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Datums define what input data is seen by your code. It can be all data at once, each directory independently, individual files one by one, or combined data from multiple inputs together.

A datum is the smallest indivisible unit of computation within a job. A job can have one, many or no datums. Each datum is processed independently with a single execution of the user code and then the results of all the datums are merged together to create the final output commit.

A datum defines the input data. An input can take one or multiple repositories. Pachyderm has the following types of inputs that combine multiple repositories:

A cross input creates a cross-product of multiple repositories. Therefore, each datum from one repository is combined with each datum from the other repository.
A join input enables you to join files that are stored in different Pachyderm repositories and match a particular file path pattern. Joins are similar to cross, except instead of matching every pair of datums from each input, it only matches specific ones based on file paths. Conceptually, joins are similar to the database’s inner join operations, although they only match on file paths, not the actual file content.
A union input can take multiple repositories and processes all the data in each input independently. The pipeline processes the datums in no defined order and the output repository includes results from all input sources.

The number of datums for a job is defined by the glob pattern which you specify for each input. Think of datums as if you were telling Pachyderm how to divide your input data to efficiently distribute computation and only process the new data. You can configure a whole input repository to be one datum, each top-level filesystem object to be a separate datum, specific paths can be datums, and so on. Datums affect how Pachyderm distributes processing workloads and are instrumental in optimizing your configuration for best performance.

Pachyderm takes each datum and processes it in isolation on one of the pipeline worker nodes. You can define datums, workers, and other performance parameters can all be configured through the corresponding fields in the pipeline specification.

To understand how datums affect data processing in Pachyderm, you need to understand the following subconcepts:

Last update: July 16, 2020