# Batching

Grouping several small units of work into one task so that scheduling overhead does not dominate the time spent doing useful work.

Source: https://university.eugo.io/glossary/batching

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A task that takes a millisecond spends most of its life being scheduled. Batching a hundred such units into one task changes the ratio decisively.

## Related terms

- [Task](https://university.eugo.io/glossary/task) — One unit of distributed work: a single call to a function decorated with the distribute decorator. Tasks are stateless, so each call starts fresh.
- [Partition](https://university.eugo.io/glossary/partition) — One independently processable chunk of a dataset. Partition size is the main lever on how well a workload parallelizes.
- [Scheduling overhead](https://university.eugo.io/glossary/scheduling-overhead) — The fixed cost of dispatching a task and returning its result. When it approaches the cost of the task body, adding parallelism stops helping.