Submit Pig work - Amazon EMR
Submit Pig work using the Amazon EMR consoleSubmit Pig work using the Amazon CLI
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Submit Pig work

This section demonstrates submitting Pig work to an Amazon EMR cluster. The examples that follow generate a report containing the total bytes transferred, a list of the top 50 IP addresses, a list of the top 50 external referrers, and the top 50 search terms using Bing and Google. The Pig script is located in the Amazon S3 bucket s3://elasticmapreduce/samples/pig-apache/do-reports2.pig. Input data is located in the Amazon S3 bucket s3://elasticmapreduce/samples/pig-apache/input. The output is saved to an Amazon S3 bucket.

Submit Pig work using the Amazon EMR console

This example describes how to use the Amazon EMR console to add a Pig step to a cluster.

To submit a Pig step

  1. Open the Amazon EMR console at https://console.amazonaws.cn/emr.

  2. Choose Create cluster to create a cluster with Pig installed. For steps on how to create a cluster, see Plan and configure an Amazon EMR cluster.

  3. Open a terminal and SSH into the master node of your cluster following the steps outlined in Connect to the master node using SSH. Once you've done that, run the following steps.

    sudo mkdir -p /home/hadoop/lib/pig/
sudo aws s3 cp s3://elasticmapreduce/libs/pig/0.3/piggybank-0.3-amzn.jar /home/hadoop/lib/pig/piggybank.jar

  4. In the console, click Cluster List and select the name of the cluster you created.

  5. Scroll to the Steps section and expand it, then choose Add step.

  6. In the Add Step dialog:

    • For Step type, choose Pig program.

    • For Name, accept the default name (Pig program) or type a new name.

    • For Script S3 location, type the location of the Pig script. For example: s3://elasticmapreduce/samples/pig-apache/do-reports2.pig.

    • For Input S3 location, type the location of the input data. For example: s3://elasticmapreduce/samples/pig-apache/input.

    • For Output S3 location, type or browse to the name of your Amazon S3 output bucket.

    • For Arguments, leave the field blank.

    • For Action on failure, accept the default option (Continue).

  7. Choose Add. The step appears in the console with a status of Pending.

  8. The status of the step changes from Pending to Running to Completed as the step runs. To update the status, choose the Refresh icon above the Actions column. When your step is complete, check your Amazon S3 bucket to confirm your Pig step's output files are there.

Submit Pig work using the Amazon CLI

To submit a Pig step using the Amazon CLI

When you launch a cluster using the Amazon CLI, use the --applications parameter to install Pig. To submit a Pig step, use the --steps parameter.

  1. To launch a cluster with Pig installed, type the following command, replacing myKey and DOC-EXAMPLE-BUCKET/ with the name of your EC2 key pair and Amazon S3 bucket.

    aws emr create-cluster \
--name "Test cluster" \
--log-uri s3://DOC-EXAMPLE-BUCKET/ \
--release-label emr-5.36.1 \
--applications Name=Pig \
--use-default-roles \
--ec2-attributes KeyName=myKey \
--instance-type m5.xlarge \
--instance-count 3
    Note

    Linux line continuation characters (\) are included for readability. They can be removed or used in Linux commands. For Windows, remove them or replace with a caret (^).

    When you specify the instance count without using the --instance-groups parameter, a single master node is launched, and the remaining instances are launched as core nodes. All nodes use the instance type specified in the command.

    Note

    If you have not previously created the default EMR service role and EC2 instance profile, type aws emr create-default-roles to create them before typing the create-cluster subcommand.

  2. To submit a Pig step, enter the following command, replacing myClusterId and DOC-EXAMPLE-BUCKET with your cluster ID and name of your Amazon S3 bucket.

    aws emr add-steps \
--cluster-id myClusterId \
--steps Type=PIG,Name="Pig Program",ActionOnFailure=CONTINUE,Args=[-f,s3://elasticmapreduce/samples/pig-apache/do-reports2.pig,-p,INPUT=s3://elasticmapreduce/samples/pig-apache/input,-p,OUTPUT=s3://DOC-EXAMPLE-BUCKET/pig-apache/output]

    This command will return a step ID, which you can use to check the State of your step.

  3. Query the status of your step with the describe-step command.

    aws emr describe-step --cluster-id myClusterId --step-id s-1XXXXXXXXXXA

    The State of the step changes from PENDING to RUNNING to COMPLETED as the step runs. When your step is complete, check your Amazon S3 bucket to confirm your Pig step's output files are there.

For more information about using Amazon EMR commands in the Amazon CLI, see the Amazon CLI Command Reference.