andygrove opened a new issue, #3119:
URL: https://github.com/apache/datafusion-comet/issues/3119
## 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 `make_time` function, causing
queries using this function to fall back to Spark's JVM execution instead of
running natively on DataFusion.
The `MakeTime` expression creates a time value from separate hour, minute,
and second components. It constructs a time of day by combining integer hour
and minute values with a decimal seconds value that can include microsecond
precision.
Supporting this expression would allow more Spark workloads to benefit from
Comet's native acceleration.
## Describe the potential solution
### Spark Specification
**Syntax:**
```sql
make_time(hours, minutes, seconds)
```
**Arguments:**
| Argument | Type | Description |
|----------|------|-------------|
| hours | IntegerType | The hour component (0-23) |
| minutes | IntegerType | The minute component (0-59) |
| secsAndMicros | DecimalType(16, 6) | The seconds component with
microsecond precision (0-59.999999) |
**Return Type:** Returns `TimeType` with microsecond precision
(`TimeType.MICROS_PRECISION`).
**Supported Data Types:**
- Hours: Integer types that can be cast to `IntegerType`
- Minutes: Integer types that can be cast to `IntegerType`
- Seconds: Numeric types that can be cast to `DecimalType(16, 6)`
**Edge Cases:**
- **Null handling**: If any input parameter is NULL, the result is NULL
- **Invalid time components**: Behavior depends on the underlying
`DateTimeUtils.makeTime` implementation for out-of-range values
- **Precision handling**: The `DecimalType(16, 6)` ensures microsecond
precision is maintained for the seconds component
- **Type casting**: Integer seconds values are safely cast to decimal
without precision loss due to the wide decimal type used
**Examples:**
```sql
-- Create a time for 14:30:45.123456
SELECT make_time(14, 30, 45.123456);
-- Create midnight
SELECT make_time(0, 0, 0);
-- Create a time with microsecond precision
SELECT make_time(23, 59, 59.999999);
```
```scala
// Example DataFrame API usage
import org.apache.spark.sql.functions._
df.select(expr("make_time(14, 30, 45.123456)"))
// Using column references
df.select(expr("make_time(hour_col, minute_col, second_col)"))
```
### 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.MakeTime`
**Related:**
- `MakeDate` - Creates date values from components
- `MakeTimestamp` - Creates timestamp values from date and time components
- Time extraction functions like `hour()`, `minute()`, `second()`
---
*This issue was auto-generated from Spark reference documentation.*
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