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  • - In-Memory Oltp: Inside the SQL Server 2016 Hekaton Engine
    av Kalen Delaney
    290,-

    In this book, Kalen Delaney explains how the new In-Memory OLTP engine works, how it stores and manipulates data, and how, even with all data stored in memory and no locking or latching, it can still guarantee the ACID properties of all transactions.

  • av Kalen Delaney
    290,-

    If you've designed your SQL code intelligently, and implemented a sensible indexing strategy, there's a good chance your queries will "fly", when tested in isolation. In the real world, however, where multiple processes can access the same data at the same time, SQL Server often has to make one process wait, sacrificing concurrency and performance, in order that in order that all can succeed, without destroying data integrity. Transactions are at the heart of concurrency. I explain their ACID properties, the transaction isolation levels that dictate the acceptable behaviors when multiple transactions access the same data simultaneously, and SQL Server's optimistic and pessimistic models for mediating concurrent access. Pessimistic concurrency, SQL Server's default, uses locks to avoid concurrency problems. I explain all the different locks and their compatibility. I show how to control locking with hints and bound connections, and how to troubleshoot excessive blocking and deadlocking. Optimistic concurrency uses row versions to support concurrency. I explain how row versioning works, cover SQL Server's two Snapshot-based isolation levels and offer troubleshooting tips for issues such as update conflicts. Your application can have world-class indexes and queries, but they won't help you if you can't get your data, because another application has it locked. That's why every DBA and developer must understand SQL Server concurrency, and how to troubleshoot any issues. I hope my book helps!

  • - In-Memory Oltp
    av Kalen Delaney
    287,-

    The SQL Server 2014 In-Memory OLTP engine (a.k.a. Hekaton) is designed from the ground up to exploit terabytes of available memory and high numbers of processing cores. It allows us to work with memory-optimized tables and indexes, and natively compiled stored procedures, in addition to the disk-based tables and indexes, and T-SQL stored procedures, that SQL Server has always provided. Hekaton in-memory data is accessible, transparently, using familiar interfaces such as T-SQL and SSMS, but Hekaton's internal behavior and capabilities are very different than those of the standard relational engine. Everything you knew about how your SQL Server stores and accesses data is different in Hekaton. Everything you understood about how multiple concurrent processes are handled needs to be reconsidered. In this book, Kalen Delaney explains how the new In-Memory OLTP engine works, how it stores and manipulates data, and how, even with all data stored in memory and no locking or latching, it can still guarantee the ACID properties of all transactions. Kalen has been working with SQL Server since 1987, specializing in query performance tuning and SQL Server internals. The Hekaton internals knowledge she provides in this book will help you migrate existing tables or databases to Hekaton, and get faster performance from your SQL Server applications than you ever thought possible.

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