MaxGekk commented on a change in pull request #31216:
URL: https://github.com/apache/spark/pull/31216#discussion_r559688491
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File path:
sql/core/src/test/scala/org/apache/spark/sql/execution/command/v2/AlterTableAddPartitionSuite.scala
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@@ -44,4 +44,13 @@ class AlterTableAddPartitionSuite
checkPartitions(t, Map("p1" -> ""))
}
}
+
+ test("SPARK-34143: add a partition to fully partitioned table") {
+ withNamespaceAndTable("ns", "tbl") { t =>
+ sql(s"CREATE TABLE $t (p0 INT, p1 STRING) $defaultUsing PARTITIONED BY
(p0, p1)")
Review comment:
I could imagine the case when fully partitioned table could speed up
table creation. Let's image we have heavy data partitioned by some meta-data
columns like date, id and etc. We need a table to analyse only meta-data, and
don't want to spend time on parsing/schema inferring/reading data columns. So,
we could quickly create a table fully partitioned only by meta-data columns,
and don't waste time on data columns.
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