Abstract: A method and system is disclosed that identifies a job written in a first language. The job is to be performed in parallel on a plurality of nodes of a plurality of clusters. The first language describes functions supported by multiple frameworks but is not specific to any of the multiple frameworks. The method and system select one or more clusters from the plurality of clusters to run the job. The selected one or more clusters of the plurality of clusters operate a different framework from other clusters of the plurality of clusters. The method and system identify a second language associated with the selected one or more clusters. The method and system convert the first language of the job into the second language and cause the job in the second language to be run on the plurality of nodes of the selected one or more clusters.

Abstract: A method and system is disclosed that identifies a job written in a first language. The job is to be performed in parallel on a plurality of nodes of a plurality of clusters. The first language describes functions supported by multiple frameworks but is not specific to any of the multiple frameworks. The method and system select one or more clusters from the plurality of clusters to run the job. The selected one or more clusters of the plurality of clusters operate a different framework from other clusters of the plurality of clusters. The method and system identify a second language associated with the selected one or more clusters. The method and system convert the first language of the job into the second language and cause the job in the second language to be run on the plurality of nodes of the selected one or more clusters.

Abstract: A method for map-reduce job virtualization is disclosed. The method includes receiving a map-reduce job written in a first map-reduce language. The map-reduce job is to be performed in parallel on a plurality of nodes of a plurality of clusters. The method also includes selecting one or more clusters to run the map-reduce job. The method further includes identifying a second map-reduce language associated with the selected clusters. The method also includes converting the first map-reduce language of the map-reduce job into the second map-reduce language. The method further causes the map-reduce job in the second map-reduce language to be run on the plurality of nodes of the selected clusters.

Abstract: A method for map-reduce job virtualization is disclosed. The method includes receiving a map-reduce job written in a first map-reduce language. The map-reduce job is to be performed in parallel on a plurality of nodes of a plurality of clusters. The method also includes selecting one or more clusters to run the map-reduce job. The method further includes identifying a second map-reduce language associated with the selected clusters. The method also includes converting the first map-reduce language of the map-reduce job into the second map-reduce language. The method further causes the map-reduce job in the second map-reduce language to be run on the plurality of nodes of the selected clusters.