Field Guide to Hadoop

If your organization is about to enter the world of big data, you not only need to decide whether Apache Hadoop is the right platform to use, but also which of its many components are best suited to your task. This field guide makes the exercise manageable by breaking down the Hadoop ecosystem into short, digestible sections. You'll quickly understand how Hadoop's projects, subprojects, and related technologies work together.

Each chapter introduces a different topicsuch as core technologies or data transferand explains why certain components may or may not be useful for particular needs. When it comes to data, Hadoop is a whole new ballgame, but with this handy reference, you'll have a good grasp of the playing field.

Topics include:

• Core technologiesHadoop Distributed File System (HDFS), MapReduce, YARN, and Spark
• Database and data managementCassandra, HBase, MongoDB, and Hive
• SerializationAvro, JSON, and Parquet
• Management and monitoringPuppet, Chef, Zookeeper, and Oozie
• Analytic helpersPig, Mahout, and MLLib
• Data transferScoop, Flume, distcp, and Storm
• Security, access control, auditingSentry, Kerberos, and Knox
• Cloud computing and virtualizationSerengeti, Docker, and Whirr

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