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Using Spark for fast in-memory computing

Justin Kestelyn from Databricks describes the differences between Hadoop and Spark processing models in a post on “Cloudera’s blog“:

At its core, Spark provides a general programming model that enables developers to write application by composing arbitrary operators, such as mappers, reducers, joins, group-bys, and filters. […] In addition, Spark keeps track of the data that each of the operators produces, and enables applications to reliably store this data in memory.

spark

✚ This looks in a way similar to the Cascading programming model combined with the capability of storing in memory the working dataset for the current computations.

Original title and link: Using Spark for fast in-memory computing (NoSQL database©myNoSQL)

via: http://blog.cloudera.com/blog/2013/11/putting-spark-to-use-fast-in-memory-computing-for-your-big-data-applications/