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I have a large set of data, split over hundreds of files, that I am copying over to my cluster vis ssh. I have 9 nodes, all but one setup as data nodes and the remaining node (hadoop-node2) has most of the MapR processes running on it. On hadoop-node2 I run hadoop dfs -mkdir /data and then copy over my data via  ssh

Hi ,   Is there  a possibility of Mapr-Hive and Apache Hive are in sync. what are the time lines or the scope of mapr-hive are in sync with new releases of apache hive. I believe we are way beyond apache-hive even though few back porting of bugs are happening to current release of hive.   Thanks, Bharath
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Log into the MapR Community to add to course discussions. Connect with and learn from other students as well as MapR subject matter experts.   Course Discussions Essentials (ESS 100) Lesson 1 – Describe your big data problem Essentials (ESS 102) Lesson 6 – What features are important for your big data projects?   Find
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Vinayak Meghraj
Steps to execute R from /opt/mapr/spark/spark-1.6.1/bin/sparkR interactive shell   Example 1)  1) people <- read.df(sqlContext, "file:///opt/mapr/spark/spark-1.6.1/examples/src/main/resources/people.json", "json") 2) head(people)   Example 2) 1) sc <- sparkR.init() 2) sqlContext <- sparkRSQL.init(sc)