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What are the different cluster managers available in Apache Spark? Finally, the results are sent back to the driver application or can be saved to the disk. A task applies its unit of work to the dataset in its partition and outputs a new partition dataset. Iterative algorithms apply operations repeatedly to the data so they can benefit from caching datasets across iterations. The resource manager or cluster manager assigns tasks to the worker nodes with one task per partition. Spark applications run as independent processes that are coordinated by the SparkSession object in the driver program. This is one of the most frequently asked spark interview questions, and the interviewer will expect you to give a thorough answer to it. Explain how Spark runs applications with the help of its architecture. Those are the Standalone cluster, Apache Mesos, and YARN.ģ. Cluster Management: Spark can be run in 3 environments.There are Spark Core, Spark SQL, Spark Streaming, Spark MLlib, and GraphX. Core Components: Spark supports 5 main core components.These languages are Java, Python, Scala, and R. Language support: Spark can integrate with different languages to applications and perform analytics.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.