I am trying to decode a message coming as part of avro message in my spark2.2 streaming. I have a schema defined for this json and whenever the json message comes with out honoring the json schema, my JsonDecoder fails with below error
Caused by: org.apache.avro.AvroTypeException: Expected field name not found: "some_field"
at org.apache.avro.io.JsonDecoder.doAction(JsonDecoder.java:477)
at org.apache.avro.io.parsing.Parser.advance(Parser.java:88)
at org.apache.avro.io.JsonDecoder.advance(JsonDecoder.java:139)
at org.apache.avro.io.JsonDecoder.readString(JsonDecoder.java:219)
at org.apache.avro.io.JsonDecoder.readString(JsonDecoder.java:214)
at org.apache.avro.io.ResolvingDecoder.readString(ResolvingDecoder.java:201)
at org.apache.avro.generic.GenericDatumReader.readString(GenericDatumReader.java:422)
at org.apache.avro.generic.GenericDatumReader.readString(GenericDatumReader.java:414)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:181)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153)
at org.apache.avro.generic.GenericDatumReader.readField(GenericDatumReader.java:232)
at org.apache.avro.generic.GenericDatumReader.readRecord(GenericDatumReader.java:222)
at org.apache.avro.generic.GenericDatumReader.readWithoutConversion(GenericDatumReader.java:175)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:153)
at org.apache.avro.generic.GenericDatumReader.read(GenericDatumReader.java:145)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:315)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:258)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:256)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1375)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
I know jackson decoding has a way to ignore the extra as well as absent fields. Is there a way in org.apache.avro.io.JsonDecoder for the same behaviour?
