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feat: support Spark-compatible json_tuple function
#20412
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| // 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. | ||
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| use std::any::Any; | ||
| use std::sync::Arc; | ||
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| use arrow::array::{Array, ArrayRef, NullBufferBuilder, StringBuilder, StructArray}; | ||
| use arrow::datatypes::{DataType, Field, FieldRef, Fields}; | ||
| use datafusion_common::cast::as_string_array; | ||
| use datafusion_common::{Result, exec_err, internal_err}; | ||
| use datafusion_expr::{ | ||
| ColumnarValue, ReturnFieldArgs, ScalarFunctionArgs, ScalarUDFImpl, Signature, | ||
| Volatility, | ||
| }; | ||
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| /// Spark-compatible `json_tuple` expression | ||
| /// | ||
| /// <https://spark.apache.org/docs/latest/api/sql/index.html#json_tuple> | ||
| /// | ||
| /// Extracts top-level fields from a JSON string and returns them as a struct. | ||
| /// | ||
| /// `json_tuple(json_string, field1, field2, ...) -> Struct<c0: Utf8, c1: Utf8, ...>` | ||
| /// | ||
| /// Note: In Spark, `json_tuple` is a Generator that produces multiple columns directly. | ||
| /// In DataFusion, a ScalarUDF can only return one value per row, so the result is wrapped | ||
| /// in a Struct. The caller (e.g. Comet) is expected to destructure the struct fields. | ||
| /// | ||
| /// - Returns NULL for each field that is missing from the JSON object | ||
| /// - Returns NULL for all fields if the input is NULL or not valid JSON | ||
| /// - Non-string JSON values are converted to their JSON string representation | ||
| /// - JSON `null` values are returned as NULL (not the string "null") | ||
| #[derive(Debug, PartialEq, Eq, Hash)] | ||
| pub struct JsonTuple { | ||
| signature: Signature, | ||
| } | ||
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| impl Default for JsonTuple { | ||
| fn default() -> Self { | ||
| Self::new() | ||
| } | ||
| } | ||
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| impl JsonTuple { | ||
| pub fn new() -> Self { | ||
| Self { | ||
| signature: Signature::variadic(vec![DataType::Utf8], Volatility::Immutable), | ||
| } | ||
| } | ||
| } | ||
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| impl ScalarUDFImpl for JsonTuple { | ||
| fn as_any(&self) -> &dyn Any { | ||
| self | ||
| } | ||
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| fn name(&self) -> &str { | ||
| "json_tuple" | ||
| } | ||
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| fn signature(&self) -> &Signature { | ||
| &self.signature | ||
| } | ||
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| fn return_type(&self, _arg_types: &[DataType]) -> Result<DataType> { | ||
| internal_err!("return_field_from_args should be used instead") | ||
| } | ||
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| fn return_field_from_args(&self, args: ReturnFieldArgs) -> Result<FieldRef> { | ||
| if args.arg_fields.len() < 2 { | ||
| return exec_err!( | ||
| "json_tuple requires at least 2 arguments (json_string, field1), got {}", | ||
| args.arg_fields.len() | ||
| ); | ||
| } | ||
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| let num_fields = args.arg_fields.len() - 1; | ||
| let fields: Fields = (0..num_fields) | ||
| .map(|i| Field::new(format!("c{i}"), DataType::Utf8, true)) | ||
| .collect::<Vec<_>>() | ||
| .into(); | ||
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| Ok(Arc::new(Field::new( | ||
| self.name(), | ||
| DataType::Struct(fields), | ||
| true, | ||
| ))) | ||
| } | ||
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| fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> { | ||
| let ScalarFunctionArgs { | ||
| args: arg_values, | ||
| return_field, | ||
| .. | ||
| } = args; | ||
| let arrays = ColumnarValue::values_to_arrays(&arg_values)?; | ||
| let result = json_tuple_inner(&arrays, return_field.data_type())?; | ||
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| Ok(ColumnarValue::Array(result)) | ||
| } | ||
| } | ||
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| fn json_tuple_inner(args: &[ArrayRef], return_type: &DataType) -> Result<ArrayRef> { | ||
| let num_rows = args[0].len(); | ||
| let num_fields = args.len() - 1; | ||
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| let json_array = as_string_array(&args[0])?; | ||
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| let field_arrays = args[1..] | ||
| .iter() | ||
| .map(|arg| as_string_array(arg)) | ||
| .collect::<Result<Vec<_>>>()?; | ||
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| let mut builders: Vec<StringBuilder> = | ||
| (0..num_fields).map(|_| StringBuilder::new()).collect(); | ||
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| let mut null_buffer = NullBufferBuilder::new(num_rows); | ||
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| for row_idx in 0..num_rows { | ||
| if json_array.is_null(row_idx) { | ||
| for builder in &mut builders { | ||
| builder.append_null(); | ||
| } | ||
| null_buffer.append_null(); | ||
| continue; | ||
| } | ||
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| let json_str = json_array.value(row_idx); | ||
| match serde_json::from_str::<serde_json::Value>(json_str) { | ||
| Ok(serde_json::Value::Object(map)) => { | ||
| null_buffer.append_non_null(); | ||
| for (field_idx, builder) in builders.iter_mut().enumerate() { | ||
| if field_arrays[field_idx].is_null(row_idx) { | ||
| builder.append_null(); | ||
| continue; | ||
| } | ||
| let field_name = field_arrays[field_idx].value(row_idx); | ||
| match map.get(field_name) { | ||
| Some(serde_json::Value::Null) => { | ||
| builder.append_null(); | ||
| } | ||
| Some(serde_json::Value::String(s)) => { | ||
| builder.append_value(s); | ||
| } | ||
| Some(other) => { | ||
| builder.append_value(other.to_string()); | ||
| } | ||
| None => { | ||
| builder.append_null(); | ||
| } | ||
| } | ||
| } | ||
| } | ||
| _ => { | ||
| for builder in &mut builders { | ||
| builder.append_null(); | ||
| } | ||
| null_buffer.append_null(); | ||
| } | ||
| } | ||
| } | ||
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| let struct_fields = match return_type { | ||
| DataType::Struct(fields) => fields.clone(), | ||
| _ => { | ||
| return internal_err!( | ||
| "json_tuple requires a Struct return type, got {:?}", | ||
| return_type | ||
| ); | ||
| } | ||
| }; | ||
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| let arrays: Vec<ArrayRef> = builders | ||
| .into_iter() | ||
| .map(|mut builder| Arc::new(builder.finish()) as ArrayRef) | ||
| .collect(); | ||
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| let struct_array = StructArray::try_new(struct_fields, arrays, null_buffer.finish())?; | ||
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| Ok(Arc::new(struct_array)) | ||
| } | ||
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| #[cfg(test)] | ||
| mod tests { | ||
| use super::*; | ||
| use datafusion_expr::ReturnFieldArgs; | ||
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| #[test] | ||
| fn test_return_field_shape() { | ||
|
Contributor
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. We could test this in SLT using
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Added |
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| let func = JsonTuple::new(); | ||
| let fields = vec![ | ||
| Arc::new(Field::new("json", DataType::Utf8, false)), | ||
| Arc::new(Field::new("f1", DataType::Utf8, false)), | ||
| Arc::new(Field::new("f2", DataType::Utf8, false)), | ||
| ]; | ||
| let result = func | ||
| .return_field_from_args(ReturnFieldArgs { | ||
| arg_fields: &fields, | ||
| scalar_arguments: &[None, None, None], | ||
| }) | ||
| .unwrap(); | ||
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| match result.data_type() { | ||
| DataType::Struct(inner) => { | ||
| assert_eq!(inner.len(), 2); | ||
| assert_eq!(inner[0].name(), "c0"); | ||
| assert_eq!(inner[1].name(), "c1"); | ||
| assert_eq!(inner[0].data_type(), &DataType::Utf8); | ||
| assert!(inner[0].is_nullable()); | ||
| } | ||
| other => panic!("Expected Struct, got {other:?}"), | ||
| } | ||
| } | ||
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| #[test] | ||
| fn test_too_few_args() { | ||
| let func = JsonTuple::new(); | ||
| let fields = vec![Arc::new(Field::new("json", DataType::Utf8, false))]; | ||
| let result = func.return_field_from_args(ReturnFieldArgs { | ||
| arg_fields: &fields, | ||
| scalar_arguments: &[None], | ||
| }); | ||
| assert!(result.is_err()); | ||
| assert!( | ||
| result | ||
| .unwrap_err() | ||
| .to_string() | ||
| .contains("at least 2 arguments") | ||
| ); | ||
| } | ||
| } | ||
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I wonder if this means this is technically a UDTF instead of a scalar UDF? Something to potentially explore in future if we want closer compatibility with Spark (i.e. don't require comet to do the destructuring to handle this)
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Good point. In Spark,
json_tupleis indeed a Generator (UDTF) that produces multiple columns directly. Using a UDTF in DataFusion would remove the need for Comet to destructure the Struct.