Re: Table API: Joining on Tables of Complex Types

Timo Walther Wed, 19 Feb 2020 04:12:39 -0800

Hi Andreas,

you are right, currently the Row type only supports accessing fields byindex. Usually, we recommend to fully work in Table API. There you canaccess structured type fields by name (`SELECT row.field.field` or`'row.get("field").get("field")`) and additional utilities such as`flatten()`.

Can't you just use the schema of the table to as a helper for bridgingthe names to indices?


Regards,
Timo


On 14.02.20 18:41, Hailu, Andreas wrote:

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

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Re: Table API: Joining on Tables of Complex Types

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