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Oreilly - Using Kudu with Apache Spark and Apache Flume - 9781491985724
Oreilly - Using Kudu with Apache Spark and Apache Flume
by Ryan Bosshart | Released March 2017 | ISBN: 9781491985717


Apache Kudu, the breakthrough storage technology, is often used in conjunction with other Hadoop ecosystem frameworks for data ingest, processing, and analysis. This is a practical, hands-on course that shows you how Kudu works with four of those frameworks: Apache Spark, Spark SQL, MLlib, and Apache Flume.You'll use the Kudu-Spark module with Spark and SparkSQL to seamlessly create, move, and update data between Kudu and Spark; then use Apache Flume to stream events into a Kudu table, and finally, query it using Apache Impala. The course is designed for learners with some limited experience using Hadoop ecosystem components like HDFS, Hive, Spark, or Impala. Get hands-on experience with Kudu and add more tools to your Big Data toolbox Learn how to move data between Kudu tables and Spark apps using the Kudu-Spark module Understand how to stream and analyze data in real-time with Flume and Kudu Create a movie ratings predictor using Flume and save the predicted values into Kudu See how these open source tools combine to create simple and fast data engineering pipelinesRyan Bosshart is a Principal Systems Engineer at Cloudera, where he leads a specialized team focused on Hadoop ecosystem storage technologies such as HDFS, Hbase, and Kudu. An architect and builder of large-scale distributed systems since 2006, Ryan is co-chair of the Twin Cities Spark and Hadoop User Group. He speaks about Hadoop technologies at conferences throughout North America and holds a degree in computer science from Augsburg College. Show and hide more Publisher resources Download Example Code
  1. Welcome To The Course 00:00:23
  2. About The Author 00:01:27
  3. Integrating Kudu With Apache Flume 00:11:49
  4. Using Kudu With Apache Spark Part 1 00:07:45
  5. Using Kudu With Apache Spark Part 2 00:06:07
  6. Show and hide more

    Oreilly - Using Kudu with Apache Spark and Apache Flume


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