Amazon Elastic MapReduce Introduces Resizing Running Job Flows
We are excited to announce the immediate ability for Amazon Elastic MapReduce customers to dynamically modify the size of their running job flows. Through the API, command line client, or Java SDK, you now have the flexibility to add or remove slave nodes based on the changing capacity needs of your job flow. You may also include a predefined step in your workflow that automatically resizes a job flow between steps that are known to have different capacity needs. This will allow you to better customize your capacity usage to meet the unique requirements of your job flows, improving performance while enabling you to save money. Further, Elastic MapReduce now automatically provisions new slave nodes if a slave node fails, providing you an even greater level of fault tolerance. For more details on modifying the size of your running job flows, please visit Resizing Running Job Flows in the Elastic MapReduce Developer’s Guide.
We are excited to announce the immediate ability for Amazon Elastic MapReduce customers to dynamically modify the size of their running job flows. Through the API, command line client, or Java SDK, you now have the flexibility to add or remove slave nodes based on the changing capacity needs of your job flow. You may also include a predefined step in your workflow that automatically resizes a job flow between steps that are known to have different capacity needs. This will allow you to better customize your capacity usage to meet the unique requirements of your job flows, improving performance while enabling you to save money. Further, Elastic MapReduce now automatically provisions new slave nodes if a slave node fails, providing you an even greater level of fault tolerance. For more details on modifying the size of your running job flows, please visit Resizing Running Job Flows in the Elastic MapReduce Developer’s Guide.