Pull the image from Docker Repository:
docker pull kairen/yarn-spark:1.5
Running the image:
docker run -d -p 8088:8088 -p 50070:50070 -h spark-master \
-v <your_dir>:/root/spark-run/ \
--name yarn-spark kairen/yarn-spark:1.5 -d
The
<your_dir>
is a share directory, you can put a dataset or run file in here.
This image provides Java, Scala, R, Python example, You can perform the following operation.
Enter the container:
Using exec
into the docker container:
docker exec -ti <container id> bash
Creating a test data:
$ touch test.txt
$ vi test.txt
# add the following
Absence of evidence
is not evidence
of absence
Absence of evidence
is not evidence
of absence
Absence of evidence
is not evidence
of absence
Upload test data to HDFS:
hadoop fs -mkdir /test
hadoop fs -put test.txt /test
Running the spark on standard:
cd /root/python
spark-submit wordcount.py hdfs://spark-master:9000/test/test.txt
Running the spark on YARN:
cd /root/python
spark-submit --master yarn-cluster wordcount.py hdfs://spark-master:9000/test/test.txt