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Readme

Oreilly - 2018

This tutorial can either be run in spark-shell or in an IDE (IntelliJ or Scala IDE for Eclipse)

Below are the steps for the setup.

Pre-requisites for Installation

Java/JDK 1.8+ has to be installed on the laptop before proceeding with the steps below.

Running in spark-shell

Download Spark 2.3.1

Download Spark 2.3.1 from here : http://spark.apache.org/downloads.html

Direct Download link : https://www.apache.org/dyn/closer.lua/spark/spark-2.3.1/spark-2.3.1-bin-hadoop2.7.tgz

Install Spark 2.3.1 on Mac/Linux

tar -zxvf spark-2.3.1-bin-hadoop2.7.tgz

export PATH=$PATH:/<path_to_downloaded_spark>/spark-2.3.1-bin-hadoop2.7/bin

Running spark-shell on mac

  • spark-shell

Install Spark 2.3.1 on Windows

Unzip spark-2.3.1-bin-hadoop2.7.tgz

Add the spark bin directory to Path : ...\spark-2.3.1-bin-hadoop2.7\bin

Set up winutils.exe on Windows (not needed on mac)

  • download winutils.exe from https://github.com/steveloughran/winutils/tree/master/hadoop-2.7.1/bin
  • move it to c:\hadoop\bin
  • set HADOOP_HOME in your environment variables
    • HADOOP_HOME = C:\hadoop
  • run from command prompt:
    • mkdir \tmp\hive
    • C:\hadoop\bin\winutils.exe chmod 777 \tmp\hive
  • run spark-shell from command prompt with extra conf parameter
    • spark-shell --driver-memory 2G --executor-memory 3G --executor-cores 2 --conf spark.sql.warehouse.dir=file:///c:/tmp/spark-warehouse

Pasting code in spark-shell

When pasting larger sections of the code in spark-shell, use the below:

scala> :paste

Running in IDE

If you prefer to use IDE over spark-shell, below are the steps.

You can either use IntelliJ or Scala IDE for Eclipse.

IntelliJ

Scala IDE for Eclipse

Summary of Downloads needed

Have the following downloaded before the session

Git

Nice to have

hadoop fs -copyToLocal /strata-nyc/transferlearning.tgz .

tar -zxvf transferlearning.tgz

pip install tensorflow

pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.3.0-cp27-none-linux_x86_64.whl

pip install numpy scipy

pip install scikit-learn

pip install pillow

pip install h5py

pip install keras

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