Cloudera Engineering Blog · Spark Posts
Sure, Spark is fast, but it also gives developers a positive experience they won’t soon forget.
Apache Spark is well known today for its performance benefits over MapReduce, as well as its versatility. However, another important benefit – the elegance of the development experience – gets less mainstream attention.
Spark is a compelling multi-purpose platform for use cases that span investigative, as well as operational, analytics.
Data science is a broad church. I am a data scientist — or so I’ve been told — but what I do is actually quite different from what other “data scientists” do. For example, there are those practicing “investigative analytics” and those implementing “operational analytics.” (I’m in the second camp.)
Cloudera is announcing the general availability of support for Spark, bringing interactive machine learning and stream processing to enterprise data hubs.
Cloudera is pleased to announce the immediate availability of its first release of Apache Spark for Cloudera Enterprise (comprising CDH and Cloudera Manager).
With the close of 2013, we also thought it appropriate to include some high points from across the year (not listed in any particular order):
The team behind Hue, the open source Web UI that makes Apache Hadoop easier to use, strikes again with a new Spark app.
Editor’s note: This post was recently published on the Hue blog. We republish it here for your convenience.
Our thanks to Databricks, the company behind Apache Spark (incubating), for providing the guest post below. Cloudera and Databricks recently announced that Cloudera will distribute and support Spark in CDH. Look for more posts describing Spark internals and Spark + CDH use cases in the near future.