
Delve into Big Data essentials, explore data types, and gain insights into Hadoop components like YARN, MapReduce, HDFS, and Spark. Discover foundations to excel in the growing Big Data field.

data.tar.gz

HADOOP_HOME

JAVA_HOME

HDFS_NAMENODE_USER

HDFS_DATANODE_USER

HDFS_SECONDARYNAMENODE_USER

YARN_RESOURCEMANAGER_USER

YARN_NODEMANAGER_USER

HADOOP_CONF_DIR

ZK_HOME

PIG_HOME

AvroWriteExample

AvroReadExample

AvroGeneratedCodeReadExample

AvroGeneratedCodeWriteExample

AvroRPCExample

ParquetReadExampleJob

ParquetWriteExampleJob

ParquetAvroReadExampleJob

ParquetAvroWriteExampleJob

ParquetProjectionReadExampleJob

SequenceFileReadExampleJob

SequenceFileWriteExampleJob

SequenceFileSyncPointExampleJob

TestCarMapperJob

TestCarReducerJob

CarCounterMrProgramJob

MyLiveAppJob

DataNodeWebUI2

YarnWebUI

YarnWebUI-copy

YarnWebUI-copy-copy

JHS-UI

Spark-UI-copy

Spark-History-Server-UI-3

This course offers a one-of-a-kind rich and interactive experience to learn the fundamentals and basics of Big Data. Throughout this course, you will have plenty of opportunities to get your hands dirty with functioning Hadoop clusters.

You will start off by learning about the rise of Big Data as well as the different types of data like structured, unstructured, and semi-structured data. You will then dive into the fundamentals of Big Data such as YARN (yet another resource manager), MapReduce, HDFS (Hadoop Distributed File System), and Spark.

By the end of this course, you will have the foundations in place to start working with Big Data, which is a massively growing field.

Introduction to Big Data and Hadoop

## Rows vs Columnar Databases

Databases are frequently used to store data. They do so in a manner different from how we visually perceive data arranged in rows. TData is stored in two  possible formats:

+ Row Format
+ Columnar Format

We are already familiar with databases that use the row format. These are the traditional relational databases such as MySQL, PostgreSQL, Oracle, and others Row format databases store records as rows in a table. A typical representation of our example Car table, consisting of four columns when stored in a relational database, is like this:

# Rows vs Columnar Databases

Databases are frequently used to store data. They do so in a manner different from how we visually perceive data arranged in rows. TData is stored in two  possible formats:

+ Row Format
+ Columnar Format

We are already familiar with databases that use the row format. These are the traditional relational databases such as MySQL, PostgreSQL, Oracle, and others Row format databases store records as rows in a table. A typical representation of our example Car table, consisting of four columns when stored in a relational database, is like this:

 This lesson explains the differences between row and columnar databases.

Rows vs Columnar Databases

Hadoop

YARN

Map Reduce

HDFS

Spark

Input & Output Formats

Misc

Quiz

Reference: Replication

Reference: Partitioning

Reference: Transactions

Reference: Issues in Distributed Systems

Rows vs Columnar Databases

Rows vs Columnar Databases