How to Install Hadoop, Hive, and HBase on WSL | Windows 11

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📦 What We Are Setting Up

• WSL with Ubuntu

• Java 8 (because Hadoop/Hive are allergic to newer Java)

• Hadoop 3.3.6 (pseudo-distributed)

• Hive 3.1.3 (with built-in Derby Metastore)

• HBase 2.4.17 (lightweight standalone)

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🛠️ Step 1: Install WSL (Ubuntu)

1. Open PowerShell as Administrator.

2. Run:

   wsl --install
   

3. Restart the computer if it asks.

4. Set your Ubuntu username and password after reboot.

✅ WSL Ready!

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🛠️ Step 2: Update Ubuntu Packages

In Ubuntu terminal:

sudo apt update && sudo apt upgrade -y

Always update before installing stuff, bro.

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🛠️ Step 3: Install Java 8

Java is non-negotiable for Hadoop.

Install it:

sudo apt install openjdk-8-jdk -y

Verify:

java -version

You should see something like:

openjdk version "1.8.0_xxx"

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🛠️ Step 4: Install Hadoop 3.3.6

🔹 Download Hadoop

cd ~
wget https://downloads.apache.org/hadoop/common/hadoop-3.3.6/hadoop-3.3.6.tar.gz

🔹 Extract Hadoop

tar -xvzf hadoop-3.3.6.tar.gz
mv hadoop-3.3.6 /usr/local/hadoop

🔹 Set Environment Variables

Edit ~/.bashrc:

nano ~/.bashrc

Add at the bottom:

export HADOOP_HOME=/usr/local/hadoop
export PATH=$PATH:$HADOOP_HOME/bin:$HADOOP_HOME/sbin
export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64

Apply changes:

source ~/.bashrc

🔹 Configure Hadoop

Edit hadoop-env.sh:

nano /usr/local/hadoop/etc/hadoop/hadoop-env.sh

Set Java path:

export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64

Edit core-site.xml:

nano /usr/local/hadoop/etc/hadoop/core-site.xml

Paste:

<configuration>
  <property>
    <name>fs.defaultFS</name>
    <value>hdfs://localhost:9000</value>
  </property>
</configuration>

Edit hdfs-site.xml:

nano /usr/local/hadoop/etc/hadoop/hdfs-site.xml

Paste:

<configuration>
  <property>
    <name>dfs.replication</name>
    <value>1</value>
  </property>
</configuration>

🔹 Format Hadoop

hdfs namenode -format

🔹 Start Hadoop

start-dfs.sh
start-yarn.sh

Check Namenode UI âž” Open browser:

http://localhost:9870

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🛠️ Step 5: Install Hive 3.1.3

🔹 Download Hive

cd ~
wget https://downloads.apache.org/hive/hive-3.1.3/apache-hive-3.1.3-bin.tar.gz

🔹 Extract Hive

tar -xvzf apache-hive-3.1.3-bin.tar.gz
mv apache-hive-3.1.3-bin /usr/local/hive

🔹 Set Environment Variables

Edit ~/.bashrc:

nano ~/.bashrc

Add at the bottom:

export HIVE_HOME=/usr/local/hive
export PATH=$PATH:$HIVE_HOME/bin

Apply changes:

source ~/.bashrc

🔹 Configure Hive

Create hive-env.sh:

cp $HIVE_HOME/conf/hive-env.sh.template $HIVE_HOME/conf/hive-env.sh
nano $HIVE_HOME/conf/hive-env.sh

Add:

export HADOOP_HOME=/usr/local/hadoop
export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64

🔹 Initialize Metastore

schematool -dbType derby -initSchema

🔹 Start Hive CLI

hive

Done! You're inside Hive now.

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🛠️ Step 6: Install HBase 2.4.17

🔹 Download HBase

cd ~
wget https://downloads.apache.org/hbase/2.4.17/hbase-2.4.17-bin.tar.gz

🔹 Extract HBase

tar -xvzf hbase-2.4.17-bin.tar.gz
mv hbase-2.4.17 /usr/local/hbase

🔹 Set Environment Variables

Edit ~/.bashrc:

nano ~/.bashrc

Add at bottom:

export HBASE_HOME=/usr/local/hbase
export PATH=$PATH:$HBASE_HOME/bin

Apply:

source ~/.bashrc

🔹 Configure HBase

Edit hbase-site.xml:

nano /usr/local/hbase/conf/hbase-site.xml

Paste:

<configuration>
  <property>
    <name>hbase.rootdir</name>
    <value>hdfs://localhost:9000/hbase</value>
  </property>
  <property>
    <name>hbase.zookeeper.property.dataDir</name>
    <value>/usr/local/hbase/zookeeper</value>
  </property>
</configuration>

🔹 Start HBase

start-hbase.sh

🔹 Open HBase Shell

hbase shell

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📋 Quick Commands Cheat Sheet

Tool	Start Command
Hadoop DFS	start-dfs.sh
Hadoop YARN	start-yarn.sh
Hive CLI	hive
HBase	start-hbase.sh then hbase shell

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🛡️ Important Pro Tips

• Hadoop must be running before starting Hive or HBase.

• If Hive says connection refused, it means Hadoop isn’t started yet.

• Always source ~/.bashrc after setting new environment variables.

• WSL can choke RAM if you don’t cap it — add .wslconfig file if needed.

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🏁 Conclusion

Setting up Hadoop, Hive, and HBase on WSL isn't impossible you just need patience, attention to small configs, and correct Java version.
Now you’ve got a mini Big Data lab running inside your Windows machine. No VM needed. No Docker drama.