [USING culture])

TRY_PARSE(string_value AS data_type [,USING culture])

Other functions: IIF(boolean expr, true_value, false_value)

CHOOSE(index,val1,val2 [,valN])

CONCAT(val1, val2…[,valn])

ADDITIONAL SCALAR FUNCTIONS

New date & time related functions: EOMONTH(date [, months_to_add])

DATEFROMPARTS(year, month, day)

TIMEFROMPARTS(hour, minutes, seconds, fractions, scale)

DATETIME2FROMPARTS(year, month, day ,hour, minutes, seconds,

fractions, scale)

DATETIMEFROMPARTS(year, month, day, hour, minutes, seconds, miliseconds)

SMALLDATETIMEFROMPARTS(year, month, day, hour, minutes)

OFFSET / FETCH

Enforce contract for Result Sets for EXEC

SSMS ENHANCEMENTS

CLOUD ENABLE SQL SERVER

Better Integration with Azure Platform Logical backup to Azure Storage

Move database to SQL Azure

Import database from Azure Storage

SQL Azure Management with SSMS Support for Federations

PRODUCTIVITY ENHANCEMENTS Enhanced developer experience

Intellisense Substring matching in completion list

Error handling & performance improvements

Code snippets Use your own code snippets

Share snippets with team members

Keyboard shortcuts default = ‘SQL 2008 R2 compatible’

Assign shortcuts to frequently used stored procedures

Share with team and between SSMS & SQL Studio

PRODUCTIVITY ENHANCEMENTS Better T-SQL debugging

Conditional Breakpoints Breakpoint validation

Expression evaluation in Watch window

DataTips and Pinned DataTips

Features available when debugging… SQL Server 2005

SQL Server 2008

SQL Server 2008 R2 instances

PRODUCTIVITY ENHANCEMENTS Management

Log Viewer View SQL Server logs for offline + online instances

Improved Search & Better performance

Database Recovery Advisor Spend lesser time on restore operations

Analyze backup files from a folder (not just from msdb)

‘Point in Time’ & Page Level restores

Construct correct & optimal restore sequence

Check for corrupted pages

Extended Events

AZURE SQL DATABASE MANAGEMENT PACK FOR SCOM

BEYOND RELATIONAL IN SQL SERVER 2012

Address important customer requests for Capabilities and rich services for Rich Unstructured Data (RUDS) Scale Up for storage and search to 100mio to 500mio documents

Easy use/access to Unstructured data from all applications

Rich insight into unstructured data to make better decisions

We deliver what you asked for to build Spatial-aware

Applications Advanced 2D Spatial

Make Spatial pervasive across platform

Developer Agility Part of the Paradigms driving NoSQL adoption

Can easily evolve data tier driven by Application and Business requirements from within the

Application

Multi-Tenancy with heterogeneous schemas

Databases with heterogeneous record types in a table Type specific properties, inherited properties in a type hierarchy

Examples: Product catalogs (Commerce Server), Location/business specific properties (Maps)

Item-Level Property bag scenarios Distinct customized property sets associated with data

Large number of unique properties, user annotations

Examples: Document management systems (SharePoint), Media stores

Large number of sparsely populated properties

Distinct property sets

Heterogeneous structures

Evolving and co-existing structures

Sets, nested structures

Forum and mailing list threads

Business organization charts

Content management categories

Product categories

Files/folders management

A system data type with variable length CLR UDT

Microsoft.SqlServer.Types

Varbinary encoding ( < 900 bytes)

To represent position in a hierarchy

Logically encodes the path from the root of the tree to a node

Rich built-in methods for manipulating hierarchies

Simplifies storage and querying of hierarchical data

Comparison a<b is in depth-first order

Support for arbitrary insertions and deletions

Pro: Simple range scans to find descendants or ancestors with QP support

(trie-statistics)

Provide depth first clustering

Simple query for specific ID or IDs of a parent/children (benefits from

clustering)

Cons: Programming model not the easiest

Nesting level limited by the datatype size (but still enough)

Wide Sparse Table: only rows that have a value for the property have a value, others are NULL

“Sparse” as a storage attribute on a column Storage Optimization: 0 bytes stored for a NULL value

Co-location of data: Performance benefits

NULL Compression in the TDS layer

No change in Query/DML behavior

Wide Tables/Column Sets Large number of sparse columns allowed in a table (30,000 Columns, 1000 indexes, 30,000 statistics)

Requires defining a “Sparse Column Set”

An un-typed XML column, with a published format

Logical grouping for all sparse columns in a table

Select * returns all non-sparse-columns, sparse column set (XML)

Allows generic retrieval/update of all sparse columns as a set

SPARSE COLUMN STORAGE

0 Bytes stored for NULL Values ~20% CPU overhead for non-null value access

Additional 2- 4 bytes for non-null values

Sparse columns are beneficial when space savings >40%

FILTERED INDEXES

Filtered Indexes and Statistics Indexing a portion of the data in a table

Filtered/co-related statistics creation and usage

Query/DML Optimization to use filtered indexes and statistics

Restrictions Simple limited grammar for the predicate

Only on non-clustered indexes

Benefits Lower storage and maintenance costs for large number of indexes

Query/DML performance benefits: IO only for qualifying rows

XML is ubiquitous, extensible, platform independent transport format

Message Envelope in XML Simple Object Access Protocol (SOAP), RSS, REST

Message Payload/Business Data in XML

Vertical Industry Exchange schemas

XHTML, DocBook, Home-grown, domain-specific markup (e.g. contracts), OpenOffice, Microsoft Office

XML (both default and user-extended)

Storing and querying heterogeneous complex objects

Semistructured data with sparse, highly-varying structure at the instance level

XML provides self-describing format and extensible schemas

Is format used by COLUMNSET

NEW XQUERY ALGEBRA OPERATORS XML Reader TVF

Table-Valued Function XML Reader UDF with XPath Filter

Used if no XML Index is present

Creates node table rowset in query flow

Multiple XPath filters can be pushed in to reduce node table to subtree

Base cardinality estimate is always 10’000 rows!

Some adjustment based on pushed path filters

NEW XQUERY ALGEBRA OPERATORS UDX

Serializer UDX serializes the query result as XML

XQuery String UDX evaluates the XQuery string() function

XQuery Data UDX evaluates the XQuery data() function

Check UDX validates XML being inserted

UDX name visible in SSMS properties window

XML INDICES

Create XML index on XML column CREATE PRIMARY XML INDEX idx_1 ON docs (xDoc)

Create secondary indexes on tags, values, paths

Creation: Single-threaded only for primary XML index

Multi-threaded for secondary XML indexes

Uses: Primary Index will always be used if defined (not a cost based decision)

Results can be served directly from index

SQL’s cost based optimizer will consider secondary indexes

Maintenance: Primary and Secondary Indices will be efficiently maintained during updates

Only subtree that changes will be updated

No online index rebuild

Clustered key may lead to non-linear maintenance cost

Schema revalidation still checks whole instance

EXAMPLE INDEX CONTENTS

PRIMARY XML INDEX

SECONDARY XML INDICES

SOME CUSTOMER WORKLOAD COMPARISONS

FILESTREAM

SCALE-UP & ALWAYSON SUPPORT

FILETABLE OVERVIEW

CREATING A FILETABLE

MODIFYING A FILETABLE

DATA ACCESS – FILE SYSTEM ACCESS

DATA ACCESS – T-SQL ACCESS

MANAGING FILETABLE

MANAGING FILETABLE – HIGH AVAILABILITY

UNSTRUCTURED DATA SCALE-UP Multiple containers for FILESTREAM data

UNSTRUCTURED DATA: MULTIPLE CONTAINERS

Use of multiple spindles for achieving better I/O Scalability

RUDS SCALE-UP: FILESTREAM PERF/SCALE

SUMMARY: FILETABLE

SPATIAL DATA IN SQL SERVER

Storage and retrieval of spatial data using standard SQL syntax Spatial Data Types (geometry, geography)

Spatial Methods (intersects, buffer, etc.)

Spatial Indexes

Offers full set of Open Geospatial Consortium components (OGC/SQL MM, ISO 19125)

Spatial Builder Interface

SQL Server Management Studio visualization

Integration with Bing Maps

Integration with Reporting Services

COMPREHENSIVE SPATIAL SUPPORT Spatial data types

OTHER NEW TYPE FEATURES IN SQL SERVER 2012

CREATING SPATIAL OBJECTS

USING SPATIAL OBJECTS

SPATIAL FORMAT EXAMPLE

CIRCULAR ARCS Geography type considerations

If a circular linestring encloses an area, a

curve polygon can be created

CURVEPOLYGON (CIRCULARSTRING

(0 50, 90 50, 180 50, 270 50, 0 50))

Coordinate pair order is important for the

geography type. This set of coordinates is

ordered according to the “left foot rule” for

exterior rings.

PERFORMING SPATIAL OPERATIONS

Find streets that intersect the Microsoft campus SELECT StreetName

FROM Streets

WHERE Streets.StreetGeo.STIntersects(@ms) = 1

CONVERT EXISTING DATA TO SPATIAL DATA

CONVERT EXISTING DATA TO SPATIAL DATA

SPATIAL REFERENCE ID (SRID)

HIGH PERFORMANCE SPATIAL CAPABILITIES Spatial indexing

Spatial indexing is built into the query engine Grid-based quad-tree index structure

Query optimizer determines cost-based query plans

PERFORMANCE ENHANCEMENTS FOR SPATIAL APPLICATIONS IN SQL SERVER 2012

Support Persisted computed spatial columns

New geodetic SRID for faster calculations

Improved implementation of operations Faster Spatial index creation for point data (4 to 5 times faster)

Faster point data queries

Optimized STBuffer, lower memory footprint

Faster “secondary” filter step

Improved default spatial indexing scheme and new hints AutoGrid

Query Window Grid density hint

Spatial Index Compression

Improved index-aware query plans Nearest Neighbor

Optimized spatial query plan for STDistance and STIntersects like queries

WHAT IS NEW IN AZURE SPATIAL SUPPORT

New Methods GEOGRAPHY Parity with GEOMETRY TYPE: STContains, STOverlaps etc

New Capabilities:

AsBinaryZM(), IsValidDetailed(), ShortestLineTo()

Spatial Aggregators:

CollectionAggregate, ConvexHullAggregate, EnvelopeAggregate*, UnionAggregate

Better Performance Nearest Neighbor Query Plan

Persisted Computed Spatial Columns

UnitSphere SRID 104001 for GEOGRAPHY

STATISTICAL SEMANTIC SEARCH

Semantic Insight into textual content Uses language models to find most important keywords in document

No need to build brittle ontologies!

Statistically Prominent Keywords

Autogenerated tag clouds

Potentially Related Content based on extracted Keywords, such as

Similar Products (based on description)

Similar Jobs or Applicants

Similar Support Incidents (based on call logs)

Potential Solutions (based on similar incidents)

First class usage experience Efficent linear algorithms

Integrated with FTS and SQL

New Rowset functions for all results using SQL query

SEMANTIC SIMILARITY

FUNCTIONAL SURFACE: INITIATE SEMANTICS

Create / Alter Full-Text with Semantics Makes internal design dependency on FTS explicit

BETTER CLOUD MANAGEMENT SYSTEM CENTER 2012

Virtual Machine Manager

› P2V conversion of SQL Server instances

› Conversion of virtual SQL Server

instances from VMware Hyper-V

› Faster creation of SQL Server VMs

based on pre-built template with SQL

Server SysPrep

› Creation of database application

profiles inside SQL Server VMs based

on SQL Server data-tier applications

(DACs)

› Creation & management of private

cloud based on SQL Server VMs

App Controller

› Self-Service, role-based management of SQL Server

VMs in private cloud & public cloud

› Deployment of SQL Server VM across multiple private

cloud environments

› Deployment of SQL Server VM from private

to public cloud

BETTER CLOUD MANAGEMENT WITH WINDOWS SERVER TECHNICAL BENEFITS

NEXT STEPS

SQL Server 2012 Case Studies: http://www.microsoft.com/casestudies/Case_Study_Advanced_Search.aspx

(Search on SQL Technologies)

SQL Server 2012 Hands On Labs: http://www.microsoft.com/sqlserver/en/us/learning-center/virtual-labs.aspx

SQL Server 2012 Certification: http://www.microsoft.com/learning/en/us/certification/cert-sql-server.aspx

SQL Server 2012 Best Practices: http://technet.microsoft.com/en-us/sqlserver/bb671430

© 2011 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation.

MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

© 2011 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.

The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation.

MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.