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// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may not use this file except in compliance
// with the License. You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing,
// software distributed under the License is distributed on an
// "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the License for the
// specific language governing permissions and limitations
// under the License.
use datafusion::arrow::datatypes::{DataType, IntervalUnit, TimeUnit};
use datafusion_common::{DataFusionError, ScalarValue};
use pyo3::prelude::*;
use crate::errors::py_datafusion_err;
#[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
#[pyclass(name = "RexType", module = "datafusion.common")]
pub enum RexType {
Alias,
Literal,
Call,
Reference,
ScalarSubquery,
Other,
}
/// These bindings are tying together several disparate systems.
/// You have SQL types for the SQL strings and RDBMS systems itself.
/// Rust types for the DataFusion code
/// Arrow types which represents the underlying arrow format
/// Python types which represent the type in Python
/// It is important to keep all of those types in a single
/// and managable location. Therefore this structure exists
/// to map those types and provide a simple place for developers
/// to map types from one system to another.
#[derive(Debug, Clone)]
#[pyclass(name = "DataTypeMap", module = "datafusion.common", subclass)]
pub struct DataTypeMap {
#[pyo3(get, set)]
pub arrow_type: PyDataType,
#[pyo3(get, set)]
pub python_type: PythonType,
#[pyo3(get, set)]
pub sql_type: SqlType,
}
impl DataTypeMap {
fn new(arrow_type: DataType, python_type: PythonType, sql_type: SqlType) -> Self {
DataTypeMap {
arrow_type: PyDataType {
data_type: arrow_type,
},
python_type,
sql_type,
}
}
pub fn map_from_arrow_type(arrow_type: &DataType) -> Result<DataTypeMap, PyErr> {
match arrow_type {
DataType::Null => Ok(DataTypeMap::new(
DataType::Null,
PythonType::None,
SqlType::NULL,
)),
DataType::Boolean => Ok(DataTypeMap::new(
DataType::Boolean,
PythonType::Bool,
SqlType::BOOLEAN,
)),
DataType::Int8 => Ok(DataTypeMap::new(
DataType::Int8,
PythonType::Int,
SqlType::TINYINT,
)),
DataType::Int16 => Ok(DataTypeMap::new(
DataType::Int16,
PythonType::Int,
SqlType::SMALLINT,
)),
DataType::Int32 => Ok(DataTypeMap::new(
DataType::Int32,
PythonType::Int,
SqlType::INTEGER,
)),
DataType::Int64 => Ok(DataTypeMap::new(
DataType::Int64,
PythonType::Int,
SqlType::BIGINT,
)),
DataType::UInt8 => Ok(DataTypeMap::new(
DataType::UInt8,
PythonType::Int,
SqlType::TINYINT,
)),
DataType::UInt16 => Ok(DataTypeMap::new(
DataType::UInt16,
PythonType::Int,
SqlType::SMALLINT,
)),
DataType::UInt32 => Ok(DataTypeMap::new(
DataType::UInt32,
PythonType::Int,
SqlType::INTEGER,
)),
DataType::UInt64 => Ok(DataTypeMap::new(
DataType::UInt64,
PythonType::Int,
SqlType::BIGINT,
)),
DataType::Float16 => Ok(DataTypeMap::new(
DataType::Float16,
PythonType::Float,
SqlType::FLOAT,
)),
DataType::Float32 => Ok(DataTypeMap::new(
DataType::Float32,
PythonType::Float,
SqlType::FLOAT,
)),
DataType::Float64 => Ok(DataTypeMap::new(
DataType::Float64,
PythonType::Float,
SqlType::FLOAT,
)),
DataType::Timestamp(unit, tz) => Ok(DataTypeMap::new(
DataType::Timestamp(unit.clone(), tz.clone()),
PythonType::Datetime,
SqlType::DATE,
)),
DataType::Date32 => Ok(DataTypeMap::new(
DataType::Date32,
PythonType::Datetime,
SqlType::DATE,
)),
DataType::Date64 => Ok(DataTypeMap::new(
DataType::Date64,
PythonType::Datetime,
SqlType::DATE,
)),
DataType::Time32(unit) => Ok(DataTypeMap::new(
DataType::Time32(unit.clone()),
PythonType::Datetime,
SqlType::DATE,
)),
DataType::Time64(unit) => Ok(DataTypeMap::new(
DataType::Time64(unit.clone()),
PythonType::Datetime,
SqlType::DATE,
)),
DataType::Duration(_) => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", arrow_type),
))),
DataType::Interval(interval_unit) => Ok(DataTypeMap::new(
DataType::Interval(interval_unit.clone()),
PythonType::Datetime,
match interval_unit {
IntervalUnit::DayTime => SqlType::INTERVAL_DAY,
IntervalUnit::MonthDayNano => SqlType::INTERVAL_MONTH,
IntervalUnit::YearMonth => SqlType::INTERVAL_YEAR_MONTH,
},
)),
DataType::Binary => Ok(DataTypeMap::new(
DataType::Binary,
PythonType::Bytes,
SqlType::BINARY,
)),
DataType::FixedSizeBinary(_) => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", arrow_type)),
)),
DataType::LargeBinary => Ok(DataTypeMap::new(
DataType::LargeBinary,
PythonType::Bytes,
SqlType::BINARY,
)),
DataType::Utf8 => Ok(DataTypeMap::new(
DataType::Utf8,
PythonType::Str,
SqlType::VARCHAR,
)),
DataType::LargeUtf8 => Ok(DataTypeMap::new(
DataType::LargeUtf8,
PythonType::Str,
SqlType::VARCHAR,
)),
DataType::List(_) => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
arrow_type
)))),
DataType::FixedSizeList(_, _) => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", arrow_type)),
)),
DataType::LargeList(_) => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", arrow_type),
))),
DataType::Struct(_) => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", arrow_type),
))),
DataType::Union(_, _) => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", arrow_type),
))),
DataType::Dictionary(_, _) => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", arrow_type),
))),
DataType::Decimal128(precision, scale) => Ok(DataTypeMap::new(
DataType::Decimal128(*precision, *scale),
PythonType::Float,
SqlType::DECIMAL,
)),
DataType::Decimal256(precision, scale) => Ok(DataTypeMap::new(
DataType::Decimal256(*precision, *scale),
PythonType::Float,
SqlType::DECIMAL,
)),
DataType::Map(_, _) => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", arrow_type),
))),
DataType::RunEndEncoded(_, _) => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", arrow_type)),
)),
}
}
/// Generate the `DataTypeMap` from a `ScalarValue` instance
pub fn map_from_scalar_value(scalar_val: &ScalarValue) -> Result<DataTypeMap, PyErr> {
DataTypeMap::map_from_arrow_type(&DataTypeMap::map_from_scalar_to_arrow(scalar_val)?)
}
/// Maps a `ScalarValue` to an Arrow `DataType`
pub fn map_from_scalar_to_arrow(scalar_val: &ScalarValue) -> Result<DataType, PyErr> {
match scalar_val {
ScalarValue::Boolean(_) => Ok(DataType::Boolean),
ScalarValue::Float32(_) => Ok(DataType::Float32),
ScalarValue::Float64(_) => Ok(DataType::Float64),
ScalarValue::Decimal128(_, precision, scale) => {
Ok(DataType::Decimal128(*precision, *scale))
}
ScalarValue::Dictionary(data_type, scalar_type) => {
// Call this function again to map the dictionary scalar_value to an Arrow type
Ok(DataType::Dictionary(
Box::new(*data_type.clone()),
Box::new(DataTypeMap::map_from_scalar_to_arrow(scalar_type)?),
))
}
ScalarValue::Int8(_) => Ok(DataType::Int8),
ScalarValue::Int16(_) => Ok(DataType::Int16),
ScalarValue::Int32(_) => Ok(DataType::Int32),
ScalarValue::Int64(_) => Ok(DataType::Int64),
ScalarValue::UInt8(_) => Ok(DataType::UInt8),
ScalarValue::UInt16(_) => Ok(DataType::UInt16),
ScalarValue::UInt32(_) => Ok(DataType::UInt32),
ScalarValue::UInt64(_) => Ok(DataType::UInt64),
ScalarValue::Utf8(_) => Ok(DataType::Utf8),
ScalarValue::LargeUtf8(_) => Ok(DataType::LargeUtf8),
ScalarValue::Binary(_) => Ok(DataType::Binary),
ScalarValue::LargeBinary(_) => Ok(DataType::LargeBinary),
ScalarValue::Date32(_) => Ok(DataType::Date32),
ScalarValue::Date64(_) => Ok(DataType::Date64),
ScalarValue::Time32Second(_) => Ok(DataType::Time32(TimeUnit::Second)),
ScalarValue::Time32Millisecond(_) => Ok(DataType::Time32(TimeUnit::Millisecond)),
ScalarValue::Time64Microsecond(_) => Ok(DataType::Time64(TimeUnit::Microsecond)),
ScalarValue::Time64Nanosecond(_) => Ok(DataType::Time64(TimeUnit::Nanosecond)),
ScalarValue::Null => Ok(DataType::Null),
ScalarValue::TimestampSecond(_, tz) => {
Ok(DataType::Timestamp(TimeUnit::Second, tz.to_owned()))
}
ScalarValue::TimestampMillisecond(_, tz) => {
Ok(DataType::Timestamp(TimeUnit::Millisecond, tz.to_owned()))
}
ScalarValue::TimestampMicrosecond(_, tz) => {
Ok(DataType::Timestamp(TimeUnit::Microsecond, tz.to_owned()))
}
ScalarValue::TimestampNanosecond(_, tz) => {
Ok(DataType::Timestamp(TimeUnit::Nanosecond, tz.to_owned()))
}
ScalarValue::IntervalYearMonth(..) => Ok(DataType::Interval(IntervalUnit::YearMonth)),
ScalarValue::IntervalDayTime(..) => Ok(DataType::Interval(IntervalUnit::DayTime)),
ScalarValue::IntervalMonthDayNano(..) => {
Ok(DataType::Interval(IntervalUnit::MonthDayNano))
}
ScalarValue::List(_val, field_ref) => Ok(DataType::List(field_ref.to_owned())),
ScalarValue::Struct(_, fields) => Ok(DataType::Struct(fields.to_owned())),
ScalarValue::FixedSizeBinary(size, _) => Ok(DataType::FixedSizeBinary(*size)),
}
}
}
#[pymethods]
impl DataTypeMap {
#[new]
pub fn py_new(arrow_type: PyDataType, python_type: PythonType, sql_type: SqlType) -> Self {
DataTypeMap {
arrow_type,
python_type,
sql_type,
}
}
#[staticmethod]
#[pyo3(name = "arrow")]
pub fn py_map_from_arrow_type(arrow_type: &PyDataType) -> PyResult<DataTypeMap> {
DataTypeMap::map_from_arrow_type(&arrow_type.data_type)
}
#[staticmethod]
#[pyo3(name = "sql")]
pub fn py_map_from_sql_type(sql_type: &SqlType) -> PyResult<DataTypeMap> {
match sql_type {
SqlType::ANY => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::ARRAY => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::BIGINT => Ok(DataTypeMap::new(
DataType::Int64,
PythonType::Int,
SqlType::BIGINT,
)),
SqlType::BINARY => Ok(DataTypeMap::new(
DataType::Binary,
PythonType::Bytes,
SqlType::BINARY,
)),
SqlType::BOOLEAN => Ok(DataTypeMap::new(
DataType::Boolean,
PythonType::Bool,
SqlType::BOOLEAN,
)),
SqlType::CHAR => Ok(DataTypeMap::new(
DataType::UInt8,
PythonType::Int,
SqlType::CHAR,
)),
SqlType::COLUMN_LIST => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::CURSOR => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::DATE => Ok(DataTypeMap::new(
DataType::Date64,
PythonType::Datetime,
SqlType::DATE,
)),
SqlType::DECIMAL => Ok(DataTypeMap::new(
DataType::Decimal128(1, 1),
PythonType::Float,
SqlType::DECIMAL,
)),
SqlType::DISTINCT => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::DOUBLE => Ok(DataTypeMap::new(
DataType::Decimal256(1, 1),
PythonType::Float,
SqlType::DOUBLE,
)),
SqlType::DYNAMIC_STAR => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::FLOAT => Ok(DataTypeMap::new(
DataType::Decimal128(1, 1),
PythonType::Float,
SqlType::FLOAT,
)),
SqlType::GEOMETRY => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::INTEGER => Ok(DataTypeMap::new(
DataType::Int8,
PythonType::Int,
SqlType::INTEGER,
)),
SqlType::INTERVAL => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::INTERVAL_DAY => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_DAY_HOUR => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_DAY_MINUTE => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::INTERVAL_DAY_SECOND => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::INTERVAL_HOUR => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_HOUR_MINUTE => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::INTERVAL_HOUR_SECOND => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::INTERVAL_MINUTE => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_MINUTE_SECOND => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::INTERVAL_MONTH => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_SECOND => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_YEAR => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::INTERVAL_YEAR_MONTH => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::MAP => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::MULTISET => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::NULL => Ok(DataTypeMap::new(
DataType::Null,
PythonType::None,
SqlType::NULL,
)),
SqlType::OTHER => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::REAL => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::ROW => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::SARG => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::SMALLINT => Ok(DataTypeMap::new(
DataType::Int16,
PythonType::Int,
SqlType::SMALLINT,
)),
SqlType::STRUCTURED => Err(py_datafusion_err(DataFusionError::NotImplemented(
format!("{:?}", sql_type),
))),
SqlType::SYMBOL => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::TIME => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::TIME_WITH_LOCAL_TIME_ZONE => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::TIMESTAMP => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::TIMESTAMP_WITH_LOCAL_TIME_ZONE => Err(py_datafusion_err(
DataFusionError::NotImplemented(format!("{:?}", sql_type)),
)),
SqlType::TINYINT => Ok(DataTypeMap::new(
DataType::Int8,
PythonType::Int,
SqlType::TINYINT,
)),
SqlType::UNKNOWN => Err(py_datafusion_err(DataFusionError::NotImplemented(format!(
"{:?}",
sql_type
)))),
SqlType::VARBINARY => Ok(DataTypeMap::new(
DataType::LargeBinary,
PythonType::Bytes,
SqlType::VARBINARY,
)),
SqlType::VARCHAR => Ok(DataTypeMap::new(
DataType::Utf8,
PythonType::Str,
SqlType::VARCHAR,
)),
}
}
}
/// PyO3 requires that objects passed between Rust and Python implement the trait `PyClass`
/// Since `DataType` exists in another package we cannot make that happen here so we wrap
/// `DataType` as `PyDataType` This exists solely to satisfy those constraints.
#[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
#[pyclass(name = "DataType", module = "datafusion.common")]
pub struct PyDataType {
pub data_type: DataType,
}
impl From<PyDataType> for DataType {
fn from(data_type: PyDataType) -> DataType {
data_type.data_type
}
}
impl From<DataType> for PyDataType {
fn from(data_type: DataType) -> PyDataType {
PyDataType { data_type }
}
}
/// Represents the possible Python types that can be mapped to the SQL types
#[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
#[pyclass(name = "PythonType", module = "datafusion.common")]
pub enum PythonType {
Array,
Bool,
Bytes,
Datetime,
Float,
Int,
List,
None,
Object,
Str,
}
/// Represents the types that are possible for DataFusion to parse
/// from a SQL query. Aka "SqlType" and are valid values for
/// ANSI SQL
#[allow(non_camel_case_types)]
#[allow(clippy::upper_case_acronyms)]
#[derive(Debug, Clone, PartialEq, Eq, Hash, PartialOrd, Ord)]
#[pyclass(name = "SqlType", module = "datafusion.common")]
pub enum SqlType {
ANY,
ARRAY,
BIGINT,
BINARY,
BOOLEAN,
CHAR,
COLUMN_LIST,
CURSOR,
DATE,
DECIMAL,
DISTINCT,
DOUBLE,
DYNAMIC_STAR,
FLOAT,
GEOMETRY,
INTEGER,
INTERVAL,
INTERVAL_DAY,
INTERVAL_DAY_HOUR,
INTERVAL_DAY_MINUTE,
INTERVAL_DAY_SECOND,
INTERVAL_HOUR,
INTERVAL_HOUR_MINUTE,
INTERVAL_HOUR_SECOND,
INTERVAL_MINUTE,
INTERVAL_MINUTE_SECOND,
INTERVAL_MONTH,
INTERVAL_SECOND,
INTERVAL_YEAR,
INTERVAL_YEAR_MONTH,
MAP,
MULTISET,
NULL,
OTHER,
REAL,
ROW,
SARG,
SMALLINT,
STRUCTURED,
SYMBOL,
TIME,
TIME_WITH_LOCAL_TIME_ZONE,
TIMESTAMP,
TIMESTAMP_WITH_LOCAL_TIME_ZONE,
TINYINT,
UNKNOWN,
VARBINARY,
VARCHAR,
}