MapR Brings Spark In-Memory Analysis To Hadoop - InformationWeek
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4/11/2014
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MapR Brings Spark In-Memory Analysis To Hadoop

MapR adds Apache Spark to its Hadoop distribution to power machine learning plus ad hoc, graph, and streaming analysis. Databricks partners on support.
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MapR adds the Spark stack, highlighted in gray, to its list of more than 20 supported Apache open source projects.
MapR adds the Spark stack, highlighted in gray, to its list of more than 20 supported Apache open source projects.

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Michael Franklin
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Michael Franklin,
User Rank: Apprentice
4/14/2014 | 12:35:45 PM
Clarification of Spark's Origin
MapR's announcement is indeed an important milestone in the progress of Spark as an enterprise solution.   However I need to correct one key point in your article.  Spark, Shark, Spark Streaming, ML-lib etc were all developed at the UC Berkeley AMPLab (amplab.cs.berkeley.edu) and have been open source since their inception.  They are components of the Berkeley Data Analytics Stack (BDAS) which has been and continues to be developed by students and researchers in the AMPLab.   Databricks is a company that spun out of the lab and that was founded by many of the key developers of Spark.
Charlie Babcock
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Charlie Babcock,
User Rank: Author
4/11/2014 | 7:45:38 PM
The powerful Hadoop platform
Hadoop is one of those brilliantly simple platforms -- a distributed file system on top of distributed processing combined with data mapping -- on which many increasingly sophisticated systems may be built. Good description here of Spark streaming analysis; it's probably one of them.
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