From e42e6e2bef38ca1d6fb92c27a7556f30be940574 Mon Sep 17 00:00:00 2001 From: Matei Alexandru Zaharia Date: Wed, 8 Jan 2014 05:43:23 +0000 Subject: Added links to Nabble archvies of mailing lists --- .../screencasts/3-transformations-and-caching.html | 157 --------------------- site/screencasts/4-a-standalone-job-in-spark.html | 157 --------------------- site/screencasts/index.html | 4 +- 3 files changed, 2 insertions(+), 316 deletions(-) (limited to 'site/screencasts') diff --git a/site/screencasts/3-transformations-and-caching.html b/site/screencasts/3-transformations-and-caching.html index 2f144ea28..e4010148c 100644 --- a/site/screencasts/3-transformations-and-caching.html +++ b/site/screencasts/3-transformations-and-caching.html @@ -1,137 +1,3 @@ - - - - - - - - - - - - - Transformations and Caching - Spark Screencast #3 | Apache Spark - - - - - - - - - - - - - - - - -
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Transformations and Caching - Spark Screencast #3

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In this third Spark screencast, we demonstrate more advanced use of RDD actions and transformations, as well as caching RDDs in memory.

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Check out the next spark screencast in the series, Spark Screencast #4 - A Standalone Job in Scala.

For more information and links to other Spark screencasts, check out the Spark documentation page.

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A Standalone Job in Scala - Spark Screencast #4

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In this Spark screencast, we create a standalone Apache Spark job in Scala. In the job, we create a spark context and read a file into an RDD of strings; then apply transformations and actions to the RDD and print out the results.

For more information and links to other Spark screencasts, check out the Spark documentation page.

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A Standalone Job in Scala - Spark Screencast #4

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4 A Standalone Job In Spark

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In this Spark screencast, we create a standalone Apache Spark job in Scala. In the job, we create a spark context and read a file into an RDD of strings; then apply transformations and actions to the RDD and print out the results.

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