101 ab 1345-1415

Copyright © 2012, SAS Institute Inc. All rights reserved.

巨量分析BigData，發掘企業新契機，讓不可能變可能 SAS巨量分析事業處產品顧問林輝倫( Allen Lin ) 2012/9/11

http://www.sas.com/offices/asiapacific/taiwan/high-performance-analytics/index.html


2


SAS是企業成長最忠實的夥伴

全球企業；在地支援

成立於 1976年

總部：美國北卡羅來納州卡麗

全球52個國家有400+個據點

台灣分公司成立於1989年(20年以上)

深耕台灣；國際接軌

全球10,000+位員工

台灣50+位

全球超過55,000個客戶

台灣300+客戶

Fortune 500前100大中有97家採用SAS

BusinessWeek 50 List中有41家採用SAS

2011營收：US $2.75 Billion 研發經費：24 % ($660 million)


SAS 致力於進階商業分析已超過35年

商業智慧

進階商業分析

反應型決策模式

主動型決策模式

未來會發生什麼?

過去發生了什麼?

警示

Alert

多維度分析

OLAP

即時性報表

Ad-hoc Report

標準報表

Standard Report

最適化分析

Optimization

預測模型

Predictive Modeling

趨勢分析

Forecasting

統計分析

Statistical Analysis

傳統的商業智慧 Business Intelligence

進階的商業分析 Advanced Analytics

文字分析

Text Analytics

No. 1 World Leader In Business Analytics

SAS leads Advanced Analytics Market by Wide Margin (IDC, June 2011)


資料量 VOLUME

資料種類 VARIETY

資料產生的速度 VELOCITY

資料蘊含的價值 VALUE

現在未來

資料量大小

趨勢巨量資料的挑戰


當進階商業分析遇到巨量資料…

巨量資料 Big Data

SAS高效能分析 SAS High Performance

Analytics

進階商業分析 Advanced Analytics

能夠充分運用平行處理資源進行高效能進階分析的廠商

讓分析不需受限於資料種類、樣本大小、變數量、及歷史資料的長短

讓充分的情境模擬分析可於短時間內完成

讓分析人員得以解決更多更複雜的業務問題

讓即時分析、預測、與模擬的結果融入於決策過程中

支援Hadoop, Greenplum與其他資料庫廠商等

+ =



Copyright © 2012, SAS Institute Inc. All rights reserved. 6

Allows in-memory modeling against entire data

sets on a specialized Greenplum appliance

Increases business value of models by

improving model selection

Dramatically accelerates the analytic lifecycle

process for select models

DATA

EXPLORATION

MODEL

DEVELOPMENT

MODEL

DEPLOYMENT

•

PREDICT

IVE

MODELI

NG

•

VARIABL

E

SELECTI

ON

ANALYTIC

LIFECYCLE

Scoring Accelerators – Translate Enterprise Miner models into

database-specific functions to execute

in database.

SAS Visual Analytics– Visualize ALL your data – billions of records

-- to understand the variables that your

datasets contain. Uncover relationships and

correlations in your data.

SAS HPA (the

product) – Develop predictive models in

memory alongside distributed

relational databases. Data is not

physically moved, SAS

processing is brought to the

database appliance. Models can

be built on ALL of the data.

SAS High-Performance Analytics

for Greenplum Offering

7


SAS High-Performance Analytics Key Components

8


SAS Server

libname GP joe;

proc means data=joe.flights;

var delay;

run;

Approach: Use Access Engines

Appliance

SELECT delay

FROM flights SELECT delay

FROM flights

Master Workers

Access

Engine

SELECT delay

FROM flights Big Data

9


SAS Server

libname GP joe;

proc reg data=joe.flights;

model delay=length day;

run;

Inside the Database – SQL and UDF’s

Appliance

UDF that accumulates X’X Aggregator UDF

Master Workers Access

Engine

TKTS

X’X X’X


Data Extracts

Analytical Data Preparation

Modeling Scoring

Scoring

ADS

Data Extracts

Scoring Data Preparation

Modeling

ADS

Model Development Model Deployment

Database /Data Warehouse

Database /Data Warehouse

SAS

M

Model

SAS

Traditional Architecture

Model Development Model Deployment

SAS

M

Model

SAS

Model Translation

In-database Scoring

Analytical Data Preparation

Scoring Data Preparation

Scoring

ADS

Modeling

ADS

Modeling ADS

Modeling

SAS Model

Greenplum

In-Database Architecture

SAS® IN-DATABASE

SAS高效能分析解決方案 – 架構說明

11



12


SAS Server

libname GP joe;

proc hpreg data=joe.flights;

class airline day(split);

model delay=airline day

duration …;

selection method=lasso;

run;

Alongside-the-Database

Appliance

Master Workers

tkgrid

Access

Engine

General Captains

TK TK TK TK TK

MPI

SQL SQL SQL SQL SQL


SAS High-Performance Analytics Appliance

SAS高效能分析解決方案運作方式 SAS® IN-MEMORY ANALYTICS

Greenplum Node

14


SAS High-Performance Analytics: Architecture

Submit a program from a SAS client session (eg. HPLOGISTIC)

proc hplogistic data=GPlib.sgf_binary;

class A B C;

model y = a b c x1 x2 x3;

performance details host="green1";

run;

15



Worker Node 1

Worker Node 2

Worker Node N

Master

Request is sent to the appliance

and received by the Master Node

16



Worker Node 1

Worker Node 2

Worker Node N

Master

Analytical Computation and data request sent to the worker nodes

17



Worker Node 1

Worker Node 2

Worker Node N

Master

Data request sent to the database, data slice moved into memory

18



Worker Node 1

Worker Node 2

Worker Node N

Master

Analytic Processing with internode communication

19



Worker Node 1

Worker Node 2

Worker Node N

Master

Worker node results returned to the Master Node, finalize

computation

20



Worker Node 1

Worker Node 2

Worker Node N

Root Node

Result returned to the client


高效能資料採礦與SAS EM整合，提供多個高效能運算分析節點

採礦處理流程可進

行自動化處理

與模型比較整合

SAS® IN-MEMORY ANALYTICS

SAS高效能分析解決方案 – SAS HAP與EM整合

22


SAS® HPA Server

MODELING RESULTS

Variable Selection Classification and

Prediction Text Mining


Central Entry Point Integration Role-based Views

MOBILE DATA PREPARATION EXPLORER DESIGNER

• Native iOS application

that delivers interactive

reports created in the

designer

• Monitor SAS® LASR™

Analytic server

• Load and join data

• Create calculated

columns

• Perform ad-hoc analysis

and data discovery • Create dashboard style

reports for web

or mobile

SAS® LASR™ ANALYTIC SERVER

(VISUAL ANALYTICS) SAS高效能分析解決方案 SAS® IN-MEMORY ANALYTICS

24



Copyright © 2012, SAS Institute Inc. All rights reserved. 25

Allows in-memory modeling against entire data

sets on a specialized Greenplum appliance

Increases business value of models by

improving model selection

Dramatically accelerates the analytic lifecycle

process for select models

DATA

EXPLORATION

MODEL

DEVELOPMENT

MODEL

DEPLOYMENT

•

PREDICT

IVE

MODELI

NG

•

VARIABL

E

SELECTI

ON

ANALYTIC

LIFECYCLE

Scoring Accelerators – Translate Enterprise Miner models into

database-specific functions to execute

in database.

SAS Visual Analytics– Visualize ALL your data – billions of records

-- to understand the variables that your

datasets contain. Uncover relationships and

correlations in your data.

SAS HPA (the

product) – Develop predictive models in

memory alongside distributed

relational databases. Data is not

physically moved, SAS

processing is brought to the

database appliance. Models can

be built on ALL of the data.

SAS High-Performance Analytics

for Greenplum Offering


最高準確度之預測

最佳之執行效能

最大廣度及深度之分析

無與倫比之企業績

效

WHY SAS 巨量分析

• SAS是充分運用平行處理資源進行高效能進階分析的廠商

• 讓分析人員得以解決更多更複雜的業務問題

• 讓即時分析、預測、與模擬的結果融入於決策過程中

• 讓原本很多不可能的服務與應用變可能



Documents

101 ab 1345-1415