metanil commented on code in PR #55885:
URL: https://github.com/apache/spark/pull/55885#discussion_r3547814330
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sql/catalyst/src/main/java/org/apache/spark/sql/connector/catalog/functions/ReducibleFunction.java:
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@@ -60,6 +61,48 @@
@Evolving
public interface ReducibleFunction<I, O> {
+ /**
+ * Generic reducer for parameterized functions (bucket, truncate, etc.).
+ *
+ * If this function is 'reducible' on another function, return the {@link
Reducer}.
+ * <p>
+ * Each parameter is a non-complex {@link Literal} carrying both its value
and data type:
+ * array/map/struct/UDT-typed values are filtered out by Spark and not
passed here, but other
+ * scalar values (e.g. bucket numBuckets, truncate width, or a
+ * {@code CalendarInterval}) may be. {@link Literal#value()} is Spark's
internal representation
+ * (e.g. {@code UTF8String} for strings, {@code Decimal} for decimals); use
+ * {@link Literal#dataType()} to interpret it rather than assuming a JVM
type.
+ * <p>
+ * {@code thisParams} and {@code otherParams} hold each side's own literal
parameters and may have
+ * different lengths -- for example a zero-parameter transform reducing onto
a one-parameter one.
+ * Implementations must check each array's length before indexing into it.
+ * <p>
+ * Returning {@code null} means "not reducible for these parameters".
Throwing
+ * {@link UnsupportedOperationException} signals that this overload is not
implemented (Spark then
Review Comment:
@sunchao thanks, this is fixed, but it prompted a larger change worth
flagging: **the dispatch was reversed to generalized-first**, so a couple of
the premises in this comment are now inverted. See more on my top level comment.
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