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Using Spark in the Hadoop ecosystem : data analytics using Spark, HDFS, YARN, MapReduce and other Hadoop tools / with Rich Morrow.

By:

Morrow, Rich [speaker.]

Contributor(s):

Safari eBooks

Publisher: [Place of publication not identified] : O'Reilly, [2016]Description: 1 online resource (1 streaming video file (11 hr., 12 min.)) : digital, sound, colorContent type:

two-dimensional moving image

Media type:

computer
video

Carrier type:

online resource

Subject(s):

Genre/Form:

Electronic books.

LOC classification:

QA76.76.A65

Online resources:

Click here to access online

Presenter, Rich Morrow.Summary: "You're new to Big Data, you've heard about Apache Spark and Apache Hadoop and you want to play. Big Data coach Rich Morrow gets you into the game via sixteen sprints (sixteen hands-on labs) across the Spark-Hadoop ball field. First, you'll create playing areas using Amazon Web Services EMR and Cloudera Quickstart VM. Then you'll install Hadoop, run basic HDFS commands, learn MapReduce, use Flume and Sqoop, run Spark and then run Spark again. You'll play with Spark SQL, learn common MLLib usage, do analysis with Hive, ETL with Pig, and then jog through Hadoop/Cloud use cases, Hbase basics, and enterprise integration. When practice is over, you'll know Spark, it's associated modules, the Hadoop ecosystem, and the when, where, how, and why each technology is used."--Resource description page.

Item type:

eBooks

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Presenter, Rich Morrow.

Title from title screen (viewed June 24, 2016).

Date of publication from resource description page.

"You're new to Big Data, you've heard about Apache Spark and Apache Hadoop and you want to play. Big Data coach Rich Morrow gets you into the game via sixteen sprints (sixteen hands-on labs) across the Spark-Hadoop ball field. First, you'll create playing areas using Amazon Web Services EMR and Cloudera Quickstart VM. Then you'll install Hadoop, run basic HDFS commands, learn MapReduce, use Flume and Sqoop, run Spark and then run Spark again. You'll play with Spark SQL, learn common MLLib usage, do analysis with Hive, ETL with Pig, and then jog through Hadoop/Cloud use cases, Hbase basics, and enterprise integration. When practice is over, you'll know Spark, it's associated modules, the Hadoop ecosystem, and the when, where, how, and why each technology is used."--Resource description page.