MaxGekk commented on code in PR #43451:
URL: https://github.com/apache/spark/pull/43451#discussion_r1365590894
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sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetSchemaSuite.scala:
##########
@@ -1087,6 +1087,27 @@ class ParquetSchemaSuite extends ParquetSchemaTest {
}
}
+ test("SPARK-45604: schema mismatch failure error on timestamp_nz to
array<timestamp_nz>") {
+ import testImplicits._
+
+ withTempPath { dir =>
+ val path = dir.getCanonicalPath
+ val timestamp = java.time.LocalDateTime.of(1, 2, 3, 4, 5)
+ val df1 = Seq((1, timestamp)).toDF()
+ val df2 = Seq((2, Array(timestamp))).toDF()
+ df1.write.mode("overwrite").parquet(s"$path/parquet")
+ df2.write.mode("append").parquet(s"$path/parquet")
+
+ withSQLConf(SQLConf.PARQUET_VECTORIZED_READER_ENABLED.key -> "true") {
+ val e = intercept[SparkException] {
+ spark.read.schema(df2.schema).parquet(s"$path/parquet").collect()
+ }
+ assert(e.getCause.isInstanceOf[SparkException])
+
assert(e.getCause.getCause.isInstanceOf[SchemaColumnConvertNotSupportedException])
Review Comment:
This exception should be migrated to `SparkThrowable`, and we should throw
an exception with proper error class. Please, add a follow up ticket to
https://issues.apache.org/jira/browse/SPARK-37935
##########
sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/ParquetVectorUpdaterFactory.java:
##########
@@ -109,15 +109,17 @@ public ParquetVectorUpdater getUpdater(ColumnDescriptor
descriptor, DataType spa
// For unsigned int64, it stores as plain signed int64 in Parquet
when dictionary
// fallbacks. We read them as decimal values.
return new UnsignedLongUpdater();
- } else if
(isTimestampTypeMatched(LogicalTypeAnnotation.TimeUnit.MICROS)) {
+ } else if (sparkType instanceof DatetimeType &&
Review Comment:
`DatetimeType` also includes the `DATE` type. Does this `if` handle the date
types too?
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