Processing Environments

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Earth Engine has different environments for processing data: interactive and batch. These two environments (or "realms") handle different types of queries and have very different performance characteristics, so it's important to understand when and how to use each.

Interactive environment

Also called the "synchronous" or "online" stack, this environment is optimized for answering small requests which finish quickly (responses are limited to tens of megabytes of data and must finish processing within five minutes). Many requests can be made in parallel up to the quota limits.

Endpoints

The interactive environment is composed of different API endpoints: standard and high volume.

Standard endpoint

The standard endpoint is appropriate for most human-driven usage, and it's what powers the Code Editor and Earth Engine Apps. Specifically, this endpoint is best suited for latency-sensitive applications which involve a low volume of concurrent, non-programmatic requests.

High-volume endpoint

The high-volume API endpoint is designed to handle more requests in parallel than the standard endpoint, with the tradeoff of higher average latency and reduced caching. The high-volume API is often the best choice when making many requests programmatically. See more in the High Volume API docs.

Batch environment

Also called the "asynchronous" or "offline" stack, this environment is optimized for high-latency parallel processing of large amounts of data. Requests are submitted as tasks to batch processing endpoints, usually by calling data import or export functions (e.g., Export.* and ee.batch.*) from the Earth Engine client libraries. Each batch task has a maximum lifetime of ten days. Up to 3000 tasks can be submitted per user, but each individual user is limited to a small number of concurrently running tasks.

Task lifecycle

Tasks are held in a per-user queue, starting in the order in which they were submitted. Tasks progress from the SUBMITTED (queued) state to the RUNNING state when they're assigned to a batch processor. Each processor is responsible for orchestrating a varying number of batch workers to run the computation and produce the task's results. The number of workers for a task is determined by the EE service's ability to parallelize the job and is not user-configurable.

Tasks can be monitored via the Code Editor Tasks Tab, the standalone Task Manager page, the task command from the Earth Engine CLI, or by calling the ListOperations endpoint.

Tasks complete successfully when they create the necessary artifacts (Earth Engine assets, files in Google Cloud Storage, etc.).

Task failures

If a task fails for a reason which won't be fixed by retrying (e.g., the data are invalid), the task will be marked as FAILED and won't be run again.

If a task fails for a reason which could be intermittent (e.g., it timed out when running a computation), Earth Engine will automatically attempt to retry it and populate the retries field. Tasks can fail up to five times, and the final failure will cause the entire task to be marked as FAILED.

List of task states

Tasks can have the following state values:

    • UNSUBMITTED, still pending on the client
    • READY, queued on the server
    • RUNNING, currently running
    • COMPLETED, completed successfully
    • FAILED, completed unsuccessfully
    • CANCEL_REQUESTED, still running but has been requested to be cancelled (i.e., not a guarantee that the task will be cancelled)
    • CANCELLED, cancelled by the owner