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Map-reduce, or its open source version Hadoop, is a parallel programming framework for running scripts, Java, C, and other external programming languages on hundreds of nodes. It is popular with Dot.Com companies who have large server farms and need to produce reports on website activity or produce search indexes. In general, Map-reduce applications overlap BI applications and data warehouses. However, Map-reduce applications can coexist with a data warehouse: one parallel processing, the other parallel database. Coexistence allows each subsystem’s best capabilities to be used to complement the other. With Teradata’s in-database processing technology, Map-reduce can become MPP ETL subsystem, or we can run Map-Reduce functions inside the EDW, or using table functions we can directly integrate with the Map-reduce nodes. This article illustrates a commonly used Map-reduce function running inside the Teradata EDW.