aokolnychyi commented on a change in pull request #35374:
URL: https://github.com/apache/spark/pull/35374#discussion_r801073133
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File path:
sql/core/src/test/scala/org/apache/spark/sql/connector/WriteDistributionAndOrderingSuite.scala
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@@ -712,15 +831,84 @@ class WriteDistributionAndOrderingSuite
}
}
+ private def checkMicroBatchWriteRequirements(
+ tableDistribution: Distribution,
+ tableOrdering: Array[SortOrder],
+ tableNumPartitions: Option[Int],
+ expectedWritePartitioning: physical.Partitioning,
+ expectedWriteOrdering: Seq[catalyst.expressions.SortOrder],
+ writeTransform: DataFrame => DataFrame = df => df,
+ outputMode: String = "append",
+ expectAnalysisException: Boolean = false): Unit = {
+
+ catalog.createTable(ident, schema, Array.empty, emptyProps,
tableDistribution,
+ tableOrdering, tableNumPartitions)
+
+ withTempDir { checkpointDir =>
+ val inputData = MemoryStream[(Long, String)]
+ val inputDF = inputData.toDF().toDF("id", "data")
+
+ val queryDF = outputMode match {
+ case "append" =>
+ inputDF
+ case "complete" =>
Review comment:
Now I remember why I did not add `update` initially. It is because
`InMemoryTable` does not support it. Looks like it will be quite some work to
make that happen as `InMemoryTable` has no notion of a key or something.
Any thoughts on the easiest way to test the update mode, @HeartSaVioR?
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