andygrove opened a new issue, #3153:
URL: https://github.com/apache/datafusion-comet/issues/3153
## What is the problem the feature request solves?
> **Note:** This issue was generated with AI assistance. The specification
details have been extracted from Spark documentation and may need verification.
Comet does not currently support the Spark `length_of_json_array` function,
causing queries using this function to fall back to Spark's JVM execution
instead of running natively on DataFusion.
The `LengthOfJsonArray` expression returns the number of elements in a JSON
array string. It is implemented as a runtime-replaceable expression that
delegates to the JsonExpressionUtils utility class for actual JSON parsing and
length calculation.
Supporting this expression would allow more Spark workloads to benefit from
Comet's native acceleration.
## Describe the potential solution
### Spark Specification
**Syntax:**
```sql
json_array_length(json_string)
```
```scala
// DataFrame API
import org.apache.spark.sql.functions.expr
df.select(expr("json_array_length(json_column)"))
```
**Arguments:**
| Argument | Type | Description |
|----------|------|-------------|
| json_string | String (with collation support) | A JSON string representing
an array whose length is to be calculated |
**Return Type:** Returns `IntegerType` representing the number of elements
in the JSON array.
**Supported Data Types:**
- String types with collation support (specifically supports trim collation)
- Input must be a valid JSON array string format
**Edge Cases:**
- Returns `NULL` when input is `NULL` (expression is nullable)
- Behavior with malformed JSON depends on JsonExpressionUtils implementation
- Empty JSON array `[]` should return `0`
- Non-array JSON values (objects, primitives) handling depends on underlying
utility
- Invalid JSON strings may return `NULL` or throw exceptions based on
implementation
**Examples:**
```sql
-- Basic usage
SELECT json_array_length('[1, 2, 3, 4]') AS length;
-- Returns: 4
-- Empty array
SELECT json_array_length('[]') AS length;
-- Returns: 0
-- NULL input
SELECT json_array_length(NULL) AS length;
-- Returns: NULL
-- With table data
SELECT id, json_array_length(json_data) AS array_size
FROM table_with_json
WHERE json_data IS NOT NULL;
```
```scala
// DataFrame API usage
import org.apache.spark.sql.functions._
val df = spark.createDataFrame(Seq(
("1", "[1, 2, 3]"),
("2", "[]"),
("3", null)
)).toDF("id", "json_array")
df.select(
col("id"),
expr("json_array_length(json_array)").as("length")
).show()
```
### Implementation Approach
See the [Comet guide on adding new
expressions](https://datafusion.apache.org/comet/contributor-guide/adding_a_new_expression.html)
for detailed instructions.
1. **Scala Serde**: Add expression handler in
`spark/src/main/scala/org/apache/comet/serde/`
2. **Register**: Add to appropriate map in `QueryPlanSerde.scala`
3. **Protobuf**: Add message type in `native/proto/src/proto/expr.proto` if
needed
4. **Rust**: Implement in `native/spark-expr/src/` (check if DataFusion has
built-in support first)
## Additional context
**Difficulty:** Medium
**Spark Expression Class:**
`org.apache.spark.sql.catalyst.expressions.LengthOfJsonArray`
**Related:**
- Other JSON functions in the `json_funcs` group
- `JsonExpressionUtils` utility class
- `StaticInvoke` expression for runtime delegation
- JSON parsing and extraction functions
---
*This issue was auto-generated from Spark reference documentation.*
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