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Scaling Apache Solr

You're reading from   Scaling Apache Solr Optimize your searches using high-performance enterprise search repositories with Apache Solr

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Product type Paperback
Published in Jul 2014
Publisher
ISBN-13 9781783981748
Length 298 pages
Edition 1st Edition
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Author (1):
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Hrishikesh Vijay Karambelkar Hrishikesh Vijay Karambelkar
Author Profile Icon Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Table of Contents (13) Chapters Close

Preface 1. Understanding Apache Solr FREE CHAPTER 2. Getting Started with Apache Solr 3. Analyzing Data with Apache Solr 4. Designing Enterprise Search 5. Integrating Apache Solr 6. Distributed Search Using Apache Solr 7. Scaling Solr through Sharding, Fault Tolerance, and Integration 8. Scaling Solr through High Performance 9. Solr and Cloud Computing 10. Scaling Solr Capabilities with Big Data A. Sample Configuration for Apache Solr Index

Loading data using native handlers


Apache Solr supports add, delete, and update operations on its index store. It ships with inbuilt native handers to work with JSON, XML, and CSV format. These handlers can be called over HTTP by posting a message to them in one of these formats through an update call. Apache Solr also provides an inbuilt posting tool (client application), that can be used to upload data to an Apache Solr server.

Quick and simple data loading – post tool

Apache Solr provides a command-line tool by default for posting your XML information directly to the Apache Solr server. Using this tool, one can upload a document file/folder or it can also be provided through a standard input (STDIN), that is, typed using your keyboard. $SOLR_HOME/example/exampledocs/post.jar provides this data upload capability. There are some example files that you can use to upload to Solr Server. You can run it using the following command:

$ java <arguments> –jar post.jar <filenames/raw data...
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