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When you write an application that calls the Amazon Elastic MapReduce (Amazon EMR) API, there are several concepts that apply when calling one of the wrapper functions of an SDK.
An endpoint is a URL that is the entry point for a web service. Every web
service request must contain an endpoint. The endpoint specifies the AWS region
where clusters are created, described, or terminated. It has the form
If you specify the general endpoint (
elasticmapreduce.amazonaws.com), Amazon EMR
directs your request to an endpoint in the default region. For accounts created on
or after March 8, 2013, the default region is us-west-2; for older accounts, the
default region is us-east-1.
For more information about the endpoints for Amazon EMR, see Regions and Endpoints in the Amazon Web Services General Reference.
Instances parameters enable you to configure the type and
number of EC2 instances to create nodes to process the data. Hadoop spreads the
processing of the data across multiple cluster nodes. The master node is responsible for
keeping track of the health of the core and task nodes and polling the nodes for job
result status. The core and task nodes do the actual processing of the data. If you have
a single-node cluster, the node serves as both the master and a core node.
KeepJobAlive parameter in a
RunJobFlow request determines whether to terminate the cluster
when it runs out of cluster steps to execute. Set this value to
you know that the cluster is running as expected. When you are troubleshooting the job
flow and adding steps while the cluster execution is suspended, set the value to
True. This reduces the amount of time and expense of uploading the
results to Amazon Simple Storage Service (Amazon S3), only to repeat the process after modifying a step to restart the
true, after successfully
getting the cluster to complete its work, you must send a
TerminateJobFlows request or the cluster continues to run and
generate AWS charges.
Amazon EMR uses EC2 instances as nodes to process clusters. These EC2 instances have locations composed of Availability Zones and regions. Regions are dispersed and located in separate geographic areas. Availability Zones are distinct locations within a region insulated from failures in other Availability Zones. Each Availability Zone provides inexpensive, low-latency network connectivity to other Availability Zones in the same region. For a list of the regions and endpoints for Amazon EMR, see Regions and Endpoints in the Amazon Web Services General Reference.
AvailabilityZone parameter specifies the general location
of the cluster. This parameter is optional and, in general, we discourage its use. When
AvailabilityZone is not specified Amazon EMR automatically picks the
AvailabilityZone value for the cluster. You might find this
parameter useful if you want to colocate your instances with other existing running
instances, and your cluster needs to read or write data from those instances. For more
information, see the Amazon Elastic Compute Cloud Developer Guide.
There are times when you might like to use additional files or custom libraries with your mapper or reducer applications. For example, you might like to use a library that converts a PDF file into plain text.
AWS provides tutorials that show you how to create complete applications, including:
For more Amazon EMR code examples, go to Sample Code & Libraries.