Dragoljub Ljubičić, SAP West Balkans November,...

SAP HANA – In-Memory Database

Dragoljub Ljubičić, SAP West Balkans

November, 2013

In-Memory computing Innovations in hardware and software

© 2013 SAP AG or an SAP affiliate company. All rights reserved. 3

What is In-Memory computing

Orchestrating Technology Innovations

Dramatically improved hardware economics and technology innovations

in software have made it possible for SAP to deliver on its vision of the

Real-Time Enterprise with in-memory business applications


In-Memory computing

Rethink

Yesterday Today

Disk

Partitioning

Insert Only on Delta Compression

Row and Column Store

No aggregates Memory

+ +

+ +

Memory

Logging and Backup –

Solid State / Flash / HDD

CPU

Multi-Core

Massively Parallel

SingleOptimized Platform

64-bit address space

supports 2TB RAM

100GB/s throughput

Software and data reside on HDD

• IO constraint

• Support many platforms

• Optimized for None

• Take advantage of latest advances in hardware

• Minimum IO time

• Optimized for x86 platform

Disk

CPU

+


Hardware technology innovations

Moore's law

Innovations in the area of memory

Continues increase in size (8/16/32 GB)

Continues decrease in power consumption

Continuously decreasing price

Innovations in the area of CPUs

Continues increase in cores (10 cores today)

Memory controller in each CPU

Quick Path Interconnect between CPUs


Challenges of In-Memory computing

Use the full potential of your hardware

Parallelism! Take advantage of tens, hundreds of cores

Data locality! Yes, DRAM is 100,000 times faster than disk…

But DRAM access is still 4-60 times slower than on-chip caches


In-Memory computing conclusion

Data in memory keeps cores happy


SAP SW Technology Innovations

Row and column store



Columnar dictionary compression

Dictionary per column

Uses data-driven fixed-length bit encodings

Operations directly on compressed data

More in cache, less main memory access


Compress repeated values in column memory

Works best on sparse, sorted columns

Other encodings in other cases

Order Country Product Sales

456 France corn 1000

457 Italy wheat 900

458 Spain rice 600

459 Italy rice 800

460 Denmark corn 500

461 Denmark rice 600

462 Belgium rice 600

463 Italy rice 1100 … … … …

1 Belgium

2 Denmark

3 France

4 Italy

5 Spain

3

4

5

4

2x2

1

4 …

Logical Table Country

1 corn

2 wheat

3 rice

1

2

2x3

1

3x3 …

Product


Columnar Run-length Encoding



Data partitioning and parallelism

Data partitioning, on one host or

distributed to multiple hosts

Horizontal and vertical

parallelization of a single query

operation, using multiple cores /

threads

Transparent to app developer

SAP HANA SAP AG's implementation of in-memory database technology


Best suite of applications on best performing platform Unifying OLAP and OLTP: From vision to reality

User-Driven Experience

SAP HANA

SAP Business Suite

Ne

w A

pp

s

SA

P N

etW

eaver

BW

SAP UI HTML5 Mobile SAP BI 4

+ +

+ + +

OLTP | Relational | Columnar | OLAP

Real-Time Analytics

Real-Time

Transactions

Design Thinking

Real-Time

Applications

Real-Time

Platform

SAP NetWeaver

SAP HANA Live

SAP

CRM

SAP

SCM

SAP

PLM

SAP

SRM

SAP

ERP


SAP HANA Next generation platform for real-time business

HANA New Apps

New Frontiers: New breeds of real-time app on HANA

w/o requiring SAP apps but can integrate with them.

Smart Meter Analytics

Precision Retailing

Cash Forecasting

Standalone app from partners

HANA RDS

SAP HANA Innovation Overview:

HANA

DB

Apps


System considerations

Migration of database server only

AnyDB/ AnyOS

An

yO

S

SAP HANA/ SUSE Linux

(SLES)

SAP HANA migration

No Change

No change of frontends

Re-use of available

application servers

Sizing of current

application servers

remains valid

Change

Migration of database

to SAP HANA appliance

required

Co-deployment of

application servers

(e.g. central instances)

on database hardware

not possible with SAP

HANA

Frontends

Application Servers


Landscape considerations Standard 3-system landscapes

Optimizations for SAP HANA require all relevant systems to run on SAP HANA

(i.e. Development, Quality Assurance and Production)

SAP HANA-based systems interact with non-SAP HANA-based systems as expected

SAP HANA runs natively on Unicode only

DYY QYY PYY

DXX QXX PXX

RF

C

RF

C

RF

C

SAP

HANA-

based

Not SAP

HANA-

based


Running multiple applications Installation options


SAP HANA deployment options What is your customer usage scenario?


SAP HANA installation and maintenance Overview of Process and Tools

The SAP HANA unified

installer

• Used by HW partner

The SAP HANA on-site

configuration tool

• Used by certified SAP field

specialist

The Software Update

Manager (SUM) for SAP

HANA

• Used by customer or SAP field

specialist


SAP HANA Tailored Data Center Integration Customer Feedback & Challenges and alternative Concept

SAP HANA tailored data center integration is an additional option to the

existing appliance model

HANA Server

HANA Server

Storage

HANA Server

HANA Server

HANA Server

(Corp.)

Storage

HANA Server

Reduce hardware and operation

cost at installed based customers

Mitigate risk and optimize time to

value by taking more responsibility

Gain additional flexibility in

hardware vendor selection

Limited flexibility in server/ storage

combinations (well defined packages)

Established IT operation processes

have to be adapted slightly

Well defined HW and performance

KPIs


SAP HANA tailored Data Center Integration Customer Pilot Program

Prepare

Measure

Release

• Order hardware

• Set up targeted HANA infrastructure

• Server, network, storage

• Fill out questionnaire

• Technical prerequisites • Install HANA HW Verification Tool

• Iterative hardware verification test

• Evaluate and discuss measured KPI‘s

• If KPI‘s fullfilled proceed to „Release“

• Ensure support for all HW components

• Get go-live approval from SAP


SAP HANA virtualization Private cloud options

Currently, the only SAP supported virtualization solution is VMware

vSphere 5.1 on HANA SPS 05 (or later) and is limited to non-productive

and non-performance critical use.


SAP HANA Enterprise Cloud

SAP HANA Enterprise Cloud

SAP Business Warehouse BW | BPC

SAP Business Suite ERP | CRM | …

Custom Apps Big Data | Consumer

SAP HANA Cloud Platform

Services

Assessment

Onboarding &

Migration

Cloud Hosting &

Managed Services

Custom Services

In-memory Infrastructure

• 24x7 customer support availability

• SAP experts in our operations center

• Enterprise grade service availability

• Disaster recovery solutions for mission-critical systems

• Mission critical operations with cloud elasticity

• Power of real time plus the simplicity of the cloud


Choice of Deployment Scenario

Hybrid Cloud On-premise

Develop, Test, Deploy in Any Environment or in a Hybrid

Pilot

Final


SAP HANA scalability Scales from very small servers to very large clusters

Single Server

• 2 CPU 128GB to 8 CPU 1TB

(Special layout for Suite on HANA

for up to 4 TB per host)

• Single SAP HANA deployments for

data marts or accelerators

• Support for high availability

and disaster recovery

Scale Out Cluster

• 2 to n servers per cluster

• Each server is either 4 CPU/512GB or 8

CPU/1TB

• Largest certified configuration: 56 servers

• Largest tested configuration: 100+

servers

• Support for high availability

and disaster recovery

Cloud Deployment

• SAP HANA instances can be

deployed to AWS

• Limited to developer license

• SAP HANA Enterprise Cloud


Scale out Distributed systems and Building blocks

Server 1

Server 2

Server 3

Server 4

Server 5

Server 6

1 server:

40 cores, 512 GB RAM

TOTAL:

240 cores, 3 TB RAM

SAP HANA hardware partners provide appliances in blocks e.g.:

S 1 server with 2 CPUs (20 cores) and 128/256 GB RAM

M 1 server with 4 CPUs (40 cores) and up to 512 GB RAM

L 1 server with 8 CPUs (80 cores) and up to 1 TB GB RAM


SAP HANA High Availability Minimal Setup for Host Auto-Failover

Minimal setup for a Host Auto-Failover (Scale-Out):

2 Servers including one Standby

External storage or similar technology necessary which ensures the data provisioning to second node via external data location

This setup aims for High Availability not performance scaling or size.

Note: Some use cases (e.g. SAP BW powered by HANA) might have different requirements or recommendations for minimal setups (e.g. BW has a defined setup for SAP HANA Scale-Out – SAP note 1637145 attached PDF).

Master

Name

Server

Index

Server

Data

Disks

Log

Disks

active standby

Index

Server

Name

Server

https://service.sap.com/sap/support/notes/1637145


SAP HANA High Availability Different HA implementation by HW partners

Server 1

Server 2

Server 3

Server 4

Server 5

Server 6

Standby server

Share

d s

tora

ge

OR

Server 1

Server 2

Server 3

Server 4

Server 5

Server 6

Standby server

Share

d inte

rnal dis

ks


SAP HANA Disaster Recovery: Storage Replication Cluster across Data Centers


SAP HANA Disaster Recovery: System Replication Cluster across Data Centers with DB controlled transfer

Data Center 2 Data Center 1

OS: Mounts

Data

Volumes

Log

Volume

OS: DNS, hostnames, virt. IPs

Primary (active)

Name

Server

Index

server

Name

Server

Index

server

Name

Server

Index

server

Secondary (active, data pre-loaded)

Name

Server

Index

server

Name

Server

Index

server

Name

Server

Index

server

HA

Solu

tion P

art

ner

Clients Application Servers

HA

Solu

tion P

art

ner

Data

Volumes

Log

Volume

Data

Volumes

Log

Volume

Data

Volumes

Log

Volume

Transfer

by

HANA

database

kernel


SAP HANA Disaster Recovery: System Replication Cluster across Data Centers with QA & Dev on 2nd site

Data Center 2 Data Center 1

OS: Mounts

Data

Volumes

Log

Volumes

OS: DNS, hostnames, virt. IPs

Primary (active)

Name

Server

Index

server

Name

Server

Index

server

Name

Server

Index

server

Secondary (active,)

Name

Server

Index

server

Name

Server

Index

server

Name

Server

Index

server

HA

Solu

tion P

art

ner

Clients Application Servers

HA

Solu

tion P

art

ner

Data

Volumes

Log

Volumes

Data

Volumes

Log

Volumes

Data

Volumes

Log

Volumes

Transfer

by

HANA

database

kernel

Data

Volumes

Log

Volume

Data

Volumes

Log

Volume

PRD QA/DEV

QA/DEV

running

PRD

shadow

operation

QA/DEV

running

PRD

shadow

operation

SAP HANA Building applications


Further optimization for speed

Delegate data intense operations to the in-memory computing

Application Layer

Data Layer

Avoid movement of detailed data! Calculate first then move results.

Today, many data

intense operations

are executed in the

application layer

High performant

apps delegate data

intense operations

to the in-memory

computing


SAP ERP powered by SAP HANA - Optimizations Where to find them?

New Report ID:

RFBNUM10H

RFDRRE01H

…

New Transaction ID:

FAGLL03H

FBL1H

…

New bussines function:

FIN_TRM_PERF_OPT

LOG_MM_OPT_POH

…

Note 1761546 - SAP ERP powered by SAP HANA - Optimizations









Use stored procedures (MM example)

New ABAP feature ’CALL DATABASE PROCEDURE’ calls a store

procedure in HANA



Use stored procedures (MM example cont.)


ABAP coding

The way we know it


ABAP coding

Optimized


SAP HANA System Landscape

Data Provisioning


HANA – Developer Scenarios

Business Analytics with HANA

HANA

Analytics

1. Load data

Develop business analytics scenarios on top of HANA using SAP

Business Objects tools.

2. Create model

3. Build apps using

BOBJ tools



JDBC/SQL Programming HANA

HANA

New Apps

1. Load data

Develop applications on top of HANA using ODBC/JDBC and SQL

2. Create model

4. Build custom apps

using ODBC/JDBC

ODBC/JDBC

3. Use SQL Script or

advanced libraries

(e.g. Predictive

Analytics)



HANA Apps

HANA

New Apps

1. Load data

Develop lightweight apps directly on HANA

2. Create model

4. Build custom apps

using

JavaScript/XS/HTML5

3. Use SQL Script or

advanced libraries

(e.g. Predictive

Analytics)


SAP HANA Extended Application Services

HANA

Browser

http(s); OData (pure data only)

(minimal data volume)

XSEngine

Procedural Appl. Logic

Complete UI Rendering

HTML5: Javascript execution

IndexServer

Data-oriented Appl. Logic

XS Applications

Inbound channel

• HTTP

OData

• Drastic code reduction

Outbound connectivity

HTTP, SMTP

UI services

• SAPUI5

• Portal Services

Built-in services


SAP HANA

Further information

http://www.saphana.com/

http://www.sap.com/hana/

http://www.suiteonhana.com/





http://www.suiteonhana.com/


SAP HANA Training Curriculum

OHA10

OKP – SAP HANA

Tec Dev Mod

43 h

HAIMPE

SAP HANA eAcademy

Tec Dev Mod

20 h

HA100

SAP HANA – Introduction

Tec Dev Mod

2 d

HA100E 8 h

HA150

SQL Basics for SAP

HANA

Tec Dev Mod

2 d

HA901

CO-PA Accelerator with

SAP HANA

Mod

4 h

HA300

SAP HANA –

Implementation and

Modeling

Tec Dev Mod

3 d

HA300E 12 h

HA200

SAP HANA –

Administration and

Operations

Tec Dev Mod

3 d

HA200R 9 h

HA400

SQL Basics for SAP

HANA

Tec Dev Mod

2 d

HA360

SAP HANA – Hands-on

Lab

Tec Dev Mod

2 d C_HANAIMP_1


Tec Dev Mod

3 h

C_HANATEC_1


Tec Dev Mod

3 h

P_HANAIMP_1

SQL Basics for SAP

HANA

Tec Dev Mod

3 h

BW362

SAP BW on SAP HANA

Tec Dev Mod

3 d

BW362R 9 h

Target audience

Development Role

Technical Role

Modeling Role

Delivery Formats

3 d Classroom

43 h E-Learning, OKP, RCT

43 h Certification

© 2013 SAP AG or an SAP affiliate company. All rights reserved.

Hvala!

Contact information:

Dragoljub Ljubičić

Senior Technology Consultant

SAP West Balkans d.o.o.

[email protected]

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