kazuyukitanimura commented on code in PR #1470:
URL: https://github.com/apache/datafusion-comet/pull/1470#discussion_r1978834551
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spark/src/main/scala/org/apache/comet/serde/QueryPlanSerde.scala:
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@@ -1586,6 +1586,18 @@ object QueryPlanSerde extends Logging with
ShimQueryPlanSerde with CometExprShim
case StringTrimBoth(srcStr, trimStr, _) =>
trim(expr, srcStr, trimStr, inputs, binding, "btrim")
+ case StringLPad(srcStr, size, chars) =>
+ val arg0 = exprToProtoInternal(srcStr, inputs, binding)
+ val arg1 = exprToProtoInternal(Cast(size, LongType), inputs, binding)
+ val arg2 = exprToProtoInternal(chars, inputs, binding)
+ scalarExprToProto("lpad", arg0, arg1, arg2)
+
+ case StringRPad(srcStr, size, chars) =>
+ val arg0 = exprToProtoInternal(srcStr, inputs, binding)
+ val arg1 = exprToProtoInternal(Cast(size, LongType), inputs, binding)
+ val arg2 = exprToProtoInternal(chars, inputs, binding)
+ scalarExprToProto("rpad", arg0, arg1, arg2)
Review Comment:
https://github.com/apache/datafusion-comet/blob/main/native/spark-expr/src/static_invoke/char_varchar_utils/read_side_padding.rs#L60
I remember DataFusion uses graphemes vs Spark uses chars. Perhaps best to
check postgres if it uses chars. If so, we may fix in DataFusion?
chars has better performance as well
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