kazuyukitanimura commented on code in PR #513:
URL: https://github.com/apache/datafusion-comet/pull/513#discussion_r1631556263
##########
core/src/execution/datafusion/expressions/scalar_funcs.rs:
##########
@@ -130,6 +133,10 @@ pub fn create_comet_physical_fun(
let func = Arc::new(spark_xxhash64);
make_comet_scalar_udf!("xxhash64", func, without data_type)
}
+ "chr" => {
Review Comment:
Got it, makes sense
##########
core/src/execution/datafusion/expressions/scalar_funcs/chr.rs:
##########
@@ -0,0 +1,108 @@
+// 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 std::{any::Any, sync::Arc};
+
+use arrow::{
+ array::{ArrayRef, StringArray},
+ datatypes::{
+ DataType,
+ DataType::{Int64, Utf8},
+ },
+};
+
+use datafusion::logical_expr::{ColumnarValue, ScalarUDFImpl, Signature,
Volatility};
+use datafusion_common::{cast::as_int64_array, exec_err, DataFusionError,
Result};
+
+/// chr(65) = 'A'
+
+// Compatible with Apache Spark's Chr function
+pub fn spark_chr(args: &[ColumnarValue]) -> Result<ColumnarValue,
DataFusionError> {
+ let chr_func = ChrFunc::default();
+ chr_func.invoke(args)
+}
+
+pub fn chr(args: &[ArrayRef]) -> Result<ArrayRef> {
+ let integer_array = as_int64_array(&args[0])?;
+
+ // first map is the iterator, second is for the `Option<_>`
+ let result = integer_array
+ .iter()
+ .map(|integer: Option<i64>| {
+ integer
+ .map(|integer| match core::char::from_u32(integer as u32) {
+ Some(integer) => Ok(integer.to_string()),
+ None => {
+ exec_err!("requested character too large for
encoding.")
+ }
+ })
+ .transpose()
+ })
+ .collect::<Result<StringArray>>()?;
+
+ Ok(Arc::new(result) as ArrayRef)
+}
+
+#[derive(Debug)]
+pub struct ChrFunc {
+ signature: Signature,
+}
+
+impl Default for ChrFunc {
+ fn default() -> Self {
+ Self::new()
+ }
+}
+
+impl ChrFunc {
+ pub fn new() -> Self {
+ Self {
+ signature: Signature::uniform(1, vec![Int64],
Volatility::Immutable),
+ }
+ }
+}
+
+impl ScalarUDFImpl for ChrFunc {
+ fn as_any(&self) -> &dyn Any {
+ self
+ }
+
+ fn name(&self) -> &str {
+ "chr"
+ }
+
+ fn signature(&self) -> &Signature {
+ &self.signature
+ }
+
+ fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
+ Ok(Utf8)
+ }
+
+ fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
+ let array = args[0].clone();
+ match array {
+ ColumnarValue::Array(array) => {
+ let array = chr(&[array])?;
+ Ok(ColumnarValue::Array(array))
+ }
+ _ => {
+ exec_err!("The first argument must be an array, but got:
{:?}", array)
+ }
Review Comment:
Is handling only Array correct?
It looks DataFusion is using `make_scalar_function`
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