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High-Performance SQL Server Databases You Will Learn How To Design and implement high-performance databases for SQL Server Create indexes that optimize different types of queries Design transactions that maximize concurrency and minimize contention Interpret the data access plans produced by the query optimizer Minimize I/O by designing efficient physical data structures Analyze and cure performance problems using SQL Server's tools   Course Benefits High-availability database systems offer timely access to business-critical data. Microsoft SQL Server offers powerful features to maintain these vital systems. In this course, you acquire an in-depth knowledge of SQL Server's essential tools--the storage engine, lock manager and query optimizer. Through hands-on exercises, you gain the skills to implement a high-performance SQL Server database solution.   Who Should Attend Those responsible for increasing the performance and efficiency of SQL Server databases. Knowledge of SQL at the level of, "SQL Server Transact-SQL Programming," and a familiarity with logical database design is assumed.   Hands-On Training Hands-on exercises provide experience developing high-performance SQL Server databases. Exercises include: Monitoring and analyzing performance Developing a performance baseline Setting up a server-side Profiler trace Eliminating extent fragmentation Inspecting procedures in the procedure cache Creating indexes for different query types Improving performance with indexed views Implementing partitioning solutions   Fundamental Concepts Analyzing performance Selecting an appropriate monitoring tool Investigating plans with SHOWPLAN_ALL Interpreting STATISTICS IO output Pinpointing performance problems with aggregated Profiler data Developing a monitoring plan Establishing a performance baseline Tracking changes over time Creating server-side Profiler traces Monitoring SQL Server and the operating system with System Monitor Managing Storage Database architecture Page and extent allocation Controlling data placement with file groups Defining tables Selecting the correct data types Specifying text and image locations Examining internal page structures Creating and managing indexes Clustered vs. non-clustered Defining indexed views Analyzing and repairing fragmentation Memory and Locking Managing memory Buffer pool Buffer manager Lazywriter Checkpoint Log writer Designing transactions Consistency vs. concurrency Investigating lock types and their compatibility Choosing isolation levels Designing transactions to limit lock duration Resolving contention problems Handling deadlock Implementing row versioning Optimizing Queries Query optimizer architecture Phases Strategies Data access plans Auto-parameterization Avoiding recompilation of queries Maintaining up-to-date statistics Index vs. column Automatic vs. manual Full-scan vs. sample Distinguishing among query types Point Multipoint Range Prefix match Extremal Ordering Grouping Join Designing effective indexes Relating indexes to query types Providing alternate access paths Improving join performance Increasing sort efficiency Reducing I/O with covering indexes Implementing sparse indexes Getting design advice from built-in tuning tools Designing a Physical Data Model Storing summarized data for faster retrieval Defining roll-up tables Materializing aggregated data with indexed views Minimizing response time by introducing redundant data Maintaining redundant data with triggers Enhancing performance with surrogate keys Creating a read-only query database Solving performance problems with partitioning strategies Horizontal vs. vertical partitioning Partitioning tables Defining partitioned views Managing diverse workloads Creating resource pools and workload groups Developing a classifier function

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