I have an EC2 instance and an EMR. I want to run spark jobs on EMR using airflow. Where would airflow needs to be installed for this?
On EC2 instance.
On EMR master node.
I am considering using SparkSubmit operator for this. What arguments should I provide while creating the airflow task?
You will be installing airflow on ec2 and I will suggest installing a containerized version of it. See this answer.
For submitting spark jobs, you will need EmrAddStepsOperator from airflow, and you will need to provide the step for spark-submit.
(Note: If you are starting the cluster from the script, you will need to use EmrCreateJobFlowOperator as well, see details here)
A typical submit step will look something like this
spark_submit_step = [
{
'Name': 'Run Spark',
'ActionOnFailure': 'TERMINATE_CLUSTER',
'HadoopJarStep': {
'Jar': 'command-runner.jar',
'Args': ['spark-submit',
'--jars',
"/emr/instance-controller/lib/bootstrap-actions/1/spark-iforest-2.4.0.jar,/home/hadoop/mysql-connector-java-5.1.47.jar",
'--py-files',
'/home/hadoop/mysqlConnect.py',
'/home/hadoop/main.py',
'custum_argument',
another_custum_argument,
another_custom_argument]
}
}
]
Related
I have an Apache Zeppelin notebook running and I'm trying to load the jdbc and/or postgres interpreter to my notebook in order to write to a postgres DB from Zeppelin.
The main resource to load new interpreters here tells me to run the code below to get other interpreters:
./bin/install-interpreter.sh --all
However, when I run this command in EMR terminal, I find that the EMR cluster does not come with an install-interpreter.sh executable file.
What is the recommended path?
1. Should I find the install-interpreter.sh file and load that to the EMR cluster under ./bin/?
2. Is there an EMR configuration on start time that would enable the install-interpreter.sh file?
Currently all tutorials and documentations assumes that you can run the install-interpreter.sh file.
The solution is to not run this code below in root (aka - ./ )
./bin/install-interpreter.sh --all
Instead in EMR, run the code above in Zeppelin, which in the EMR cluster, is in /usr/lib/zeppelin
Amazon EMR Documentation to add steps to cluster says that a single Elastic MapReduce step can submit several jobs to Hadoop. However, Amazon EMR Documentation for Step configuration suggests that a single step can accommodate just one execution of hadoop-streaming.jar (that is, HadoopJarStep is a HadoopJarStepConfig rather than an array of HadoopJarStepConfigs).
What is the proper syntax for submitting several jobs to Hadoop in a step?
Like Amazon EMR Documentation says, you can create a cluster to run some script my_script.sh on the master instance in a step:
aws emr create-cluster --name "Test cluster" --ami-version 3.11 --use-default-roles
--ec2-attributes KeyName=myKey --instance-type m3.xlarge --instance count 3
--steps Type=CUSTOM_JAR,Name=CustomJAR,ActionOnFailure=CONTINUE,Jar=s3://elasticmapreduce/libs/script-runner/script-runner.jar,Args=["s3://mybucket/script-path/my_script.sh"]
my_script.sh should look something like this:
#!/usr/bin/env bash
hadoop jar my_first_step.jar [mainClass] args... &
hadoop jar my_second_step.jar [mainClass] args... &
.
.
.
wait
This way, multiple jobs are submitted to Hadoop in the same step---but unfortunately, the EMR interface won't be able to track them. To do this, you should use the Hadoop web interfaces as shown here, or simply ssh to the master instance and explore with mapred job.
How do you run a script on all nodes (master and slaves) on Amazon EMR, the script-runner.jar runs only on the Namenode.
You have the bootstrap option:
You can use a bootstrap action to install additional software and to change the configuration of applications on the cluster. Bootstrap actions are scripts that are run on the cluster nodes when Amazon EMR launches the cluster. They run before Hadoop starts and before the node begins processing data. You can create custom bootstrap actions, or use predefined bootstrap actions provided by Amazon EMR.
from the documentation: http://docs.aws.amazon.com/ElasticMapReduce/latest/DeveloperGuide/emr-plan-bootstrap.html
It's as simple as placing a script to do the copying into S3, and then if you're starting EMR from the command line, add a parameter like this:
--bootstrap-action 's3://my-bucket/boostrap.sh'
Or if you're doing it through the web interface, just enter the location of the file in as a "Custom action" in "Bootstrap Actions".
I am wondering if we can setup a cloudera cluster on amazon and kick off a hadoop job from my local linux without ssh into amazon's node.
Is there anything like a client to do this communication?
The tips from the following tutorial really work. You should be able to put a working Hadoop Cluster in under 20 minutes, from cold iron to production ready, using just his guidance:
Hadoop Quickstart: Build a Cluster In The Cloud In 20 Minutes
Really worth checking it.
You can install an Hadoop client in your local linux and use the "hadoop jar" command with your own jar. Specify the option mapred.job.tracker in the command line and the client will push your jar to the jobtracker and duplicate it in all the tasktrackers that will be used for this job.
I am a newbie in hadoop and I am trying to run a hadoop jar on Amazon EC2. I have started my amazon ec2 instance through the console, uploaded my files to the dfs and then was able to successfully run the job jar and generate output on the instance.
But still I am confused on one part. I am not sure if the job was run on a single machine in amazon ec2 or was it ran on a cluster? How do I find the number of worker nodes involved for my jar run?
In some reference links I see we have to use launch-cluster command , for example "bin/hadoop-ec2 launch-cluster test-cluster 2" . What is the difference in starting the instance from the console and using this command like launch-cluster.