Introduction to Memory-Optimized Tables > 자유게시판

Memory-optimized tables are created utilizing CREATE Table (Transact-SQL). Memory-optimized tables are fully durable by default, and, like transactions on (traditional) disk-primarily based tables, transactions on memory-optimized tables are fully atomic, constant, isolated, and durable (ACID). Memory-optimized tables and natively compiled saved procedures help only a subset of Transact-SQL options. Beginning with SQL Server 2016, and in Azure SQL Database, there are not any limitations for collations or code pages which might be specific to In-Memory OLTP. The first storage for memory-optimized tables is the main memory. Rows in the desk are learn from and written to memory. A second copy of the desk data is maintained on disk, however only for durability purposes. See Creating and Managing Storage for Memory-Optimized Objects for more details about durable tables. Knowledge in memory-optimized tables is barely learn from disk throughout database restoration (for instance, after a server restart). For even larger performance positive aspects, In-Memory OLTP supports durable tables with transaction sturdiness delayed. Delayed durable transactions are saved to disk quickly after the transaction commits and control is returned to the shopper.

In exchange for the increased efficiency, dedicated transactions that aren't persisted to disk are lost in a server crash or fail over. Besides the default durable memory-optimized tables, SQL Server additionally supports non-durable memory-optimized tables, which aren't logged and their data is not persisted on disk. This means that transactions on these tables don't require any disk IO, however the info is lost if there is a server crash or failover. In-Memory OLTP is built-in with SQL Server to supply a seamless experience in all areas equivalent to development, deployment, manageability, and supportability. A database can comprise in-memory in addition to disk-based mostly objects. Rows in memory-optimized tables are versioned. This means that every row within the table potentially has multiple versions. All row variations are maintained in the same table data structure. Row versioning is used to permit concurrent reads and writes on the same row. For extra details about concurrent reads and writes on the identical row, see Transactions with Memory-Optimized Tables.

The next figure illustrates multi-versioning. The determine shows a desk with three rows and every row has different variations. The table has three rows: r1, r2, and r3. 1 has three variations, r2 has two versions, and r3 has four variations. Different variations of the same row don't necessarily occupy consecutive memory places. The totally different row versions can be dispersed all through the desk data structure. The memory-optimized desk data construction can be seen as a collection of row variations. Rows in disk-primarily based tables are organized in pages and extents, and individual rows addressed utilizing page quantity and Memory Wave Audio page offset, row versions in memory-optimized tables are addressed utilizing 8-byte memory pointers. Through natively compiled saved procedures. By means of interpreted Transact-SQL, outside of a natively compiled saved procedure. These Transact-SQL statements may be both inside interpreted saved procedures or they may be advert hoc Transact-SQL statements. Memory-optimized tables might be accessed most effectively from natively compiled saved procedures (Natively Compiled Stored Procedures).

Memory-optimized tables will also be accessed with (conventional) interpreted Transact-SQL. Interpreted Transact-SQL refers to accessing memory-optimized tables with no natively compiled stored procedure. Some examples of interpreted Transact-SQL entry include accessing a memory-optimized desk from a DML set off, advert hoc Transact-SQL batch, view, and desk-valued perform. The next table summarizes native and interpreted Transact-SQL entry for various objects. 1You cannot entry a memory-optimized desk or natively compiled stored procedure from the context connection (the connection from SQL Server when executing a CLR module). You can, however, create and open another connection from which you'll access memory-optimized tables and natively compiled saved procedures. Delicate data in Memory Wave Audio-optimized tables can be protected through the use of Always Encrypted. When using At all times Encrypted with secure enclaves, the usage of enclave-enabled keys for columns in memory-optimized tables is not supported. This means that in-place encryption can't be used, and the preliminary encryption is finished on the client.

At all times Encrypted is not supported for any column in a memory-optimized desk when the table is referenced in a natively compiled module. Communication: An application utilizing many quick saved procedure calls may see a smaller efficiency achieve in comparison with an application with fewer calls and extra performance applied in every saved process. Transact-SQL Execution: In-Memory OLTP achieves the best efficiency when using natively compiled stored procedures quite than interpreted stored procedures or query execution. There generally is a profit to accessing memory-optimized tables from such saved procedures. Vary Scan vs Level Lookup: Memory-optimized nonclustered indexes support vary scans and ordered scans. For level lookups, memory-optimized hash indexes have better performance than memory-optimized nonclustered indexes. Memory-optimized nonclustered indexes have better performance than disk-based mostly indexes. Beginning in SQL Server 2016, the query plan for a memory-optimized table can scan the table in parallel. This improves the efficiency of analytical queries. Index operations: Index operations aren't logged, they usually exist solely in memory.