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Scaling Big Data with Hadoop and Solr, Second Edition

You're reading from   Scaling Big Data with Hadoop and Solr, Second Edition Understand, design, build, and optimize your big data search engine with Hadoop and Apache Solr

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Product type Paperback
Published in Apr 2015
Publisher
ISBN-13 9781783553396
Length 166 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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Apache Solr and Cassandra


Cassandra is one of the most widely used distributed, fault-tolerant NoSQL databases. Cassandra is designed to handle big data workloads across multiple nodes with no single point of failure. There are some interesting performance benchmarks published at Planet Cassandra (http://planetcassandra.org/NoSQL-performance-benchmarks/), which places Apache Cassandra as one of the fastest NoSQL databases among its competitors in terms of the throughput, load, and so on. Apache Cassandra allows the schema-ess storage of user information in its store called the Column Families pattern. For example, look at the data model for sales lead information as shown in the following screenshot:

This model, when transformed for the Cassandra store, becomes columnar storage. The following screenshot shows how this model would look using Apache Cassandra:

As one can see, the key here is the customer ID, and the value is a set of attributes/columns that vary for each row key. Further, columns...

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