alamb commented on code in PR #15947: URL: https://github.com/apache/datafusion/pull/15947#discussion_r2073954485
########## datafusion/spark/src/function/math/hex.rs: ########## @@ -0,0 +1,404 @@ +// 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; +use std::sync::Arc; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; +use arrow::array::{Array, StringArray}; +use arrow::datatypes::DataType; +use arrow::{ + array::{as_dictionary_array, as_largestring_array, as_string_array}, + datatypes::Int32Type, +}; +use datafusion_common::{ + cast::{as_binary_array, as_fixed_size_binary_array, as_int64_array}, + exec_err, DataFusionError, +}; +use datafusion_expr::Signature; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Volatility}; +use std::fmt::Write; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#hex> +#[derive(Debug)] +pub struct SparkHex { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkHex { + fn default() -> Self { + Self::new() + } +} + +impl SparkHex { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec![], + } + } +} + +impl ScalarUDFImpl for SparkHex { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "hex" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type( + &self, + _arg_types: &[DataType], + ) -> datafusion_common::Result<DataType> { + Ok(DataType::Utf8) + } + + fn invoke_with_args( + &self, + args: ScalarFunctionArgs, + ) -> datafusion_common::Result<ColumnarValue> { + spark_hex(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn coerce_types( + &self, + arg_types: &[DataType], + ) -> datafusion_common::Result<Vec<DataType>> { + if arg_types.len() != 1 { + return Err(invalid_arg_count_exec_err("hex", (1, 1), arg_types.len())); + } + match &arg_types[0] { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + DataType::Dictionary(key_type, value_type) => match value_type.as_ref() { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + other => { + if other.is_numeric() { + Ok(vec![DataType::Dictionary( + key_type.clone(), + Box::new(DataType::Int64), + )]) + } else { + Err(unsupported_data_type_exec_err( + "hex", + "Numeric, String, or Binary", + &arg_types[0], + )) + } + } + }, + other => { + if other.is_numeric() { + Ok(vec![DataType::Int64]) + } else { + Err(unsupported_data_type_exec_err( + "hex", + "Numeric, String, or Binary", + &arg_types[0], + )) + } + } + } + } +} + +fn hex_int64(num: i64) -> String { + format!("{:X}", num) +} + +#[inline(always)] +fn hex_encode<T: AsRef<[u8]>>(data: T, lower_case: bool) -> String { + let mut s = String::with_capacity(data.as_ref().len() * 2); + if lower_case { + for b in data.as_ref() { + // Writing to a string never errors, so we can unwrap here. + write!(&mut s, "{b:02x}").unwrap(); + } + } else { + for b in data.as_ref() { + // Writing to a string never errors, so we can unwrap here. + write!(&mut s, "{b:02X}").unwrap(); + } + } + s +} + +#[inline(always)] +fn hex_bytes<T: AsRef<[u8]>>(bytes: T) -> Result<String, std::fmt::Error> { + let hex_string = hex_encode(bytes, false); + Ok(hex_string) +} + +/// Spark-compatible `hex` function +pub fn spark_hex(args: &[ColumnarValue]) -> Result<ColumnarValue, DataFusionError> { + if args.len() != 1 { + return Err(DataFusionError::Internal( + "hex expects exactly one argument".to_string(), + )); + } + + let input = match &args[0] { + ColumnarValue::Scalar(value) => ColumnarValue::Array(value.to_array()?), + ColumnarValue::Array(_) => args[0].clone(), + }; + + match &input { + ColumnarValue::Array(array) => match array.data_type() { + DataType::Int64 => { + let array = as_int64_array(array)?; + + let hexed_array: StringArray = + array.iter().map(|v| v.map(hex_int64)).collect(); + + Ok(ColumnarValue::Array(Arc::new(hexed_array))) + } + DataType::Utf8 => { + let array = as_string_array(array); + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::LargeUtf8 => { + let array = as_largestring_array(array); + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::Binary => { + let array = as_binary_array(array)?; + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::FixedSizeBinary(_) => { + let array = as_fixed_size_binary_array(array)?; + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::Dictionary(_, value_type) => { + let dict = as_dictionary_array::<Int32Type>(&array); + + let values = match **value_type { + DataType::Int64 => as_int64_array(dict.values())? + .iter() + .map(|v| v.map(hex_int64)) + .collect::<Vec<_>>(), + DataType::Utf8 => as_string_array(dict.values()) + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?, + DataType::Binary => as_binary_array(dict.values())? + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?, + _ => exec_err!( + "hex got an unexpected argument type: {:?}", + array.data_type() + )?, + }; + + let new_values: Vec<Option<String>> = dict Review Comment: You can likely make this more efficient by avoiding the Strings here and reuse the dictionary values Something like ```rust let new_dict_array = DictionaryArray::new(dict.keys().clone(), values) ``` ########## datafusion/spark/src/function/math/hex.rs: ########## @@ -0,0 +1,404 @@ +// 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; +use std::sync::Arc; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; +use arrow::array::{Array, StringArray}; +use arrow::datatypes::DataType; +use arrow::{ + array::{as_dictionary_array, as_largestring_array, as_string_array}, + datatypes::Int32Type, +}; +use datafusion_common::{ + cast::{as_binary_array, as_fixed_size_binary_array, as_int64_array}, + exec_err, DataFusionError, +}; +use datafusion_expr::Signature; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Volatility}; +use std::fmt::Write; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#hex> +#[derive(Debug)] +pub struct SparkHex { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkHex { + fn default() -> Self { + Self::new() + } +} + +impl SparkHex { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec![], + } + } +} + +impl ScalarUDFImpl for SparkHex { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "hex" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type( + &self, + _arg_types: &[DataType], + ) -> datafusion_common::Result<DataType> { + Ok(DataType::Utf8) Review Comment: If this function outputs `Utf8View` it will likely be more performant rather than Utf8 ########## datafusion/spark/src/function/math/hex.rs: ########## @@ -0,0 +1,404 @@ +// 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; +use std::sync::Arc; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; +use arrow::array::{Array, StringArray}; +use arrow::datatypes::DataType; +use arrow::{ + array::{as_dictionary_array, as_largestring_array, as_string_array}, + datatypes::Int32Type, +}; +use datafusion_common::{ + cast::{as_binary_array, as_fixed_size_binary_array, as_int64_array}, + exec_err, DataFusionError, +}; +use datafusion_expr::Signature; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Volatility}; +use std::fmt::Write; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#hex> +#[derive(Debug)] +pub struct SparkHex { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkHex { + fn default() -> Self { + Self::new() + } +} + +impl SparkHex { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec![], + } + } +} + +impl ScalarUDFImpl for SparkHex { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "hex" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type( + &self, + _arg_types: &[DataType], + ) -> datafusion_common::Result<DataType> { + Ok(DataType::Utf8) + } + + fn invoke_with_args( + &self, + args: ScalarFunctionArgs, + ) -> datafusion_common::Result<ColumnarValue> { + spark_hex(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn coerce_types( + &self, + arg_types: &[DataType], + ) -> datafusion_common::Result<Vec<DataType>> { + if arg_types.len() != 1 { + return Err(invalid_arg_count_exec_err("hex", (1, 1), arg_types.len())); + } + match &arg_types[0] { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + DataType::Dictionary(key_type, value_type) => match value_type.as_ref() { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + other => { + if other.is_numeric() { + Ok(vec![DataType::Dictionary( + key_type.clone(), + Box::new(DataType::Int64), + )]) + } else { + Err(unsupported_data_type_exec_err( + "hex", + "Numeric, String, or Binary", + &arg_types[0], + )) + } + } + }, + other => { + if other.is_numeric() { + Ok(vec![DataType::Int64]) + } else { + Err(unsupported_data_type_exec_err( + "hex", + "Numeric, String, or Binary", + &arg_types[0], + )) + } + } + } + } +} + +fn hex_int64(num: i64) -> String { + format!("{:X}", num) +} + +#[inline(always)] +fn hex_encode<T: AsRef<[u8]>>(data: T, lower_case: bool) -> String { + let mut s = String::with_capacity(data.as_ref().len() * 2); + if lower_case { + for b in data.as_ref() { + // Writing to a string never errors, so we can unwrap here. + write!(&mut s, "{b:02x}").unwrap(); + } + } else { + for b in data.as_ref() { + // Writing to a string never errors, so we can unwrap here. + write!(&mut s, "{b:02X}").unwrap(); + } + } + s +} + +#[inline(always)] +fn hex_bytes<T: AsRef<[u8]>>(bytes: T) -> Result<String, std::fmt::Error> { + let hex_string = hex_encode(bytes, false); + Ok(hex_string) +} + +/// Spark-compatible `hex` function +pub fn spark_hex(args: &[ColumnarValue]) -> Result<ColumnarValue, DataFusionError> { + if args.len() != 1 { + return Err(DataFusionError::Internal( + "hex expects exactly one argument".to_string(), + )); + } + + let input = match &args[0] { + ColumnarValue::Scalar(value) => ColumnarValue::Array(value.to_array()?), + ColumnarValue::Array(_) => args[0].clone(), + }; + + match &input { + ColumnarValue::Array(array) => match array.data_type() { + DataType::Int64 => { + let array = as_int64_array(array)?; + + let hexed_array: StringArray = Review Comment: You can probably make this much faster by avoiding the allocation by using StringBuilder directly If you are using StringArray something like this: https://docs.rs/arrow/latest/arrow/array/type.GenericStringBuilder.html#example-incrementally-writing-strings-with-stdfmtwrite If you are using StringView I think you'll have to provide a fast path for shorter strings and use the StringView builder for longer strings ########## datafusion/spark/src/function/math/hex.rs: ########## @@ -0,0 +1,404 @@ +// 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; +use std::sync::Arc; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; +use arrow::array::{Array, StringArray}; +use arrow::datatypes::DataType; +use arrow::{ + array::{as_dictionary_array, as_largestring_array, as_string_array}, + datatypes::Int32Type, +}; +use datafusion_common::{ + cast::{as_binary_array, as_fixed_size_binary_array, as_int64_array}, + exec_err, DataFusionError, +}; +use datafusion_expr::Signature; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Volatility}; +use std::fmt::Write; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#hex> +#[derive(Debug)] +pub struct SparkHex { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkHex { + fn default() -> Self { + Self::new() + } +} + +impl SparkHex { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec![], + } + } +} + +impl ScalarUDFImpl for SparkHex { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "hex" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type( + &self, + _arg_types: &[DataType], + ) -> datafusion_common::Result<DataType> { + Ok(DataType::Utf8) + } + + fn invoke_with_args( + &self, + args: ScalarFunctionArgs, + ) -> datafusion_common::Result<ColumnarValue> { + spark_hex(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn coerce_types( + &self, + arg_types: &[DataType], + ) -> datafusion_common::Result<Vec<DataType>> { + if arg_types.len() != 1 { + return Err(invalid_arg_count_exec_err("expm1", (1, 1), arg_types.len())); + } + match &arg_types[0] { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + DataType::Dictionary(key_type, value_type) => match value_type.as_ref() { Review Comment: I think it would be simpler if you could use some of the existing signatures and then return something for `signature()`: https://github.com/apache/datafusion/blob/a39c07a2338a46fccc1111cafb5a2ffdcf6fd329/datafusion/functions/src/string/to_hex.rs#L116 That way the built in coercion logic would take over. If that doesn't work for spark functions, perhaps we can define some spark compatible signatures (as in implement `SparkSignature` that would return a https://docs.rs/datafusion/latest/datafusion/logical_expr/enum.TypeSignature.html) ########## datafusion/sqllogictest/test_files/spark/math/hex.slt: ########## @@ -0,0 +1,26 @@ +# 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. + +query T Review Comment: It would be nice to add some array level tests, which is described in https://github.com/apache/datafusion/blob/main/datafusion/sqllogictest/test_files/spark/README.md ########## datafusion/spark/src/function/math/hex.rs: ########## @@ -0,0 +1,404 @@ +// 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; +use std::sync::Arc; + +use crate::function::error_utils::{ + invalid_arg_count_exec_err, unsupported_data_type_exec_err, +}; +use arrow::array::{Array, StringArray}; +use arrow::datatypes::DataType; +use arrow::{ + array::{as_dictionary_array, as_largestring_array, as_string_array}, + datatypes::Int32Type, +}; +use datafusion_common::{ + cast::{as_binary_array, as_fixed_size_binary_array, as_int64_array}, + exec_err, DataFusionError, +}; +use datafusion_expr::Signature; +use datafusion_expr::{ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Volatility}; +use std::fmt::Write; + +/// <https://spark.apache.org/docs/latest/api/sql/index.html#hex> +#[derive(Debug)] +pub struct SparkHex { + signature: Signature, + aliases: Vec<String>, +} + +impl Default for SparkHex { + fn default() -> Self { + Self::new() + } +} + +impl SparkHex { + pub fn new() -> Self { + Self { + signature: Signature::user_defined(Volatility::Immutable), + aliases: vec![], + } + } +} + +impl ScalarUDFImpl for SparkHex { + fn as_any(&self) -> &dyn Any { + self + } + + fn name(&self) -> &str { + "hex" + } + + fn signature(&self) -> &Signature { + &self.signature + } + + fn return_type( + &self, + _arg_types: &[DataType], + ) -> datafusion_common::Result<DataType> { + Ok(DataType::Utf8) + } + + fn invoke_with_args( + &self, + args: ScalarFunctionArgs, + ) -> datafusion_common::Result<ColumnarValue> { + spark_hex(&args.args) + } + + fn aliases(&self) -> &[String] { + &self.aliases + } + + fn coerce_types( + &self, + arg_types: &[DataType], + ) -> datafusion_common::Result<Vec<DataType>> { + if arg_types.len() != 1 { + return Err(invalid_arg_count_exec_err("hex", (1, 1), arg_types.len())); + } + match &arg_types[0] { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + DataType::Dictionary(key_type, value_type) => match value_type.as_ref() { + DataType::Int64 + | DataType::Utf8 + | DataType::LargeUtf8 + | DataType::Binary + | DataType::LargeBinary => Ok(vec![arg_types[0].clone()]), + other => { + if other.is_numeric() { + Ok(vec![DataType::Dictionary( + key_type.clone(), + Box::new(DataType::Int64), + )]) + } else { + Err(unsupported_data_type_exec_err( + "hex", + "Numeric, String, or Binary", + &arg_types[0], + )) + } + } + }, + other => { + if other.is_numeric() { + Ok(vec![DataType::Int64]) + } else { + Err(unsupported_data_type_exec_err( + "hex", + "Numeric, String, or Binary", + &arg_types[0], + )) + } + } + } + } +} + +fn hex_int64(num: i64) -> String { + format!("{:X}", num) +} + +#[inline(always)] +fn hex_encode<T: AsRef<[u8]>>(data: T, lower_case: bool) -> String { + let mut s = String::with_capacity(data.as_ref().len() * 2); + if lower_case { + for b in data.as_ref() { + // Writing to a string never errors, so we can unwrap here. + write!(&mut s, "{b:02x}").unwrap(); + } + } else { + for b in data.as_ref() { + // Writing to a string never errors, so we can unwrap here. + write!(&mut s, "{b:02X}").unwrap(); + } + } + s +} + +#[inline(always)] +fn hex_bytes<T: AsRef<[u8]>>(bytes: T) -> Result<String, std::fmt::Error> { + let hex_string = hex_encode(bytes, false); + Ok(hex_string) +} + +/// Spark-compatible `hex` function +pub fn spark_hex(args: &[ColumnarValue]) -> Result<ColumnarValue, DataFusionError> { + if args.len() != 1 { + return Err(DataFusionError::Internal( + "hex expects exactly one argument".to_string(), + )); + } + + let input = match &args[0] { + ColumnarValue::Scalar(value) => ColumnarValue::Array(value.to_array()?), + ColumnarValue::Array(_) => args[0].clone(), + }; + + match &input { + ColumnarValue::Array(array) => match array.data_type() { + DataType::Int64 => { + let array = as_int64_array(array)?; + + let hexed_array: StringArray = + array.iter().map(|v| v.map(hex_int64)).collect(); + + Ok(ColumnarValue::Array(Arc::new(hexed_array))) + } + DataType::Utf8 => { + let array = as_string_array(array); + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::LargeUtf8 => { + let array = as_largestring_array(array); + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::Binary => { + let array = as_binary_array(array)?; + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::FixedSizeBinary(_) => { + let array = as_fixed_size_binary_array(array)?; + + let hexed: StringArray = array + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?; + + Ok(ColumnarValue::Array(Arc::new(hexed))) + } + DataType::Dictionary(_, value_type) => { + let dict = as_dictionary_array::<Int32Type>(&array); + + let values = match **value_type { + DataType::Int64 => as_int64_array(dict.values())? + .iter() + .map(|v| v.map(hex_int64)) + .collect::<Vec<_>>(), + DataType::Utf8 => as_string_array(dict.values()) + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?, + DataType::Binary => as_binary_array(dict.values())? + .iter() + .map(|v| v.map(hex_bytes).transpose()) + .collect::<Result<_, _>>()?, + _ => exec_err!( + "hex got an unexpected argument type: {:?}", + array.data_type() + )?, + }; + + let new_values: Vec<Option<String>> = dict Review Comment: You can likely make this more efficient by avoiding the Strings here and reuse the dictionary keys with the new values Something like ```rust let new_dict_array = DictionaryArray::new(dict.keys().clone(), values) ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: github-unsubscr...@datafusion.apache.org For additional commands, e-mail: github-h...@datafusion.apache.org
