Nesting of natively compiled stored procedures is now supported. FeatureĪccess Using a Natively Compiled Stored Procedure The following table summarizes native and interpreted Transact-SQL access for various objects. Some examples of interpreted Transact-SQL access include accessing a memory-optimized table from a DML trigger, ad hoc Transact-SQL batch, view, and table-valued function. Interpreted Transact-SQL refers to accessing memory-optimized tables without a natively compiled stored procedure. Memory-optimized tables can also be accessed with (traditional) interpreted Transact-SQL. Memory-optimized tables can be accessed most efficiently from natively compiled stored procedures ( Natively Compiled Stored Procedures).
These Transact-SQL statements may be either inside interpreted stored procedures or they may be ad-hoc Transact-SQL statements.Īccessing Data in Memory-Optimized Tables Through interpreted Transact-SQL, outside of a natively-compiled stored procedure. Through natively compiled stored procedures. Rows in disk-based tables are organized in pages and extents, and individual rows addressed using page number and page offset, row versions in memory-optimized tables are addressed using 8-byte memory pointers.ĭata in memory-optimized tables is accessed in two ways: The memory-optimized table data structure can be seen as a collection of row versions. The different row versions can be dispersed throughout the table data structure. Note that different versions of the same row do not necessarily occupy consecutive memory locations. r1 has three versions, r2 has two versions, and r3 has four versions.
The table has three rows: r1, r2, and r3. The figure shows a table with three rows and each row has different versions. The following figure illustrates multi-versioning. For more information about concurrent reads and writes on the same row, see Transactions with Memory-Optimized Tables. Row versioning is used to allow concurrent reads and writes on the same row. All row versions are maintained in the same table data structure. This means that each row in the table potentially has multiple versions. Rows in memory-optimized tables are versioned. A database can contain in-memory as well as disk-based objects. In-Memory OLTP is integrated with SQL Server to provide a seamless experience in all areas such as development, deployment, manageability, and supportability.
This means that transactions on these tables do not require any disk IO, but the data will not be recovered if there is a server crash or failover. In exchange for the increased performance, committed transactions that have not saved to disk are lost in a server crash or fail over.īesides the default durable memory-optimized tables, SQL Server also supports non-durable memory-optimized tables, which are not logged and their data is not persisted on disk. Delayed durable transactions are saved to disk soon after the transaction has committed and control was returned to the client. after a server restart).įor even greater performance gains, In-Memory OLTP supports durable tables with transaction durability delayed. Data in memory-optimized tables is only read from disk during database recovery (eg. See Creating and Managing Storage for Memory-Optimized Objects for more information about durable tables. A second copy of the table data is maintained on disk, but only for durability purposes. Rows in the table are read from and written to memory. The primary storage for memory-optimized tables is the main memory.
#Memori berkasih mp3wifi code
Starting with SQL Server 2016, and in Azure SQL Database, there are no limitations for collations or code pages that are specific to In-Memory OLTP. Memory-optimized tables and natively compiled stored procedures support only a subset of Transact-SQL features. Memory-optimized tables are fully durable by default, and, like transactions on (traditional) disk-based tables, transactions on memory-optimized tables are fully atomic, consistent, isolated, and durable (ACID). Memory-optimized tables are created using CREATE TABLE (Transact-SQL).
0 kommentar(er)
