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Articles Home » Big Data » CCA 175 Spark And Hadoop Developer Certification Scala

CCA 175 Spark And Hadoop Developer Certification Scala

CCA 175 – Spark And Hadoop Developer Certification – Scala

Created by Durga Viswanatha Raju Gadiraju, Sunil Abhishek, Vinod Nerella, Koushik M L N, Perraju Vegiraju, Balusai


70135 Spark Streaming - Data Structure (DStream) and APIs overview


Who this course is for

Any IT aspirant/professional willing to learn Big Data and give CCA 175 certification


Description

CCA 175 Spark and Hadoop Developer is one of the well recognized Big Data certification. This scenario based certification exam demands basic programming using Python or Scala along with Spark and other Big Data technologies. This comprehensive course covers all aspects of the certification using Scala as programming language. Scala Fundamentals Core Spark – Transformations and Actions Spark SQL and Data Frames File formats Flume, Kafka and Spark Streaming Apache Sqoop Exercises will be provided to prepare before attending the certification. Intention of the course is to boost the confidence to attend the certification.



What you will learn:
  • Entire curriculum of CCA Spark and Hadoop Developer
  • Apache Sqoop
  • HDFS
  • Scala Fundamentals
  • Core Spark – Transformations and Actions
  • Spark SQL and Data Frames
  • Streaming analytics using Kafka, Flume and Spark Streaming
Requirements:
  • Basic programming skills
  • Cloudera Quickstart VM or valid account for IT Versity Big Data labs or any Hadoop clusters where Hadoop, Hive and Spark are well integrated.
  • Minimum memory required based on the environment you are using with 64 bit operating system
      
Course Contents
01 Introduction 02 Scala Fundamentals 03 Getting Started 04 Data Ingestion - Apache Sqoop 05 Transform Stage and Store - Spark 06 Data Analysis - Spark SQL or HiveQL 07 Data Ingest - real time near real time and streaming analytics 08 Sample scenarios with solutions

· Posted by Superadmin on November 15 2020 · 0 Comments · 500 Reads · Print
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