zeruibao commented on code in PR #41521:
URL: https://github.com/apache/spark/pull/41521#discussion_r1224523551
##########
connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroDeserializer.scala:
##########
@@ -160,6 +160,14 @@ private[sql] class AvroDeserializer(
(logicalDataType, catalystType) match {
case (LongType, LongType) => (updater, ordinal, value) =>
updater.setLong(ordinal, value.asInstanceOf[Long])
+ case (_, LongType) => avroType.getLogicalType match {
+ case _: TimestampMicros | _: TimestampMillis |
Review Comment:
I just follow the behavior of this test suite in runtime repo
```
Seq(
"time-millis",
"time-micros",
"timestamp-micros",
"local-timestamp-millis",
"local-timestamp-micros"
).foreach { timeLogicalType =>
val timestampSchema = timestampSchemaTemplate.format(timeLogicalType)
if (DatabricksEdgeConfigs.edgeModeEnabled) {
test(s"$timeLogicalType type write support of Avro Hive serde") {
Seq(true, false).foreach { useNativeAvro =>
withSQLConf(DatabricksSQLConf.CONVERT_METASTORE_AVRO,
useNativeAvro) {
val tableName = "tab1"
withTable(tableName) {
// Creates the (non-)partitioned Avro table
versionSpark.sql(
s"""
|CREATE TABLE $tableName
|ROW FORMAT SERDE
'org.apache.hadoop.hive.serde2.avro.AvroSerDe'
|STORED AS
| INPUTFORMAT
'org.apache.hadoop.hive.ql.io.avro.AvroContainerInputFormat'
| OUTPUTFORMAT
'org.apache.hadoop.hive.ql.io.avro.AvroContainerOutputFormat'
|TBLPROPERTIES ('avro.schema.literal' =
'$timestampSchema')
""".stripMargin
)
val insertStmt = s"INSERT OVERWRITE TABLE $tableName SELECT
1000"
val result = versionSpark.sql(s"SELECT 1000").collect()
versionSpark.sql(insertStmt)
assert(versionSpark.table(tableName).collect() === result)
}
}
}
}
}
```
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