Today, we announce certification of Apache Spark as YARN Ready. This certification ensures memory and CPU intensive Spark-based applications can co-exist within a single Hadoop cluster with all the other workloads you have deployed. Together, they allow you to use a single cluster with a single set of data for multiple purposes rather than silo your Spark workloads into a separate cluster.
The Hortonworks Blog
I’m a pretty heavy Unix user and I tend to prefer doing things the Unix Way™, which is to say, composing many small command line oriented utilities. With composability comes power and with specialization comes simplicity. Although, sometimes if two utilities are used all the time, sometimes it makes sense for either:
- A utility that specializes in a very common use-case
- One utility to provide basic functionality from another utility
For example, one thing that I find myself doing a lot of is searching a directory recursively for files that contain an expression:
Despite the fact that you can do this, specialized utilities, such as ack have come up to simplify this style of querying.…
Hadoop 2 and its YARN-based architecture has increased the interest in new engines to be run on Hadoop and one such workload is in-memory computing for machine learning and data science use cases. Apache Spark has emerged as an attractive option for this type of processing and today, we announce availability of our HDP 2.1 Tech Preview Component of Apache Spark. This is a key addition to the platform and brings another workload supported by YARN on HDP.…