OPTIMIZED PRODUCTIVITYCloud On Your Terms
THE FANTASTIC 12 OF 2012        1         2        3    4        5         6        7    8        9        10        11   12
BUILD IN A PRODUCTIVE DEV ENVIRONMENTSQL Server Data Tools (SSDT)
SQL SERVER DATA TOOLSDeclarative, model based database developmentIntegrated tools with modern language servicesConnected ...
BUILD IN OPEN DEV ENVIRONMENTSQuickly build database applications with Visual Studio, Java, PHP & Ruby                    ...
VISUAL STUDIO 2012SQL Server database projects (*.sqlproj) are supported inall Visual Studio 2012 SKUsSupported in VS2010 ...
CONNECTED DEVELOPMENT
PROJECT BASED DEVELOPMENT
SCHEMA DEPLOYMENT
SSDT SCHEMA COMPARE
INTRODUCING DATA TIER APPLICATIONS!Self contained database entity used by an applicationSingle unit of deployment and life...
PACKAGE ARTIFACTS.dacpacPackaged schema representing the declarative model of the database  Not SQL, but a declarative Sch...
DAC FRAMEWORK (DACFX)Core SQL Server component providing modeling, reverseengineering, and deployment capabilities
A QUICK DAC HISTORYDAC 1.0SQL Server 2008 R2 UtilityVS 2010 SP1 DAC ProjectDAC 1.1 – Upgrade in PlaceDAC 2.0 – Object supp...
SUPPORTED VERSIONS
DACFX OBJECT SUPPORT AND COMPATSQL Server 2012 DACFx (v3.0) supports full SQL Serverdatabase domainSQL Server 2005SQL Serv...
DAC IN SQL SERVER DATA TOOLS (SSDT)Developer-focused toolset for authoring, building, andpublishing DACPACsExperiences Ena...
WHAT DOES IT DO?SQL Server Data Tools/DACFx features include:Building a DACPAC from a set of T-SQL scriptsExtracting a DAC...
WHATS THE POINT?Provides services around SQL ServerDatabase extraction and packagingFile formats are SQL Server version-in...
WHAT PROBLEM DOES IT SOLVE?Meant to simplify deployment acrossSQL Server release/version differences  Features, T-SQL dial...
DAC IN SQL SERVER MANAGEMENT STUDIO (SSMS)DBA-focused tools for creating, deploying, and managingDAC packages
DACFX 3.0 IN SSMS 2012On SQL Server or SQL Azure node in Object ExplorerDatabases FolderDeploy (from DACPAC)Import (from B...
DAC IN AZURE MANAGEMENT PORTALDBA-focused tools for creating, deploying, and managingDAC packages
DAC LIFECYCLE
DAC LIFECYCLE
DAC SCENARIOS
NEW QUERY & SCHEMA CONSTRUCTSSupport for Simplified PagingSELECT...ORDER BY ...OFFSET <expr> ROWSFETCH NEXT <expr> ROWS ON...
SEQUENCESNew Sequence Object , similar to the IDENTITY propertySeparates number-generation from column and tableANSI stand...
EXCEPTIONS & MESSAGESUse cases:Send progress updates to the applicationLog eventsRaise & handle exceptionsOptions:RAISERRO...
NEW ERROR HANDLING WITH THROWTHROW <number>, <message>, <state>;Always aborts the batchBatch aborts if not in SET XACT_ABO...
CALCULATIONS & AGGREGATIONSUse cases:Include aggregations in detailsCumulative sum, averages etc.Reference other rows in a...
CALCULATIONS ACROSS ROWS                    Referencing same row is                    simple:                    Transact...
WINDOW FUNCTIONSCalculate the average amount of the last 3 transactions
WINDOW FUNCTIONSMultiple partitions, e.g. for calculating the balance for different accounts
WINDOW FUNCTIONSAggregationAVG, CHECKSUM_AGG, COUNT, COUNT_BIG, MIN, MAX, SUM, STDEV, STDEVP, VAR, VARPUser-defined CLR Ag...
COMMON TASKSUse cases:Transform data to and from stringsConstructing date instancesHandle conversion errorsPagingOptions:W...
ADDITIONAL SCALAR FUNCTIONSNew conversion functions for all types:TRY_CONVERT(data_type[(length)], [,style])TRY_CAST(expre...
ADDITIONAL SCALAR FUNCTIONSNew date & time related functions:EOMONTH(date [, months_to_add])DATEFROMPARTS(year, month, day...
OFFSET / FETCHEnforce contract for Result Sets for EXEC
SSMS ENHANCEMENTS
CLOUD ENABLE SQL SERVERBetter Integration with Azure PlatformLogical backup to Azure StorageMove database to SQL AzureImpo...
PRODUCTIVITY ENHANCEMENTSEnhanced developer experienceIntellisenseSubstring matching in completion listError handling & pe...
PRODUCTIVITY ENHANCEMENTSBetter T-SQL debuggingConditional BreakpointsBreakpoint validationExpression evaluation in Watch ...
PRODUCTIVITY ENHANCEMENTSManagementLog ViewerView SQL Server logs for offline + online instancesImproved Search & Better p...
AZURE SQL DATABASE MANAGEMENT PACK FOR SCOM
BEYOND RELATIONAL IN SQL SERVER 2012Address important customer requests for Capabilities andrich services for Rich Unstruc...
Developer AgilityPart of the Paradigms driving NoSQL adoptionCan easily evolve data tier driven by Application and Busines...
Large number of sparsely populated propertiesDistinct property setsHeterogeneous structuresEvolving and co-existing struct...
Forum and mailing list threadsBusiness organization chartsContent management categoriesProduct categoriesFiles/folders man...
A system data type with variable lengthCLR UDTMicrosoft.SqlServer.TypesVarbinary encoding ( < 900 bytes)To represent posit...
Pro:Simple range scans to find descendants or ancestors with QP support(trie-statistics)Provide depth first clusteringSimp...
Wide Sparse T able: only rows that have a value for the property havea value, others are NULL“Sparse” as a storage attribu...
Wide Tables/Column SetsLarge number of sparse columns allowed in a table (30,000 Columns, 1000 indexes, 30,000 statistics)...
SPARSE COLUMN STORAGE0 Bytes stored for NULL Values~20% CPU overhead for non-null value accessAdditional 2- 4 bytes for no...
FILTERED INDEXESFiltered Indexes and StatisticsIndexing a portion of the data in a tableFiltered/co-related statistics cre...
XML is ubiquitous, extensible, platform independent transport formatMessage Envelope in XML Simple Object Access Protocol ...
                    
NEW XQUERY ALGEBRA OPERATORSXML Reader TVFTable-Valued Function XML Reader UDF with XPath FilterUsed if no XML Index is pr...
NEW XQUERY ALGEBRA OPERATORSUDXSerializer UDXserializes the query result as XMLXQuery String UDXevaluates the XQuery strin...
XML INDICESCreate XML index on XML columnCREATE PRIMARY XML INDEX idx_1 ON docs (xDoc)Create secondary indexes on tags, va...
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-UPMultiple containers for FILESTREAM data
UNSTRUCTURED DATA: MULTIPLE CONTAINERSUse of multiple spindles for achieving better I/O Scalability
RUDS SCALE-UP: FILESTREAM PERF/SCALE
SUMMARY: FILETABLE
SPATIAL DATA IN SQL SERVERStorage and retrieval of spatial data using standard SQL syntaxSpatial Data Types (geometry, geo...
COMPREHENSIVE SPATIAL SUPPORTSpatial data types
OTHER NEW TYPE FEATURES IN SQL SERVER 2012
CREATING SPATIAL OBJECTS
USING SPATIAL OBJECTS
SPATIAL FORMAT EXAMPLE
CIRCULAR ARCSGeography type considerationsIf a circular linestring encloses an area, acurve polygon can be createdCURVEPOL...
PERFORMING SPATIAL OPERATIONSFind streets that intersect the Microsoft campusSELECT StreetNameFROM StreetsWHERE Streets.St...
CONVERT EXISTING DATA TO SPATIAL DATA
CONVERT EXISTING DATA TO SPATIAL DATA
SPATIAL REFERENCE ID (SRID)
HIGH PERFORMANCE SPATIAL CAPABILITIESSpatial indexingSpatial indexing is built intothe query engineGrid-based quad-tree in...
PERFORMANCE ENHANCEMENTS FOR SPATIALAPPLICATIONS IN SQL SERVER 2012Support Persisted computed spatial columnsNew geodetic ...
WHAT IS NEW IN AZURE SPATIAL SUPPORTNew MethodsGEOGRAPHY Parity with GEOMETRY TYPE: STContains, STOverlaps etcNew Capabili...
STATISTICAL SEMANTIC SEARCHSemantic Insight into textual contentUses language models to find most important keywords in do...
SEMANTIC SIMILARITY
FUNCTIONAL SURFACE: INITIATE SEMANTICSCreate / Alter Full-Text with SemanticsMakes internal design dependency on FTS expli...
BETTER CLOUD MANAGEMENTSYSTEM CENTER 2012
BETTER CLOUD MANAGEMENT WITH WINDOWS SERVERTECHNICAL BENEFITS Virtual Machine Manager                    App Controller › ...
NEXT STEPSSQL Server 2012 Case Studies:http://www.microsoft.com/casestudies/Case_Study_Advanced_Search.aspx(Search on SQL ...
© 2011 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be...
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck
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Sql server 2012_sp1_08_of_12_optimize_productivity_level300_dark_deck

  1. 1. OPTIMIZED PRODUCTIVITYCloud On Your Terms
  2. 2. THE FANTASTIC 12 OF 2012 1 2 3 4 5 6 7 8 9 10 11 12
  3. 3. BUILD IN A PRODUCTIVE DEV ENVIRONMENTSQL Server Data Tools (SSDT)
  4. 4. SQL SERVER DATA TOOLSDeclarative, model based database developmentIntegrated tools with modern language servicesConnected and offline with local testingTarget SQL Server (2012, 2008 R2, 2008, 2005) and Azure SQL DatabasePublish (Direct, via SQL script, or DACPAC)Support for “Snapshots” - point-in-time representation of the schema
  5. 5. BUILD IN OPEN DEV ENVIRONMENTSQuickly build database applications with Visual Studio, Java, PHP & Ruby ,
  6. 6. VISUAL STUDIO 2012SQL Server database projects (*.sqlproj) are supported inall Visual Studio 2012 SKUsSupported in VS2010 Professional+, with exception of the Express editionsReplaces the Visual Studio 2010 database projects (*.dbproj)Codebases will be maintained in sync (VS2010 and VS2012)Project (*.sqplproj) system round trips between VS2010 and VS2012Free VS2012 hosted SSDT version based on VS2012 Isolated Shell
  7. 7. CONNECTED DEVELOPMENT
  8. 8. PROJECT BASED DEVELOPMENT
  9. 9. SCHEMA DEPLOYMENT
  10. 10. SSDT SCHEMA COMPARE
  11. 11. INTRODUCING DATA TIER APPLICATIONS!Self contained database entity used by an applicationSingle unit of deployment and lifecycle managementDAC Packages (.dacpac/.bacpac)Authored alongside your application codeExtracted from existing databaseDeployable to SQL Server and Windows Azure SQL DatabasesConsistent story for database development, migration, andversioning across the SQL Server platform
  12. 12. PACKAGE ARTIFACTS.dacpacPackaged 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.bacpacPackaged 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)
  13. 13. DAC FRAMEWORK (DACFX)Core SQL Server component providing modeling, reverseengineering, and deployment capabilities
  14. 14. A QUICK DAC HISTORYDAC 1.0SQL Server 2008 R2 UtilityVS 2010 SP1 DAC ProjectDAC 1.1 – Upgrade in PlaceDAC 2.0 – Object support for SQL Azure, BACPACDAC 3.0SQL Server 2012/SQL Server Data ToolsObject support for SQL Server 2005-above, SQL Azure
  15. 15. SUPPORTED VERSIONS
  16. 16. DACFX OBJECT SUPPORT AND COMPATSQL Server 2012 DACFx (v3.0) supports full SQL Serverdatabase domainSQL Server 2005SQL Server 2008/R2SQL Server 2012Windows Azure SQL DatabasesDACFx (v3.0) backwards compatibilityBack-compat for DACFx 1.0, 1.1, and 2.0
  17. 17. DAC IN SQL SERVER DATA TOOLS (SSDT)Developer-focused toolset for authoring, building, andpublishing DACPACsExperiences Enabled Connected Imperative and Declarative Development Project Based Development Application Lifecycle & ToolsDACPAC Actions Build/Snapshot Compare Import into Project Publish
  18. 18. WHAT DOES IT DO?SQL Server Data Tools/DACFx features include:Building a DACPAC from a set of T-SQL scriptsExtracting a DACPAC from a databaseDeploying a DACPAC to a new databaseIncrementally upgrading an existing database schema via DACPACExporting a BACPAC from an existing databaseImporting a BACPAC to a new/empty databaseSchema comparisonOnline Database Development Tools
  19. 19. WHATS THE POINT?Provides services around SQL ServerDatabase extraction and packagingFile formats are SQL Server version-independentDAC features enableManaged database application lifecycleSchema and data portability
  20. 20. WHAT PROBLEM DOES IT SOLVE?Meant to simplify deployment acrossSQL Server release/version differences Features, T-SQL dialectSQL Azure vs. SQL Server T-SQL dialect, other differencesOthers…Migrating database between instancesOn Prem => SQL Azure and back or between On Prem
  21. 21. DAC IN SQL SERVER MANAGEMENT STUDIO (SSMS)DBA-focused tools for creating, deploying, and managingDAC packages
  22. 22. DACFX 3.0 IN SSMS 2012On SQL Server or SQL Azure node in Object ExplorerDatabases FolderDeploy (from DACPAC)Import (from BACPAC) Local file system or Windows Azure storageIndividual Databases/TasksExtractMigrate Database to Azure (using BACPAC)Export (to BACPAC) Local file system or Windows Azure storageRegisterUpgradeDelete (Unregister)
  23. 23. DAC IN AZURE MANAGEMENT PORTALDBA-focused tools for creating, deploying, and managingDAC packages
  24. 24. DAC LIFECYCLE
  25. 25. DAC LIFECYCLE
  26. 26. DAC SCENARIOS
  27. 27. NEW QUERY & SCHEMA CONSTRUCTSSupport for Simplified PagingSELECT...ORDER BY ...OFFSET <expr> ROWSFETCH NEXT <expr> ROWS ONLYSupport for UTF-16, introducing _SC collationsCommon 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.
  28. 28. SEQUENCESNew Sequence Object , similar to the IDENTITY propertySeparates number-generation from column and tableANSI standard compliant implementation
  29. 29. EXCEPTIONS & MESSAGESUse cases:Send progress updates to the applicationLog eventsRaise & handle exceptionsOptions:RAISERRORxp_logeventLogging tableNEW: THROW
  30. 30. NEW ERROR HANDLING WITH THROWTHROW <number>, <message>, <state>;Always aborts the batchBatch aborts if not in SET XACT_ABORT ON where ittransaction-abortsDoes not automatically use sys.messagesIs even spelled correctly!re-THROWBEGIN CATCH …; THROW;END CATCH
  31. 31. CALCULATIONS & AGGREGATIONSUse cases:Include aggregations in detailsCumulative sum, averages etc.Reference other rows in a calculationFinding gaps, trends, etc.Options:Imperative programming patternsCorrelated sub queriesNEW: Window Functions
  32. 32. 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?
  33. 33. WINDOW FUNCTIONSCalculate the average amount of the last 3 transactions
  34. 34. WINDOW FUNCTIONSMultiple partitions, e.g. for calculating the balance for different accounts
  35. 35. WINDOW FUNCTIONSAggregationAVG, CHECKSUM_AGG, COUNT, COUNT_BIG, MIN, MAX, SUM, STDEV, STDEVP, VAR, VARPUser-defined CLR Aggregates (excl. windowing)AnalyticalROW_NUMBER, NTILE, RANK, DENSE_RANK, CUME_DIST, PERCENT_RANKDistributionPERCENTILE_CONT, PERCENTILE_DISCOffsetLAG, LEAD, FIRST_VALUE, LAST_VALUE
  36. 36. COMMON TASKSUse cases:Transform data to and from stringsConstructing date instancesHandle conversion errorsPagingOptions:Write yourselfNEW: Additional scalar functions
  37. 37. ADDITIONAL SCALAR FUNCTIONSNew 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])
  38. 38. ADDITIONAL SCALAR FUNCTIONSNew 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)
  39. 39. OFFSET / FETCHEnforce contract for Result Sets for EXEC
  40. 40. SSMS ENHANCEMENTS
  41. 41. CLOUD ENABLE SQL SERVERBetter Integration with Azure PlatformLogical backup to Azure StorageMove database to SQL AzureImport database from Azure StorageSQL Azure Management with SSMSSupport for Federations
  42. 42. PRODUCTIVITY ENHANCEMENTSEnhanced developer experienceIntellisenseSubstring matching in completion listError handling & performance improvementsCode snippetsUse your own code snippetsShare snippets with team membersKeyboard shortcutsdefault = ‘SQL 2008 R2 compatible’Assign shortcuts to frequently used stored proceduresShare with team and between SSMS & SQL Studio
  43. 43. PRODUCTIVITY ENHANCEMENTSBetter T-SQL debuggingConditional BreakpointsBreakpoint validationExpression evaluation in Watch windowDataTips and Pinned DataTipsFeatures available when debugging…SQL Server 2005SQL Server 2008SQL Server 2008 R2 instances
  44. 44. PRODUCTIVITY ENHANCEMENTSManagementLog ViewerView SQL Server logs for offline + online instancesImproved Search & Better performanceDatabase Recovery AdvisorSpend lesser time on restore operationsAnalyze backup files from a folder (not just from msdb)‘Point in Time’ & Page Level restores Construct correct & optimal restore sequence Check for corrupted pagesExtended Events
  45. 45. AZURE SQL DATABASE MANAGEMENT PACK FOR SCOM
  46. 46. BEYOND RELATIONAL IN SQL SERVER 2012Address important customer requests for Capabilities andrich services for Rich Unstructured Data (RUDS)Scale Up for storage and search to 100mio to 500mio documentsEasy use/access to Unstructured data from all applicationsRich insight into unstructured data to make better decisionsWe deliver what you asked for to build Spatial-awareApplicationsAdvanced 2D SpatialMake Spatial pervasive across platform
  47. 47. Developer AgilityPart of the Paradigms driving NoSQL adoptionCan easily evolve data tier driven by Application and Business requirements from within theApplicationMulti-Tenancy with heterogeneous schemasDatabases with heterogeneous record types in a tableType specific properties, inherited properties in a type hierarchyExamples: Product catalogs (Commerce Server), Location/business specific properties (Maps)Item-Level Property bag scenariosDistinct customized property sets associated with dataLarge number of unique properties, user annotationsExamples: Document management systems (SharePoint), Media stores
  48. 48. Large number of sparsely populated propertiesDistinct property setsHeterogeneous structuresEvolving and co-existing structuresSets, nested structures
  49. 49. Forum and mailing list threadsBusiness organization chartsContent management categoriesProduct categoriesFiles/folders management
  50. 50. A system data type with variable lengthCLR UDTMicrosoft.SqlServer.TypesVarbinary encoding ( < 900 bytes)To represent position in a hierarchyLogically encodes the path from the root of thetree to a nodeRich built-in methods for manipulating hierarchiesSimplifies storage and querying of hierarchical dataComparison a<b is in depth-first orderSupport for arbitrary insertions and deletions
  51. 51. Pro:Simple range scans to find descendants or ancestors with QP support(trie-statistics)Provide depth first clusteringSimple query for specific ID or IDs of a parent/children (benefits fromclustering)Cons:Programming model not the easiestNesting level limited by the datatype size (but still enough)
  52. 52. Wide Sparse T able: only rows that have a value for the property havea value, others are NULL“Sparse” as a storage attribute on a columnStorage Optimization: 0 bytes stored for a NULL valueCo-location of data: Performance benefitsNULL Compression in the TDS layerNo change in Query/DML behavior
  53. 53. Wide Tables/Column SetsLarge 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
  54. 54. SPARSE COLUMN STORAGE0 Bytes stored for NULL Values~20% CPU overhead for non-null value accessAdditional 2- 4 bytes for non-null valuesSparse columns are beneficial when space savings >40%
  55. 55. FILTERED INDEXESFiltered Indexes and StatisticsIndexing a portion of the data in a tableFiltered/co-related statistics creation and usageQuery/DML Optimization to use filtered indexes and statisticsRestrictionsSimple limited grammar for the predicateOnly on non-clustered indexesBenefitsLower storage and maintenance costs for large number of indexesQuery/DML performance benefits: IO only for qualifying rows
  56. 56. XML is ubiquitous, extensible, platform independent transport formatMessage Envelope in XML Simple Object Access Protocol (SOAP), RSS, RESTMessage Payload/Business Data in XMLVertical Industry Exchange schemasXHTML, DocBook, Home-grown, domain-specific markup (e.g. contracts), OpenOffice, Microsoft OfficeXML (both default and user-extended)Storing and querying heterogeneous complex objectsSemistructured data with sparse, highly-varying structure at the instance levelXML provides self-describing format and extensible schemasIs format used by COLUMNSET
  57. 57.     
  58. 58. NEW XQUERY ALGEBRA OPERATORSXML Reader TVFTable-Valued Function XML Reader UDF with XPath FilterUsed if no XML Index is presentCreates node table rowset in query flowMultiple XPath filters can be pushed in to reduce node table to subtreeBase cardinality estimate is always 10’000 rows! Some adjustment based on pushed path filters
  59. 59. NEW XQUERY ALGEBRA OPERATORSUDXSerializer UDXserializes the query result as XMLXQuery String UDXevaluates the XQuery string() functionXQuery Data UDXevaluates the XQuery data() functionCheck UDXvalidates XML being insertedUDX name visible in SSMS properties window
  60. 60. XML INDICESCreate XML index on XML columnCREATE PRIMARY XML INDEX idx_1 ON docs (xDoc)Create secondary indexes on tags, values, pathsCreation:Single-threaded only for primary XML indexMulti-threaded for secondary XML indexesUses:Primary Index will always be used if defined (not a cost based decision)Results can be served directly from indexSQL’s cost based optimizer will consider secondary indexesMaintenance:Primary and Secondary Indices will be efficiently maintained during updatesOnly subtree that changes will be updatedNo online index rebuild Clustered key may lead to non-linear maintenance cost Schema revalidation still checks whole instance
  61. 61. EXAMPLE INDEX CONTENTS
  62. 62. PRIMARY XML INDEX
  63. 63. SECONDARY XML INDICES
  64. 64. SOME CUSTOMER WORKLOAD COMPARISONS
  65. 65. FILESTREAM
  66. 66. SCALE-UP & ALWAYSON SUPPORT
  67. 67. FILETABLE OVERVIEW
  68. 68. CREATING A FILETABLE
  69. 69. MODIFYING A FILETABLE
  70. 70. DATA ACCESS – FILE SYSTEM ACCESS
  71. 71. DATA ACCESS – T-SQL ACCESS
  72. 72. MANAGING FILETABLE
  73. 73. MANAGING FILETABLE – HIGH AVAILABILITY
  74. 74. UNSTRUCTURED DATA SCALE-UPMultiple containers for FILESTREAM data
  75. 75. UNSTRUCTURED DATA: MULTIPLE CONTAINERSUse of multiple spindles for achieving better I/O Scalability
  76. 76. RUDS SCALE-UP: FILESTREAM PERF/SCALE
  77. 77. SUMMARY: FILETABLE
  78. 78. SPATIAL DATA IN SQL SERVERStorage and retrieval of spatial data using standard SQL syntaxSpatial Data Types (geometry, geography)Spatial Methods (intersects, buffer, etc.)Spatial IndexesOffers full set of Open Geospatial Consortium components(OGC/SQL MM, ISO 19125)Spatial Builder InterfaceSQL Server Management Studio visualizationIntegration with Bing MapsIntegration with Reporting Services
  79. 79. COMPREHENSIVE SPATIAL SUPPORTSpatial data types
  80. 80. OTHER NEW TYPE FEATURES IN SQL SERVER 2012
  81. 81. CREATING SPATIAL OBJECTS
  82. 82. USING SPATIAL OBJECTS
  83. 83. SPATIAL FORMAT EXAMPLE
  84. 84. CIRCULAR ARCSGeography type considerationsIf a circular linestring encloses an area, acurve polygon can be createdCURVEPOLYGON (CIRCULARSTRING(0 50, 90 50, 180 50, 270 50, 0 50))Coordinate pair order is important for thegeography type. This set of coordinates isordered according to the “left foot rule” forexterior rings.
  85. 85. PERFORMING SPATIAL OPERATIONSFind streets that intersect the Microsoft campusSELECT StreetNameFROM StreetsWHERE Streets.StreetGeo.STIntersects(@ms) = 1
  86. 86. CONVERT EXISTING DATA TO SPATIAL DATA
  87. 87. CONVERT EXISTING DATA TO SPATIAL DATA
  88. 88. SPATIAL REFERENCE ID (SRID)
  89. 89. HIGH PERFORMANCE SPATIAL CAPABILITIESSpatial indexingSpatial indexing is built intothe query engineGrid-based quad-tree index structureQuery optimizer determinescost-based query plans
  90. 90. PERFORMANCE ENHANCEMENTS FOR SPATIALAPPLICATIONS IN SQL SERVER 2012Support Persisted computed spatial columnsNew geodetic SRID for faster calculationsImproved implementation of operationsFaster Spatial index creation for point data (4 to 5 times faster)Faster point data queriesOptimized STBuffer, lower memory footprintFaster “secondary” filter stepImproved default spatial indexing scheme and new hintsAutoGridQuery Window Grid density hintSpatial Index CompressionImproved index-aware query plansNearest NeighborOptimized spatial query plan for STDistance and STIntersects like queries
  91. 91. WHAT IS NEW IN AZURE SPATIAL SUPPORTNew MethodsGEOGRAPHY Parity with GEOMETRY TYPE: STContains, STOverlaps etcNew Capabilities: AsBinaryZM(), IsValidDetailed(), ShortestLineTo() Spatial Aggregators: CollectionAggregate, ConvexHullAggregate, EnvelopeAggregate*, UnionAggregateBetter PerformanceNearest Neighbor Query PlanPersisted Computed Spatial ColumnsUnitSphere SRID 104001 for GEOGRAPHY
  92. 92. STATISTICAL SEMANTIC SEARCHSemantic Insight into textual contentUses language models to find most important keywords in document No need to build brittle ontologies!Statistically Prominent Keywords Autogenerated tag cloudsPotentially 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 experienceEfficent linear algorithmsIntegrated with FTS and SQL New Rowset functions for all results using SQL query
  93. 93. SEMANTIC SIMILARITY
  94. 94. FUNCTIONAL SURFACE: INITIATE SEMANTICSCreate / Alter Full-Text with SemanticsMakes internal design dependency on FTS explicit
  95. 95. BETTER CLOUD MANAGEMENTSYSTEM CENTER 2012
  96. 96. BETTER CLOUD MANAGEMENT WITH WINDOWS SERVERTECHNICAL BENEFITS Virtual Machine Manager App Controller › P2V conversion of SQL Server instances › Self-Service, role-based management of SQL Server VMs in private cloud & public cloud › Conversion of virtual SQL Server instances from VMware Hyper-V › Deployment of SQL Server VM across multiple private cloud environments › Faster creation of SQL Server VMs based on pre-built template with SQL › Deployment of SQL Server VM from private Server SysPrep to public cloud › 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
  97. 97. NEXT STEPSSQL 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.aspxSQL Server 2012 Certification:http://www.microsoft.com/learning/en/us/certification/cert-sql-server.aspxSQL Server 2012 Best Practices:http://technet.microsoft.com/en-us/sqlserver/bb671430
  98. 98. © 2011 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademar ks 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 accu racy 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.

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