Skip to content

[SPARK-25718][SQL]Detect recursive reference in Avro schema and throw exception #22709

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
gengliangwang wants to merge 1 commit into from
Closed

[SPARK-25718][SQL]Detect recursive reference in Avro schema and throw exception #22709

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
26 changes: 19 additions & 7 deletions external/avro/src/main/scala/org/apache/spark/sql/avro/SchemaConverters.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,10 @@ object SchemaConverters {
* This function takes an avro schema and returns a sql schema.
*/
def toSqlType(avroSchema: Schema): SchemaType = {
toSqlTypeHelper(avroSchema, Set.empty)
}

def toSqlTypeHelper(avroSchema: Schema, existingRecordNames: Set[String]): SchemaType = {
avroSchema.getType match {
case INT => avroSchema.getLogicalType match {
case _: Date => SchemaType(DateType, nullable = false)
Expand All @@ -67,21 +71,28 @@ object SchemaConverters {
case ENUM => SchemaType(StringType, nullable = false)

case RECORD =>
if (existingRecordNames.contains(avroSchema.getFullName)) {
Copy link
Member Author

@gengliangwang gengliangwang Oct 12, 2018

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Another approach is to check the whole json string schema(avroSchema.toString) here. But it seems overkill. Avro requires the full name of record to be unique.

throw new IncompatibleSchemaException(s"""
|Found recursive reference in Avro schema, which can not be processed by Spark:
|${avroSchema.toString(true)}
""".stripMargin)
}
val newRecordNames = existingRecordNames + avroSchema.getFullName
val fields = avroSchema.getFields.asScala.map { f =>
val schemaType = toSqlType(f.schema())
val schemaType = toSqlTypeHelper(f.schema(), newRecordNames)
StructField(f.name, schemaType.dataType, schemaType.nullable)
}

SchemaType(StructType(fields), nullable = false)

case ARRAY =>
val schemaType = toSqlType(avroSchema.getElementType)
val schemaType = toSqlTypeHelper(avroSchema.getElementType, existingRecordNames)
SchemaType(
ArrayType(schemaType.dataType, containsNull = schemaType.nullable),
nullable = false)

case MAP =>
val schemaType = toSqlType(avroSchema.getValueType)
val schemaType = toSqlTypeHelper(avroSchema.getValueType, existingRecordNames)
SchemaType(
MapType(StringType, schemaType.dataType, valueContainsNull = schemaType.nullable),
nullable = false)
Expand All @@ -91,13 +102,14 @@ object SchemaConverters {
// In case of a union with null, eliminate it and make a recursive call
val remainingUnionTypes = avroSchema.getTypes.asScala.filterNot(_.getType == NULL)
if (remainingUnionTypes.size == 1) {
toSqlType(remainingUnionTypes.head).copy(nullable = true)
toSqlTypeHelper(remainingUnionTypes.head, existingRecordNames).copy(nullable = true)
} else {
toSqlType(Schema.createUnion(remainingUnionTypes.asJava)).copy(nullable = true)
toSqlTypeHelper(Schema.createUnion(remainingUnionTypes.asJava), existingRecordNames)
.copy(nullable = true)
}
} else avroSchema.getTypes.asScala.map(_.getType) match {
case Seq(t1) =>
toSqlType(avroSchema.getTypes.get(0))
toSqlTypeHelper(avroSchema.getTypes.get(0), existingRecordNames)
case Seq(t1, t2) if Set(t1, t2) == Set(INT, LONG) =>
SchemaType(LongType, nullable = false)
case Seq(t1, t2) if Set(t1, t2) == Set(FLOAT, DOUBLE) =>
Expand All @@ -107,7 +119,7 @@ object SchemaConverters {
// This is consistent with the behavior when converting between Avro and Parquet.
val fields = avroSchema.getTypes.asScala.zipWithIndex.map {
case (s, i) =>
val schemaType = toSqlType(s)
val schemaType = toSqlTypeHelper(s, existingRecordNames)
// All fields are nullable because only one of them is set at a time
StructField(s"member$i", schemaType.dataType, nullable = true)
}
Expand Down
65 changes: 65 additions & 0 deletions external/avro/src/test/scala/org/apache/spark/sql/avro/AvroSuite.scala
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1309,4 +1309,69 @@ class AvroSuite extends QueryTest with SharedSQLContext with SQLTestUtils {
checkCodec(df, path, "xz")
}
}

private def checkSchemaWithRecursiveLoop(avroSchema: String): Unit = {
val message = intercept[IncompatibleSchemaException] {
SchemaConverters.toSqlType(new Schema.Parser().parse(avroSchema))
}.getMessage

assert(message.contains("Found recursive reference in Avro schema"))
}

test("Detect recursive loop") {
checkSchemaWithRecursiveLoop("""
|{
| "type": "record",
| "name": "LongList",
| "fields" : [
| {"name": "value", "type": "long"}, // each element has a long
| {"name": "next", "type": ["null", "LongList"]} // optional next element
| ]
|}
""".stripMargin)

checkSchemaWithRecursiveLoop("""
|{
| "type": "record",
| "name": "LongList",
| "fields": [
| {
| "name": "value",
| "type": {
| "type": "record",
| "name": "foo",
| "fields": [
| {
| "name": "parent",
| "type": "LongList"
| }
| ]
| }
| }
| ]
|}
""".stripMargin)

checkSchemaWithRecursiveLoop("""
|{
| "type": "record",
| "name": "LongList",
| "fields" : [
| {"name": "value", "type": "long"},
| {"name": "array", "type": {"type": "array", "items": "LongList"}}
| ]
|}
""".stripMargin)

checkSchemaWithRecursiveLoop("""
|{
| "type": "record",
| "name": "LongList",
| "fields" : [
| {"name": "value", "type": "long"},
| {"name": "map", "type": {"type": "map", "values": "LongList"}}
| ]
|}
""".stripMargin)
}
}