datafusion_functions/string/
levenshtein.rsuse std::any::Any;
use std::sync::{Arc, OnceLock};
use arrow::array::{ArrayRef, Int32Array, Int64Array, OffsetSizeTrait};
use arrow::datatypes::DataType;
use crate::utils::{make_scalar_function, utf8_to_int_type};
use datafusion_common::cast::{as_generic_string_array, as_string_view_array};
use datafusion_common::utils::datafusion_strsim;
use datafusion_common::{exec_err, Result};
use datafusion_expr::scalar_doc_sections::DOC_SECTION_STRING;
use datafusion_expr::{ColumnarValue, Documentation};
use datafusion_expr::{ScalarUDFImpl, Signature, Volatility};
#[derive(Debug)]
pub struct LevenshteinFunc {
signature: Signature,
}
impl Default for LevenshteinFunc {
fn default() -> Self {
Self::new()
}
}
impl LevenshteinFunc {
pub fn new() -> Self {
Self {
signature: Signature::string(2, Volatility::Immutable),
}
}
}
impl ScalarUDFImpl for LevenshteinFunc {
fn as_any(&self) -> &dyn Any {
self
}
fn name(&self) -> &str {
"levenshtein"
}
fn signature(&self) -> &Signature {
&self.signature
}
fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
utf8_to_int_type(&arg_types[0], "levenshtein")
}
fn invoke(&self, args: &[ColumnarValue]) -> Result<ColumnarValue> {
match args[0].data_type() {
DataType::Utf8View | 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")
}
}
}
fn documentation(&self) -> Option<&Documentation> {
Some(get_levenshtein_doc())
}
}
static DOCUMENTATION: OnceLock<Documentation> = OnceLock::new();
fn get_levenshtein_doc() -> &'static Documentation {
DOCUMENTATION.get_or_init(|| {
Documentation::builder()
.with_doc_section(DOC_SECTION_STRING)
.with_description("Returns the [`Levenshtein distance`](https://en.wikipedia.org/wiki/Levenshtein_distance) between the two given strings.")
.with_syntax_example("levenshtein(str1, str2)")
.with_sql_example(r#"```sql
> select levenshtein('kitten', 'sitting');
+---------------------------------------------+
| levenshtein(Utf8("kitten"),Utf8("sitting")) |
+---------------------------------------------+
| 3 |
+---------------------------------------------+
```"#)
.with_argument("str1", "String expression to compute Levenshtein distance with str2.")
.with_argument("str2", "String expression to compute Levenshtein distance with str1.")
.build()
.unwrap()
})
}
pub fn levenshtein<T: OffsetSizeTrait>(args: &[ArrayRef]) -> Result<ArrayRef> {
if args.len() != 2 {
return exec_err!(
"levenshtein function requires two arguments, got {}",
args.len()
);
}
match args[0].data_type() {
DataType::Utf8View => {
let str1_array = as_string_view_array(&args[0])?;
let str2_array = as_string_view_array(&args[1])?;
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::Utf8 => {
let str1_array = as_generic_string_array::<T>(&args[0])?;
let str2_array = as_generic_string_array::<T>(&args[1])?;
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 str1_array = as_generic_string_array::<T>(&args[0])?;
let str2_array = as_generic_string_array::<T>(&args[1])?;
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 Utf8View, Utf8 or LargeUtf8."
)
}
}
}
#[cfg(test)]
mod tests {
use arrow::array::StringArray;
use datafusion_common::cast::as_int32_array;
use super::*;
#[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(())
}
}