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251 changes: 251 additions & 0 deletions datafusion/spark/src/function/string/elt.rs
Original file line number Diff line number Diff line change
@@ -0,0 +1,251 @@
// 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 arrow::array::{
Array, ArrayRef, AsArray, PrimitiveArray, StringArray, StringBuilder,
};
use arrow::compute::{can_cast_types, cast};
use arrow::datatypes::DataType::{Int64, Utf8};
use arrow::datatypes::{DataType, Int64Type};
use datafusion_common::cast::as_string_array;
use datafusion_common::{plan_datafusion_err, DataFusionError, Result};
use datafusion_expr::{
ColumnarValue, ScalarFunctionArgs, ScalarUDFImpl, Signature, Volatility,
};
use datafusion_functions::utils::make_scalar_function;

#[derive(Debug, PartialEq, Eq, Hash)]
pub struct SparkElt {
signature: Signature,
}

impl Default for SparkElt {
fn default() -> Self {
SparkElt::new()
}
}

impl SparkElt {
pub fn new() -> Self {
Self {
signature: Signature::user_defined(Volatility::Immutable),
}
}
}

impl ScalarUDFImpl for SparkElt {
fn as_any(&self) -> &dyn Any {
self
}

fn name(&self) -> &str {
"elt"
}

fn signature(&self) -> &Signature {
&self.signature
}

fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> {
Ok(Utf8)
}

fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
make_scalar_function(elt, vec![])(&args.args)
}

fn coerce_types(&self, arg_types: &[DataType]) -> Result<Vec<DataType>> {
let length = arg_types.len();
if length < 2 {
plan_datafusion_err!(
"ELT function expects at least 2 arguments: index, value1"
);
}

let idx_dt: &DataType = &arg_types[0];
if *idx_dt != Int64 && !can_cast_types(idx_dt, &Int64) {
return Err(DataFusionError::Plan(format!(
"ELT index must be Int64 (or castable to Int64), got {idx_dt:?}"
)));
}
let mut coerced = Vec::with_capacity(arg_types.len());
coerced.push(Int64);

for _ in 1..length {
coerced.push(Utf8);
}

Ok(coerced)
}
}

fn elt(args: &[ArrayRef]) -> Result<ArrayRef, DataFusionError> {
let n_rows = args[0].len();

let idx: &PrimitiveArray<Int64Type> =
args[0].as_primitive_opt::<Int64Type>().ok_or_else(|| {
DataFusionError::Plan(format!(
"ELT function: first argument must be Int64 (got {:?})",
args[0].data_type()
))
})?;

let num_values = args.len() - 1;
let mut cols: Vec<Arc<StringArray>> = Vec::with_capacity(num_values);
for a in args.iter().skip(1) {
let casted = cast(a, &Utf8)?;
let sa = as_string_array(&casted)?;
cols.push(Arc::new(sa.clone()));
}

let mut builder = StringBuilder::new();

for i in 0..n_rows {
if idx.is_null(i) {
builder.append_null();
continue;
}

let index = idx.value(i);

// TODO: if spark.sql.ansi.enabled is true,
// throw ArrayIndexOutOfBoundsException for invalid indices;
// if false, return NULL instead (current behavior).
if index < 1 || (index as usize) > num_values {
builder.append_null();
continue;
}

let value_idx = (index as usize) - 1;
let col = &cols[value_idx];

if col.is_null(i) {
builder.append_null();
} else {
builder.append_value(col.value(i));
}
}

Ok(Arc::new(builder.finish()) as ArrayRef)
}

#[cfg(test)]
mod tests {
use super::*;
use arrow::array::Int64Array;
use datafusion_common::Result;

use arrow::array::{ArrayRef, StringArray};
use datafusion_common::DataFusionError;
use std::sync::Arc;

fn run_elt_arrays(arrs: Vec<ArrayRef>) -> Result<Arc<StringArray>> {
let arr = elt(&arrs)?;
let string_array = arr
.as_any()
.downcast_ref::<StringArray>()
.ok_or_else(|| DataFusionError::Internal("expected Utf8".into()))?;
Ok(Arc::new(string_array.clone()))
}

#[test]
fn elt_utf8_basic() -> Result<()> {
let idx = Arc::new(Int64Array::from(vec![
Some(1),
Some(2),
Some(3),
Some(4),
Some(0),
None,
]));
let v1 = Arc::new(StringArray::from(vec![
Some("a1"),
Some("a2"),
Some("a3"),
Some("a4"),
Some("a5"),
Some("a6"),
]));
let v2 = Arc::new(StringArray::from(vec![
Some("b1"),
Some("b2"),
None,
Some("b4"),
Some("b5"),
Some("b6"),
]));
let v3 = Arc::new(StringArray::from(vec![
Some("c1"),
Some("c2"),
Some("c3"),
None,
Some("c5"),
Some("c6"),
]));

let out = run_elt_arrays(vec![idx, v1, v2, v3])?;
assert_eq!(out.len(), 6);
assert_eq!(out.value(0), "a1");
assert_eq!(out.value(1), "b2");
assert_eq!(out.value(2), "c3");
assert!(out.is_null(3));
assert!(out.is_null(4));
assert!(out.is_null(5));
Ok(())
}

#[test]
fn elt_int64_basic() -> Result<()> {
let idx = Arc::new(Int64Array::from(vec![Some(2), Some(1), Some(2)]));
let v1 = Arc::new(Int64Array::from(vec![Some(10), Some(20), Some(30)]));
let v2 = Arc::new(Int64Array::from(vec![Some(100), None, Some(300)]));

let out = run_elt_arrays(vec![idx, v1, v2])?;
assert_eq!(out.len(), 3);
assert_eq!(out.value(0), "100");
assert_eq!(out.value(1), "20");
assert_eq!(out.value(2), "300");
Ok(())
}

#[test]
fn elt_out_of_range_all_null() -> Result<()> {
let idx = Arc::new(Int64Array::from(vec![Some(5), Some(-1), Some(0)]));
let v1 = Arc::new(StringArray::from(vec![Some("x"), Some("y"), Some("z")]));
let v2 = Arc::new(StringArray::from(vec![Some("a"), Some("b"), Some("c")]));

let out = run_elt_arrays(vec![idx, v1, v2])?;
assert!(out.is_null(0));
assert!(out.is_null(1));
assert!(out.is_null(2));
Ok(())
}

#[test]
fn elt_utf8_returns_utf8() -> Result<()> {
let idx = Arc::new(Int64Array::from(vec![Some(1)]));
let v1 = Arc::new(StringArray::from(vec![Some("scala")]));
let v2 = Arc::new(StringArray::from(vec![Some("java")]));

let out = run_elt_arrays(vec![idx, v1, v2])?;
assert_eq!(out.data_type(), &Utf8);
Ok(())
}
}
8 changes: 8 additions & 0 deletions datafusion/spark/src/function/string/mod.rs
Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@

pub mod ascii;
pub mod char;
pub mod elt;
pub mod format_string;
pub mod ilike;
pub mod length;
Expand All @@ -31,6 +32,7 @@ make_udf_function!(ascii::SparkAscii, ascii);
make_udf_function!(char::CharFunc, char);
make_udf_function!(ilike::SparkILike, ilike);
make_udf_function!(length::SparkLengthFunc, length);
make_udf_function!(elt::SparkElt, elt);
make_udf_function!(like::SparkLike, like);
make_udf_function!(luhn_check::SparkLuhnCheck, luhn_check);
make_udf_function!(format_string::FormatStringFunc, format_string);
Expand All @@ -48,6 +50,11 @@ pub mod expr_fn {
"Returns the ASCII character having the binary equivalent to col. If col is larger than 256 the result is equivalent to char(col % 256).",
arg1
));
export_functions!((
elt,
"Returns the n-th input (1-indexed), e.g. returns 2nd input when n is 2. The function returns NULL if the index is 0 or exceeds the length of the array.",
select_col arg1 arg2 argn
));
export_functions!((
ilike,
"Returns true if str matches pattern (case insensitive).",
Expand Down Expand Up @@ -79,6 +86,7 @@ pub fn functions() -> Vec<Arc<ScalarUDF>> {
vec![
ascii(),
char(),
elt(),
ilike(),
length(),
like(),
Expand Down
37 changes: 33 additions & 4 deletions datafusion/sqllogictest/test_files/spark/string/elt.slt
Original file line number Diff line number Diff line change
Expand Up @@ -23,10 +23,39 @@

## Original Query: SELECT elt(1, 'scala', 'java');
## PySpark 3.5.5 Result: {'elt(1, scala, java)': 'scala', 'typeof(elt(1, scala, java))': 'string', 'typeof(1)': 'int', 'typeof(scala)': 'string', 'typeof(java)': 'string'}
#query
#SELECT elt(1::int, 'scala'::string, 'java'::string);
query T
SELECT elt(1::int, 'scala'::string, 'java'::string);
----
scala

## Original Query: SELECT elt(2, 'a', 1);
## PySpark 3.5.5 Result: {'elt(2, a, 1)': '1', 'typeof(elt(2, a, 1))': 'string', 'typeof(2)': 'int', 'typeof(a)': 'string', 'typeof(1)': 'int'}
#query
#SELECT elt(2::int, 'a'::string, 1::int);
query T
SELECT elt(2::int, 'a'::string, 1::int);
----
1

query T
SELECT elt(11::int, 10, 20)
----
NULL

query T
SELECT elt(1::int, 10, 20)
----
10

query T
SELECT elt(1::int, null, 20)
----
NULL

query T
SELECT elt(1::int, 10, null)
----
10

query T
SELECT elt(1, 10, null)
----
10