Getting Started with Kudu: Perform Fast Analytics on Fast Data Contributor(s): Spaggiari, Jean-Marc (Author), Kovacevic, Mladen (Author), Noland, Brock (Author) |
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ISBN: 1491980257 ISBN-13: 9781491980255 Publisher: O'Reilly Media OUR PRICE: $47.49 Product Type: Paperback - Other Formats Published: August 2018 |
Additional Information |
BISAC Categories: - Computers | Databases - Data Mining - Computers | Systems Architecture - Distributed Systems & Computing - Computers | System Administration - Storage & Retrieval |
Physical Information: 0.3" H x 7" W x 9.1" (0.50 lbs) 153 pages |
Descriptions, Reviews, Etc. |
Publisher Description: Fast data ingestion, serving, and analytics in the Hadoop ecosystem have forced developers and architects to choose solutions using the least common denominator--either fast analytics at the cost of slow data ingestion or fast data ingestion at the cost of slow analytics. There is an answer to this problem. With the Apache Kudu column-oriented data store, you can easily perform fast analytics on fast data. This practical guide shows you how. Begun as an internal project at Cloudera, Kudu is an open source solution compatible with many data processing frameworks in the Hadoop environment. In this book, current and former solutions professionals from Cloudera provide use cases, examples, best practices, and sample code to help you get up to speed with Kudu.
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Contributor Bio(s): Spaggiari, Jean-Marc: - Jean-Marc Spaggiari, an early adopter of Kudu, works as a Principal Solutions Architect for Cloudera to support Hadoop, Kudu, HBase and other tools through technical support and consulting work. His deep knowledge of HBase and HDFS allows him to better understand Kudu and its applications. Mladen Kovacevic comes from a development background in RDBMS technology, and sees Kudu as a game changer in the Hadoop ecosystem. He has presented Kudu at several local meetups, presented on the state of Spark on Kudu during its beta while providing feedback early enough to ensure Spark with Kudu is a first-class citizen at its launch. He is a contributor to Apache Kudu and Kite SDK projects, and works as a Solutions Architect at Cloudera. Mladen's experience includes years of RDBMS engine development, systems optimization, performance and architecture, including optimizing Hadoop on the Power 8 platform while developing IBM's Big SQL technology. Noland, Brock: -Brock Noland followed Kudu months before the first line of code was written, by following Todd Lipcon's paper reading habits. Brock is Chief Architect of phData, a pure-play Hadoop Managed Service Provider. Prior to founding phData, Brock spent four years at Cloudera as a Trainer, Solution Architect, Engineer, Sales Engineer, and Engineering Manager. Brock is a co-founder of Apache Sentry and Apache Project Committee Member on Apache Hive, Parquet, Crunch, Flume, and Incubator. Brock was a mentor to Kudu in the incubator and currently mentors Apache Impala (incubating). In addition he is a member of the Apache Software Foundation. Ryan Bosshart is a Principal Systems Engineer at Cloudera. Ryan has spent the last 10 years building and architecting distributed systems. At Cloudera, Ryan leads the field storage specialization team where he focuses on Apache HDFS, HBase, and Kudu. He has worked with many early users of Kudu to build their relational, time-series, IOT, or real-time architectures. He has seen first-hand Kudu's ability to improve performance and simplify architectures. Ryan is a co-chair of the Twin Cities Spark and Hadoop User Group and the author of the training video Getting Started with Kudu (O'Reilly). |