hvanhovell commented on code in PR #45701:
URL: https://github.com/apache/spark/pull/45701#discussion_r1583392160
##########
connector/connect/common/src/main/scala/org/apache/spark/sql/connect/client/SparkResult.scala:
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@@ -198,6 +206,29 @@ private[sql] class SparkResult[T](
nonEmpty
}
+ private def processObservedMetrics(
+ metrics: java.util.List[ObservedMetrics]): Iterable[(String, Row)] = {
+ metrics.asScala.map { metric =>
+ assert(metric.getKeysCount == metric.getValuesCount)
+ var schema = new StructType()
+ val keys = mutable.ListBuffer.empty[String]
+ val values = mutable.ListBuffer.empty[Any]
+ (0 until metric.getKeysCount).map { i =>
+ val key = metric.getKeys(i)
+ val value =
LiteralValueProtoConverter.toCatalystValue(metric.getValues(i))
+ schema = schema.add(key,
LiteralValueProtoConverter.toDataType(value.getClass))
Review Comment:
There is a bit of a twist here. So, LiteralValueProtoConverter, returns a
Tuple for a nested struct. This is not really expected in a Row. We can address
this in a follow-up.
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