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# Table API & SQL
Apache Flink features two relational APIs - the Table API and SQL - for unified stream and batch processing.
The Table API is a language-integrated query API for Java, Scala, and Python that allows the composition of queries from relational operators such as selection, filter, and join in a very intuitive way.
This documentation is intended for contributors of the table modules, and not for users.
If you want to use Table API & SQL, check out the [documentation](https://nightlies.apache.org/flink/flink-docs-master/docs/dev/table/overview/).
## Modules
### Common
* `flink-table-common`:
* Type system definition
* UDF stack and built-in function definitions
* Internal data definitions
* Extension points for catalogs, formats, connectors
* Core APIs for extension points such as `Schema`
* Utilities to deal with type system, internal data types and printing
### API
* `flink-table-api-java`:
* Java APIs for Table API and SQL
* Package `org.apache.flink.table.delegation`, which serves as entrypoint for all planner capabilities
* `flink-table-api-scala`: Scala APIs for Table API and SQL
* `flink-table-api-bridge-base`: Base classes for APIs to bridge between Table API and DataStream API
* `flink-table-api-java-bridge`:
* Java APIs to bridge between Table API and DataStream API
* Connectors that are developed using DataStream API, usually need to depend only on this module.
* `flink-table-api-scala-bridge`: Scala APIs to bridge between Table API and DataStream API
* `flink-table-api-java-uber`:
* Uber JAR bundling `flink-table-common` and all the Java API modules, including the bridging to DataStream API and 3rd party dependencies.
* This module is intended to be used by the flink-dist, rather than from the users directly.
* `flink-table-calcite-bridge`: Calcite dependencies for writing planner plugins (e.g. SQL dialects) that interact with Calcite API
### Runtime
* `flink-table-code-splitter`: Tool to split generated Java code so that each method does not exceed the limit of 64KB.
* `flink-table-runtime`:
* Operator implementations
* Built-in functions implementations
* Type system implementation, including readers/writers, converters and utilities
* Raw format
* The produced jar includes all the classes from this module and `flink-table-code-splitter`, including 3rd party dependencies
### Parser and planner
* `flink-sql-parser`: Default ANSI SQL parser implementation
* `flink-table-planner`:
* AST and Semantic tree
* SQL validator
* Query planner, optimizer and rules implementation
* Code generator
* The produced jar includes all the classes from this module together with the two parsers, including 3rd party dependencies (excluding Scala dependencies).
* `flink-table-planner-loader-bundle` Bundles `flink-table-planner`, including Scala dependencies.
* `flink-table-planner-loader`: Loader for `flink-table-planner` that loads the planner and it's Scala dependencies in a separate classpath using `flink-table-planner-loader-bundle`, isolating the Scala version used to compile the planner.
### SQL client
* `flink-sql-client`: CLI tool to submit queries to a Flink cluster
### Testing
* `flink-table-test-utils`: Brings in transitively all the dependencies you need to execute Table pipelines and provides some test utilities such as assertions, mocks and test harnesses.
### Notes
No module except `flink-table-planner` should depend on `flink-table-runtime` in production classpath,
no module except `flink-table-planner-loader` should depend on `flink-table-planner-loader-bundle` in production classpath,
and similarly no module should depend on `flink-table-planner` or `flink-table-planner-loader` in production classpath.
For testing, you should depend on `flink-table-planner-loader` and `flink-table-runtime`.
These are already shipped by the Flink distribution.