Better Performance Monitoring for Spark on Hadoop

Better Performance Monitoring for Spark on Hadoop

Spark on Hadoop: A Quick Guide

As a data processing engine for Hadoop, Spark is faster, more flexible, and easier to code than MapReduce. It’s provided enterprises with massive gains when it comes to leveraging and processing big data. However, Spark can also present some challenges of its own.

Pepperdata solutions provide administrators and developers with the power to get around these obstacles and take performance tuning to the desired level. From detailed resource usage to app performance information and much more, our free guide has all the details.

Download our free guide to Spark on Hadoop and discover how to better:

✔ Tune Spark in the most effective way, and use it to elevate Hadoop clusters
✔ Determine when to use batch processing, and when to use real-time processing
✔ Leverage auto-recommended tips for continuous improvement.

Don’t wait! Get your free guide to Spark on Hadoop performance optimization today.