| Prompt: |
| What are schemas in Apache Beam? |
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| Response: |
| A [Schema in Apache Beam](https://beam.apache.org/documentation/programming-guide/#schemas) 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 lets you continue [to use native types](https://beam.apache.org/documentation/programming-guide/#schemas-for-pl-types) while leveraging the advantage of having Beam understand your element schemas. |
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| Beam provides a collection of [schema transforms](https://beam.apache.org/documentation/programming-guide/#662-schema-transforms) that operate on schemas. For an example, see [SqlTransform](https://beam.apache.org/documentation/dsls/sql/overview/). |
| |
| 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 |
| |
| For more information about schemas and the Apache Beam best practices when working with structured data, see [Schema Usage Patterns](https://beam.apache.org/documentation/patterns/schema/). |
