xkrogen commented on code in PR #36506:
URL: https://github.com/apache/spark/pull/36506#discussion_r964068530
##########
connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala:
##########
@@ -287,14 +298,51 @@ private[sql] class AvroSerializer(
result
}
+ /**
+ * Complex unions map to struct types where field names are member0,
member1, etc.
+ * This is consistent with the behavior in [[SchemaConverters]] and when
converting between Avro
+ * and Parquet.
+ */
+ private def newComplexUnionConverter(
+ catalystStruct: StructType,
+ unionType: Schema,
+ catalystPath: Seq[String],
+ avroPath: Seq[String]): InternalRow => Any = {
+ val nonNullTypes = nonNullUnionBranches(unionType)
+ val expectedFieldNames = nonNullTypes.indices.map(i => s"member$i")
+ if (catalystStruct.fieldNames.toSeq != expectedFieldNames) {
+ throw new IncompatibleSchemaException(s"Generic Avro union at
${toFieldStr(avroPath)} " +
+ s"does not match the SQL schema at ${toFieldStr(catalystPath)}. It
expected the " +
+ s"following members ${expectedFieldNames.mkString("(", ", ", ")")} but
got " +
+ s"${catalystStruct.fieldNames.mkString("(", ", ", ")")}")
+ }
Review Comment:
We should respect `AvroOptions.positionalFieldMatching` here and only do
this check if `positionalFieldMatching = false`, WDYT?
##########
connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala:
##########
@@ -323,15 +329,30 @@ abstract class AvroSuite
avroRec.put("field2", field2)
avroRec.put("field3", new Fixed(fixedSchema, field3))
avroRec.put("field4", new EnumSymbol(enumSchema, field4))
+ avroRec.put("field5", null)
dataFileWriter.append(avroRec)
dataFileWriter.flush()
dataFileWriter.close()
- val df = spark.sqlContext.read.format("avro").load(s"$dir.avro")
+ val df = spark.sqlContext.read.format("avro").load(nativeWriterPath)
assertResult(field1)(df.selectExpr("field1.member0").first().get(0))
assertResult(field2)(df.selectExpr("field2.member1").first().get(0))
assertResult(field3)(df.selectExpr("field3.member2").first().get(0))
assertResult(field4)(df.selectExpr("field4.member3").first().get(0))
+
+ df.write.format("avro").option("avroSchema",
schema.toString).save(sparkWriterPath)
+
+ val df2 = spark.sqlContext.read.format("avro").load(nativeWriterPath)
+ assertResult(field1)(df2.selectExpr("field1.member0").first().get(0))
+ assertResult(field2)(df2.selectExpr("field2.member1").first().get(0))
+ assertResult(field3)(df2.selectExpr("field3.member2").first().get(0))
+ assertResult(field4)(df2.selectExpr("field4.member3").first().get(0))
Review Comment:
Can we confirm the value of `df2.selectExpr("field5")` as well (here and
above)?
##########
connector/avro/src/test/scala/org/apache/spark/sql/avro/AvroFunctionsSuite.scala:
##########
@@ -219,7 +219,7 @@ class AvroFunctionsSuite extends QueryTest with
SharedSparkSession {
functions.from_avro($"avro", avroTypeStruct)), df)
}
- test("to_avro with unsupported nullable Avro schema") {
+ test("to_avro with complex union Avro schema") {
val df = spark.range(10).select(struct($"id",
$"id".cast("string").as("str")).as("struct"))
for (unsupportedAvroType <- Seq("""["null", "int", "long"]""", """["int",
"long"]""")) {
Review Comment:
Yeah I agree the test as-is won't work. I was thinking more like adding
another test for the more complex case. My point was more that the
int-long/float-double case is only ... "partially complex"? And this test
claims to be testing the complex case, which (to me at least) would indicate
that we get an exploded record.
##########
connector/avro/src/main/scala/org/apache/spark/sql/avro/AvroSerializer.scala:
##########
@@ -287,14 +298,54 @@ private[sql] class AvroSerializer(
result
}
+ /**
+ * Complex unions map to struct types where field names are member0,
member1, etc.
+ * This is consistent with the behavior in [[SchemaConverters]] and when
converting between Avro
+ * and Parquet.
+ */
+ private def newComplexUnionConverter(
+ catalystStruct: StructType,
+ avroType: Schema,
+ catalystPath: Seq[String],
+ avroPath: Seq[String]): InternalRow => Any = {
+ val nonNullTypes = avroType.getTypes.asScala.filter(_.getType !=
NULL).toSeq
+ validateComplexUnionMembers(catalystStruct, nonNullTypes, catalystPath,
avroPath)
+
+ val fieldConverters = nonNullTypes.zipWithIndex.map { case (avroField, i)
=>
+ val cf = catalystStruct.fields(i)
+ newConverter(cf.dataType, resolveNullableType(avroField, nullable =
true),
+ catalystPath :+ cf.name, avroPath :+ cf.name)
Review Comment:
Yeah that's fair. Slightly less precise, but I agree it will probably be
more in-line with user expectations.
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