Cascading A feature rich API for defining and executing complex, scale-free, and fault tolerant data processing workflows on a Hadoop cluster
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notification process API event notification processing API process scheduler

Cascading Description

A feature rich API for defining and executing complex, scale-free, and fault tolerant data processing workflows on a Hadoop cluster The Cascading processing API lets the developer quickly assemble complex distributed processes without having to "think" in MapReduce, and to efficiently schedule them based on their dependencies and other available meta-data. Obviously simple data processing applications are supported as well, as complex jobs tend to start simple. Here are some key features of "Cascading": · Data Processing API · Topological Scheduler · Event Notification · MapReduce Job Planner · Stream Assertions · Failure Traps · Scriptable Interface · External Data Interfaces · Custom MapReduce Jobs What's New in This Release: · Changed behavior when cleaning temp files that allows shutdown to continue even if an exception is thrown during temp file delete. · Fix bug where c.f.FlowProcess#openTapForRead() included current input file values in iterator. · Fix for intermediate temp files not being cleaned up on c.f.Flow#stop(). · Fixed bug where NPE is thrown if all hadoop default properties are not available.

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