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.

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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: jose@sqlconqueror.com
/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

8. In-Memory OLTP Benefits
Reduce
Contention
Reduce
Logging
Minimize
execution
time
Lower
Latency

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

18. DEMO
In-Memory OLTP Basics
Workload

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

26. Transaction Performance Analysis

27. Table Contention Analysis

28. MDW reports

29. DEMO
Migration Advisors

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