rdblue commented on code in PR #7886:
URL: https://github.com/apache/iceberg/pull/7886#discussion_r1253593455
##########
spark/v3.4/spark/src/main/java/org/apache/iceberg/spark/SparkV2Filters.java:
##########
@@ -360,10 +427,96 @@ private static boolean hasNoInFilter(Predicate predicate)
{
}
private static boolean isSupportedInPredicate(Predicate predicate) {
- if (!isRef(childAtIndex(predicate, 0))) {
+ if (!couldConvert(childAtIndex(predicate, 0))) {
return false;
} else {
return
Arrays.stream(predicate.children()).skip(1).allMatch(SparkV2Filters::isLiteral);
}
}
+
+ private static <T> UnboundTerm<Object> toTerm(T input) {
+ if (input instanceof NamedReference) {
+ return Expressions.ref(SparkUtil.toColumnName((NamedReference) input));
+
+ } else if (input instanceof UserDefinedScalarFunc) {
+ return udfToTerm((UserDefinedScalarFunc) input);
+
+ } else {
+
+ return null;
+ }
+ }
+
+ @VisibleForTesting
+ @SuppressWarnings("unchecked")
+ static UnboundTerm<Object> udfToTerm(UserDefinedScalarFunc udf) {
+ switch (udf.name().toLowerCase(Locale.ROOT)) {
+ case "years":
+ Preconditions.checkArgument(
+ udf.children().length == 1, "years function should have only one
children (column)");
+ if (isRef(udf.children()[0])) {
+ return year(SparkUtil.toColumnName((NamedReference)
udf.children()[0]));
+ }
+
+ return null;
+ case "months":
+ Preconditions.checkArgument(
+ udf.children().length == 1, "months function should have only one
children (column)");
+ if (isRef(udf.children()[0])) {
+ return month(SparkUtil.toColumnName((NamedReference)
udf.children()[0]));
+ }
+
+ return null;
+ case "days":
+ Preconditions.checkArgument(
+ udf.children().length == 1, "days function should have only one
children (column)");
+ if (isRef(udf.children()[0])) {
+ return day(SparkUtil.toColumnName((NamedReference)
udf.children()[0]));
+ }
+
+ return null;
+ case "hours":
+ Preconditions.checkArgument(
+ udf.children().length == 1, "hours function should have only one
children (colum)");
+ if (isRef(udf.children()[0])) {
+ return hour(SparkUtil.toColumnName((NamedReference)
udf.children()[0]));
+ }
+
+ return null;
+ case "bucket":
+ Preconditions.checkArgument(
+ udf.children().length == 2,
+ "bucket function should have two children (numBuckets and
column)");
+ if (isLiteral(udf.children()[0]) && isRef(udf.children()[1])) {
+ int numBuckets = (Integer) convertLiteral((Literal<?>)
udf.children()[0]);
+ return bucket(SparkUtil.toColumnName((NamedReference)
udf.children()[1]), numBuckets);
+ }
+
+ return null;
+ case "truncate":
+ Preconditions.checkArgument(
+ udf.children().length == 2,
+ "truncate function should have two children (width and column)");
+ if (isLiteral(udf.children()[0]) && isRef(udf.children()[1])) {
+ int width = (Integer) convertLiteral((Literal<?>) udf.children()[0]);
+ return truncate(SparkUtil.toColumnName((NamedReference)
udf.children()[1]), width);
+ }
+
+ return null;
+ default:
+ return null;
+ }
+ }
+
+ private static class PredicateChildren {
+ private final UnboundTerm<Object> term;
+ private final Object value;
+ private final boolean termOnLeft;
Review Comment:
That's the problem with the method. It only works for equality.
In general, I'm not a big fan of the refactoring happening in this because I
think it makes it much harder to review. Can you avoid changing as much as
possible?
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