mbutrovich commented on code in PR #4267:
URL: https://github.com/apache/datafusion-comet/pull/4267#discussion_r3227489004
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common/src/main/scala/org/apache/comet/udf/CometUDF.scala:
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@@ -27,11 +27,16 @@ import org.apache.arrow.vector.ValueVector
*
* - Vector arguments arrive at the row count of the current batch.
* - Scalar (literal-folded) arguments arrive as length-1 vectors and must
be read at index 0.
- * - The returned vector's length must match the longest input.
+ * - The returned vector's length must match `numRows`.
*
- * Implementations must have a public no-arg constructor and must be
stateless: a single instance
- * per class is cached and shared across native worker threads for the
lifetime of the JVM.
+ * `numRows` mirrors DataFusion's `ScalarFunctionArgs.number_rows` and is the
batch row count.
+ * UDFs that always have at least one batch-length input can read length from
it and ignore
+ * `numRows`; UDFs that may be called with zero data columns (e.g. a zero-arg
ScalaUDF through the
+ * codegen dispatcher) need `numRows` to know how many rows to produce.
+ *
+ * Implementations must have a public no-arg constructor and should be
stateless: instances are
+ * cached per executor thread for the lifetime of the JVM.
*/
trait CometUDF {
- def evaluate(inputs: Array[ValueVector]): ValueVector
+ def evaluate(inputs: Array[ValueVector], numRows: Int): ValueVector
Review Comment:
yes, I am peeling off this and the taskcontext change to its own PRs.
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