If you use Confluent Schema Registry and want to deserialize avro messages, just add message_bytes.seek(5) to the decode function, since Confluent adds 5 extra bytes before the typical avro-formatted data. def decode(msg_value): message_bytes = io.BytesIO(msg_value) message_bytes.seek(5) decoder = BinaryDecoder(message_bytes) event_dict = reader.read(decoder) return event_dict
You can include spark-avro package, for example using –packages (adjust versions to match spark installation): bin/pyspark –packages org.apache.spark:spark-avro_2.11:2.4.0 and provide your own wrappers: from pyspark.sql.column import Column, _to_java_column def from_avro(col, jsonFormatSchema): sc = SparkContext._active_spark_context avro = sc._jvm.org.apache.spark.sql.avro f = getattr(getattr(avro, “package$”), “MODULE$”).from_avro return Column(f(_to_java_column(col), jsonFormatSchema)) def to_avro(col): sc = SparkContext._active_spark_context avro = sc._jvm.org.apache.spark.sql.avro f = … Read more
I think the main difference I can describe relates to record oriented vs. column oriented formats. Record oriented formats are what we’re all used to — text files, delimited formats like CSV, TSV. AVRO is slightly cooler than those because it can change schema over time, e.g. adding or removing columns from a record. Other … Read more
According to the explanation by Doug Cutting, Avro’s JSON encoding requires that non-null union values be tagged with their intended type. This is because unions like [“bytes”,”string”] and [“int”,”long”] are ambiguous in JSON, the first are both encoded as JSON strings, while the second are both encoded as JSON numbers. http://avro.apache.org/docs/current/spec.html#json_encoding Thus your record must … Read more
> how do I get the output of the MapReduce… Back to the basics. Since you don’t care to mention which version of Hadoop and which version of Oozie you are using, I will assume a “recent” setup (e.g. Hadoop 2.7 w/ TimelineServer and Oozie 4.2). And since you don’t mention which kind of interface … Read more
It took me a couple months of reading source code and testing things out. In a nutshell, Spark can only handle String and Binary serialization. You must manually deserialize the data. In spark, create the confluent rest service object to get the schema. Convert the schema string in the response object into an Avro schema … Read more