Data Engineering Master Course: Spark/Hadoop/Kafka/MongoDB | Udemy [Update 07/2024]
English | Size: 5.2 GB
Genre: eLearning[/center]

Full Hands on course to become Big Data Engineer: Spark/Kafka/Hadoop/Flume/Hive/Sqoop/MongoDB. Data Engineering course.

What you'll learn
Hadoop Ecosystem, Sqoop, Flume, Hive
Expertise on writing code with Apache Spark
Learn Kafka Fundamentals and using Kafka Connectors
Learn writing queries and client in MongoDB
Learn Data Engineering technologies

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 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.

In the next section, we 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

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

Spark with Cassandra Integration

Running Spark on Intellij IDE

Running Spark on EMR

You will learn about Apache Kafka

Kafka Architecture

Partitions and offsets

Kafka Producers and Consumers

Kafka SerDEs

Kafka Messages

Kafka Connector

Ingesting Data using Kafka Connector

You will learn about MongoDB

MongoDB Usecases

CRUD Operations

MongoDB Operators

Working with Arrays

MongoDB with Spark

Data Engineering Interview Preparation

Sqoop Interview Questions

Hive Interview Questions

Spark Interview Questions

Data Engineering common questions

Data Engineering Real project questions.

Who this course is for:
Who want to learn Big data technologies
Who want to become Data Engineers

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