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Move levenshtein, uuid, overlay to datafusion-functions
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,146 @@ | ||
| // 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; | ||
|
|
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| use arrow::array::{ArrayRef, Int32Array, Int64Array, OffsetSizeTrait}; | ||
| use arrow::datatypes::DataType; | ||
|
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| use datafusion_common::cast::as_generic_string_array; | ||
| use datafusion_common::utils::datafusion_strsim; | ||
| use datafusion_common::{exec_err, Result}; | ||
| use datafusion_expr::ColumnarValue; | ||
| use datafusion_expr::TypeSignature::*; | ||
| use datafusion_expr::{ScalarUDFImpl, Signature, Volatility}; | ||
|
|
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| use crate::string::common::{make_scalar_function, utf8_to_int_type}; | ||
|
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| #[derive(Debug)] | ||
| pub(super) struct LevenshteinFunc { | ||
| signature: Signature, | ||
| } | ||
|
|
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| impl LevenshteinFunc { | ||
| pub fn new() -> Self { | ||
| use DataType::*; | ||
| Self { | ||
| signature: Signature::one_of( | ||
| vec![Exact(vec![Utf8, Utf8]), Exact(vec![LargeUtf8, LargeUtf8])], | ||
| Volatility::Immutable, | ||
| ), | ||
| } | ||
| } | ||
| } | ||
|
|
||
| impl ScalarUDFImpl for LevenshteinFunc { | ||
| fn as_any(&self) -> &dyn Any { | ||
| self | ||
| } | ||
|
|
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| fn name(&self) -> &str { | ||
| "levenshtein" | ||
| } | ||
|
|
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| fn signature(&self) -> &Signature { | ||
| &self.signature | ||
| } | ||
|
|
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| fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> { | ||
| utf8_to_int_type(&arg_types[0], "levenshtein") | ||
| } | ||
|
|
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| fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> { | ||
| match args[0].data_type() { | ||
| DataType::Utf8 => make_scalar_function(levenshtein::<i32>, vec![])(args), | ||
| DataType::LargeUtf8 => make_scalar_function(levenshtein::<i64>, vec![])(args), | ||
| other => { | ||
| exec_err!("Unsupported data type {other:?} for function levenshtein") | ||
| } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| ///Returns the Levenshtein distance between the two given strings. | ||
| /// LEVENSHTEIN('kitten', 'sitting') = 3 | ||
| pub fn levenshtein<T: OffsetSizeTrait>(args: &[ArrayRef]) -> Result<ArrayRef> { | ||
| if args.len() != 2 { | ||
| return exec_err!( | ||
| "levenshtein function requires two arguments, got {}", | ||
| args.len() | ||
| ); | ||
| } | ||
| let str1_array = as_generic_string_array::<T>(&args[0])?; | ||
| let str2_array = as_generic_string_array::<T>(&args[1])?; | ||
| match args[0].data_type() { | ||
| DataType::Utf8 => { | ||
| let result = str1_array | ||
| .iter() | ||
| .zip(str2_array.iter()) | ||
| .map(|(string1, string2)| match (string1, string2) { | ||
| (Some(string1), Some(string2)) => { | ||
| Some(datafusion_strsim::levenshtein(string1, string2) as i32) | ||
| } | ||
| _ => None, | ||
| }) | ||
| .collect::<Int32Array>(); | ||
| Ok(Arc::new(result) as ArrayRef) | ||
| } | ||
| DataType::LargeUtf8 => { | ||
| let result = str1_array | ||
| .iter() | ||
| .zip(str2_array.iter()) | ||
| .map(|(string1, string2)| match (string1, string2) { | ||
| (Some(string1), Some(string2)) => { | ||
| Some(datafusion_strsim::levenshtein(string1, string2) as i64) | ||
| } | ||
| _ => None, | ||
| }) | ||
| .collect::<Int64Array>(); | ||
| Ok(Arc::new(result) as ArrayRef) | ||
| } | ||
| other => { | ||
| exec_err!( | ||
| "levenshtein was called with {other} datatype arguments. It requires Utf8 or LargeUtf8." | ||
| ) | ||
| } | ||
| } | ||
| } | ||
|
|
||
| #[cfg(test)] | ||
| mod tests { | ||
| use arrow::array::{Int32Array, StringArray}; | ||
|
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| use datafusion_common::cast::as_int32_array; | ||
|
|
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| use super::*; | ||
|
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| #[test] | ||
| fn to_levenshtein() -> Result<()> { | ||
| let string1_array = | ||
| Arc::new(StringArray::from(vec!["123", "abc", "xyz", "kitten"])); | ||
| let string2_array = | ||
| Arc::new(StringArray::from(vec!["321", "def", "zyx", "sitting"])); | ||
| let res = levenshtein::<i32>(&[string1_array, string2_array]).unwrap(); | ||
| let result = | ||
| as_int32_array(&res).expect("failed to initialized function levenshtein"); | ||
| let expected = Int32Array::from(vec![2, 3, 2, 3]); | ||
| assert_eq!(&expected, result); | ||
|
|
||
| Ok(()) | ||
| } | ||
| } |
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