[Feature] Support Spark expression: days

[andygrove]

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 days function, causing queries using this function to fall back to Spark's JVM execution instead of running natively on DataFusion.

The Days expression is a v2 partition transform that converts timestamp values to the number of days since a reference epoch. This transform is used for partitioning data by day buckets, allowing efficient querying of time-series data partitioned at the daily level.

Supporting this expression would allow more Spark workloads to benefit from Comet's native acceleration.

Describe the potential solution

Spark Specification

Syntax:

-- SQL syntax (when used in partition transforms)
PARTITIONED BY (days(timestamp_column))

// DataFrame API usage
import org.apache.spark.sql.catalyst.expressions.Days
Days(child = timestampColumn)

Arguments:

Argument	Type	Description
child	Expression	The input expression that should evaluate to a timestamp or date value

Return Type: IntegerType - Returns an integer representing the number of days since the epoch.

Supported Data Types:

• TimestampType
• DateType
• Any expression that can be implicitly cast to timestamp or date

Edge Cases:

• Null input values result in null output (standard null propagation)
• Timestamps before Unix epoch (1970-01-01) result in negative day numbers
• Leap years and daylight saving time transitions are handled according to the configured timezone
• Date boundary calculations respect the session timezone configuration

Examples:

-- Creating a table partitioned by days
CREATE TABLE events (
    id BIGINT,
    event_time TIMESTAMP,
    data STRING
) PARTITIONED BY (days(event_time))

// DataFrame API usage in partition transforms
import org.apache.spark.sql.catalyst.expressions.Days

// Used internally when defining partition transforms
val dayTransform = Days(col("event_timestamp").expr)

Implementation Approach

See the Comet guide on adding new expressions 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.Days

Related:

• Hours - Partition transform for hourly buckets
• Months - Partition transform for monthly buckets
• Years - Partition transform for yearly buckets
• Bucket - Hash-based partition transform
• PartitionTransformExpression - Base class for partition transforms

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This issue was auto-generated from Spark reference documentation.

[0lai0]

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