August 2017
Beginner to intermediate
340 pages
8h 42m
English
Content preview from Mastering Machine Learning with Spark 2.x
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Starting Spark shell
The first step is to prepare the Spark environment to perform analysis. As in the previous chapter, we are going to start Spark shell; however, in this case, the command line is slightly more complicated:
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 8g \
--executor-memory 8g \
--conf spark.executor.extraJavaOptions=-XX:MaxPermSize=384M \ --conf spark.driver.extraJavaOptions=-XX:MaxPermSize=384M \ --packages ...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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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.