Github user ueshin commented on a diff in the pull request:
https://github.com/apache/spark/pull/16781#discussion_r113346208
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/hive/ParquetHiveCompatibilitySuite.scala
---
@@ -397,13 +392,38 @@ class ParquetHiveCompatibilitySuite extends
ParquetCompatibilityTest with TestHi
schema = new StructType().add("display", StringType).add("ts",
TimestampType),
options = options
)
- Seq(false, true).foreach { vectorized =>
- withClue(s"vectorized = $vectorized;") {
+
+ // also write out a partitioned table, to make sure we can
access that correctly.
+ // add a column we can partition by (value doesn't particularly
matter).
+ val partitionedData = adjustedRawData.withColumn("id",
monotonicallyIncreasingId)
+ partitionedData.write.partitionBy("id")
+ .parquet(partitionedPath.getCanonicalPath)
+ // unfortunately, catalog.createTable() doesn't let us specify
partitioning, so just use
+ // a "CREATE TABLE" stmt.
+ val tblOpts = explicitTz.map { tz => raw"""TBLPROPERTIES
($key="$tz")""" }.getOrElse("")
+ spark.sql(raw"""CREATE EXTERNAL TABLE partitioned_$baseTable (
+ | display string,
+ | ts timestamp
+ |)
+ |PARTITIONED BY (id bigint)
--- End diff --
We should test for the partitioned table like `PARTITIONED BY (ts
timestamp)`?
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