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Master Big Data: Hadoop & Spark - CCA 175 preparation


Become a Master of Spark using Scala to Stage, Transform, and Store with ... Apache Spark is the single most revolutionizing phenomenon in Big Data ... In this course, I will be preparing you for the CCA 175 Spark Developer Certification.
4.2 (116 ratings)
500 students enrolled
Created by Navdeep Kaur
Last updated 9/2019
English
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Current priceRp182,000
Original PriceRp350,000
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This course includes
  • 8 hours on-demand video
  • 15 downloadable resources
  • 2 Practice Tests
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • HDFS, Sqoop Import, Sqoop Export, Hive, Flume, Spark RDD, Spark Dataframes, Spark SQL and CCA175 practice tests
Requirements
  • Cloudera vm installation if you want to run examples.
Description
In this course, you will start by learning what is hadoop distributed file system and most common hadoop commands required to work with Hadoop File system.

Then you will be introduced to Sqoop Import
  • Understand lifecycle of sqoop command.
  • Use sqoop import command to migrate data from Mysql to HDFS.
  • Use sqoop import command to migrate data from Mysql to Hive.
  • Use various file formats, compressions, file delimeter,where clause and queries while importing the data.
  • Understand split-by and boundary queries.
  • Use incremental mode to migrate the data from Mysql to HDFS.

Further, you will learn Sqoop Export to migrate data.
  • What is sqoop export
  • Using sqoop export, migrate data from HDFS to Mysql.
  • Using sqoop export, migrate data from Hive to Mysql.

Further, you will learn about Apache Hive
  • Hive Intro
  • External & Managed Tables
  • Working with Different Files - Parquet,Avro
  • Compressions
  • Hive Analysis
  • Hive String Functions
  • Hive Date Functions
  • Partitioning
  • Bucketing
Further, you will learn about Apache Spark
  • Spark Intro
  • Cluster Overview
  • RDD
  • DAG/Stages/Tasks
  • Actions & Transformations
  • Transformation & Action Examples
  • Spark Data frames
  • Spark Data frames - working with diff File Formats & Compression
  • Dataframes API's
  • Spark SQL
  • Dataframe Examples

Further section will have CCA175 Practice Tests with explanations
  • CCA175 practice test1
  • CCA175 practice test1 explanations
  • CCA175 practice test2
  • CCA175 practice test2 explanations



Finally, we will start with our last section Apache Flume
  • Understand Flume Architecture.
  • Using flume, Ingest data from Twitter and save to HDFS.
  • Using flume, Ingest data from netcat and save to HDFS.
  • Using flume, Ingest data from exec and show on console.
  • Describe flume interceptors and see examples of using interceptors.
  • Flume multiple agents
  • Flume Consolidation

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