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Introductie van Micorosoft SQL Server 2016

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171 C H A P T E R 8 | Improved Azure SQL Database Figure 8-7: Using elastic database tools to manage sharding. You should consider sharding your application if either of the following conditions apply: The size of application data exceeds the limitations of SQL Database. Different shards of the database must reside in different geographies for compliance, performance, or geopolitical reasons. Note The elastic database client library requires Visual Studio 2012 (or higher), C#, and Nuget 2.7 (or higher). You can find information about acquiring and using the elastic database tools at "Deploy a split-merge service," database-elastic-scale-configure-deploy-split-and-merge/#download-the-Split-Merge-packages, and at "Get started with Elastic Database tools," us/documentation/articles/sql-database-elastic-scale-get-started/. Elastic database client library The elastic database client library is a Microsoft Visual Studio add-in that integrates into Entity Framework. You use this library to implement standard sharding patterns. In addition to enabling the data tier of your application to scale in and scale out, you can use the client library to manage metadata, connections, and queries for sharded data. The elastic database client library supports the following features: Shard map management You use this feature to manage the shard metadata. After registering databases as shards, you define a shard map manager that directs applications requesting connections to the correct shard based on a sharding key or range of keys. A sharding key is a data element representing the shard to which the data is assigned, such as a customer ID number, which optimally is a single value to keep related transactions contained in a single database. Data-dependent routing This feature uses the data in a query to determine the connection to the correct shard so that you no longer need to define this connection in your application. Multishard querying This feature processes a query against separate shards in parallel and merges the results into a single result set using UNION ALL syntax. It also contains built-in retry logic.

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