Field Guide to Hadoop
O'Reilly Media (Verlag)
978-1-4919-4793-7 (ISBN)
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
Kevin Sitto is a Field Solutions Engineer with Pivotal Software, providing consulting services to help folks understand and address their big data needs. He lives in Maryland with his wife and two kids and enjoys making homebrew beer when he's not writing books about big data.
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.
Chapter 1Core Technologies
Hadoop Distributed File System (HDFS)
MapReduce
YARN
Spark
Chapter 2Database and Data Management
Cassandra
HBase
Accumulo
Memcached
Blur
Solr
MongoDB
Hive
Spark SQL (formerly Shark)
Giraph
Chapter 3Serialization
Avro
JSON
Protocol Buffers (protobuf)
Parquet
Chapter 4Management and Monitoring
Ambari
HCatalog
Nagios
Puppet
Chef
ZooKeeper
Oozie
Ganglia
Chapter 5Analytic Helpers
MapReduce Interfaces
Analytic Libraries
Pig
Hadoop Streaming
Mahout
MLLib
Hadoop Image Processing Interface (HIPI)
SpatialHadoop
Chapter 6Data Transfer
Sqoop
Flume
DistCp
Storm
Chapter 7Security, Access Control, and Auditing
Sentry
Kerberos
Knox
Chapter 8Cloud Computing and Virtualization
Serengeti
Docker
Whirr
Erscheint lt. Verlag | 21.4.2015 |
---|---|
Verlagsort | Sebastopol |
Sprache | englisch |
Maße | 161 x 228 mm |
Gewicht | 218 g |
Einbandart | Paperback |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Mathematik / Informatik ► Informatik ► Theorie / Studium | |
Schlagworte | Apache Cassandra • Apache HBase • Avro • Chef • Datenbanken • Hadoop • Hadoop Hive • JSON • MapReduce • MongoDB • parquet • Puppet • Spark • Yarn |
ISBN-10 | 1-4919-4793-4 / 1491947934 |
ISBN-13 | 978-1-4919-4793-7 / 9781491947937 |
Zustand | Neuware |
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