| Prompt: |
| What are schemas in Apache Beam? |
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| Response: |
| A Schema in Apache Beam is a language-independent type definition for a `PCollection`. The schema defines elements of that `PCollection` as an ordered list of named fields. |
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| In many cases, the element type in a `PCollection` has a structure that can be introspected. Some examples are JSON, Protocol Buffer, Avro, and database row objects. All of these formats can be converted to Beam Schemas. |
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| To take advantage of schemas, your `PCollection` objects must have a schema attached. Often, the source itself attaches a schema to the `PCollection`. |
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| Although schemas are language-independent, they're designed to embed naturally into the Beam SDK programming languages. This feature allows you to continue using native types while leveraging the advantage of having Beam understand your element schemas. |
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| Apache Beam provides a collection of schema transforms that operate on schemas. For an example, see `SqlTransform` in the 'Beam SQL overview' section of the Apache Beam documentation. |
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| The following list includes key capabilities provided by schema transforms: |
| * field selection |
| * grouping and aggregation |
| * join operations |
| * filtering data |
| * adding and removing fields |
| * renaming fields |
| * type conversion |
| * enhanced ParDo functionality |
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| For more information about schemas and the Apache Beam best practices when working with structured data, see the 'Schema Usage Patterns' section in the Apache Beam documentation. |
