Cascading is the proven application development platform for building data applications on Hadoop.

Work on Cascading 4 continues with a new sub-project that provides new Cascading local mode Tap implementations for Amazon S3 and Apache Kafka. Checkout the project on github: https://github.com/cwensel/cascading-local Historically Cascading’s in-memory local (read non-distributed) mode has been primarily promoted as a platform for testing…

Cascading 3.2.0 has been released. This release covers the following issues and improvements: – Much improved planner support for complex and tight c.p.Pipe assemblies that arise when merging files with themselves, or other split and joins with no intermediate operations. – c.t.h.DistCacheTap is now applied…

We are happy to announce Cascading 3.1 is now publicly available for download. Version 3.1 improves the performance of Cascading over 3.0, resolves a number of issues during planning of complex workloads when running on MapReduce and Apache Tez, and further delivers on the promise…

Thanks to our partners, data Artisans, Cascading users now have an additional compute fabric to execute Cascading 3.0 applications on, Apache Flink. From the project site.. “Apache Flink is a platform for scalable stream and batch processing. Flink’s execution engine features low-latency pipelined and scalable…

September 2015 Newsletter

We have just published Cascading 3.0.2, a minor maintenance release.  Upgrading is recommended for all users. This release resolves the following issues: Updated Apache Tez to 0.6.2 to prevent deadlocks in complex DAGs. Note this release is incompatible with Tez 0.6.1. Fixed issues concerning detailed…