Zhenhao Li created SPARK-38091: ---------------------------------- Summary: AvroSerializer can cause java.lang.ClassCastException at run time Key: SPARK-38091 URL: https://issues.apache.org/jira/browse/SPARK-38091 Project: Spark Issue Type: Bug Components: SQL Affects Versions: 3.2.1, 3.2.0, 3.1.2, 3.1.1, 3.1.0, 3.0.3, 3.0.2, 3.0.1, 3.0.0 Reporter: Zhenhao Li
`AvroSerializer`'s implementation, at least in `newConverter`, was not 100% based on the `InternalRow` and `SpecializedGetters` interface. It assumes many implementation details of the interface. For example, in ```scala case (TimestampType, LONG) => avroType.getLogicalType match { // For backward compatibility, if the Avro type is Long and it is not logical type // (the `null` case), output the timestamp value as with millisecond precision. case null | _: TimestampMillis => (getter, ordinal) => DateTimeUtils.microsToMillis(timestampRebaseFunc(getter.getLong(ordinal))) case _: TimestampMicros => (getter, ordinal) => timestampRebaseFunc(getter.getLong(ordinal)) case other => throw new IncompatibleSchemaException(errorPrefix + s"SQL type ${TimestampType.sql} cannot be converted to Avro logical type $other") } ``` it assumes the `InternalRow` instance encodes `TimestampType` as `java.lang.Long`. That's true for `Unsaferow` but not for `GenericInternalRow`. Hence the above code will end up with runtime exceptions when used on an instance of `GenericInternalRow`, which is the case for Python UDF. I didn't get time to dig deeper than that. I got the impression that Spark's optimizer(s) will turn a row into a `UnsafeRow` and Python UDF doesn't involve the optimizer(s) and hence each row is a `GenericInternalRow`. It would be great if someone can correct me or offer a better explanation. To reproduce the issue, `git checkout master` and `git cherry-pick --no-commit` [this-commit|https://github.com/Zhen-hao/spark/commit/1ffe8e8f35273b2f3529f6c2d004822f480e4c88] and run the test `org.apache.spark.sql.avro.AvroSerdeSuite`. You will see runtime exceptions like the following one ``` - Serialize DecimalType to Avro BYTES with logical type decimal *** FAILED *** java.lang.ClassCastException: class java.math.BigDecimal cannot be cast to class org.apache.spark.sql.types.Decimal (java.math.BigDecimal is in module java.base of loader 'bootstrap'; org.apache.spark.sql.types.Decimal is in unnamed module of loader 'app') at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getDecimal(rows.scala:45) at org.apache.spark.sql.catalyst.expressions.BaseGenericInternalRow.getDecimal$(rows.scala:45) at org.apache.spark.sql.catalyst.expressions.GenericInternalRow.getDecimal(rows.scala:195) at org.apache.spark.sql.avro.AvroSerializer.$anonfun$newConverter$10(AvroSerializer.scala:136) at org.apache.spark.sql.avro.AvroSerializer.$anonfun$newConverter$10$adapted(AvroSerializer.scala:135) at org.apache.spark.sql.avro.AvroSerializer.$anonfun$newStructConverter$2(AvroSerializer.scala:283) at org.apache.spark.sql.avro.AvroSerializer.serialize(AvroSerializer.scala:60) at org.apache.spark.sql.avro.AvroSerdeSuite.$anonfun$new$5(AvroSerdeSuite.scala:82) at org.apache.spark.sql.avro.AvroSerdeSuite.$anonfun$new$5$adapted(AvroSerdeSuite.scala:67) at org.apache.spark.sql.avro.AvroSerdeSuite.$anonfun$withFieldMatchType$2(AvroSerdeSuite.scala:217) ``` -- This message was sent by Atlassian Jira (v8.20.1#820001) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org