What are the important components of the Spark ecosystem?Īpache Spark has 3 main categories that comprise its ecosystem. Spark provides caching and in-memory data storageĢ. Hadoop MapReduce data is stored in HDFS and hence takes a long time to retrieve the data Hadoop MapReduce is slower when it comes to large scale data processing Spark runs almost 100 times faster than Hadoop MapReduce

Spark processes data in batches as well as in real-time How is Apache Spark different from MapReduce? Let us begin with a few basic Apache Spark interview questions!Īpache Spark Interview Questions for Beginners 1. Apache Spark Interview Questions for Experienced.Apache Spark Interview Questions for Beginners.

The Apache Spark interview questions have been divided into two parts: Note- If you are new to Apache Spark and want to learn more about the technology, I suggest you click here! Apache Spark Interview Questions The Spark interview questions have been segregated into different sections based on the various components of Apache Spark and surely after going through this article you will be able to answer most of the questions asked in your next Spark interview. Spark can run on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud, and can access data from multiple sources.Īnd this article covers the most important Apache Spark Interview questions that you might face in a Spark interview. It can run workloads 100 times faster and offers over 80 high-level operators that make it easy to build parallel apps.

Apache Spark is a unified analytics engine for processing large volumes of data.

Scala interview questions