TY - JOUR A1 - Schildgen, Johannes A1 - Jörg, Thomas A1 - Dossinger, Manuel A1 - Deßloch, Stefan T1 - Marimba: A framework for making MapReduce jobs incremental JF - Proceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014, 27 June 2014 - 02 July 2014, Anchorage, AK, USA N2 - Many MapReduce jobs for analyzing Big Data require many hours and have to be repeated again and again because the base data changes continuously. In this paper we propose Marimba, a framework for making MapReduce jobs incremental. Thus, a recomputation of a job only needs to process the changes since the last computation. This accelerates the execution and enables more frequent recomputations, which leads to results which are more up-to-date. Our approach is based on concepts that are popular in the area of materialized views in relational database systems where a view can be updated only by aggregating changes in base data upon the previous result. KW - Aggregates KW - Rhythm KW - Computational modeling KW - Programming KW - Google KW - Big data KW - Relational databases Y1 - 2014 U6 - https://doi.org/10.1109/BigData.Congress.2014.27 PB - IEEE ER -