Note1: This is a fork of sequenceiq/hadoop-docker + Spark, Python 2.7.8 and Mongodb Connector.

Note2: this is the master branch - for a particular Hadoop version always check the related branch

If you'd like to try directly from the Dockerfile you can build the image as:

docker build  -t cainelli/hadoop-docker:2.7.1 .

The image is also released as an official Docker image from Docker's automated build repository - you can always pull or refer the image when launching containers.

docker pull quay.io/cainelli/docker-hadoop

In order to use the Docker image you have just build or pulled use:

Make sure that SELinux is disabled on the host. If you are using boot2docker you don't need to do anything.

docker run -it quay.io/cainelli/docker-hadoop:latest /etc/bootstrap.sh -bash

Iteractive Mode

/usr/local/spark/bin/pyspark --packages com.org.mongodb.spark:mongo-spark-connector_2.11:2.0.0

Submit a Job

/usr/local/spark/bin/spark-submit --packages org.mongodb.spark:mongo-spark-connector_2.11:2.0.0 /home/sparkJob.py

You can run one of the stock examples:

cd $HADOOP_PREFIX
# run the mapreduce
bin/hadoop jar share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.1.jar grep input output 'dfs[a-z.]+'

# check the output
bin/hdfs dfs -cat output/*

The Hadoop build process is no easy task - requires lots of libraries and their right version, protobuf, etc and takes some time - we have simplified all these, made the build and released a 64b version of Hadoop nativelibs on this Bintray repo. Enjoy.