Data Types
This documentation is for an unreleased version of Apache Flink. We recommend you use the latest stable version.

Data Types #

This page describes the data types supported in PyFlink Table API.

Data Type #

A data type describes the logical type of a value in the table ecosystem. It can be used to declare input and/or output types of Python user-defined functions. Users of the Python Table API work with instances of pyflink.table.types.DataType within the Python Table API or when defining user-defined functions.

A DataType instance declares the logical type which does not imply a concrete physical representation for transmission or storage. All pre-defined data types are available in pyflink.table.types and can be instantiated with the utility methods defined in pyflink.table.types.DataTypes.

A list of all pre-defined data types can be found below.

Data Type and Python Type Mapping #

A data type can be used to declare input and/or output types of Python user-defined functions. The inputs will be converted to Python objects corresponding to the data type and the type of the user-defined functions result must also match the defined data type.

For vectorized Python UDF, the input types and output type are pandas.Series. The element type of the pandas.Series corresponds to the specified data type.

Data Type Python Type Pandas Type
BOOLEAN bool numpy.bool_
TINYINT int numpy.int8
SMALLINT int numpy.int16
INT int numpy.int32
BIGINT int numpy.int64
FLOAT float numpy.float32
DOUBLE float numpy.float64
VARCHAR str str
VARBINARY bytes bytes
DECIMAL decimal.Decimal decimal.Decimal
DATE datetime.date datetime.date
TIME datetime.time datetime.time
TimestampType datetime.datetime datetime.datetime
LocalZonedTimestampType datetime.datetime datetime.datetime
INTERVAL YEAR TO MONTH int Not Supported Yet
INTERVAL DAY TO SECOND datetime.timedelta Not Supported Yet
ARRAY list numpy.ndarray
MULTISET list Not Supported Yet
MAP dict Not Supported Yet
ROW Row dict