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Run Hadoop on Arm64 (Apple M1) and Intel CPUs Natively Using the Universal Docker Images.

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Hadoop on Docker

Note Please pull the latest code by using git pull before try to run.

See Standalone mode

How to Run Hadoop on macOS (Apple M1 and Intel CPU) by One Command

Platforms supported

ARM64 (Apple Silicon) and AMD64 (Intel)

Requirement

Docker Desktop is required (and it is the easiest way to get Docker work on your laptop). For macOS (Apple M1), Docker Desktop For macOS (Intel), Docker Desktop

Docker Test

If Docker Desktop is installed properly, you should be able to run the following command:

docker run hello-world

And see the output like:

Hello from Docker!
This message shows that your installation appears to be working correctly.
... ...

Start Hadoop Cluster

Go to terminal and clone the git repo to your computer:

git clone [email protected]:wxw-matt/docker-hadoop.git ~/docker-hadoop
cd ~/docker-hadoop
docker-compose up -d

It takes a few minutes to completely start the whole Hadoop cluster for the first time.

How to Copy Files from Host Computer to HDSF and HDFS to Local System

For example, if you want to copy a file called Test.txt from the host computer to HDFS, the file first should be copied to ./jars/data and you can use the command: ./hdfs dfs -copyFromLocal -f /app/data/Test.txt /input/ to copy it to /input in HDFS.

The directories mappings between your computer and the container are:

./jobs/jars => /app/jars
./jobs/data => /app/data
./jobs/res => /app/res

That means any files in ./jobs/jars are accessibile in the container through the path /app/jars, any files in ./jobs/data are accessibile in the container through the path /app/data.

Example:

# !! Go to docker-hadoop directory first
# Create a file on the host computer
cat > mytest.txt <<EOF
This is the first line.
This is the second line.
The last line comes here.
EOF

# Copy it to ./jobs/data
cp mytest.txt ./jobs/data
./hdfs dfs -mkdir -p /mytest_input
./hdfs dfs -copyFromLocal -f /app/data/mytest.txt /mytest_input/
./hadoop fs -cat /mytest_input/mytest.txt
# Remove the output directory, otherwise you may get an error "Output directory hdfs://namenode:9000/mytest_output already exists"
./hdfs dfs -rm -r -f /mytest_output
# Run a job
./hadoop jar jars/WordCount.jar WordCount /mytest_input /mytest_output
# Remove local output directory
rm -rf ./jobs/res/mytest_output
# Copy output to your computer
./hdfs dfs -copyToLocal /mytest_output /app/res/
# View output from host computer
cat ./jobs/res/mytest_output/*

Run the Example Map-Reduced Job on the Cluster

Run example wordcount job. The WordCount.jar is located in ./jobs/jars directory .

Typing the command below to commit the job.

./hdfs dfs -mkdir -p /input
./hdfs dfs -copyFromLocal -f /app/data/README.txt /input/
./hadoop jar jars/WordCount.jar WordCount /input /output
# View output (double quote is needed for zsh when star/asterisk occurs)
./hadoop fs -cat "/output/*"

Note You may need to remove /output first if it already exists using command ./hadoop fs -rm -r /output.

Monitor Hadoop Cluster by WebUI

Namenode: http://localhost:9870

Datanode: http://localhost:9864

Resourcemanager: http://localhost:8088

Nodemanager: http://localhost:8042

Historyserver: http://localhost:8188

Note If you are redirected to a URL like http://119e8b128bd5:8042/ or http://resourcemanager:8088/, change the host name to localhost (i.e. http://localhost:8042/) and it will work. This is because Docker containers use their own IPs which are mapped to different names.

Common Hadoop Comamnds

# Create a directory
./hdfs dfs -mkdir -p directory-name
# Remove a directory and its sub-directories
./hadoop fs -rm -r -f directory-name
# Copy files from jobs/data to HDFS
./hdfs dfs -copyFromLocal -f /app/data/README.txt /input/ 
# View files
./hdfs dfs -ls /input 

How to Run Your Own Jobs

Using Eclipse or other IDEs to generate a jar file. Copy it to ./jobs/jars. For example, if your jar file name is HelloWorld.jar and it is in the ./jobs/jars. The following command will submit your job to Hadoop.

./hadoop jar jars/HelloWorld.jar HelloWorld /input /output

And your data will go to ./jobs/data, then using ./hdfs dfs -copyFromLocal to copy it to HDFS.

Credits

The repo is inspired by @big-data-europe. Without their work, it may take me days to get this done.

References:

  1. https://hadoop.apache.org/docs/stable/hadoop-mapreduce-client/hadoop-mapreduce-client-core/MapReduceTutorial.html

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