EDUCBA

EDUCBA

MENUMENU
  • Free Tutorials
  • Free Courses
  • Certification Courses
  • 360+ Courses All in One Bundle
  • Login
Home Data Science Data Science Tutorials Hadoop Tutorial Hadoop Tools
Secondary Sidebar
Hadoop Tutorial
  • Basics
    • What is Hadoop
    • Career in Hadoop
    • Advantages of Hadoop
    • Uses of Hadoop
    • Hadoop Versions
    • HADOOP Framework
    • Hadoop Architecture
    • Hadoop Configuration
    • Hadoop Components
    • Hadoop WordCount
    • Hadoop Database
    • Hadoop Ecosystem
    • Hadoop Tools
    • Install Hadoop
    • Is Hadoop Open Source
    • What is Hadoop Cluster
    • Hadoop Namenode
    • Hadoop data lake
    • Hadoop fsck
    • HDFS File System
    • Hadoop Distributed File System
  • Commands
    • Hadoop Commands
    • Hadoop fs Commands
    • Hadoop FS Command List
    • HDFS Commands
    • HDFS ls
    • Hadoop Stack
    • HBase Commands
  • Advanced
    • What is Yarn in Hadoop
    • Hadoop?Administrator
    • Hadoop DistCp
    • Hadoop Administrator Jobs
    • Hadoop Schedulers
    • Hadoop Distributed File System (HDFS)
    • Hadoop Streaming
    • Apache Hadoop Ecosystem
    • Distributed Cache in Hadoop
    • Hadoop Ecosystem Components
    • Hadoop YARN Architecture
    • HDFS Architecture
    • What is HDFS
    • HDFS Federation
    • Apache HBase
    • HBase Architecture
    • What is Hbase
    • HBase Shell Commands
    • What is MapReduce in Hadoop
    • Mapreduce Combiner
    • MapReduce Architecture
    • MapReduce Word Count
    • Impala Shell
    • HBase Create Table
  • Interview Questions
    • Hadoop Admin Interview Questions
    • Hadoop Cluster Interview Questions
    • Hadoop developer interview Questions
    • HBase Interview Questions

Related Courses

Data Science Certification

Online Machine Learning Training

Hadoop Certification

MapReduce Certification Course

Hadoop Tools

By Priya PedamkarPriya Pedamkar

Hadoop Tools

Introduction to Hadoop Tools

Hadoop tools are defined as the framework needed to process a large amount of data distributed in form and clusters to perform distributed computation. Few of the tools that are used in Hadoop for handling the data is Hive, Pig, Sqoop, HBase, Zookeeper, and Flume where Hive and Pig are used to query and analyze the data, Sqoop is used to move the data and Flume is used to ingest the streaming data to the HDFS.

Features of Hadoop Tools

  1. Hive
  2. Pig
  3. Sqoop
  4. HBase
  5. Zookeeper
  6. Flume

Now we will see the features with a brief explanation.

1. Hive

The Apache Hive was founded by Facebook and later donated to Apache Foundation, which is a data warehouse infrastructure, it facilitates writing SQL like Query called HQL or HiveQL. These queries are internally converted to Map Reduce jobs and processing is done utilizing Hadoop’s distributed computing. It can process the data which resides in HDFS, S3 and all the storage compatible with Hadoop. We can leverage the facilities provided by Map Reduce whenever we find something difficult to implement in Hive by implementing in User Defined Functions. It enables the user to register UDF’s and use it in the jobs.

Features of Hive

Start Your Free Data Science Course

Hadoop, Data Science, Statistics & others

  • Hive can process many types of file formats such as Sequence File, ORC File, TextFile, etc.
  • Partitioning, Bucketing, and Indexing are available for faster execution.
  • Compressed Data can also be loaded into a hive table.
  • Managed or Internal tables and external tables are the prominent features of Hive.

2. Pig

Yahoo developed the Apache Pig to have an additional tool to strengthen Hadoop by having an ad-hoc way of implementing Map Reduce. Pig is having an engine called Pig Engine which converts scripts to Map Reduce. Pig is a scripting language, the scripts written for Pig are in PigLatin, just like Hive here also we can have UDF’s to enhance the functionality. Tasks in Pig are optimized automatically so programmers need not worry about it. Pig Handles both structured as well as unstructured data.

Features of Pig

  • Users can have their own functions to do a particular type of data processing.
  • It is easy to write codes in Pig comparatively also the length of the code is less.
  • The system can automatically optimize execution.

3. Sqoop

Sqoop is used to transfer data from HDFS to RDBMS and vice versa. We can pull the data to HDFS from RDBMS, Hive, etc., and we can process and export it back to RDBMS. We can append the data many times in a table. Also, we can create a Sqoop job and execute it ‘n’ number of times.

Features of Sqoop

  • Sqoop can import all tables at once into HDFS.
  • We can embed SQL queries as well as conditions on the import of data.
  • We can import data to hive if a table is present from HDFS.
  • The number of mappers can be controlled, i.e. parallel execution can be controlled by specifying the number of mappers.

4. HBase

The database management system on top of HDFS is called HBase. HBase is a NoSQL database, that is developed on top of HDFS. HBase is not a relational database; it does not support structured query languages. HBase utilizes distributed processing of HDFS. It can have large tables with millions and millions of records.

Features of HBase

  • HBase provides scalability in both linear as well as modular.
  • API’s in JAVA can be used for client access.
  • HBase provides a shell for executing queries.

5. Zookeeper

Apache Zookeeper is a centralized configuration maintaining service; it keeps a record of information, naming, it also provides distributed synchronization and group services. Zookeeper is a centralized repository that is utilized by distributed applications to put and get data off it. It also helps in managing nodes, i.e. to join or leave a node in the cluster. It provides a highly reliable data registry when a few of the nodes are down.

Features of Zookeeper

  • Performance can be increased by distributing the tasks which are achieved by adding more machines.
  • It hides the complexity of the distribution and portrays itself as a single machine.
  • Failure of a few systems does not impact the entire system, but the drawback is it may lead to partial data loss.
  • It provides Atomicity, i.e. transaction is either successful or failed but not in an imperfect state.

6. Flume

Apache Flume is a tool that provides data ingestion, which can collect, aggregate and transport a huge amount of data from different sources to an HDFS, HBase, etc. Flume is very reliable and can be configured. It was designed to ingest streaming data from the webserver or event data to HDFS, e.g. it can ingest twitter data to HDFS. Flume can store data to any of the centralized data stores such as HBase/HDFS. If there is a situation where the data produce is at a higher rate compared to that of the speed of the data can be written then flume acts as a mediator and ensures data flows steadily.

Features of Flume

  • It can ingest web servers data along with the event data such as data from social media.
  • Flume transactions are channel-based, i.e. two messages are maintained; one is for sending, and one is for receiving.
  • Horizontal scaling is possible in a flume.
  • It is highly faulted tolerant as contextual routing is present in a flume.

Conclusion

Here in this article, we have learned about a few of the Hadoop tools and how they are useful in the world of data. We have seen Hive and Pig, which is used to query and analyze data, snoop to move data and flume to ingest streaming data to HDFS.

Recommended Articles

This has been a guide to Hadoop Tools. Here we discuss different Tools of Hadoop with their features. You can also go through our other suggested articles to learn more –

  1. Hadoop Alternatives
  2. Hadoop Database
  3. SQL String Functions
  4. What is Big Data
  5. Hadoop Commands | Top 23 Commands
  6. Comprehensive Guide to Hadoop Versions
  7. How to Use LIKE Query in SQL?
Popular Course in this category
Hadoop Training Program (20 Courses, 14+ Projects, 4 Quizzes)
  20 Online Courses |  14 Hands-on Projects |  135+ Hours |  Verifiable Certificate of Completion
4.5
Price

View Course

Related Courses

All in One Data Science Bundle(360+ Courses, 50+ projects)
Python TutorialMachine LearningAWSArtificial Intelligence
TableauR ProgrammingPowerBIDeep Learning
Price
View Courses
360+ Online Courses | 50+ projects | 1500+ Hours | Verifiable Certificates | Lifetime Access
4.7 (86,650 ratings)
Data Scientist Training (85 Courses, 67+ Projects)4.9
Machine Learning Training (20 Courses, 29+ Projects)4.8
MapReduce Training (2 Courses, 4+ Projects)4.7
0 Shares
Share
Tweet
Share
Primary Sidebar
Footer
About Us
  • Blog
  • Who is EDUCBA?
  • Sign Up
  • Live Classes
  • Corporate Training
  • Certificate from Top Institutions
  • Contact Us
  • Verifiable Certificate
  • Reviews
  • Terms and Conditions
  • Privacy Policy
  •  
Apps
  • iPhone & iPad
  • Android
Resources
  • Free Courses
  • Database Management
  • Machine Learning
  • All Tutorials
Certification Courses
  • All Courses
  • Data Science Course - All in One Bundle
  • Machine Learning Course
  • Hadoop Certification Training
  • Cloud Computing Training Course
  • R Programming Course
  • AWS Training Course
  • SAS Training Course

ISO 10004:2018 & ISO 9001:2015 Certified

© 2022 - EDUCBA. ALL RIGHTS RESERVED. THE CERTIFICATION NAMES ARE THE TRADEMARKS OF THEIR RESPECTIVE OWNERS.

EDUCBA
Free Data Science Course

SPSS, Data visualization with Python, Matplotlib Library, Seaborn Package

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA Login

Forgot Password?

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA
Free Data Science Course

Hadoop, Data Science, Statistics & others

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

EDUCBA

*Please provide your correct email id. Login details for this Free course will be emailed to you

By signing up, you agree to our Terms of Use and Privacy Policy.

Let’s Get Started

By signing up, you agree to our Terms of Use and Privacy Policy.

This website or its third-party tools use cookies, which are necessary to its functioning and required to achieve the purposes illustrated in the cookie policy. By closing this banner, scrolling this page, clicking a link or continuing to browse otherwise, you agree to our Privacy Policy

Loading . . .
Quiz
Question:

Answer:

Quiz Result
Total QuestionsCorrect AnswersWrong AnswersPercentage

Explore 1000+ varieties of Mock tests View more