August 2017
Beginner to intermediate
340 pages
8h 42m
English
Content preview from Mastering Machine Learning with Spark 2.x
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Dataset preparation
Before running any data manipulation, we need to prepare the Spark environment as we did in the previous chapters. Let's start the Spark shell and request enough memory to process the downloaded dataset:
export SPARK_HOME="<path to your Spark2.0 distribution"export SPARKLING_WATER_VERSION="2.1.12"export SPARK_PACKAGES=\"ai.h2o:sparkling-water-core_2.11:${SPARKLING_WATER_VERSION},\ai.h2o:sparkling-water-repl_2.11:${SPARKLING_WATER_VERSION},\ai.h2o:sparkling-water-ml_2.11:${SPARKLING_WATER_VERSION},\com.packtpub:mastering-ml-w-spark-utils:1.0.0"$SPARK_HOME/bin/spark-shell \--master 'local[*]' \--driver-memory 10g \--executor-memory 10g \--confspark.executor.extraJavaOptions=-XX:MaxPermSize=384M \--confspark.driver.extraJavaOptions=-XX:MaxPermSize=384M ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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