Spark Applications
Supported Platform: Linux® only.
You can deploy MATLAB applications against Spark in two ways:
Deploy tall arrays to a Spark enabled Hadoop cluster
Deploy applications using the MATLAB API for Spark
To deploy MATLAB applications that contain tall arrays, see Deploy Tall Arrays to a Spark Enabled Hadoop Cluster. To learn more about how to work with tall arrays, see Tall Arrays.
To deploy MATLAB applications that use functions such as
flatMap
, which is common in Spark programs, see Deploy Applications Using the MATLAB API for Spark.
The MATLAB API for Spark exposes the Spark programming model to MATLAB. Therefore, you will find Spark functions such as flatMap
,
mapPartitions
, and aggregate
that
you can readily use when creating your MATLAB applications.
Note
MATLAB applications developed using the MATLAB API for Spark cannot be deployed if they contain tall arrays.
See Apache Spark Basics for a short summary of Spark concepts and a discussion of how deployed MATLAB applications incorporate those concepts.
MATLAB has a vast collection of scientific and engineering algorithms and Spark is a fast and general-purpose engine for large-scale data processing. By deploying MATLAB applications against Spark, you can create applications in MATLAB and execute them against a Spark enabled cluster.
Supported Apache® Spark Versions: 1.3–2.x.
Categories
- Deploy Tall Arrays to a Spark Enabled Hadoop Cluster
Create and execute MATLAB applications with tall arrays against a Spark enabled Hadoop cluster
- Deploy Applications Using the MATLAB API for Spark
Create and execute MATLAB applications against Spark using the MATLAB API for Spark