The Hortonworks Blog

Posts categorized by : Storm

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.…

We recently hosted the sixth of our seven Discover HDP 2.1 webinars, entitled Apache Storm for Stream Data Processing in Hadoop. Over 200 people attended the webinar and joined in the conversation.

Thanks to our presenters Justin Sears (Hortonworks’ Product Marketing Manager), Himanshu Bari (Hortonworks’ Senior Product Manager for Storm), and Taylor Goetz (Hortonworks’ Software Engineer and Apache Storm Committer) who presented the webinar. The speakers covered:

  • Why use Apache Storm?

The first use of the term BoF session was used at the Digital Equipment Users’ Society (DECUS) conference in the 1960s. Its essence was to bring together like minds and thought leaders—just as birds of the feather flock together— to share and exchange computing ideas, in an informal yet spirited way. Since then, the organizers and sponsors of most computing conferences have been loyal to its essence and spirit.

For ideas and innovation happen in collaboration—not in isolation. …

If you’re excited to get started with the new features in Hortonworks Data Platform 2.1, then we’ve included 4 tutorials for you try out – Sandbox-style.

You can download the HDP 2.1 Technical Preview here, and then get stuck into these great tutorials.

Interactive Query with Apache Hive and Apache Tez

OK, so you’re not going to get huge performance out of a one-node VM, but you can try out Hive on Tez, and see the performance gains versus MapReduce, and also try out features such as Vectorized Query, and the host of new SQL features.…

The pace of innovation within the Apache Hadoop community is truly remarkable, enabling us to announce the availability of Hortonworks Data Platform 2.1, incorporating the very latest innovations from the Hadoop community in an integrated, tested, and completely open enterprise data platform.

Download HDP 2.1 Technical Preview Now

What’s In Hortonworks Data Platform 2.1?

The advancements in HDP 2.1 span every aspect of Enterprise Hadoop: from data management, data access, integration & governance, security and operations. …

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. 

I recently sat down with Himanshu Bari to discuss how Apache Ambari will serve as the single point of management for Hadoop 2 clusters integrated with Apache Storm and its real-time, streaming event processing.

Himanshu discusses Apache Storm’s five key benefits and how those will add to the power and stability of a Hadoop 2 stack, providing analysis of huge data flows from the second data is created and then for decades of historical analysis of that data stored in HDFS.…

Last week was a busy week for shipping code, so here’s a quick recap on the new stuff to keep you busy over the holiday season.

In October, we announced our intent to include and support Storm as part of Hortonworks Data Platform. With this commitment, we also outlined and proposed an open roadmap to improve the enterprise readiness of this key project.  We are committed to doing this with a 100% open source approach and your feedback is immensely valuable in this process.

Today, we invite you to take a look at our Storm technical preview.…

Join Hortonworks and Pactera for a Webinar on Unlocking Big Data’s Potential in Financial Services Thursday, November 21st at 12:00 EST.

Have you ever had your debit or credit card declined for seemingly no reason? Turns out, the rejections are not so random. Banks are increasingly turning to analytics to predict and prevent fraud in real-time. That can sometimes be an inconvenience for customers who are traveling or making large purchases, but it’s necessary inconvenience today in order for banks to reduce billions in losses due to fraud.…

Apache Storm and YARN extend Hadoop to handle real time processing of data and provides the ability to process and respond events as they happen. Our customers have told us many use cases for this technology combination and below we present a demo example complete with code so you can try it yourself.

For the demo below, we used our Sandbox VM which is a full implementation of the Hortonworks Data Platform.…

Hortonworks will be making a preview of Apache Storm integration available in Q4 of this year and will be including Apache Storm in the Hortonworks Data Platform in first half of 2014.

Any time now, the Apache Hadoop community will declare the General Availability of Hadoop 2.0 which includes the much anticipated Apache Hadoop YARN.  The YARN-based architecture of Hadoop 2 is the most significant change to Hadoop introduced in the past six years and enables Hadoop to expand from a single-purpose, batch-oriented data platform based on MapReduce into a truly multi-purpose platform supporting a wide range of data processing approaches.…