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You're reading from  Scaling Big Data with Hadoop and Solr, Second Edition

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Published inApr 2015
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ISBN-139781783553396
Edition1st Edition
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Hrishikesh Vijay Karambelkar
Hrishikesh Vijay Karambelkar
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Hrishikesh Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
Read more about Hrishikesh Vijay Karambelkar

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Distributed search using Apache Blur


Apache Blur is a distributed search engine that can work with Apache Hadoop. It is different from the traditional big data system in that it provides a relational data model-like storage, on top of HDFS. Apache Blur does not use Apache Solr; however, it consumes Apache Lucene APIs. Blur provides faster data ingestion using MapReduce and advanced searches such as a faceted search, fuzzy, pagination, and a wildcard search.

Apache Blur provides a row-based data model (similar to RDBMS), with unique row IDs. Records should have a unique record ID, row ID, and column family. Column family is a group of logical columns. For example, the personal information column family will have columns such as name, companies with which the person works, and contact information. The following figure shows how Apache Blur works closely with Apache Hadoop:

Apache Blur uses Hadoop to store its indexes in a distributed manner. It uses Thrift APIs for all interprocess communication...

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Scaling Big Data with Hadoop and Solr, Second Edition
Published in: Apr 2015Publisher: ISBN-13: 9781783553396

Author (1)

author image
Hrishikesh Vijay Karambelkar

Hrishikesh Vijay Karambelkar is an innovator and an enterprise architect with 16 years of software design and development experience, specifically in the areas of big data, enterprise search, data analytics, text mining, and databases. He is passionate about architecting new software implementations for the next generation of software solutions for various industries, including oil and gas, chemicals, manufacturing, utilities, healthcare, and government infrastructure. In the past, he has authored three books for Packt Publishing: two editions of Scaling Big Data with Hadoop and Solr and one of Scaling Apache Solr. He has also worked with graph databases, and some of his work has been published at international conferences such as VLDB and ICDE.
Read more about Hrishikesh Vijay Karambelkar