Overview of Running Scoring Models in Hadoop

The integration of the SAS Embedded Process and Hadoop allows scoring code to be run directly on Hadoop using the SAS Embedded Process.
The SAS Embedded Process is a SAS server process that runs inside Hadoop to read and write data. A model publishing macro creates scoring files and stores them in a Hadoop Distributed File System (HDFS) directory. These scoring files are then used by a Hadoop MapReduce function to run the scoring model.
You can create traditional scoring models by using the SAS Enterprise Miner Score Code Export node. In the July 2015 release of SAS 9.4, the SAS Scoring Accelerator for Hadoop supports analytic store scoring. SAS Factory Miner components, the HPFOREST and HPSVM components, generate the analytic store file and the SAS scoring model program, and format catalog that are used in analytic store scoring.
The SAS Scoring Accelerator for Hadoop requires a specific version of Hadoop. For more information, see the SAS Foundation system requirements documentation for your operating environment.