The document outlines the essential components and architecture of the Hadoop ecosystem, necessary for mastering Apache Hadoop skills in big data training. Key components include Hadoop Common, HDFS, MapReduce, YARN, Pig, Hive, Sqoop, Flume, HBase, Oozie, and Zookeeper, each serving specific roles in data processing, storage, and management. Understanding these components is crucial for efficient data analysis and processing within the Hadoop framework.

1. HADOOPCOMPONENTS
&ARCHITECTURE:
BIGDATA&HADOOP
TRAINING

2. UNDERSTAND HOW THE HADOOP ECOSYSTEM WORKS TO MASTER
APACHE HADOOP SKILLS AND GAIN IN-DEPTH KNOWLEDGE OF BIG
DATA ECOSYSTEM AND HADOOP ARCHITECTURE. HOWEVER, BEFORE
YOU ENROLL FOR ANY BIG DATA HADOOP TRAINING COURSE IT IS
NECESSARY TO GET SOME BASIC IDEA ON HOW THE HADOOP
ECOSYSTEM WORKS. LEARN ABOUT THE VARIOUS HADOOP
COMPONENTS THAT CONSTITUTE THE APACHE HADOOP
ARCHITECTURE IN THIS PRESENTATION.

3. DEFINING ARCHITECTURE COMPONENTS OF THE BIG
DATA ECOSYSTEM

5. CORE HADOOP COMPONENTS
• Hadoop Common
• 2) Hadoop Distributed File System (HDFS)
• 3) MapReduce- Distributed Data Processing Framework of Apache Hadoop
• 4)YARN
•
• Read More in Detail about Hadoop Components -
https://www.dezyre.com/article/hadoop-components-and-architecture-big-
data-and-hadoop-training/114

6. DATA ACCESS COMPONENTS OF HADOOP ECOSYSTEM-
PIG AND HIVE

7. APACHE PIG
• Apache Pig is a convenient tool developed by Yahoo for analysing
huge data sets efficiently and easily. It provides a high level data
flow language Pig Latin that is optimized, extensible and easy to
use.

8. APACHE HIVE
• Hive developed by Facebook is a data warehouse built on top of
Hadoop and provides a simple language known as HiveQL similar
to SQL for querying, data summarization and analysis. Hive
makes querying faster through indexing.

9. DATA INTEGRATION COMPONENTS OF HADOOP ECOSYSTEM-
SQOOP AND FLUME

10. APACHE SQOOP
• Sqoop component is used for importing data from external
sources into related Hadoop components like HDFS, HBase or
Hive. It can also be used for exporting data from Hadoop o other
external structured data stores.

11. FLUME
• Flume component is used to gather and aggregate large amounts
of data. Apache Flume is used for collecting data from its origin
and sending it back to the resting location (HDFS).

12. DATA STORAGE COMPONENT OF HADOOP ECOSYSTEM –
HBASE

13. HBASE
• HBase is a column-oriented database that uses HDFS for
underlying storage of data. HBase supports random reads and
also batch computations using MapReduce. With HBase NoSQL
database enterprise can create large tables with millions of rows
and columns on hardware machine.

14. MONITORING, MANAGEMENT AND ORCHESTRATION
COMPONENTS OF HADOOP ECOSYSTEM- OOZIE AND
ZOOKEEPER

15. OOZIE
• Oozie is a workflow scheduler where the workflows are
expressed as Directed Acyclic Graphs. Oozie runs in a Java servlet
container Tomcat and makes use of a database to store all the
running workflow instances, their states ad variables along with
the workflow definitions to manage Hadoop jobs (MapReduce,
Sqoop, Pig and Hive).

16. ZOOKEEPER
• Zookeeper is the king of coordination and provides simple, fast, reliable and
ordered operational services for a Hadoop cluster. Zookeeper is responsible
for synchronization service, distributed configuration service and for
providing a naming registry for distributed systems.
•
• To Know about other Hadoop Components -
https://www.dezyre.com/article/hadoop-components-and-architecture-big-
data-and-hadoop-training/114