Hi Timo, Dawid, This was very helpful - thanks! The Row type seems to only support getting fields by their index. Is there a way to get a field by its name like the Row class in Spark? Link: https://spark.apache.org/docs/2.1.0/api/java/org/apache/spark/sql/Row.html#getAs(java.lang.String)
Our use case is that we're developing a data-processing library for developers leveraging our system to refine existing datasets and produce new ones. The flow is as follows: Our library reads Avro/Parquet GenericRecord data files from a source and turns it into a Table --> users write a series of operations on this Table to create a new resulting Table--> resulting Table is then transformed persisted back to the file system as Avro GenericRecords in Avro/Parquet file. We can map the Row field names to their corresponding indexes by patching the AvroRowDeserializationSchema class, but it's the step where we handle expose the Table to our users and then try and persist which will end up in this metadata loss. We know what fields the Table must be composed of, but we just won't know which index they live in so Row#getField() isn't what quite what we need. // ah -----Original Message----- From: Timo Walther <twal...@apache.org> Sent: Friday, January 17, 2020 11:29 AM To: user@flink.apache.org Subject: Re: Table API: Joining on Tables of Complex Types Hi Andreas, if dataset.getType() returns a RowTypeInfo you can ignore this log message. The type extractor runs before the ".returns()" but with this method you override the old type. Regards, Timo On 15.01.20 15:27, Hailu, Andreas wrote: > Dawid, this approach looks promising. I'm able to flatten out my Avro > records into Rows and run simple queries atop of them. I've got a > question - when I register my Rows as a table, I see the following log > providing a warning: > > /2020-01-14 17:16:43,083 [main] INFO TypeExtractor - class > org.apache.flink.types.Row does not contain a getter for field fields/ > > /2020-01-14 17:16:43,083 [main] INFO TypeExtractor - class > org.apache.flink.types.Row does not contain a setter for field fields/ > > /2020-01-14 17:16:43,084 [main] INFO TypeExtractor - Class class > org.apache.flink.types.Row cannot be used as a POJO type because not > all fields are valid POJO fields, and must be processed as GenericType. > Please read the Flink documentation on "Data Types & Serialization" > for details of the effect on performance./ > > Will this be problematic even now that we've provided TypeInfos for > the Rows? Performance is something that I'm concerned about as I've > already introduced a new operation to transform our records to Rows. > > *// *ah** > > *From:* Hailu, Andreas [Engineering] > *Sent:* Wednesday, January 8, 2020 12:08 PM > *To:* 'Dawid Wysakowicz' <mailto:dwysakow...@apache.org>; > mailto:user@flink.apache.org > *Cc:* Richards, Adam S [Engineering] <mailto:adam.richa...@ny.email.gs.com> > *Subject:* RE: Table API: Joining on Tables of Complex Types > > Very well - I'll give this a try. Thanks, Dawid. > > *// *ah** > > *From:* Dawid Wysakowicz <dwysakow...@apache.org > <mailto:dwysakow...@apache.org>> > *Sent:* Wednesday, January 8, 2020 7:21 AM > *To:* Hailu, Andreas [Engineering] <andreas.ha...@ny.email.gs.com > <mailto:andreas.ha...@ny.email.gs.com>>; mailto:user@flink.apache.org > <mailto:user@flink.apache.org> > *Cc:* Richards, Adam S [Engineering] <adam.richa...@ny.email.gs.com > <mailto:adam.richa...@ny.email.gs.com>> > *Subject:* Re: Table API: Joining on Tables of Complex Types > > Hi Andreas, > > Converting your GenericRecords to Rows would definitely be the safest > option. You can check how its done in the > org.apache.flink.formats.avro.AvroRowDeserializationSchema. You can > reuse the logic from there to write something like: > > DataSet<GenericRecord> dataset = ... > > dataset.map( /* convert GenericRecord to Row > */).returns(AvroSchemaConverter.convertToTypeInfo(avroSchemaString)); > > Another thing you could try is to make sure that GenericRecord is seen > as an avro type by fink (flink should understand that avro type is a > complex type): > > dataset.returns(new GenericRecordAvroTypeInfo(/*schema string*/) > > than the TableEnvironment should pick it up as a structured type and > flatten it automatically when registering the Table. Bear in mind the > returns method is part of SingleInputUdfOperator so you can apply it > right after some transformation e.g. map/flatMap etc. > > Best, > > Dawid > > On 06/01/2020 18:03, Hailu, Andreas wrote: > > Hi David, thanks for getting back. > > From what you've said, I think we'll need to convert our > GenericRecord into structured types - do you have any references or > examples I can have a look at? If not, perhaps you could just show > me a basic example of flattening a complex object with accessors > into a Table of structured types. Or by structured types, did you > mean Row? > > *// *ah > > *From:* Dawid Wysakowicz <mailto:dwysakow...@apache.org> > <mailto:dwysakow...@apache.org> > *Sent:* Monday, January 6, 2020 9:32 AM > *To:* Hailu, Andreas [Engineering] <mailto:andreas.ha...@ny.email.gs.com> > <mailto:andreas.ha...@ny.email.gs.com>; mailto:user@flink.apache.org > <mailto:user@flink.apache.org> > *Cc:* Richards, Adam S [Engineering] > <mailto:adam.richa...@ny.email.gs.com> > <mailto:adam.richa...@ny.email.gs.com> > *Subject:* Re: Table API: Joining on Tables of Complex Types > > Hi Andreas, > > First of all I would highly recommend converting a non-structured > types to structured types as soon as possible as it opens more > possibilities to optimize the plan. > > Have you tried: > > Table users = > batchTableEnvironment.fromDataSet(usersDataset).select("getField(f0, > userName) as userName", "f0") > Table other = > batchTableEnvironment.fromDataSet(otherDataset).select("getField(f0, > userName) as user", "f1") > > Table result = other.join(users, "user = userName") > > You could also check how the > org.apache.flink.formats.avro.AvroRowDeserializationSchema class is > implemented which internally converts an avro record to a structured > Row. > > Hope this helps. > > Best, > > Dawid > > On 03/01/2020 23:16, Hailu, Andreas wrote: > > Hi folks, > > I'm trying to join two Tables which are composed of complex > types, Avro's GenericRecord to be exact. I have to use a custom > UDF to extract fields out of the record and I'm having some > trouble on how to do joins on them as I need to call this UDF to > read what I need. Example below: > > batchTableEnvironment.registerFunction("getField", new > GRFieldExtractor()); // GenericRecord field extractor > > Table users = batchTableEnvironment.fromDataSet(usersDataset); > // Converting from some pre-existing DataSet > > Table otherDataset = > batchTableEnvironment.fromDataSet(someOtherDataset); > > Table userNames = t.select("getField(f0, userName)"); // This is > how the UDF is used, as GenericRecord is a complex type > requiring you to invoke a get() method on the field you're > interested in. Here we get a get on field 'userName' > > I'd like to do something using the Table API similar to the > query "SELECT * from otherDataset WHERE otherDataset.userName = > users.userName". How is this done? > > Best, > > Andreas > > *The Goldman Sachs Group, Inc. 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