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Apache Spark Interview Question and Answer (100 FAQ)

 

Apache Spark Interview Question and Answer (100 FAQ)

GETTING STARTED

Apache Spark Interview Questions has a collection of 100 questions with answers asked in the interview for freshers and experienced (Programming, Scenario-Based, Fundamentals, Performance Tuning based Question and Answer). This course is intended to help Apache Spark Career Aspirants to prepare for the interview.

What you'll learn

  • By attending this course you will get to know frequently and most likely asked Programming, Scenario based, Fundamentals, and Performance Tuning based Question asked in Apache Spark Interview along with the answer This will help Apache Spark Career Aspirants to prepare for the interview. During your Scheduled Interview you do not have to spend time searching the Internet for Apache Spark interview questions. We have already compiled the most frequently asked and latest Apache Spark Interview questions in this course.

Requirements

  •  Apache Spark basic fundamental knowledge is required

Description

Apache Spark Interview Questions has a collection of 100 questions with answers asked in the interview for freshers and experienced (Programming, Scenario-Based, Fundamentals, Performance Tuning based Question and Answer). This course is intended to help Apache Spark Career Aspirants to prepare for the interview.

We are planning to add more questions in upcoming versions of this course.

Apache Spark is a fast and general-purpose cluster computing system. It provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs. It also supports a rich set of higher-level tools including Spark SQL for SQL and structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming.

Course Consist of the Interview Question on the following Topics

  • RDD Programming Spark basics - RDDs ( Spark Core)
  • Spark SQL, Datasets, and DataFrames: processing structured data with relational queries
  • Structured Streaming: processing structured data streams with relation queries (using Datasets and DataFrames, newer API than DStreams)
  • Spark Streaming: processing data streams using DStreams (old API)
  • MLlib: applying machine learning algorithms
  • GraphX: processing graphs

Who this course is for:

  • This course is designed for Apache Spark Job seeker with 6 months to 4 years of Experience in Apache Spark Development and looking out for new job as Spark Developer,Bigdata Engineers or Developers, Software Developer, Software Architect, Development Manager
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