The Hortonworks Blog

More from Taylor Goetz
YARN and Apache Storm: A Powerful Combination

YARN changed the game for all data access engines in Apache Hadoop. As part of Hadoop 2, YARN took the resource management capabilities that were in MapReduce and packaged them for use by new engines. Now Apache Storm is one of those data-processing engines that can run alongside many others, coordinated by YARN.

YARN’s architecture makes it much easier for users to build and run multiple applications in Hadoop, all sharing a common resource manager.…

The Apache Storm community recently announced the release of Apache Storm 0.9.2, which includes improvements to Storm’s user interface and an overhaul of its netty-based transport.

We thank all who have contributed to Storm – whether through direct code contributions, documentation, bug reports, or helping other users on the mailing lists. Together, we resolved 112 JIRA issues.

Here are summaries of this version’s important fixes and improvements.

New Feature Highlights Netty Transport Overhaul

Storm’s Netty-based transport has been overhauled to significantly improve performance through better utilization of thread, CPU, and network resources, particularly in cases where message sizes are small.…

In February 2014, the Apache Storm community released Storm version 0.9.1. Storm is a distributed, fault-tolerant, and high-performance real-time computation system that provides strong guarantees on the processing of data. Hortonworks is already supporting customers using this important project today.

Many organizations have already used Storm, including our partner Yahoo! This version of Apache Storm (version 0.9.1) is:

  • Highly scalable. Like Hadoop, Storm scales linearly
  • Fault-tolerant. Automatically reassigns tasks if a node fails
  • Reliable.