MapReduce and Teradata Aster SQL-MapReduce®

MapReduce and SQL-MapReduce Resources and Learning

What is MapReduce? What is SQL-MapReduce? Learn and see business applications.

What is MapReduce?

MapReduce, or map reduce, is a programming framework developed by Google to simplify data processing across massive data sets. As people rapidly increase their online activity and digital footprint, organizations are finding it vital to quickly analyze the huge amounts of data their customers and audiences generate to better understand and serve them. MapReduce is the tool that is helping those organizations.

What is SQL-MapReduce?

SQL-MapReduce® is a framework created by Teradata Aster to allow developers to write powerful and highly expressive SQL-MapReduce functions in languages such as Java, C#, Python, C++, and R and push them into the discovery platform for high performance analytics. Analysts can then invoke SQL-MapReduce functions using standard SQL or R through Aster Database, the first discovery platform that allows applications to be fully embedded within the database engine to enable ultra-fast, deep analysis of massive data sets.

SQL-MapReduce functions are simple to write and are seamlessly integrated within SQL statements and R scripts. They rely on SQL queries to manipulate the underlying data and provide input. The functions can procedurally manipulate such input data and provide outputs that can be further consumed by SQL queries or written into tables within the database.

MapReduce functions seamlessly integrate into SQL queries.

Business Use Cases

Teradata Aster's customers use SQL-MapReduce to ask questions of their data that were previously impossible, or the results were so slow that they could not meet service level agreements. In these short tutorials and case studies, you will learn how companies are writing SQL-MapReduce functions for:

  • Fraud Detection A large online gaming company catches cases of fraud that previous queries could not detect. And the company reduced its fraud analytics cycle time from one week to 15 minutes, with query response dropping from 90 minutes to 90 seconds.
    See Case Study
  • Graph Analysis A social media company uses the SQL-MapReduce function nPath for graph analysis to understand how its users are connected and enhance the networks of its community.
    See Case Study
  • Sharing Behavior ShareThis uses MapReduce to reduce query times as it analyzes the items that people share online to understand sharing behavior.
    See Case Study
  • Sessionization A social network uses the SQL-MapReduce function "sessionize" to break user data into sessions based on the length of time between activity on the network. With sessionize, the SQL code dropped from more than 1000 lines to less than 100 and performance improved dramatically.
    See Case Study
  • Search Behavior – An online media company uses the SQL-MapReduce function nPath to better understand the paths its users follow after conducting a search to improve search results.
    See Case Study
  • Transformations Where data transformations previously required multiple complex self joins, a media company now uses the SQL-MapReduce function nPath to make a single pass of its data, significantly simplifying the code and improving performance.
    See Case Study


  • Fastest path to business value from raw big data
  • Novel, high value business insights driving growth and profitability
  • Leverage existing skills and investments
  • Minimal time, cost and effort spent

Why Teradata?

"Teradata’s Aster Database is a mature and robust implementation of SQL-MapReduce and has proven itself as a discovery platform."

Rick F. van der Lans
Independent Business Intelligence Analyst, R20/Consultancy: "Discovering Business Insights in Big Data Using SQL-MapReduce®"


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