How do I enable and use memoization?

Flyte provides the ability to cache the output of task executions in order to make subsequent executions faster. A well-behaved Flyte Task should generate deterministic output given the same inputs and task functionality. This is useful in situations where a user knows that many executions with the exact same inputs can occur. For example, your task may be periodically run on a schedule, run multiple times when debugging workflows, or commonly shared across different workflows but receive the same inputs.

Enable Caching For a Task - SDK?

In order to enable your task to be cached, mark cache=True below:

@task(cache=True, cache_version='1.0.0')
def hash_string_task(original: str) -> str:

A task execution is cached based on the Project, Domain, cache_version, the task signature and inputs associated with the execution of the task.

  • Project: A task run under one project cannot use the cached task execution from another project. This could cause inadvertent results between project teams that could cause data corruption.

  • Domain: For separation of test, staging, and production data, task executions are not shared across these environments.

  • cache_version: When task functionality changes, you can change the cache_version of the task. Flyte will know not to use older cached task executions and create a new cache entry on the next execution.

  • Task signature:: The cache is specific to the task signature that is associated with the execution. The signature is made up of task name, input parameter names/types and also the output parameter name/types.

  • Task input values: A well-formed Flyte Task always produces deterministic outputs. This means given a set of input values, every execution should produce identical outputs. When a task execution is cached, the input values are part of the cache key.

Notice that task executions can be cached across different versions of the task. This is because a change in SHA does not neccessarily mean that it correlates to a change in task functionality.

Flyte provides several ways to break the old task execution cache, and cache new output:

  • cache_version: this field indicates that the task functionality has changed. Flyte users can manually update this version and Flyte will cache the next execution instead of relying on the old cache.

  • Task signature: If a Flyte user changes the task interface in any way (such as by adding, removing, or editing inputs/outputs), Flyte will treat that as a task functionality change. On the next execution, Flyte will run the task and store the outputs as new cached values.

Enable Caching in your FlytePlatform