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SQL Server 2008 R2 Overview

SQL Server 2008 R2 Overview. Name Title Group/Company. Information Platform Vision. Pervasive Insight. Empowered IT. Dynamic Development. MISSION CRITICAL PLATFORM. Desktop & Mobile. Server & Datacenter . Cloud. A Comprehensive Platform. Managed Self-Service BI

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SQL Server 2008 R2 Overview

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  1. SQL Server 2008 R2 Overview Name Title Group/Company

  2. Information Platform Vision Pervasive Insight Empowered IT Dynamic Development MISSION CRITICAL PLATFORM Desktop & Mobile Server & Datacenter Cloud

  3. A Comprehensive Platform Managed Self-Service BI Multi-server management Virtualization & Live Migration MPP support for 10s to 100s TB DW Highly scalable appliances Seamless integration with Microsoft BI Scalable relational database platform Consistent, familiar model & tools Self-managed, highly available cloud services

  4. TRUSTED, SCALABLE PLATFORM IT & DEVELOPER EFFICIENCY MANAGED SELF-SERVICE BI Enterprise-level security, scalability High-scale, complex event processing Data consistency across heterogeneous systems Multi-server management Virtualization & Live Migration Accelerated development& deployment Self-service analytics Self-service reporting Streamlined collaboration& management COMPREHENSIVE PLATFORM FOR IT VALUE MPP support for 10s-100s TB DW Highly scalable appliances Seamless BI Integration Scalable relational database platform Consistent, familiar model & toolsSelf-managed, highly available cloud service

  5. What is CEP? Event Complex Event Processing (CEP) is the continuous and incremental processing of event streams from multiple sources based on declarative query and pattern specifications with near-zero latency. request output stream input stream response

  6. Latency Scenarios for Event Processing Relational Database Applications CEP Target Scenarios Operational Analytics Applications, e.g., Logistics, etc. Data Warehousing Applications Web Analytics Applications Manufacturing Applications Financial trading Applications Monitoring Applications Aggregate Data Rate (Events/sec.)

  7. Example CEP Scenarios • Manufacturing: • Sensor on plant floor • React through device controllers • Aggregated data • 10,000 events/sec • Power, Utilities: • Energy consumption • Outages • Smart grids • 100,000 events/sec • Web Analytics: • Click-stream data • Online customer behavior • Page layout • 100,000 events /sec • Financial Services: • Stock & news feeds • Algorithmic trading • Patterns over time • Super-low latency • 100,000 events /sec Asset Instrumentation for Data Acquisition, Subscriptions to Data Feeds Data Stream Data Stream Visual trend-line and KPI monitoring Batch & product management Automated anomaly detection Real-time customer segmentation Algorithmic trading Proactive condition-based maintenance Stream Data Store & Archive Asset Specs & Parameters Event Processing Engine • Threshold queries • Event correlation from multiple sources • Pattern queries Lookup

  8. Virtuous Cycle: Monitor, Manage, Mine

  9. Microsoft’s CEP Solution Data Sources, Operations, Assets, Feeds, Sensors, Devices Input Data Streams OutputData Streams Input Data Streams CEP Engine Monitor & Record Mine & Design Manage & Benefit f(x) f'(x) g(y) h(x,y) Results Deploy History Operational Data Store & Archive CEP Engine f(x) g(y) f'(x) h(x,y)

  10. CEP Deployment Alternatives CEP CEP for lightweight processing and filtering CEP CEP for aggregation and correlation of in-flight events CEP CEP for complex analytics including historical data • Event processing engines are deployed at multiple places on different scales • At the edge – close to the data source • In the mid-tier – consolidate related data sources, • In the data center – historical archive, mining, large scale correlation. Web servers Sensors CEP CEP Feeds Devices CEP CEP CEP CEP CEP CEP CEP • Complex Analytics & • Mining

  11. Overview: CEP Platform from Microsoft Platform from Microsoft for continuous and incremental processing of event streams from multiple sources based on declarative query and pattern specifications with low latency EVENT TARGETS EVENT SOURCES APPLICATION Pagers & Monitoring devices Devices, Sensors MSFT CEP Engine Input Adapters Output Adapters Web servers KPI Dashboards, SharePoint UI Event stores & Databases Trading stations Bloomberg.com Reference data Stock tickers & News feeds Event stores & Databases PLATFORM FOR KEY MARKET OPPORTUNITIES KEY SOLUTION REQUIREMENTS • Event driven • Low latency processing (< milliseconds) • High volume (>100,000 events /second) • Correlated events from multiple sources • Time interval oriented standing queries • Manufacturing: Process monitoring i.e. scheduling, control, inventory • Financial: algorithmic trading, compliance monitoring, fraud detection • Web: Click stream analysis ,ad-delivery model • Utility: Grid monitoring • Healthcare: Patient Monitoring • Networking: traffic monitoring ,security intrusion detection • Telecom: Network monitoring • Oil and Gas: Geological data analysis, process control

  12. Events • Events expose different temporal characteristics • Point in time events • Interval events with fixed duration • Interval events with initially unknown duration • Rich payloads capture all properties of an event d c e Payload/ value  b a t5 t3 t4 t1 t2 Time 

  13. Event Types • Events in Microsoft’s CEP platform use the .NET type system • Events are structured and can have multiple fields • Fields are typed using the .NET framework types • CEP engine provisioned timestamp fields capture all the different temporal event characteristics • Event sources populate time stamp fields

  14. Event Streams • A stream is a possibly infinite sequence of events • Insertions of new events • Changes to event durations • Examples: time series sensor data, log entries • Stream characteristics: • Event/data arrival patterns • Steady rate with end-of-stream indication Examples: files, tables • Intermittent, random, or in burstsExample: retail scanners, web, weather telemetry • Out of order events • Order of arrival of events does not match the order of theirapplication timestamps • Takeaway: CEP engine does the heavy lifting for you when dealing with out-of-order data

  15. Event Stream Adapters • Design time specification of an adapter • for a particular event type and particular source/sink • methods to handle event and stream behavior, and • properties to indicate adapter features to the engine • Adapter features

  16. Core CEP Query Engine Event Event Event Event Event Event Event Event Event CEP Engine • Hosts “standing queries” • Operators consume and produce streams • Queries are composable • Query results are computed incrementally Standing Queries Output Adapters Input Adapters • Query instance management: • Submit, start, stop • Runtime statistics • Takeaway: CEP engine does the heavy lifting for you when processing temporal event data

  17. Typical CEP Queries • Typical CEP queries require combination of functionality • Complex type describes event properties • Calculations introduce additional event properties • Grouping by one or more event properties • Aggregation for each event group over a pre-defined period of time, typically a window • Multiple event groups monitored by the same query • Correlate event streams • Check for absence of activity with a data source • Enrich events with reference data • Collection of assets may change over time • We want to make writing and maintaining those queries easy or even effortless

  18. CEP Query Features • Operators over streams • Calculations (PROJECT) • Correlation of streams from different data sources (JOIN) • Check for absence of activity with a data source (EXISTS) • Selection of events from streams (FILTER) • Stream partitioning (GROUP & APPLY) • Aggregation (SUM, COUNT, …) • Ranking and heavy hitters (TOP-K) • Temporal operations: hopping window, sliding window • Extensibility – to add new domain-specific operators • Queries are written over specific event types • They can be evaluated on all data sources with the same event type • Support for streaming data, reference data (lookup), and historical data (replay)

  19. LINQ Query Examples LINQ Example – JOIN, PROJECT, FILTER: from e1 in MyStream1 join e2 in MyStream2 e1.ID equals e2.ID where e1.f2 = “foo” select new { e1.f1, e2.f4 }; Filter Project Window Grouping Join LINQ Example – GROUP&APPLY, WINDOW: from e3 in MyStream3 group e3 by e3.i intoSubStreams from s4 inSubStreams from e4 in s4.SlidingWindow(FiveMinutes,ThreeSeconds) selectnew { pl = newMyNewPayload(e4.i, e4.f)};

  20. Extensibility • Built-in operators do not cover all functionality • Need for domain-specific extensions • Integrate with functionality available in existing libraries • Support for extensions in the CEP platform: • User-defined operators, functions, aggregates • Code written in .NET, deployed as .NET assembly • Query operators can refer to functionality of the assembly • LINQ queries can easily refer to user-defined functionality • Temporal snap-shot operator framework • Interface to implement user-defined operators • Manages operator state and snapshot changes • Framework does the heavy lifting to deal with intricate temporal behavior such as out-of-order events

  21. Developer Experience with the CEP Platform • Goals • Easy to use and highly productive • Most comprehensive toolset • Supports various deployment models for CEP applications • Embedded applications • Server applications • Compelling story for domain-specific extensions • CEP development environment • Builds on top of .NET • Microsoft Visual Studio as IDE • Applications written in C# • Queries written in LINQ • LINQ: • varqueryFilter = • from c inTestEventStream • where c.Field1 > 1 • select c;

  22. Managing CEP Data Sources & Queries • Typical CEP Application • Multiple different data sources and adapters • Several queries • Intellectual property is in the queries • Protect investment in queries over time • Re-use existing queries as newer version of an asset, device or data source become available • Re-use existing queries for new data source types • Seamlessly switch between live data feeds and historical data

  23. Query Binding Event Event Event Event Event Event Analytics & Queries Data Sources • Binding a query with data sources yields a query instance • Configure multiple query instances for a query • Similar to data independence: the same query can be bound to different data sources as long as they deliver the required event type QT1 CEP Engine AT1 Standing Queries Q1 Input Adapters Output Adapters AT2 Q1’ AT3 Q1’’

  24. CEP Query Configuration Query • Query binding: • Coupling adapters with a query • Event types required by the query need to be matched by types delivered by adapters • Query can be re-used for all data sources of the same type • No changes to query necessary for re-use Output Adapter Type Type Query Template Proj. Join Type Type Type Type Input Adapter Input Adapter

  25. Recap: CEP Platform from Microsoft Event Event Event Event Event Event Event Event Event Development experience with .NET, C#, LINQ and Visual Studio 2008 CEP Application Development CEP platform from Microsoft to build event-driven applications Event targets Event sources Event-driven applications are fundamentally different from traditional database applications: queries are continuous, consume and produce streams, and compute results incrementally CEP Engine Standing Queries Output Adapters Input Adapters Flexible adapter SDK with high performance to connect to different event sources and sinks The CEP platform does the heavy lifting for you to deal with temporal characteristics of event stream data Static reference data

  26. CEP Deployment Scenarios Scenario 1: Custom CEP Application Dev Scenario 2: Embed CEP in Application Custom CEP Application .NET, C#, LINQ ISV Application with CEP Engine CEP Engine CEP Engine KPIs KPI mining ETL Pipeline with CEP engine CEP Engine CEP CEP Scenario 4: Operational Intelligence w/ CEP Scenario 3: CEP Enabled Device CEP CEP Reference data Device with Embedded CEP Engine Reference data Madison CEP Engine

  27. CEP Platform Roadmap • Focus on • Custom development platform for CEP applications • CEP platform for Microsoft partners • TAP (Technology Adopter Program) will launch in July 2009 • Product availability targeted for 2010 CTP2 TAP program CTP3 TAP continues General Availability time Late 2009 2010 July 2009

  28. © 2009 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.

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