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Supported DataFrame Data Types

BodoSQL uses Pandas DataFrames to represent SQL tables in memory and converts SQL types to corresponding Python types which are used by Bodo. Below is a table mapping SQL types used in BodoSQL to their respective Python types and Bodo data types.

SQL Type(s) Equivalent Python Type Bodo Data Type
TINYINT np.int8 bodo.int8
SMALLINT np.int16 bodo.int16
INT np.int32 bodo.int32
BIGINT np.int64 bodo.int64
FLOAT np.float32 bodo.float32
DECIMAL, DOUBLE np.float64 bodo.float64
VARCHAR, CHAR str bodo.string_type
TIMESTAMP, DATE np.datetime64[ns] bodo.datetime64ns
INTERVAL(day-time) np.timedelta64[ns] bodo.timedelta64ns
BOOLEAN np.bool_ bodo.bool_

BodoSQL can also process DataFrames that contain Categorical or Date columns. However, Bodo will convert these columns to one of the supported types, which incurs a performance cost. We recommend restricting your DataFrames to the directly supported types when possible.

Nullable and Unsigned Types

Although SQL does not explicitly support unsigned types, by default, BodoSQL maintains the exact types of the existing DataFrames registered in a [BodoSQLContext], including unsigned and non-nullable type behavior. If an operation has the possibility of creating null values or requires casting data, BodoSQL will convert the input of that operation to a nullable, signed version of the type.

Supported Literals

BodoSQL supports the following literal types:

  • array_literal
  • boolean_literal
  • datetime_literal
  • float_literal
  • integer_literal
  • interval_literal
  • object_literal
  • string_literal

Array Literal


<[> [expr[, expr...]] <]>

where <[> and <]> indicate literal [ and ]s, and expr is any expression.

Array literals are lists of comma seperated expressions wrapped in square brackets.

Note that BodoSQL currently only supports homogenous lists, and all exprs must coerce to a single type.

Boolean Literal



Boolean literals are case-insensitive.

Datetime Literal


DATE 'yyyy-mm-dd' |
TIMESTAMP 'yyyy-mm-dd' |
TIMESTAMP 'yyyy-mm-dd HH:mm:ss'

Float Literal


[ + | - ] { digit [ ... ] . [ digit [ ... ] ] | . digit [ ... ] }

where digit is any numeral from 0 to 9

Integer Literal


[ + | - ] digit [ ... ]

where digit is any numeral from 0 to 9

Interval Literal


INTERVAL integer_literal interval_type

Where integer_literal is a valid integer literal and interval type is one of:


In addition, we also have limited support for YEAR[S] and MONTH[S]. These literals cannot be stored in columns and currently are only supported for operations involving add and sub.

Object Literal


{['k1': `v1`[, 'k2': `v2`, ...]]}

Where each ki is a unique string literal, and each vi is an expression. Obeys the same semantics as the function OBJECT_CONSTRUCT , so any pair where the key or value is null is omitted, and for now BodoSQL only supports when all values are the same type.

String Literal


'char [ ... ]'

Where char is a character literal in a Python string.