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Sinopsis
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 topic--such as core technologies or data transfer--and 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 technologies--Hadoop Distributed File System (HDFS), MapReduce, YARN, and Spark
- Database and data management--Cassandra, HBase, MongoDB, and Hive
- Serialization--Avro, JSON, and Parquet
- Management and monitoring--Puppet, Chef, Zookeeper, and Oozie
- Analytic helpers--Pig, Mahout, and MLLib
- Data transfer--Scoop, Flume, distcp, and Storm
- Security, access control, auditing--Sentry, Kerberos, and Knox
- Cloud computing and virtualization--Serengeti, Docker, and Whirr
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Acerca del autor
Kevin Sitto is a Sr. Field Solutions Engineer where he provides consulting services helping clients understand and address their big data needs. His duties include developing prototypes and proof of concept applications, providing solution architecture guidance and assisting with detailed technical design. Prior to joining Pivotal Kevin was a Principal Software Engineer with RequiTest Inc, a small consulting firm in Columbia MD. At RequiTest he lead efforts develop secure and scalable cloud computing systems based on the Hadoop Map/Reduce platform. He has a background in software development and engineering and has experience with every stage of the SDLC. Kevin is based in Columbia MD and holds a B.A. in Computer Engineering from DeVry University in addition to a number of technical certifications. He has authored a number of technical articles and has spoken at several conferences on the topics of Big Data and Cybersecurity.Marshall Presser is a Field Chief Technology Officer for Pivotal and is based in McLean VA. In addition to helping customers solve complex analytic problems with the Greenplum Database, he leads the Hadoop Virtual Field Team, working on issues of integrating Hadoop with relational databases. Prior to coming to Pivotal (formerly Greenplum), he spent 12 years at Oracle, specializing in High Availability, Business Continuity, Clustering, Parallel Database Technology, Disaster Recovery and Large Scale Database Systems. Marshall has also worked for a number of hardware vendors implementing clusters and other parallel architectures. His background includes parallel computation, operating system and compiler development as well as private consulting for organizations in heath care, financial services, and federal and state governments. Marshall holds a B.A in Mathematics and an M.A. in Economics and Statistics from the University of Pennsylvania and a M.Sc. in Computing from Imperial College, London.
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Field Guide to Hadoop: An Introduction to Hadoop, Its Ecosystem, and Aligned Technologies
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Field Guide to Hadoop: An Introduction to Hadoop, its Ecosystem, and Aligned Technologies
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ISBN 13: 9781491947937
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Field Guide to Hadoop: An Introduction to Hadoop, Its Ecosystem, and Aligned Technologies
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Field Guide to Hadoop : An Introduction to Hadoop, Its Ecosystem, and Aligned Technologies
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Paperback. Condición: New. 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 topic-such as core technologies or data transfer-and 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 technologies-Hadoop Distributed File System (HDFS), MapReduce, YARN, and Spark Database and data management-Cassandra, HBase, MongoDB, and Hive Serialization-Avro, JSON, and Parquet Management and monitoring-Puppet, Chef, Zookeeper, and Oozie Analytic helpers-Pig, Mahout, and MLLib Data transfer-Scoop, Flume, distcp, and Storm Security, access control, auditing-Sentry, Kerberos, and Knox Cloud computing and virtualization-Serengeti, Docker, and Whirr. Nº de ref. del artículo: LU-9781491947937
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