Click here to Skip to main content
14,027,634 members
Click here to Skip to main content
Add your own
alternative version


3 bookmarked
Posted 26 Dec 2015
Licenced CPOL

Debugging Hadoop HDFS using IntelliJ IDEA on Linux

, 27 Dec 2015
Rate this:
Please Sign up or sign in to vote.
This article helps to setup debug environment for hadoop framework on Linux Ubuntu using IntelliJ IDEA


This article is intended for beginners who want to setup Hadoop debug environment, i.e., debugging Namenode, Datanode and Map Reduce APIs. This will help in better understanding of the framework itself. Being a Microsoft developer, I was new to Java, IntelliJ IDEA and Hadoop development. The reason why I wrote this article is I struggled for a couple of days to setup debug environment as I didn't get complete details online. However I had a strong feeling of learning this wonderful bigdata technology and that helped me cross all the hurdles.:) I hope this article helps those who want to start learning hadoop from scratch.

This article is divided into two parts:

  • Part 1. Running HDFS by building the source code
  • Part 2. Setting up debug environment using IntelliJ


In general, Hadoop technology consists of two parts - data storage and analyzing the stored data.

HDFS (Hadoop Distributed File System) that stores and manages data and MapReduce framework that does data analysis job.

HDFS consists of Namenode to manage metadata of file system and several Datanodes to store the data.

I assume the reader has sufficient understanding of the basics of Hadoop architecture. If not, please spend some time learning and come back to this article. I suggest reading Tom White's "Hadoop, The Definitive Guide" book.

HDFS Components

Namenode and Datanode are implemented as Linux daemons and both exposes RPC and HTTP interfaces for communication.

Namenode RPC interface listen on port 8020 by default and HTTP interface on port 50070 by default.

Datanode RPC interface listen on port 50010 by default and HTTP interface on port 50075.

These ports can be overridden using the configuration.

The Namenode and Datanode runs on their own JVM process. So we can run them on the same machine with some simple configuration changes.

Tools Required

I've used Ubuntu 14.x Linux VM on my Windows box.

  1. Install Java SDK 1.8

    Run the below commands on your command prompt and Ubuntu will install sdk on your machine.
    sudo apt-add-repository ppa:webupd8team/java
    sudo apt-get update
    sudo apt-get install oracle-java8-installer

    Verify the installation by running java -version on command prompt. On my machine, it displays as below.

    java version "1.8.0_65"
    Java(TM) SE Runtime Environment (build 1.8.0_65-b17)
    Java HotSpot(TM) 64-Bit Server VM (build 25.65-b01, mixed mode)
  2. Install Maven
    sudo apt-get install maven

    Verify maven installation. Type mvn -version on command prompt. You should get:

    Apache Maven 3.0.5
    Maven home: /usr/share/maven
    Java version: 1.8.0_65, vendor: Oracle Corporation
    Java home: /usr/local/jdk1.8.0_65/jre
    Default locale: en_US, platform encoding: UTF-8
    OS name: "Linux", version: "3.19.0-25-generic", arch: "amd64", family: "unix"
  3. Install native libraries
    sudo apt-get -y install maven build-essential autoconf automake libtool
    cmake zlib1g-dev pkg-config libssl-dev libfuse-dev
  4. Install Google's protocol buffers
    sudo apt-get install protobuf-compiler

    Verify it by typing protoc on command prompt. You should get:

    Missing input file.
  5. Download IntelliJ IDEA for Linux. You should choose community edition.

Download Hadoop Source Code

There are different ways to get hadoop source code. I chose to get it from github directly so that I can get latest codebase. When you start contributing to hadoop, you can use git tool to clone the repository. For now, we can download it directly from github.

  1. Goto
  2. Click on download ZIP option and it'll be downloaded to 'Downloads' folder.
  3. Unzip it and you get a folder called hadoop-trunk
  4. Place this folder in home directory. I placed it under ~/code/hadoop-trunk

Hadoop Source Code Structure

Hadoop consists of many projects that are listed below. Each project contains various modules.

The projects that we're interested right now are hadoop-common-project and hadoop-hdfs-project.

The hadoop-common-project has module called hadoop-common that has all the common libraries shared by all the projects/modules.

The hadoop-hdfs-project has hadoop-hdfs module that's the standard implementation of HDFS. It contains Namenode and Datanode implementation.

Build Hadoop Source Code

Hadoop has many dependencies that are typically available in maven repository. So we need to build the source code once to get all the dependencies. Make sure that you're connected to the Internet.

Goto hadoop source code and run this command

mvn clean install -Pdist -DskipTests

~/code/hadoop-trunk/   $mvn clean install -Pdist -DskipTests

It will take some time based on your Internet speed to resolve dependencies and build the source code, so relax!

Make sure that build is successful. If you've followed instructions correctly, then you shouldn't get any errors. If you get any errors, then Google it for resolution or please post in the comment section. We will try to help!

Configure Environment

The build produces two important folders that are interests us now. In my case, they are:

One is in hadoop-common : /home/mallan/code/hadoop-trunk/hadoop-common-project/hadoop-common/target/hadoop-common-3.0.0-SNAPSHOT

One is in hadoop-hdfs: /home/mallan/code/hadoop-trunk/hadoop-hdfs-project/hadoop-hdfs/target/hadoop-hdfs-3.0.0-SNAPSHOT

3.0.0 indicates the hadoop version. It might change based on your source version.

Whatever we need for HDFS exist in only these two folders. Spend some time in exploring the content of these folders.

Let's configure the hadoop environment variables for these two folders.

open the .bashrc file (exists in your home location) and copy below lines.

export JAVA_HOME=/usr/lib/jvm/java-8-oracle
export HADOOP_COMMON_HOME=~/code/hadoop-trunk/hadoop-common-project/hadoop-common/target/hadoop-common-3.0.0-SNAPSHOT
export HADOOP_HDFS_HOME=~/code/hadoop-trunk/hadoop-hdfs-project/hadoop-hdfs/target/hadoop-hdfs-3.0.0-SNAPSHOT
export HADOOP_YARN_HOME=~/code/hadoop-trunk/
export HADOOP_MAPRED_HOME=~/code/hadoop-trunk/
export HADOOP_CONF_DIR=~/code/hadoop-trunk/hadoop-common-project/hadoop-common/target/hadoop-common-3.0.0-SNAPSHOT/etc/hadoop
export PATH=$JAVA_HOME/bin:$PATH

The HADOOP_YARN_HOME and HADOOP_MAPRED_HOME are needed to just make script happy, else it will will cry. So, I've provided dummy paths. They need to be configured properly when you need to enable Map reduce and YARN framework.

Close all open Terminals and open them back so that these environment variables will be set.

Next, we need to configure default file system home in /home/mallan/code/hadoop-trunk/hadoop-common-project/hadoop-common/target/hadoop-common-3.0.0-SNAPSHOT/etc/core-site.xml and add this property to the configuration section.

  <description>The name of the default file system. </description>

Run HDFS (Namenode and Datanode)

You are ready to run your own built Namenode and Datanode.

Go to prompt and type hdfs namenode -format. This will prepare the file system metadata files in the /tmp folder.

Type hdfs namenode. This will run the Namenode that will start listening at 8020 and 50070 port.

In another terminal, type hdfs datanode. This will run Datanode that will start listening at 50010 and 50075 port as explained above.

Now using other Terminal, you can run dfs commands such as:

hdfs dfs -ls /
hdfs dfs -mkdir /folder1
hdfs dfs -coptyFromLocal <source> <destination>


What Next?

I hope you are able to run HDFS using the binaries that you've built. In the following section let's setup our own debug environment where you we debug Namenode and Datanode.

Setup source code with IntelliJ

The hadoop project uses Maven for building and maintaining the project. If you are new to Maven then I suggest spending some time learning it.

Maven project consists POM.xml file that defines the project structure and dependecies. The IntelliJ is very good in parsing the POM file.

Follow these steps

       1. Run IntelliJ, you get below screen


      2. Click Open and select the POM.xml in the hadoop-trunk folder.



      3. IntelliJ IDEA will read the POM file and loads all the projects. Each project/module in turn contains its own POM.xml file. The IntelliJ resolves all the dependencies and finally it looks as below.



    4. If you build the projects using Build->Rebuild option, it should just build fine.  However if you goto (hadoop-hdfs-project->hadoop-hdfs->src->main->java->org.apache.hadoop->hdfs->server->Namenode->

And tries to Run is using Run option (you get it if you right click on the file) It doesn’t run, it throws some NoClassFoundErros.  Use below steps to fix it.

            4.1 We need to make some changes to POM file in (hadoop-hdfs-project->hadoop-                           hdfs->POM.xml file.

            Go to <dependencies> section, you see that some of the dependency has provided as scope              type. It means that the container that runs process should provide these dependencies in run             time. The IntelliJ IDEA cannot provide this so change all ‘provided’ to ‘compile’ option

            Learn more about Maven dependency here

            4.2 Go to hadoop-common-projectàhadoop-commonàsrcàmainàresourcesàcore-defaults.xml.

            Make sure that fs.defaultFS and has the hdfs://localhost/ as a value

  <description>The name of the default file system. </description>


           4.3 We need to fix one last thing.  The Namenode runs HttpServer and it has to locate the web            application folder.

            In explorer Go to ~/code/hadoop-trunk/hadoop-hdfs-project/hadoop-hdfs/target/ you’ll fine              webapps folder. Copy this and place it inside ‘classes’ folder. Where run time looks for this                        webapps folder. The below screenshot shows after copying webapps folder.




   5. Before we start  debugging run hdfs namenode –format   This will prepares the metadata folder in   /tmp.

   6. Now we are ready to run Namenode in debug mode. Go to, right click on it   and  select ‘debug Namenode’ option. Before this you may want to place break point in main method of Namenode.

   7. Once Namenode is running in debug mode, you can run some hdfs commands from command   prompt. i.e. hdfs dfs –ls  /    Below  screenshot shows hitting the breakpoint in NamenodeRpcServer class


Side by Side Execution

When debugging either Namenode or Datanode we can make use of the instances that we are running from the binaries that we built. For e.g.

When trying to debug Namenode, we can run only Datanode from the binaries that we built. The debugging Namenode from IntelliJ can connect to Datanode that’s running. Similarly for  Datanode debugging.

I hope you're succefully able to debug HDFS now. I believe it's a agreat way to learn Hadoop architecture.  If you come across any issues please do post a comment. Thank you.



  • 26th December, 2015: Initial version
  • 27th Decemeber, 2015: Update with setting up debug environment.


This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


About the Author

Mallanagouda Patil
Architect CA Technologies
India India
I'm an enthusiastic software developer with experience in Open Source and MS Technologies. I'm passionate about BigData technologies particularly HDFS, YARN, SPark and Kafka.I love learning new things and sharing knowledge. I like to travel, listen music, watch thriller movies, play chess etc.

You may also be interested in...


Comments and Discussions

QuestionDatanode starts and shutdowns immediately Pin
Member 1241242623-Mar-16 6:15
memberMember 1241242623-Mar-16 6:15 
AnswerRe: Datanode starts and shutdowns immediately Pin
Mallanagouda Patil18-Jul-16 20:49
professionalMallanagouda Patil18-Jul-16 20:49 
PraiseGreat into for newbies Pin
Member 122498967-Jan-16 17:43
memberMember 122498967-Jan-16 17:43 
GeneralRe: Great into for newbies Pin
Mallanagouda Patil10-Jan-16 21:49
professionalMallanagouda Patil10-Jan-16 21:49 
GeneralMy vote of 5 Pin
Member 85828454-Jan-16 2:35
memberMember 85828454-Jan-16 2:35 
GeneralRe: My vote of 5 Pin
Mallanagouda Patil10-Jan-16 21:49
professionalMallanagouda Patil10-Jan-16 21:49 
GeneralMy vote of 5 Pin
Sandeep Khurana31-Dec-15 19:45
memberSandeep Khurana31-Dec-15 19:45 
GeneralRe: My vote of 5 Pin
Mallanagouda Patil10-Jan-16 21:48
professionalMallanagouda Patil10-Jan-16 21:48 
QuestionEnhancement Pin
Member 1223539429-Dec-15 19:23
memberMember 1223539429-Dec-15 19:23 
AnswerRe: Enhancement Pin
Mallanagouda Patil10-Jan-16 21:48
professionalMallanagouda Patil10-Jan-16 21:48 

General General    News News    Suggestion Suggestion    Question Question    Bug Bug    Answer Answer    Joke Joke    Praise Praise    Rant Rant    Admin Admin   

Use Ctrl+Left/Right to switch messages, Ctrl+Up/Down to switch threads, Ctrl+Shift+Left/Right to switch pages.

Permalink | Advertise | Privacy | Cookies | Terms of Use | Mobile
Web06 | 2.8.190419.4 | Last Updated 27 Dec 2015
Article Copyright 2015 by Mallanagouda Patil
Everything else Copyright © CodeProject, 1999-2019
Layout: fixed | fluid