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Apache Spark 2.x Cookbook

You're reading from   Apache Spark 2.x Cookbook Over 70 cloud-ready recipes for distributed Big Data processing and analytics

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Product type Paperback
Published in May 2017
Publisher
ISBN-13 9781787127265
Length 294 pages
Edition 1st Edition
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Author (1):
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Rishi Yadav Rishi Yadav
Author Profile Icon Rishi Yadav
Rishi Yadav
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Apache Spark FREE CHAPTER 2. Developing Applications with Spark 3. Spark SQL 4. Working with External Data Sources 5. Spark Streaming 6. Getting Started with Machine Learning 7. Supervised Learning with MLlib — Regression 8. Supervised Learning with MLlib — Classification 9. Unsupervised Learning 10. Recommendations Using Collaborative Filtering 11. Graph Processing Using GraphX and GraphFrames 12. Optimizations and Performance Tuning

Deploying Spark on a cluster with Mesos

Mesos is slowly emerging as a data center operating system for managing all the compute resources across a data center. Mesos runs on any computer running the Linux operating system. It is built using the same principles as the Linux kernel. Let's see how we can install Mesos.

How to do it...

Mesosphere provides a binary distribution of Mesos. The most recent package of the Mesos distribution can be installed from the Mesosphere repositories by performing the following steps:

  1. Execute Mesos on a Ubuntu OS with the trusty version:
        $ sudo apt-key adv --keyserver keyserver.ubuntu.com --recv E56151BF 
DISTRO=$(lsb_release -is | tr '[:upper:]' '[:lower:]') CODENAME=$(lsb_release
-cs)

$ sudo vi /etc/apt/sources.list.d/mesosphere.list
deb http://repos.mesosphere.io/Ubuntu trusty main
  1. Update the repositories:
        $ sudo apt-get -y update
  1. Install Mesos:
        $ sudo apt-get -y install mesos
  1. To connect Spark to Mesos and to integrate Spark with Mesos, make Spark binaries available to Mesos and configure the Spark driver to connect to Mesos.
  2. Use the Spark binaries from the first recipe and upload them to HDFS:
        $ hdfs dfs -put spark-2.1.0-bin-hadoop2.7.tgz spark-2.1.0-bin-hadoop2.7.tgz
  1. The master URL of a single master Mesos is mesos://host:5050; the master URL of a ZooKeeper-managed Mesos cluster is mesos://zk://host:2181.
  2. Set the following variables in spark-env.sh:
        $ sudo vi spark-env.sh
export MESOS_NATIVE_LIBRARY=/usr/local/lib/libmesos.so
export SPARK_EXECUTOR_URI= hdfs://localhost:9000/user/hduser/spark-2.1.0-bin-
hadoop2.7.tgz
  1. Run the following commands from the Scala program:
        Val conf = new SparkConf().setMaster("mesos://host:5050")
Val sparkContext = new SparkContext(conf)
  1. Run the following command from the Spark shell:
        $ spark-shell --master mesos://host:5050
Mesos has two run modes:
  • Fine-grained: In the fine-grained (default) mode, every Spark task runs as a separate Mesos task. 
  • Coarse-grained: This mode will launch only one long-running Spark task on each Mesos machine
  1. To run in the coarse-grained mode, set the spark.mesos.coarse property:
        Conf.set("spark.mesos.coarse","true")
You have been reading a chapter from
Apache Spark 2.x Cookbook
Published in: May 2017
Publisher:
ISBN-13: 9781787127265
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