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extract_date_part.rs
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121 lines (109 loc) · 4.77 KB
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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 crate::utils::array_with_timezone;
use arrow::compute::{date_part, DatePart};
use arrow::datatypes::{DataType, TimeUnit::Microsecond};
use datafusion::common::{internal_datafusion_err, ScalarValue};
use datafusion::logical_expr::{
ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility,
};
use std::{any::Any, fmt::Debug};
macro_rules! extract_date_part {
($struct_name:ident, $fn_name:expr, $date_part_variant:ident) => {
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct $struct_name {
signature: Signature,
aliases: Vec<String>,
timezone: String,
}
impl $struct_name {
pub fn new(timezone: String) -> Self {
Self {
signature: Signature::user_defined(Volatility::Immutable),
aliases: vec![],
timezone,
}
}
}
impl ScalarUDFImpl for $struct_name {
fn as_any(&self) -> &dyn Any {
self
}
fn name(&self) -> &str {
$fn_name
}
fn signature(&self) -> &Signature {
&self.signature
}
fn return_type(&self, arg_types: &[DataType]) -> datafusion::common::Result<DataType> {
Ok(match &arg_types[0] {
DataType::Dictionary(_, _) => {
DataType::Dictionary(Box::new(DataType::Int32), Box::new(DataType::Int32))
}
_ => DataType::Int32,
})
}
fn invoke_with_args(
&self,
args: ScalarFunctionArgs,
) -> datafusion::common::Result<ColumnarValue> {
let args: [ColumnarValue; 1] = args.args.try_into().map_err(|_| {
internal_datafusion_err!(concat!($fn_name, " expects exactly one argument"))
})?;
match args {
[ColumnarValue::Array(array)] => {
let array = array_with_timezone(
array,
self.timezone.clone(),
Some(&DataType::Timestamp(
Microsecond,
Some(self.timezone.clone().into()),
)),
)?;
let result = date_part(&array, DatePart::$date_part_variant)?;
Ok(ColumnarValue::Array(result))
}
[ColumnarValue::Scalar(scalar)] => {
// When Spark's ConstantFolding is disabled, literal-only expressions like
// hour can reach the native engine as scalar inputs.
// Instead of failing and requiring JVM folding, we evaluate the scalar
// natively by broadcasting it to a single-element array and then
// converting the result back to a scalar.
let array = scalar.clone().to_array_of_size(1)?;
let array = array_with_timezone(
array,
self.timezone.clone(),
Some(&DataType::Timestamp(
Microsecond,
Some(self.timezone.clone().into()),
)),
)?;
let result = date_part(&array, DatePart::$date_part_variant)?;
let scalar_result = ScalarValue::try_from_array(&result, 0)?;
Ok(ColumnarValue::Scalar(scalar_result))
}
}
}
fn aliases(&self) -> &[String] {
&self.aliases
}
}
};
}
extract_date_part!(SparkHour, "hour", Hour);
extract_date_part!(SparkMinute, "minute", Minute);
extract_date_part!(SparkSecond, "second", Second);