CloverETL 3.4.0-M2 - Strides Toward Parallel Data Processing and Complete Hadoop Support

April 2, 2013

In this second and final milestone for the upcoming CloverETL 3.4 release, we added the finishing touches to our efforts started with the M1 – improvements to the Cluster in the area of parallel processing of a single transformation; Hadoop support (now adding integration with MapReduce jobs); and improvements to the Server, such as a more legible user interface and redesigned management of database connections, both of which greatly improve the Designer-Server development experience.

Hadoop Support Complete with ExecuteMapReduce

The new ExecuteMapReduce component closes the loop of full integration with Hadoop. Building upon support for HDFS and Hive queries introduced in the first milestone, you can now fully integrate CloverETL and Hadoop processing stacks.

Cluster Enhancements: Repartitioning Parallel Flows and Detailed Tracking

Following the effort to bring user control over the Cluster node allocation for parallel data processing, in this milestone, we introduce Repartition – a component that lets you re-route an already parallel data flow onto a different set of nodes, efficiently and on the fly.

Database Connections Overhaul on the Server

Enjoy simplified development on the Server with Server-based remote database connections.

Data Profiler Automation with REST API

Enterprise applications can now access the core of the Data Profiler to manage and retrieve useful historical profile data from the Data Profiler repository. Use it for automating trends analysis, reporting, or monitoring.

Server User Interface Redesign

We're introducing a new look & feel to the Server Console user interface. It's geared towards continuous improvements for support personnel – better insight into the Server processes and a simpler configuration.

Learn more about CloverETL 3.4.0-M2 release ›