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Getting Started with Greenplum for Big Data Analytics
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Table of Contents
Getting Started with Greenplum for Big Data Analytics
Credits
Foreword
About the Author
Acknowledgement
About the Reviewers
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Errata
Piracy
Questions
1. Big Data, Analytics, and Data Science Life Cycle
Enterprise data
Classification
Features
Big Data
So, what is Big Data?
Multi-structured data
Data analytics
Data science
Data science life cycle
Phase 1 – state business problem
Phase 2 – set up data
Phase 3 – explore/transform data
Phase 4 – model
Phase 5 – publish insights
Phase 6 – measure effectiveness
References/Further reading
Summary
2. Greenplum Unified Analytics Platform (UAP)
Big Data analytics – platform requirements
Greenplum Unified Analytics Platform (UAP)
Core components
Greenplum Database
Hadoop (HD)
Chorus
Command Center
Modules
Database modules
HD modules
Data Integration Accelerator (DIA) modules
Core architecture concepts
Data warehousing
Column-oriented databases
Parallel versus distributed computing/processing
Shared nothing, massive parallel processing (MPP) systems, and elastic scalability
Shared disk data architecture
Shared memory data architecture
Shared nothing data architecture
Data loading patterns
Greenplum UAP components
Greenplum Database
The Greenplum Database physical architecture
The Greenplum high-availability architecture
High-speed data loading using external tables
External table types
Polymorphic data storage and historic data management
Data distribution
Hadoop (HD)
Hadoop Distributed File System (HDFS)
Hadoop MapReduce
Chorus
Greenplum Data Computing Appliance (DCA)
Greenplum Data Integration Accelerator (DIA)
References/Further reading
Summary
3. Advanced Analytics – Paradigms, Tools, and Techniques
Analytic paradigms
Descriptive analytics
Predictive analytics
Prescriptive analytics
Analytics classified
Classification
Forecasting or prediction or regression
Clustering
Optimization
Simulations
Modeling methods
Decision trees
Association rules
The Apriori algorithm
Linear regression
Logistic regression
The Naive Bayesian classifier
K-means clustering
Text analysis
R programming
Weka
In-database analytics using MADlib
References/Further reading
Summary
4. Implementing Analytics with Greenplum UAP
Data loading for Greenplum Database and HD
Greenplum data loading options
External tables
gpfdist
gpload
Hadoop (HD) data loading options
Sqoop 2
Greenplum BulkLoader for Hadoop
Using external ETL to load data into Greenplum
Extraction, Load, and Transformation (ELT) and Extraction, Transformation, Load, and Transformation (ETLT)
Greenplum target configuration
Sourcing large volumes of data from Greenplum
Unsupported Greenplum data types
Push Down Optimization (PDO)
Greenplum table distribution and partitioning
Distribution
Data skew and performance
Optimizing the broadcast or redistribution motion for data co-location
Partitioning
Querying Greenplum Database and HD
Querying Greenplum Database
Analyzing and optimizing queries
The ANALYZE function
The EXPLAIN function
Dynamic Pipelining in Greenplum
Querying HDFS
Hive
Pig
Data communication between Greenplum Database and Hadoop (using external tables)
Data Computing Appliance (DCA)
Storage design, disk protection, and fault tolerance
Master server RAID configurations
Segment server RAID configurations
Monitoring DCA
Greenplum Database management
In-database analytics options (Greenplum-specific)
Window functions
The PARTITION BY clause
The ORDER BY clause
The OVER (ORDER BY…) clause
Creating, modifying, and dropping functions
User-defined aggregates
Using R with Greenplum
DBI Connector for R
PL/R
Using Weka with Greenplum
Using MADlib with Greenplum
Using Greenplum Chorus
Pivotal
References/Further reading
Summary
Index
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Getting Started with Greenplum for Big Data Analytics
Copyright © 2013 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: October 2013
Production Reference: 1171013
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-...
