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Greenplum hadoop
1.
© Copyright 2012
EMC Corporation. All rights reserved. 1
2.
整合分析結構與非結構
性資料暨應用案例 Greenplum Enable Big Data Analytics 邱垂吉 Jimmy Chiu 技術顧問/EMC Greenplum Taiwan © Copyright 2012 EMC Corporation. All rights reserved. 2
3.
Volume, Variety, Velocity,
Value + Complexity New insights on Contextual and customers, products, Velocity Volume location-aware and operations delivery to any Big Data device Variety Complexity Documents Transactional Smart Grid Images Audio Text Video Data • Volume: data volumes approaching multiple petabytes • Velocity: data being generated and ingested for analysis in real-time • Variety: tabular, documents, e-mail, metering, network, video, image, audio • Complexity: different standards, domain rules, and storage formats per data type Gartner March 2011 © Copyright 2010 EMC Corporation. All rights reserved. 3
4.
Sample Big Data
Scenarios LOAN PROCESSING AUTO INSURANCE SMART GRID ANALYTICS IN BANKING IN P&C INSURANCE IN UTILITIES/ENERGY REAL-TIME STATISTICAL PROACTIVE EMERGENCY RESPONSE VIDEO ANALYTICS IN HEALTHCARE IN RETAIL PROCESS CONTROL IN MANUFACTURING © Copyright 2010 EMC Corporation. All rights reserved. 4
5.
Big Data Analytics
For Competitive Advantage Suppliers Suppliers Who are my most valuable Manufacturing customers? Manufacturing Inventory Inventory Physical Assets Physical Assets What are my most Distribution important Services Distribution products? Personal Marketing Services Mass Additional Marketing Profits What are my most successful campaigns? Customers Customers Today’s Business Model Big Data Analytics Business Model © Copyright 2010 EMC Corporation. All rights reserved. 5
6.
Big Data meets
Fast Data Social and Personal – Every Minutes: •Google gets more than 2 million search queries •About 47,000 people download an App •Some 100,000 tweets hit Twitter •Almost 300,000 people log on to Facebook Business and Transactional: •CERN (European Organization for Nuclear Research) generates 40TB/sec of scientific data •Wal-Mart – 1 million transactions per hour •World’s top systems currently trade at faster than 50 microseconds •New York Stock Exchange generates 1TB of new trading data daily © Copyright 2010 EMC Corporation. All rights reserved. 6
7.
Working together, they
enable entirely New Business Models Big Data allows you to find opportunities you didn’t know you had. Fast Data allows you to respond to opportunities before they are gone. In the Financial Services Industry, large quantities of historical data need to be processed against a growing number of fast-moving data feeds. Batch processing is no longer a suitable solution! © Copyright 2010 EMC Corporation. All rights reserved. 7
8.
Effective Customer Segmentation
is all about blending Structured and Unstructured Data – Transaction data (structured data) tells you what the customer did. – Unstructured data can tell you why they did it, why some others did not, what else they need or want, and what problems they may have. © Copyright 2010 EMC Corporation. All rights reserved. 8
9.
Big Data Architecture
Solving Big Data challenge involves more than just Requirements managing volumes of data. ― Gartner • Multiple data types: structured, semi-structured, unstructured • Integrated data stores: real-time, traditional, data warehouse • Modern development tools: Java, lightweight messages, mobile-enabled • Cloud-enabled: elastic scale, self-healing Beware point solutions – integration is critical! © Copyright 2010 EMC Corporation. All rights reserved. 9
10.
Greenplum Overview © Copyright
2010 EMC Corporation. All rights reserved. 10
11.
Greenplum Product Line ©
Copyright 2010 EMC Corporation. All rights reserved. 11
12.
Architecture of Greenplum Flexible
framework for processing large datasets Process large datasets with support for SQL both SQL and MapReduce MapReduce Master Master Master servers optimize queries for the most efficient query execution Interconnect for continuous pipelining of data processing Segment servers process queries close to the data in parallel MPP Scatter/Gather streaming for fast loading of data © Copyright 2010 EMC Corporation. All rights reserved. 12
13.
Greenplum MPP Share-Nothing
Arch. MPP Share Share Disk Share nothing everything eg: eg: eg: Oracle RAC Greenplum Unix server Intranet Master Intranet DB DB DB DB DB DB DB DB DB SAN/FC Disk SAN Disk Disk Disk Disk Share disk © Copyright 2010 EMC Corporation. All rights reserved. 13
14.
Benefits of the
Greenplum Database Architecture • Simplicity – Parallelism is automatic – no manual partitioning required – No complex tuning required – just load and query – HA – Best of breed x86 and Ethernet networking technologies • Scalability – Linear scalability – Each node adds storage, query performance, loading performance • Flexibility – Fully parallelism for SQL92, SQL99, SQL2003 OLAP, MapReduce – Any schema (star, snowflake, 3NF, hybrid, etc) – Rich extensibility and language support (Perl, Python, R, C, etc) – Structure, semi-structure and unstructure © Copyright 2010 EMC Corporation. All rights reserved. 14
15.
Greenplum and Hadoop
Analytics Semi-Structured Structured Machine Data UnStructured ERP/CRM Logs Images/Sound Ad-hoc Analysis batch reporting on static data Dynamic Data © Copyright 2010 EMC Corporation. All rights reserved. 15
16.
Big Data Analytics The
Power of Data Co-Processing Greenplum Chorus Analytic Productivity & Tool Integration End-to-end Platform Management & Control Data Access And Query Greenplum Commander SQL, MapReduce, SAS, MADLib, Mahout, R, and others SQL Engine MapReduce Engine parallel For Unstructured Data For Structured Data data exchange •Enterprise ready Apache • In-database Advanced Analytics Hadoop • Extreme performance on •Faster, more dependable, and commodity hardware parallel easier to use data exchange Greenplum Database Greenplum Hadoop Network Parallel Loading Of All Data Types © Copyright 2010 EMC Corporation. All rights reserved. 16
17.
Greenplum Hadoop • Greenplum
HD – Enterprise-ready Apache Hadoop – Proven at Scale in 1,000 node Analytics Workbench – Single product with 2 storage options (Isilon & HDFS) • Enterprise Edition becomes Greenplum MR: – Advanced features – 100% API compatible – Software-only product © Copyright 2010 EMC Corporation. All rights reserved. 17
18.
AWB Update Analytics Workbench
Operational! •1025 nodes operational •1011 nodes with GPHD installed •8 total projects have been on boarded from university collaboration to partner technology evaluation Proposals accepted by customer engagement team – info@analyticsworkbench.com •Engagement team will learn project objectives •JEDI council approves/disproves project based on technical feasibility and alignment with company goals •Projects informed of decisions and timelines Cluster access via - http://portal.analyticsworkbench.com/ © Copyright 2010 EMC Corporation. All rights reserved. 18
19.
Apache Hadoop Pain
Points • Poor Job and Application Monitoring Monitoring Solution • Non-existent Performance Monitoring Operability • Complex System Configuration and Manageability and • No Data Format Interoperability & Manageability Storage Abstractions • Poor Dimensional Lookup Performance Performance • Very poor Random Access and Serving Performance © Copyright 2010 EMC Corporation. All rights reserved. 19
20.
Greenplum MR: Enterprise Edition
Stack 100% APACHE Enhanced Monitoring INTERFACE Hive Pig HBase Zookeeper MapReduce Framework (MapRed) Distributed File System © Copyright 2010 EMC Corporation. All rights reserved. 20
21.
Greenplum MR: Enterprise
Edition Enterprise-Ready Hadoop Platform for Unstructured Data • 2 – 5x Faster than Apache Faster Hadoop • High Availability Reliable • Mirroring Easier to • NFS mountable Use • Graphical System Management © Copyright 2010 EMC Corporation. All rights reserved. 21
22.
Greenplum MR Simple
Management • Health Monitoring • Cluster Administratio n • Application Provisioning © Copyright 2010 EMC Corporation. All rights reserved. 22
23.
Rack Level Monitoring ©
Copyright 2010 EMC Corporation. All rights reserved. 23
24.
Greenplum MR Delivers
True Return on Investment • NFS direct access to simply load and access data directly in a Hadoop cluster • Enables standard tools and utilities to work directly on data contained in Hadoop • Heatmap user interface provides full cluster visibility and control. • Eliminates all single points of failure • High Availability for Job Tracker , NameNode & NFS • Snapshots allow point-in-time data protection and recovery. • Mirroring for business continuity includes wide area replication support. • Speeds jobs by 2X – 5X • Provides faster performance with ½ the hardware • Substantial capital and operating expense savings © Copyright 2010 EMC Corporation. All rights reserved. 24
25.
EMC Greenplum
Fastest data loading Advanced analytics DATA IN IN-DATABASE ANALYTICS DECISIONS OUT Scatter/Gather Streaming Optimized for fast query execution Unified data access for greater technology for the world’s and linear scalability insight and value from data fastest data loading •Move processing closer to data •Enable parallel analysis •Eliminate data load •Shared-nothing, massively across the enterprise bottlenecks parallel processing (MPP) •Open platform with broad •Clean and integrate new data scale-out architecture language support •Several loading options, •Computing is automatically •Certified enterprise ranging from bulk load optimized and distributed connectivity and integration updates to micro-batching for across resources with most business near real-time processing • Provides the best concurrent intelligence; extract, multi-workload performance transform, and load (ETL); and management products © Copyright 2010 EMC Corporation. All rights reserved. 25
26.
EMC Big Data
Analytics Reference Architecture Data Sources Hadoop Alerts Statistics Reduce Documents Genetic Algorithms Map- Map- Ecosystem* HDFS Reduce Dashboards Mobile Key Values Documents Other NoSql Machine Reports Data Mining Data Quality NoSQL Stores Multimedia parallel data exchange Spreadsheets SQL Stores Web/Social OLAP BU 1 Operations Research Data Marts LOB data MDM Mobile Enterprise Data BU 2 ERP Warehouse Neural Nets BU 3 ETL Data Visualization CRM Federated BI as a Data Service POS Warehouse Data Data Stores and Data Presentation & Integration Input Access Analysis Delivery Structured Traditional data Traditional data Big data analytics data sources Integration warehousing ramifications *Hadoop Ecosystem includes: Hive, Pig, Mahout, HBase, ZooKeeper, Oozie, Sqoop, Avro © Copyright 2010 EMC Corporation. All rights reserved. 26
27.
Architecture for Business
Value Business Value Chorus for Collaboration Analytics Analytics Self-develop app Self-develop app Java API Analytics tools Analytics tools JDBC (Mahout) (SAS, R, MADlib and more) ODBC Hbase .csv SAS & MADlib .txt GPDB - In GPDB - In Memory MapRFS (GPMR) ETL MapRFS: C++; MR: C++ x Load Performance: 2~5X DB’s Files High Availability Stable © Copyright 2010 EMC Corporation. All rights reserved. 27
28.
Big Data And
EMC 4 New Analytic Applications Data Science 3 2 Unified Analytics Platform Petabyte Scale Data Storage 1 © Copyright 2010 EMC Corporation. All rights reserved. 29
29.
SAS / Greenplum
Product Overview SAS High Performance Computing SAS Access for SAS In-Database SAS In-Memory Integration Processing Analytics Provides integration capability to Requires SAS Enterprise Miner in New functionality from SAS that a number of databases order to be of value requires dedicated database appliance Allows for increased performance Will lead to significant Very high performance for business of Base SAS Procs improvement in performance users that can significantly increase revenues or decrease costs as a result of improved performance Products: SAS Access for Greenpum Products: SAS Access for Products: SAS Access for Greenplum, SAS Grid Manager, SAS Greenplum, SAS Grid Manager, SAS Enterprise Miner, SAS Scoring High Performance Analytics Accelerator for Greenplum © Copyright 2010 EMC Corporation. All rights reserved. 30
30.
SAS and Greenplum
UAP Integrated Architecture Data Data Data Bl LOB Scientist Engineer Analyst Analyst User SAS Business Intelligence DATA SCIENCE TEAM Greenplum Chorus - Analytic Productivity Layer SAS Analytics Data Access & Query Layer (SAS ACCESS, SQL, MapReduce) Greenplum Database Greenplum Hadoop Private/Hybrid Cloud Infrastructure or Appliance Data Platform Admin SAS Information Management © Copyright 2010 EMC Corporation. All rights reserved. 31
31.
In A Single
Unified Analytics Platform Self-Service Iterative, Agile Transparent, Real-time Collaboration Structured & Unstructured Data Analyze Petabytes Of Current Data Virtual, Scale Out Architecture © Copyright 2010 EMC Corporation. All rights reserved. 32
32.
© Copyright 2010
EMC Corporation. All rights reserved. 33
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