kbendick commented on a change in pull request #3529:
URL: https://github.com/apache/iceberg/pull/3529#discussion_r747023205
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File path:
spark/v3.2/spark/src/main/java/org/apache/iceberg/spark/SparkDistributionAndOrderingUtil.java
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@@ -71,7 +72,8 @@ public static Distribution buildRequiredDistribution(Table
table, DistributionMo
}
public static SortOrder[] convert(org.apache.iceberg.SortOrder sortOrder) {
- List<OrderField> converted = SortOrderVisitor.visit(sortOrder, new
SortOrderToSpark());
+ Map<Integer, String> quotedNameById =
SparkSchemaUtil.indexQuotedNameById(sortOrder.schema());
Review comment:
I do think it's right to be a bit concerned. I often hear about tables
that have hundred(s) of columns.
If I'm not mistaken though, we're only indexing the columns that are sorted
/ involved in the transform spec. Even when tables have hundreds of columns, do
we think it's very common to have nearly as many in the partition spec / sort
ordering?
If I have the correct, I personally don't see the need to add that
additional complexity. At the least, it could be handled in another PR.
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