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Whats New Sql Server 2008 R2


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Presentacion realizada en el Hotel Aurola Holiday Inn en el Evento de Grupo Asesor - Comunidad Windows

Eduardo Castro Martinez
Costa Rica

Published in: Technology, Business
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Whats New Sql Server 2008 R2

  1. 1. Ing. Eduardo Castro, PhD Grupo Asesor en Informática
  2. 2. Overview of SQL Server 2008 Major Enhancements from SQL Server 2008 to SQL Server 2008 R2
  3. 3. SQL Server 2008 is a very powerful tool of Microsoft. SQL Server 2008 comes up with many enhancements in Security, Availability, Performance, Management, Storage, Programmability, BI( Business Intelligence ) and SSRS (Reporting Services) .
  4. 4. New Editions 2 new premium editions to meet the needs of large scale datacenters and data warehouses New R2 Technologies Application and Multi-Server Management Managed Self-Service Business Intelligence Master Data Services StreamInsight Complex Event Processing Technology
  5. 5. New R2 Solutions PowerPivot for SharePoint PowerPivot for Excel Parallel Data Warehouse Fast Track Data Warehouse
  6. 6. Building on the momentum of SQL Server 2008, “R2” improves IT efficiency by reducing the time and cost of developing and managing applications Empowers end users to make better decisions through Self-Service Business Intelligence and enables organizations to scale with confidence by providing high levels of reliability, security and scalability for business critical applications.
  7. 7. Report Builder 3.0 with support for geospatial visualization Application and Multi-server Management - SMP scale up with support for up to 256 logical processors. This CTP provides the first opportunity to explore some of the features of SQL Server 2008 R2 and see how it all comes together to enhance performance and scalability, enable self-service BI and improve IT and developer efficiency.
  8. 8. SQL Server 2008 R2 comes up with two new feature in scalability and performance enhancements: Support for More Than 64 CPUs- The number of CPU cores that a server can use for database operations been increased from 64 to 512. Unicode Compression-Unicode data that is stored in nvarchar(n) and nchar(n) columns is now compressed by using an implementation of the standard Compression Scheme for Unicode(SCSU) algorithm.
  9. 9. Datacenter Designed to deliver a high-performing data platform that provides the highest levels of scalability for large application workloads, virtualization and consolidation Key features new to Datacenter: Application and Multi-Server Management for enrolling, gaining insights and managing over 25 instances
  10. 10. High-scale complex event processing with SQL Server StreamInsight Supports more processors and up to 256 logical processors for highest levels of scale Supports memory limits up to OS maximum
  11. 11. SQL Server 2008 R2 Parallel Data Warehouse is a highly scalable data warehouse appliance-based solution
  12. 12. Key features new to Parallel Data Warehouse: 10s to 100s TBs enabled by MPP architecture Advanced data warehousing capabilities like Star Join Queries and Change Data Capture Integration with SSIS, SSRS, and SSAS Supports industry standard data warehousing hub and spoke architecture and parallel database copy
  13. 13.  Pre-configured For Each SQL Server Instance On Each Compute Node.  Drives Configured As RAID1 To Avoid Appliance Failover for a Single Drive Failure  IBM Compute Nodes Will Have 1 Lun (1 RAID1 Pair)  Dell Compute Nodes Will Have 2 Lun’s (2 RAID1 Pairs)  HP Compute Nodes Will Have 3 Luns’s (3 RAID1 Pairs)  Tempdb:  Sort-work Area For Data Loading Into Clustered Index Tables  Spill Area For Hash Joins Not Fitting Into Memory
  14. 14. Pre-configured 4 RAID10 Pairs for Primary User Data 1 RAID10 Pair for Database Logs 2 LUN’s Are Spread Across Each RAID Pair User Databases Are Separate Physical SQLServer Databases Staging Database (Optional) Used for Loading and to Minimize Fragmentation
  15. 15. You can implement it simply when creating table: With (Data_Compression=ROW) or after creating table: Alter Table [Name] REBUILD WITH(Data_Compression=ROW)
  16. 16. SQL Server 2008 R2 introduces the SQL Server Utility for managing multiple instances of the SQL Server Database Engine. In SQL Server Management Studio, organizations will gain insights into their growing applications and SQL Server instances
  17. 17. Consolidation management Use a new explorer in SQL Server Management Studio to access the central management for multi-server management and at-a-glance dashboard views Improve service levels Set policies to define desired utilization thresholds across target servers or applications within a new central management point. Identify issues with instances and applications
  18. 18. Ing. Eduardo Castro, PhD Grupo Asesor en Informática
  19. 19. It also introduces a unit of management called a data-tier application that provides an application-based view for managing the data-tier objects in the SQL Server Utility or stand-alone instances of the Database Engine. R2 makes it easier for DBAs to move databases around from server to server in much the same way virtualization admins move guest OS’s around between physical hosts.
  20. 20. SQL Server 2008 R2 still has the same concept of databases, but it’s added a new level above databases called Data-Tier Applications, abbreviated DAC The DAC includes the database schema plus some server-level objects required in order to support the database, like logins. The DAC does not include the data inside your database.
  21. 21. For deployment best practices, you should have any necessary data (configuration tables, basic lookup tables) already scripted out as part of your deployment strategy. With the DAC approach, it makes sense to put these scripts inside the database as objects. For example, you might have a stored procedure called usp_deploy that populates all of the necessary configuration tables via insert statements.
  22. 22. Developers create and update their database schema, stored procedures, functions, etc. inside Visual Studio, packaging them into DAC Packs, and handing them to the database administrator.
  23. 23. Ing. Eduardo Castro, PhD Grupo Asesor en Informática
  24. 24. SQL Server installs by creating sysprep-ed images of SQL Server standalone instances that can be copied and quickly installed on target systems. Enables rapid provisioning and configuration using prepared images stored in VHDMart for Hyper-V deployments.
  25. 25. SQL Server 2008 Sysprep accomplishes the install in two phases behind the scenes: prepare and configure. In SQL Server 2008 R2, two new SQL Server setup actions are exposed to the users: PrepareImage (also referred to as “prepare”) and CompleteImage (also referred to as “complete” or “configure”).
  26. 26. SQL Server PrepareImage takes about 30 minutes for Engine and RS components, whereas CompleteImage takes a few minutes. Windows SysPrep process can be run in between the two steps to create Windows OS image and deploy to target computers, but is not a required step. These two steps can be run back-to-back on the same computer. Sysprep will be able to save on the average an estimated 30 minutes per install.
  27. 27. Empower your business units and users to create and share BI solutions through familiar and intuitive tools SQL Server PowerPivot Add-in for Excel(formerly known as "Gemini) SharePoint 2010 based Operations Dashboard SQL Server Reporting Services Report Builder 3.0 Rich visualization of geospatial data
  28. 28. So, what is PowerPivot then? New client and server components for self- service, managed BI Client component lights up Excel 2010 Huge data capacities and mash-ups In-memory SSAS data model Server component lights up in SharePoint 2010 Integrated SSAS service to handle data models Excel Services used to render spreadsheets
  29. 29. PowerPivot client tool Add-in for Excel 2010 Provides SSAS engine, PowerPivot UI Creates in-memory database model Gather data for analysis Load & Prepare Data option Connect to data sources (lots of options) Import data into PowerPivot tab Select columns, filter data as needed
  30. 30. Describe how data is related Inform PowerPivot of data relationships Supports basic PK-FK type relationships Create basic data model Use expressions (DAX) to add calculations Includes many Excel functions Expressions based on columns, not cells
  31. 31. Use pivot-tables and pivot-charts Updated task pane for selecting data Data elements grouped by PowerPivot tab Use as dimensions or measures as appropriate New and updated visualizations Slicers (excellent!) Sparklines (excellent!) Improved icon sets, data bar formatting Improved chart options and performance
  32. 32. Ing. Eduardo Castro, PhD Grupo Asesor en Informática
  33. 33. Master Data Services helps enterprises standardize the data people rely on to make critical business decisions. With Master Data Services, IT organizations can centrally manage critical data assets companywide and across diverse systems, enable more people to securely manage master data directly, and ensure the integrity of information over time.
  34. 34. Master Data Services is a Master Data Management application that consists of the following components and tools Master Data Services Configuration Manager, Master Data Manager Master Data Services Web service
  35. 35. Master data hub that provides central management of master data entities and hierarchies and collections Thin-client stewardship portal that provides secure, role-based Web access to master data Versioning of all data entities and hierarchies Human workflow that notifies assigned owners by e-mail of business rule violations
  36. 36. Flexible and extensible business rules that safeguard the quality of data entered in the master data hub Support for a broad range of hierarchy and attribute management strategies and requirements Comprehensive role-based security model that enables fine-grained, secure access to master data
  37. 37. Models are the highest level of data organization in Master Data Services Entities Attributes and attribute groups Hierarchies (derived and explicit) Collections
  38. 38. Ing. Eduardo Castro, PhD Grupo Asesor en Informática
  39. 39. Data volumes are exploding with event data streaming from sources such as RFID, sensors and web logs The size and frequency of the data make it challenging to store for data mining and analysis. The ability to monitor, analyze and take business decisions in near real-time
  40. 40. SQL Server StreamInsight’s ability to derive insights from data streams and act in near real time provides significant business benefits. Some of the possible scenarios include: Algorithmic trading and fraud detection for financial services Industrial process control (chemicals, oil and gas) for manufacturing Electric grid monitoring and advanced metering for utilities Click stream web analytics Network and data center system monitoring.
  41. 41. .NET StreamInsight Application C# Development LINQ StreamInsight Application at Runtime Event sources Event targets Input StreamInsight Engine Output Devices, Sensors Adapters Adapters Pagers & Monitoring devices Standing Queries KPI ` Dashboards, Web servers SharePoint UI Query Query Logic Logic Trading stations Event stores & Databases Query Logic Stock ticker, news feeds Event stores & Databases
  42. 42. Events Represent the user payload along with temporal characteristics Streams Sequence of events Flows into (one or more) standing queries in StreamInsight engine Queries Operate on event streams Apply desired semantics on events Adapters Convert custom data from event sources to / from StreamInsight events
  43. 43. Database Applications Event-driven Applications Query Ad-hoc queries or Continuous standing Paradigm requests queries Latency Seconds, hours, days Milliseconds or less Data Rate Hundreds of events/sec Tens of thousands of events/sec or more Event request output input stream response stream
  44. 44. Latency Months CEP Target Scenarios Days Hours Relational Database Applications Operational Analytics Applications, Logistics, etc. Minutes Data Warehousing Applications Seconds Web Analytics Applications 100 ms Monitoring Manufacturing Financial Trading Applications Applications < 1 ms Applications 0 10 100 1,000 10,000 100,000 ~1million Aggregate Data Rate (Events/sec)
  45. 45. Analysis of Click Streams on Web Server log streamed into StreamInsight Categorizing user behavior based on URL: Click targets Search keywords Segmentation of user IDs into markets Adapting navigational structure and ad placement in real time Patterns over time windows: user first clicks PageA, then PageB, then PageC within X seconds High performance requirements Millions of online users Low latency (seconds) Possible late events
  46. 46. New Editions 2 new premium editions to meet the needs of large scale datacenters and data warehouses New R2 Technologies Application and Multi-Server Management Managed Self-Service Business Intelligence Master Data Services StreamInsight Complex Event Processing Technology
  47. 47. New R2 Solutions PowerPivot for SharePoint PowerPivot for Excel Parallel Data Warehouse Fast Track Data Warehouse
  48. 48. SQL Server 2008 R2 High Availability and Windows 2008 R2 Group Policy Changes
  49. 49. Ing. Eduardo Castro, PhD Grupo Asesor en Informática