The ETLMR MapReduce-based ETL framework

Authors:
Xiufeng Liu;Christian Thomsen;Torben Bach Pedersen
Affiliations:
Dept. of Computer Science, Aalborg University;Dept. of Computer Science, Aalborg University;Dept. of Computer Science, Aalborg University
Venue:
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Year:
2011

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Abstract

This paper presents ETLMR, a parallel Extract-Transform-Load (ETL) programming framework based on MapReduce. It has builtin support for high-level ETL-specific constructs including star schemas, snowflake schemas, and slowly changing dimensions (SCDs). ETLMR gives both high programming productivity and high ETL scalability.