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Hekaton (XTP)
Tara Shankar Jana
PFE- Microsoft Australia
Why Hekaton (XTP)?
Market need for ever higher throughput and
lower latency OLTP at a lower cost
HW trends demand architectural changes on
RDBMS to meet those demands

Stalled CPU’s, Attainment of Balanced Systems.

Hekaton is: High performance, memoryoptimized OLTP engine integrated into SQL Server
and architected for modern hardware trends
2
Why Hekaton (XTP)?
Market need for ever higher throughput and
lower latency OLTP at a lower cost
HW trends demand architectural changes on
RDBMS to meet those demands

Stalled CPU’s, Attainment of Balanced Systems.

Hekaton is: High performance, memoryoptimized OLTP engine integrated into SQL Server
and architected for modern hardware trends
3
What is Hekaton (XTP)?
Hekaton is Greek for “hundreds,” and it was given this name for its
ability to speed up database function 100x (possibly)

With a new latch-free technology Hekaton is claimed to
dramatically increase performance.
SQL Server 2014 allows you to migrate the most-used tables in an
existing database to memory-optimised 'Hekaton' technology.

It is also known as SQL Server In-Memory database, touted to
accelerate transaction throughput up to 30x performance increases
on existing hardware.
4
What is Hekaton (XTP)?
Hekaton is Greek for “hundreds,” and it was given this name for its
ability to speed up database function 100x (possibly)

With a new latch-free technology Hekaton is claimed to
dramatically increase performance.

Hekaton doesn’t use SQL’s Buffer Cache
SQLor VAS, it allows youeverything most-used tables in an
Server 2014 stores to migrate the in the RAM
existing database to memory-optimised 'Hekaton' technology.

It is also known as SQL Server In-Memory database, touted to
accelerate transaction throughput up to 30x performance increases
on existing hardware.
5
Drivers

Architectural Pillars

Customer
Benefits

In-Memory OLTP – Architectural Pillars
High performance
data operations

Efficient businesslogic processing

Frictionless scaleup

Hybrid engine and
integrated
experience

Main-Memory
Optimized

T-SQL Compiled to
Machine Code

High Concurrency

SQL Server
Integration

• 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 via C code
generator and VC
• Invoking a procedure is
just a DLL entry-point
• Aggressive
optimizations @
compile-time

• Multi-version optimistic
concurrency control with
full ACID support
• Core engine uses lockfree algorithms
• No lock manager, latches
or spinlocks

Business

Hardware trends
Steadily declining
memory price, NVRAM

Stalling CPU clock rate

• Same
manageability, administr
ation & development
experience
• Integrated queries &
transactions
• Integrated HA and
backup/restore

Many-core processors

TCO
In-Memory OLTP Integration and Application
Migration
Client App

TDS Handler and Session Management

Natively Compiled
SPs and Schema

Parser, Cat
alog, Opti
mizer

Native
Compiler

Key
Existing
SQL
Component

T-SQL Query Execution

In-mem
OLTP
Component

Query
Interop

T1

T2

T3

Tables
Indexes

T1

Memory Optimized Data
Filegroup

Buffer Pool for Tables & Indexes

SQL Server.exe

Memory Optimized Tables & Indexes

T2

Transaction Log

T3

T1

T2

Data Filegroup

T3

Generated
.dll
HEKATON- XTP (How to
Create Memory-Optimized
Tables)

demo
HEKATON- AMR TOOL

demo
For more consulting and support offerings from
Microsoft, contact your Microsoft Services representative or
visit www.microsoft.com.au/services.

Contact
Email: tarasden@hotmail.com
tarasha@Microsoft.com
Blog: http://blogs.msdn.com/b/sql-bi-sapcloud-crm_all_in_one_place/
Website: http://sqlmasters.jimdo.com

© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The
information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market
conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT
MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION

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Hekaton (xtp) introduction

  • 1. Hekaton (XTP) Tara Shankar Jana PFE- Microsoft Australia
  • 2. Why Hekaton (XTP)? Market need for ever higher throughput and lower latency OLTP at a lower cost HW trends demand architectural changes on RDBMS to meet those demands Stalled CPU’s, Attainment of Balanced Systems. Hekaton is: High performance, memoryoptimized OLTP engine integrated into SQL Server and architected for modern hardware trends 2
  • 3. Why Hekaton (XTP)? Market need for ever higher throughput and lower latency OLTP at a lower cost HW trends demand architectural changes on RDBMS to meet those demands Stalled CPU’s, Attainment of Balanced Systems. Hekaton is: High performance, memoryoptimized OLTP engine integrated into SQL Server and architected for modern hardware trends 3
  • 4. What is Hekaton (XTP)? Hekaton is Greek for “hundreds,” and it was given this name for its ability to speed up database function 100x (possibly) With a new latch-free technology Hekaton is claimed to dramatically increase performance. SQL Server 2014 allows you to migrate the most-used tables in an existing database to memory-optimised 'Hekaton' technology. It is also known as SQL Server In-Memory database, touted to accelerate transaction throughput up to 30x performance increases on existing hardware. 4
  • 5. What is Hekaton (XTP)? Hekaton is Greek for “hundreds,” and it was given this name for its ability to speed up database function 100x (possibly) With a new latch-free technology Hekaton is claimed to dramatically increase performance. Hekaton doesn’t use SQL’s Buffer Cache SQLor VAS, it allows youeverything most-used tables in an Server 2014 stores to migrate the in the RAM existing database to memory-optimised 'Hekaton' technology. It is also known as SQL Server In-Memory database, touted to accelerate transaction throughput up to 30x performance increases on existing hardware. 5
  • 6. Drivers Architectural Pillars Customer Benefits In-Memory OLTP – Architectural Pillars High performance data operations Efficient businesslogic processing Frictionless scaleup Hybrid engine and integrated experience Main-Memory Optimized T-SQL Compiled to Machine Code High Concurrency SQL Server Integration • 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 via C code generator and VC • Invoking a procedure is just a DLL entry-point • Aggressive optimizations @ compile-time • Multi-version optimistic concurrency control with full ACID support • Core engine uses lockfree algorithms • No lock manager, latches or spinlocks Business Hardware trends Steadily declining memory price, NVRAM Stalling CPU clock rate • Same manageability, administr ation & development experience • Integrated queries & transactions • Integrated HA and backup/restore Many-core processors TCO
  • 7. In-Memory OLTP Integration and Application Migration Client App TDS Handler and Session Management Natively Compiled SPs and Schema Parser, Cat alog, Opti mizer Native Compiler Key Existing SQL Component T-SQL Query Execution In-mem OLTP Component Query Interop T1 T2 T3 Tables Indexes T1 Memory Optimized Data Filegroup Buffer Pool for Tables & Indexes SQL Server.exe Memory Optimized Tables & Indexes T2 Transaction Log T3 T1 T2 Data Filegroup T3 Generated .dll
  • 8. HEKATON- XTP (How to Create Memory-Optimized Tables) demo
  • 10. For more consulting and support offerings from Microsoft, contact your Microsoft Services representative or visit www.microsoft.com.au/services. Contact Email: tarasden@hotmail.com tarasha@Microsoft.com Blog: http://blogs.msdn.com/b/sql-bi-sapcloud-crm_all_in_one_place/ Website: http://sqlmasters.jimdo.com © 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION

Notas do Editor

  1. Moore’s law for CPU and Transistors and CPU Stalled, Memory cheaper (think tank behind In-Memory OLTP)the DigitalAlpha 21164 microprocessor had 9.3 million transistors
  2. Moore’s law for CPU and Transistors and CPU Stalled, Memory cheaper (think tank behind In-Memory OLTP)the DigitalAlpha 21164 microprocessor had 9.3 million transistors
  3. Hekaton is a really interesting technology, but is a world away from the functionality that we know and love. The SQL team have done a great job of disguising this departure from us by integrating it inside the SQL Server engine but none the less is a different beast entirely. Although the ultimate aim, I would imagine, is a seamless integration where the user ( and developer) is not really concerned with the underlying storage technology there will be many real world issues occurring if the differences are not fully understood. Hekaton doesn’t use SQL’s Buffer Cache or VAS, it stores everything into the RAMThe way that Hekaton stores data is in hash buckets, this is a fundamental tenet. A hash is simply a function applied to some key data and the bucket is where the relating row is stored. For example : if our hash function was X%5 then our buckets for the values 1 through 10 would be populated thusly : Bucket     Values 5,10 1,6 2,7 3,8 4,9 As % is the function for modulo (divide an return the remainder) 9%5 = 4. The hash function for SQL Server would be much more complicated than this and like the hash function used in a hash join will differ depending on the data being hashed. So this is quite interesting since when we define a hekaton table we need to specify the number of buckets that we think ( perhaps even assume that we need) upfront:
  4. By taking advantage of modern HW trends, we will enable new applications with higher real-time processing needs, and hence increase the addressable market size. Pigeon hole: For mailboxes.. Collisions are ought to happen, hash bucket collisions.. Reduce it