Spark Metrics

Swaroop Ramachandra looks at some key metrics for Spark administration:

Once you have identified and broken down the Spark and associated infrastructure and application components you want to monitor, you need to understand the metrics that you should really care about that affects the performance of your application as well as your infrastructure. Let’s dig deeper into some of the things you should care about monitoring.

  1. In Spark, it is well known that Memory related issues are typical if you haven’t paid attention to the memory usage when building your application. Make sure you track garbage collection and memory across the cluster on each component, specifically, the executors and the driver. Garbage collection stalls or abnormality in patterns can increase back pressure.

There are a few metrics of note here.  Check it out.

Related Posts

A Simple Example With Spark And Kafka

Gary Dusbabek has a nice example showing how to build a simple application with Spark and Kafka: This is a hands-on tutorial that can be followed along by anyone with programming experience. If your programming skills are rusty, or you are technically minded but new to programming, we have done our best to make this […]

Read More

Talking To Secure Hadoop Clusters

Mubashir Kazia shows how to connect to a secured Hadoop cluster using Active Directory: The primary form of strong authentication used on a secure cluster is Kerberos. Kerberos supports credentials delegation where a server process to which a user has authenticated, can perform actions on behalf of the user. This involves the server process accessing […]

Read More

Categories

June 2016
MTWTFSS
« May Jul »
 12345
6789101112
13141516171819
20212223242526
27282930