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SQL/MapReduce Applications

Customer Use Cases

Aster customers are using In-Database 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 webcasts, you will learn how customers are writing SQL/MR functions for:

Fraud Detection
Graph Analysis
Sharing Behavior
Sessionization
Search Behavior
Transformations

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.


Graph Analysis
A social media company uses the SQL/MR function nPath for graph analysis to understand how its users are connected and enahance the networks of its community.


Sharing Behavior
ShareThis uses MapReduce to reduce query times as it analyzes the items that people share online to understand sharing behavior.


Sessionization
A social network uses the SQL/MR 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.


Search Behavior
An online media company uses the SQL/MR function nPath to better understand the patterns its users follow after conducting a search so the company can improve search results.


Transformations
Where data transformations previously required multiple complex self joins, a media company now uses the SQL/MR function nPath to make a single pass of its data, significantly simplifying the code while improving performance.


Read much more on In-Database MapReduce on our blog

Download Now:
Webcast: MapReduce for Data Warehousing and Analytics
TDWI Webinar: Scaling Up to Support Large-Scale Reporting and Analytics
TDWI Monograph: Beyond Reporting: Requirements for Large-Scale Analytics
By using Aster, we were able to take advantage of distributed computing power and run MapReduce functionality within the database. The queries ran in minutes versus hours.

Lenin Gali, Director of BI, ShareThis
We‘re excited about In-Database MapReduce and the promise it offers of scalable execution of advanced statistics without having to move data to a separate statistics platform.

Scott Becker, CTO
Invite Media