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corrected to erroneous README files and typos
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‎README.md‎

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@@ -16,8 +16,6 @@ Instructions for how to build and run examples are in [README.md](chapter2/READM
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Instructions for how to build and run examples are in [README.md](chapter3/README.md)
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### Chapter 4
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Instructions for how to build and run examples are in [README.md](chapter4/README.md)
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### Chapter 5
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Instructions for how to build and run examples are in [README.md](chapter5/README.md)
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### Chapter 6
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Instructions for how to build and run examples are in [README.md](chapter6/README.md)
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### Chapter 7

‎chapter2/README.md‎

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This directory contains all the Scala examples for Chapter 2. Along with the code to generate the M&Ms data set.
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This directory contains all the Scala and Python examples for Chapter 2. Along with the code to generate the M&Ms data set.
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The equivalent code for Scala is in the scala directory, along instructions how to build the jar.
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To use build and run thes examples cd in respective Scala and Python directory and follow simple
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intructions in relevant README.md files.
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Have Fun
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Cheers!

‎chapter3/README.md‎

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This directory contains all the Scala and Python examples for chapter 3.
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This directory contains all the Scala and Python examples for Chapter 3.
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To use build and run thes examples cd in respective scala and py/src directory and follow simple
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intructions in relevant README.md files
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Have Fun
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Cheers!

‎chapter4/README.md‎

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This directory contains all the Scala and Python examples for chapter 4.
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This directory contains all the Scala and Python examples for Chapter 4.
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To run Scala code for this chapter use:
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* `spark-submit --class main.scala.chapter4.Example4_1 jars/main-scala-chapter4_2.11-1.0.jar <args>`
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* `spark-submit --class main.scala.chapter4.SparkTables jars/main-scala-chapter4_2.11-1.0.jar <args>`
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The equivalent code for Scala is in the scala directory, along instructions how to build jar
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To use build and run thes examples cd in respective scala and py/src directory and follow simple
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intructions in relevant README.md files
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Have Fun
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Cheers!

‎chapter4/scala/README.md‎

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### How to build the package
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1. sbt clean package
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2. mkdir jars
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3. cp main-scala-chapter4_2.12-1.0.jar from the target/ directory into the jars/
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This directory contains all the Scala and Python examples for chapter 4.
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### How to run the example
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To run Scala code for this chapter use:
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* `spark-submit --class main.scala.chapter8.8_3_MapAndMapPartition jars/main-scala-chapter8_2.12-1.0.jar`
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* `spark-submit --class main.scala.chapter4.Example4_1 jars/main-scala-chapter4_2.11-1.0.jar <args>`
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* `spark-submit --class main.scala.chapter4.SparkTables jars/main-scala-chapter4_2.11-1.0.jar <args>`
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The equivalent code for Python is in the python directory, along instructions how to run it.
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The equivalent code for Scala is in the scala directory, along instructions how to build jar
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Have Fun
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Cheers!
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~

‎chapter6/README.md‎

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This directory contains all the Java examples for chapter 6.
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This directory contains all the Java examples and notebooks for Chapter 6.
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To build the java jars, cd to java directory and follow the [README.md](java/README.md) instructions
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To use build and run thes examples cd in respective java directory and follow simple
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intructions in relevant README.md files
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Have Fun!
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Cheers
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Have Fun
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Cheers!

‎chapter7/README.md‎

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This directory contains all the Java examples for chapter 7.
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This directory contains all the Scala examples for Chapter 7.
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To build the java jars, cd to java directory and follow the [README.md](scala/README.md) instructions
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To use build and run thes examples cd in respective scala and follow simple
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intructions in relevant README.md files
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Have Fun!
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Cheers
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Have Fun
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Cheers!

‎notebooks/README.md‎

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# Learning Spark 2nd Edition
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GitHub repo for the "Learning Spark 2nd Edition" code notebooks.
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If you are using Databricks to run the notebook, you can import a LearninSparkv2.dbc file containing all of the notebooks for
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relevant chapters from the folder.
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Sign up for a free [Databricks Community Edition](https://www.databricks.com/try-databrick) account for free.
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Follow this instructions to import notebook after signing into the Databricks Community Edition
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* Step 1:
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* Step 2:
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* Step 3:
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Cheers,
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Have Fun!
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