Hi,
I'm trying to solve a task with getting data from topic. This topic keeps avro format data. I wrote next code: public static void main(String[] args) throws Exception { StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); Schema schema = ReflectData.get().getSchema(User.class); FlinkKafkaConsumer<GenericRecord> userConsumer = new FlinkKafkaConsumer<>( "test_topic", *// First* AvroDeserializationSchema.forGeneric(schema), *// Second* // ConfluentRegistryAvroDeserializationSchema.forGeneric(schema, "http://xxx.xx.xxx.xx:8081"), getConsumerProperties()); DataStream<GenericRecord> userStream = env.addSource(userConsumer).name("UserSource").uid("UserSourceUID"); userStream.print("users"); env.execute(); } So, as I think right, there are two ways to get the result: 1. AvroDeserializationSchema.forGeneric(schema) 2. ConfluentRegistryAvroDeserializationSchema.forGeneric(schema, "http://xxx.xx.xxx.xx:8081") And I use ReflectData.get().getSchema(User.class) to get schema. Please, Flink guru, tell me if I am on the right way or not. If I use First way, there is next error: java.io.EOFException at org.apache.avro.io.BinaryDecoder.ensureBounds(BinaryDecoder.java:510) at org.apache.avro.io.BinaryDecoder.readInt(BinaryDecoder.java:150) at org.apache.avro.io.ValidatingDecoder.readInt(ValidatingDecoder.java:82) If I use Second way, there is next error: Caused by: org.apache.avro.AvroTypeException: Found user_visit.Envelope, expecting cep.model.User, missing required field userId at org.apache.avro.io.ResolvingDecoder.doAction(ResolvingDecoder.java:308) at org.apache.avro.io.parsing.Parser.advance(Parser.java:86) How can I get the correct result? Sorry, if duplicated: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/DataStream-lt-GenericRecord-gt-from-kafka-topic-td42607.html Today is third day I'm working with this issue.... ((( -- Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/ |
Hi Maminspapin again, have you checked whether your topic actually contains data that matches your schema specified through cep.model.User? Best, Matthias On Tue, Mar 30, 2021 at 3:39 PM Maminspapin <[hidden email]> wrote: Hi, |
Hi, it seems as if the data is written with a confluent registry in mind, so you cannot use option 1: the kafka record is invalid avro as it contains a 5 byte prefix that identifies the schema. So the second way, is the way to go and it actually works well: it tells you that you have read with a schema that is mismatching the data. Once you use the correct schema (user_visit.Envelope), it will work. On Wed, Mar 31, 2021 at 1:46 PM Matthias Pohl <[hidden email]> wrote:
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Hi, @Arvid Heise-4, @Matthias
I'm very appreciate for your attention, guys. And sorry for my late reply. Yes, Arvid, you are right, the second way in fact works. I coppied schema from Schema Registry using it's API and created the .avsc format file. And thanks again for explaining me why the first way is not compatible. So, my code to define schema is (I don't know is it good decision...): Path path = Paths.get("path_to_schema/schema.avsc"); String content = new String(Files.readAllBytes(path)); Schema schema = new Schema.Parser().parse(content); And it really works. But, I don't understand why should I use two schemas: 1. schema I created (reader schema) 2. schema I get with SR url (writer schema) I have some expirience with KafkaStreams lib and using it there is no need to get reader schema. There is one service to communicate with schemas - it's Schema Registry. Why not to use single source to get schema in Flink? Again, the second way is correct, and I can to go farther with my program. Thanks. -- Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/ |
Hi Maminspapin, I just answered another question similarly, so let me just c&p it here: The beauty of Avro lies in having reader and writer schema and
schema compatibility, such that if your schema evolves over time (which
will happen in streaming naturally but is also very common in batch),
you can still use your application as is without modification. For
streaming, this methodology also implies that you can process elements
with different schema versions in the same run, which is mandatory for
any non-toy example. If you read into this
topic, you will realize that it doesn't make sense to read from Avro
without specifying your reader schema (except for some generic
applications, but they should be written in DataStream). If you keep in
mind that your same dataset could have different schemas, you will
notice that your ideas quickly reach some limitations (which schema to
take?). What you could do, is to write a small script to generate the
schema DDL from your current schema in your actual data if you have very
many columns and datasets. It certainly would also be an interesting
idea to pass a static Avro/Json schema to the DDL. Note that in KafkaStreams, you have the same issue. You usually generate your Java classes from some schema version, which will become your reader schema. You can and should do the same in Flink. Please read [1] for more information. On Sun, Apr 4, 2021 at 4:21 PM Maminspapin <[hidden email]> wrote: Hi, @Arvid Heise-4, @Matthias |
Arvid Heise-4, Ok, this is clear for me now. Good answer.
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