SQL Server In-Memory OLTP Migration Overview
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This document provides an overview of SQL Server 2014 In-Memory OLTP. It discusses the benefits of In-Memory OLTP such as reducing contention, reducing logging, and minimizing execution time. It covers pre-implementation requirements, limitations, memory optimized structures like tables and indexes, and the table and stored procedure creation processes. It also discusses hardware trends enabling In-Memory OLTP, demoes basic functionality, and outlines approaches for migrating workloads to In-Memory OLTP.
SQL Server In-Memory OLTP Migration Overview
- 1. www.facebook.com/prpass SQL Server 2014 In-Memory OLTP Migration Overview Jose L. Rivera PASS Global Spanish VC Leader MVP | MCTS | MCITP | MCSA
- 2. • Microsoft SQL Server MVP • Líder del Capítulo Global PASS en Español • VP - Puerto Rico PASS • Profesional de Bases de Datos con mas de 10 años usando SQL Server y tecnologías relacionadas • Especializado en ETL e Inteligencia de Negocios • Blog: http://sqlconqueror.com • Email: [email protected] /SQLConqueror
- 3. Weekly Meetings Different Time Zones Spanish speakers from all over the globe! /SpanishPASSVC /user/SpanishPASSVC /SpanishPASSVC http://globalspanish.sqlpass.org
- 4. Agenda In-Memory OLTP Overview In-Memory Implementation Migration Scenarios Q&A
- 5. What’s in SQL Server 2014 In-Memory Technologies Hybrid Scenarios Enhanced HA/DR Other Investments
- 6. In-Memory OLTP? Memory-optimized OLTP engine High performance Full integration into SQL Server Architected for modern hardware
- 7. Hardware Trends More complex CPUs CPU clock rate stalled Parallel processing RAM is really cheap! SSD: Minimize IO bottleneck
- 9. Pre-Implementation Requirements Enough memory and disk space cmpxchg16b instruction support (in most 64bit processors) Database should not exceed 250 GB At least 2 or 4 sockets and fewer than 60 cores
- 10. Limitations memory-optimized filegroup cannot be deleted (Yes! DROP DATABASE) No triggers, LOBs, XML, CLR No FOREIGN KEY, CHECK No schema changes, add/remove index (drop/recreate only)
- 11. Memory optimized Structures • Tables, Indexes, SPs
- 12. Row Format Row header Payload (table columns) Begin Ts End Ts StmtId IdxLinkCount 8 bytes 8 bytes 4 bytes 2 + 2 (padding) bytes 8 bytes * (IdxLinkCount)
- 13. Memory-Optimized Tables 90,150 Susan Bogota 50, ∞ Jane Prague 100, 200 John Paris 70, 90 Susan Brussels 200, ∞ John Beijing Timestamps NameChain ptrs City Hash index on City B P Row format BW-tree index on Name J S
- 14. Memory-Optimized Indexes 90, 150 Susan Bogota 50, ∞ Jane Prague Timestamps NameChain ptrs City Hash index on City Hash index on Name 100, 200 John Prague 200, ∞ John Beijing f(John) f(Jane) f(Beijing) f(Bogota) f(Prague)
- 15. Table Creation Process CREATE TABLE DDL Code generation and compilation Table DLL produced Table DLL loaded
- 16. Natively Compiled SPs It is ALL in All tables must be memory optimized CLR like Execution plan as a result of the TSQL is compiled into native code (machine code)
- 17. SP Creation Process CREATE PROC DDL Query optimization Code generation and compilation Procedure DLL produced Procedure DLL loaded
- 19. Migration Methodology Analyze Application Know your app Define goals Identify bottlenecks Test, Test, Test Examine Gains
- 20. In-Memory OLTP Patterns Implementation Scenario Pattern Characteristics and Challenge Main Benefits of In-Memory OLTP High Data Insert Rate Primarily append-only store Inability to ingest write workload Eliminate contention Minimize I/O logging Read Performance and Scale High performance read operations Unable to meet scale-up requirements Eliminate contention Efficient data retrieval Minimize code execution time o CPU efficiency for scale Compute Heavy Data Processing Insert/Update/Delete workload Heavy computation inside database Read and write contention Eliminate contention Minimize code execution time Efficient data processing
- 21. In-Memory OLTP Patterns Implementation Scenario Pattern Characteristics and Challenge Main Benefits of In-Memory OLTP Low Latency Require low latency business transactions that typical database solutions cannot achieve High concurrency exacerbates latency Eliminate contention Minimize code execution time Efficient data retrieval Session State Management Heavy insert, update, and point lookups User scale under load from multiple stateless web servers Eliminate contention Efficient data retrieval Optional I/O reduction/removal
- 22. Migration Approach Identify bottlenecks in tables Address unsupported constructs and migrate data Perform minimal changes for interpreted access Identify performance critical transaction code Address surface area limitations and migrate code
- 23. Migration Advisors Memory Optimization Advisor Identifies which tables in your database will benefit Native Compilation Advisor Identifies interpreted stored procedures in your database that will benefit
- 24. DEMO ARM tool from MDW (Screenshots)
- 25. MDW Reports
- 28. MDW reports
- 30. /SQLConqueror