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Sql Server 2014 In Memory
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Sql Server 2014 In Memory

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Slides from my presentation at Code Camp NYC

Slides from my presentation at Code Camp NYC

Published in: Technology

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Transcript

  • 1. Ravi Okade
  • 2. Agenda  Why do you need it ?  How it is done  Benefits  Limitations
  • 3. Why do you need a new architecture ?  In-Memory  Memory is cheap  Servers have HUGE memory  Some data is hot  Traditional page based architecture has limitations, even when all pages are in memory  Native Compilation, Lock-less architecture  Individual cores are not getting any faster  While number of cores is increasing, Parallel processing has its limits due to lock contention  You cannot scale linearly by adding more cores
  • 4. Comparable Products and Technologies  Similar Products  Oracle TimesTen  Sybase ASE  Other technologies with some similarities  Distributed Cache ○ Oracle Coherence is one of many distributed cache’s that support query language (CQL). It can also persist to Oracle. Another example with similar capabilities is Gigaspaces  NoSQL Databases ○ Most NoSQL databases support distributed querying and aggressively cache data (e.g. MongoDB)
  • 5. What it all means..
  • 6. Use Cases  Hot tables – frequent inserts and updates, but queried heavily e.g:  Stock Trading applications  Patient Vital Stats  Flight information (live)  Transient data e.g.:  Web Session data  Stock Market data  Need for High speed OLTP queries
  • 7. In-memory Architecture  Main Concepts  In-memory  Lock free (row versions)  Native compiled stored procedures  Data storage optimizations  Memory optimized data structures  Transaction log optimization (block writes, no undo)  Data file Optimization (Sequential writes, Merging)  Index optimization (Only in-memory, Not persisted to disk, no tx logging)  No TempDB  Garbage collection optimization (huh?)  Non-durable option (Not persisted to disk)
  • 8. In Memory – Myths and Realities  Myth: In-Memory OLTP is the same as DBCC PINTABLE  Reality: In-Memory OLTP uses a completely new design built from the ground up.  Myth: If SQL Server crashes all data is lost  Reality: No – it is persisted to disk and is fully recoverable.
  • 9. SQL Server 2014 In-Memory Architecture SQL Server Integration • Same manageability, administration & development experience • Integrated queries & transactions • Integrated HA and backup/restore Main-Memory Optimized • Optimized for in-memory data • Indexes (hash and range) exist only in memory • No buffer pool, B-trees • Stream-based storage T-SQL Compiled to Machine Code • T-SQL compiled to machine code via C code generator and VC • Invoking a procedure is just a DLL entry-point • Aggressive optimizations @ compile-time High Concurrency • Multi-version optimistic concurrency control with full ACID support • Core engine uses lock-free algorithms • No lock manager, latches or spinlocks
  • 10. In-Memory integration with SQL Server
  • 11. Memory Management  Table data resides in memory at all times.  No paging.  Must configure SQL box with sufficient memory to store memory-optimized tables. Max supported 512GB  Failure to allocate memory will fail transactional workload at run-time
  • 12. In-Memory Data Structures  Rows  New row format ○ Structure of the row is optimized for in-memory residency and access.  One copy of row ○ Indexes point to rows, they do not duplicate them.  Indexes  Hash Index for equality search  memory-optimized B-tree for range and equality search (In CTP2)  Do not exist on disk – recreated during recovery.
  • 13. In Memory – Table DDL: Need filestream filegroup FILEGROUP [Hekaton_DB_hk_fs_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [Hekaton_DB_hk_fs_dir], FILENAME = 'C:Hekaton_testsqlservrdataHekaton_DB_hk_fs_dir')
  • 14. Table creation internals CREATE TABLE DDL Code generation and compilation Table DLL produced Table DLL loaded
  • 15. Table Storage  Filestream is the underlying storage mechanism  Data files  Store inserted records  Data written only upon Tx commit  Delta files  Store deleted records (updates are an insert/delete pair)
  • 16. Transaction Logging  Uses SQL transaction log to store content  All logging is logical  No log records for physical structure modifications.  No index-specific / index-maintenance log records.  No UNDO information is logged
  • 17. Native Compiled Stored Procedures  Compiled to C language and compiled into a dll using VC  Optimized aggressively at compile time  Can only access In-memory tables  Not all T-SQL constructs and functions supported  No alter procedure – must drop and recreate
  • 18. Procedure Creation CREATE PROC DDL Query optimization Code generation and compilation Procedure DLL produced Procedure DLL loaded
  • 19. Using Row Versions for Lock free architecture  SQL Server 2014 In Memory DB has no locks (period).  Row versions are used to maintain updates  No TempDB  Row Versions which are no longer referenced are garbage collected.  Supports Snapshot, Repeatable Read and Serializable Isolation levels
  • 20. Transaction Isolation Levels  SNAPSHOT  Reads are consistent as of start of the transaction  Writes are always consistent  REPEATABLE READ  Read operations yield same row versions if repeated at commit time  SERIALIZABLE  Transaction is executed as if there are no concurrent transactions – all actions happen at a single serialization point (commit time)
  • 21. Garbage Collection
  • 22. Benefits  Uses Commodity Hardware  Works seamlessly with current SQL Server objects  Yes, it is still ACID compliant  Yes, you can mix in-memory and disk based tables in the same database  Yes, your transactions can span in-memory and disk based tables  No, you cannot have partial in-memory tables  Yes, it has to fit in-memory 100%, forever.  Yes, you can limit how much memory is used by the in-memory tables (think resource pools) (not in CTP1)  Yes, you can have high availability
  • 23. Limitations  Row Sizes can’t be larger than 8060 bytes (incl. Variable Length Columns)  LOB, XML Data Types are not supported  No Foreign Key and Check Constraints  No IDENTITY, SEQUENCE  No DML Triggers  No ALTER Table (Need to recreate table)  No Add/Remove Index (Need to recreate table)  No diff backups  Indexes are rebuilt (consider startup time)  Disk files are merged while being loaded  Running out of memory
  • 24. CTP1 Limitations  No B-Tree index (used for range search)  No Resource Pools  No always on
  • 25. Demo  Performance against disk based table  Performance with native sproc  Number of Tx records written disk vs memory  Northwind example  [TBD] Dealing with transactions  [TBD] Performance of T-SQL/Interop sprocs with In memory tables  [TBD] Disk files and merging ?  [TBD] Backup, Tx log backup; no diff backups
  • 26. More information  Tech-ed SQL Server 2014 Videos  Microsoft SQL Server In-Memory OLTP: Overview of Project “Hekaton”  Microsoft SQL Server In-Memory OLTP Project “Hekaton”: App Dev Deep Dive  Microsoft SQL Server In-Memory OLTP Project “Hekaton”: Management Deep Dive  Microsoft SQL Server 2014 In-Memory OLTP: Overview  SQL Server In-Memory OLTP: DB Developer Deep Dive  SQL Server In-Memory OLTP: DBA Deep Dive  SIGMOD 2013 article by Microsoft  Hekaton Whitepaper by Kalen Delaney  High-Performance Concurrency Control Mechanisms for Main-Memory Databases, Microsoft Research  SQL Server 2014 - MSDN Online Documentation  Blog articles by Bob Beauchemin  Getting Started with SQL Server 2014 In-Memory OLTP (SQL Server Team blog)  Additional links  Oracle TimesTen FAQs  SQL Server In Memory Set up and Demos (My Blog)