PacktLib: Scaling Big Data with Hadoop and Solr

Scaling Big Data with Hadoop and Solr

Credits

About the Author

About the Reviewer

www.PacktPub.com

Preface

Processing Big Data Using Hadoop and MapReduce

Understanding Apache Hadoop and its ecosystem

Storing large data in HDFS

Creating MapReduce to analyze Hadoop data

Installing and running Hadoop

Managing a Hadoop cluster

Summary

Understanding Solr

Installing Solr

Apache Solr architecture

Configuring Apache Solr search

Loading your data for search

Summary

Making Big Data Work for Hadoop and Solr

The problem

Understanding data-processing workflows

Using Solr 1045 patch – map-side indexing

Using Solr 1301 patch – reduce-side indexing

Using SolrCloud for distributed search

Using Katta for Big Data search (Solr-1395 patch)

Summary

Using Big Data to Build Your Large Indexing

Understanding the concept of NOSQL

The CAP theorem

Understanding the concepts of distributed search

Lily – running Solr and Hadoop together

Deep dive – shards and indexing data of Apache Solr

Configuring SolrCloud to work with large indexes

Summary

Improving Performance of Search while Scaling with Big Data

Understanding the limits

Optimizing the search schema

Index optimization

Optimization the search runtime

Monitoring the Solr instance

Summary

Use Cases for Big Data Search

Use Cases for Big Data Search

Use Cases for Big Data Search

Creating Enterprise Search Using Apache Solr

Creating Enterprise Search Using Apache Solr

Creating Enterprise Search Using Apache Solr

Creating Enterprise Search Using Apache Solr

Creating Enterprise Search Using Apache Solr

Creating Enterprise Search Using Apache Solr

Creating Enterprise Search Using Apache Solr

Sample MapReduce Programs to Build the Solr Indexes

Sample MapReduce Programs to Build the Solr Indexes

Sample MapReduce Programs to Build the Solr Indexes

Sample MapReduce Programs to Build the Solr Indexes

Index