# Submit a streaming step
<a name="CLI_CreateStreaming"></a>

This section covers the basics of submitting a streaming step to a cluster. A streaming application reads input from standard input and then runs a script or executable (called a mapper) against each input. The result from each of the inputs is saved locally, typically on a Hadoop Distributed File System (HDFS) partition. After all the input is processed by the mapper, a second script or executable (called a reducer) processes the mapper results. The results from the reducer are sent to standard output. You can chain together a series of streaming steps, where the output of one step becomes the input of another step. 

The mapper and the reducer can each be referenced as a file or you can supply a Java class. You can implement the mapper and reducer in any of the supported languages, including Ruby, Perl, Python, PHP, or Bash.

## Submit a streaming step using the console
<a name="emr-dev-create-stream-console"></a>

This example describes how to use the Amazon EMR console to submit a streaming step to a running cluster.

**To submit a streaming step**

1. Open the Amazon EMR console at [https://console.aws.amazon.com/emr](https://console.aws.amazon.com/emr/).

1. In the **Cluster List**, select the name of your cluster.

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

1. In the **Add Step** dialog box:
   + For **Step type**, choose **Streaming program**.
   + For **Name**, accept the default name (Streaming program) or type a new name.
   + For **Mapper**, type or browse to the location of your mapper class in Hadoop, or an S3 bucket where the mapper executable, such as a Python program, resides. The path value must be in the form *BucketName*/*path*/*MapperExecutable*.
   + For **Reducer**, type or browse to the location of your reducer class in Hadoop, or an S3 bucket where the reducer executable, such as a Python program, resides. The path value must be in the form *BucketName*/*path*/*MapperExecutable*. Amazon EMR supports the special *aggregate* keyword. For more information, go to the Aggregate library supplied by Hadoop.
   + For **Input S3 location**, type or browse to the location of your input data. 
   + 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**).

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

1. 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. 

## AWS CLI
<a name="emr-dev-create-stream-cli"></a>

These examples demonstrate how to use the AWS CLI to create a cluster and submit a Streaming step. 

**To create a cluster and submit a streaming step using the AWS CLI**
+ To create a cluster and submit a streaming step using the AWS CLI, type the following command and replace *myKey* with the name of your EC2 key pair. Note that your argument for `--files` should be the Amazon S3 path to your script's location, and the arguments for `-mapper` and `-reducer` should be the names of the respective script files.

  ```
  aws emr create-cluster --name "Test cluster" --release-label emr-7.12.0 --applications Name=Hue Name=Hive Name=Pig --use-default-roles \
  --ec2-attributes KeyName=myKey --instance-type m5.xlarge --instance-count 3 \
  --steps Type=STREAMING,Name="Streaming Program",ActionOnFailure=CONTINUE,Args=[--files,pathtoscripts,-mapper,mapperscript,-reducer,reducerscript,aggregate,-input,pathtoinputdata,-output,pathtooutputbucket]
  ```
**Note**  
Linux line continuation characters (\$1) 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 Amazon EMR service role and EC2 instance profile, type aws `emr create-default-roles` to create them before typing the `create-cluster` subcommand.

  For more information on using Amazon EMR commands in the AWS CLI, see [https://docs.aws.amazon.com/cli/latest/reference/emr](https://docs.aws.amazon.com/cli/latest/reference/emr).