Abstract
This paper presents ETLMR, a parallel Extract–Transform–Load (ETL) programming framework based on MapReduce. It has built-in 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.
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http://www.cs.aau.dk/~xiliu/etlmr/ as of (April 13 ,2011)
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http://www.discoproject.org as of (April 13 ,2011)
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Liu, X., Thomsen, C., Bach Pedersen, T. (2011). The ETLMR MapReduce-Based ETL Framework. In: Bayard Cushing, J., French, J., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2011. Lecture Notes in Computer Science, vol 6809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22351-8_48
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DOI: https://doi.org/10.1007/978-3-642-22351-8_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22350-1
Online ISBN: 978-3-642-22351-8
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