Whether modifying an existing application or writing entirely new code, parallel applications can be much more challenging to work with than their sequential counterparts. Without a doubt, the ...

Google today announced that it has teamed up with the Hadoop specialists at Cloudera to bring its Cloud Dataflow programming model to Apache’s Spark data processing engine.. With Google Cloud ...

Through dataflow block composition, a myriad of problems can be solved in a simple, efficient and elegant manner. Stay tuned for Part 3 in this series on dataflow programming with the Task Parallel ...

Hadoop software company Cloudera has worked with Google to make Google’s Dataflow programming model run on Apache Spark. Dataflow, which Google announced as a cloud service in June, lets ...

The dataflow programming model with its ‘shared-nothing’ semantics and explicitly expressed data dependencies provides pipeline parallelism by its very nature (a form of task parallelism). That is, ...

The parallel programming challenge will continue to grow as multicore platforms become more common and their complexity and number of cores continue to increase. The domination of sequential ...

Google’s Cloud Dataflow is a programming model for combining batch and stream processing tasks on large data sets. The technology is designed for companies looking to extract business value from ...

See dataflow diagram and dataflow programming. (2) In communications, the path taken by a message from origination to destination that includes all nodes through which the data travels. Advertisement ...

Google, in conjunction with Cloudera, Data Artisan, Cask and Talend, announced this week that the Dataflow programming model that Google created to develop streaming Big Data applications is now an ...

A dataflow diagram also includes the locations where the data are placed in permanent storage (SSD, disk, tape, etc.). See dataflow programming . Advertisement ...