Re: Table API: Joining on Tables of Complex Types
Hi Andreas,
you are right, currently the Row type only supports accessing fields by
index. Usually, we recommend to fully work in Table API. There you can
access 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 bridging
the 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
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 mailto:dwysakow...@apache.org>>
*Sent:* Wednesday, January 8, 2020 7:21 AM
*To:* Hailu, Andreas [Engineering] 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>>
*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 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
RE: Table API: Joining on Tables of Complex Types
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 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 <mailto:dwysakow...@apache.org>> > *Sent:* Wednesday, January 8, 2020 7:21 AM > *To:* Hailu, Andreas [Engineering] <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>> > *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 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 >
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' ; user@flink.apache.org
*Cc:* Richards, Adam S [Engineering]
*Subject:* RE: Table API: Joining on Tables of Complex Types
Very well – I’ll give this a try. Thanks, Dawid.
*// *ah**
*From:* Dawid Wysakowicz <mailto:dwysakow...@apache.org>>
*Sent:* Wednesday, January 8, 2020 7:21 AM
*To:* Hailu, Andreas [Engineering] <mailto:andreas.ha...@ny.email.gs.com>>; user@flink.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
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 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>
*Sent:* Monday, January 6, 2020 9:32 AM
*To:* Hailu, Andreas [Engineering]
<mailto:andreas.ha...@ny.email.gs.com>; user@flink.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
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 b
RE: Table API: Joining on Tables of Complex Types
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' ; user@flink.apache.org
Cc: Richards, Adam S [Engineering]
Subject: RE: Table API: Joining on Tables of Complex Types
Very well - I'll give this a try. Thanks, Dawid.
// ah
From: Dawid Wysakowicz mailto:dwysakow...@apache.org>>
Sent: Wednesday, January 8, 2020 7:21 AM
To: Hailu, Andreas [Engineering]
mailto:andreas.ha...@ny.email.gs.com>>;
user@flink.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
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 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>
Sent: Monday, January 6, 2020 9:32 AM
To: Hailu, Andreas [Engineering]
<mailto:andreas.ha...@ny.email.gs.com>;
user@flink.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
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 f
RE: Table API: Joining on Tables of Complex Types
Very well - I'll give this a try. Thanks, Dawid.
// ah
From: Dawid Wysakowicz
Sent: Wednesday, January 8, 2020 7:21 AM
To: Hailu, Andreas [Engineering] ;
user@flink.apache.org
Cc: Richards, Adam S [Engineering]
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 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>
Sent: Monday, January 6, 2020 9:32 AM
To: Hailu, Andreas [Engineering]
<mailto:andreas.ha...@ny.email.gs.com>;
user@flink.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
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
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 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
> *Sent:* Monday, January 6, 2020 9:32 AM
> *To:* Hailu, Andreas [Engineering] ;
> user@flink.apache.org
> *Cc:* Richards, Adam S [Engineering]
> *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. All rights reserved*.
>
> See http://www.gs.com/disclaimer/global_email for important risk
> disclosures, conflicts of interest and other terms and conditions
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> in it. This message may contain confidential or privileged
> information. If you are not the intended recipient, please advise
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RE: Table API: Joining on Tables of Complex Types
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
Sent: Monday, January 6, 2020 9:32 AM
To: Hailu, Andreas [Engineering] ;
user@flink.apache.org
Cc: Richards, Adam S [Engineering]
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. All rights reserved.
See http://www.gs.com/disclaimer/global_email for important risk disclosures,
conflicts of interest and other terms and conditions relating to this e-mail
and your reliance on information contained in it. This message may contain
confidential or privileged information. If you are not the intended recipient,
please advise us immediately and delete this message. See
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Your Personal Data: We may collect and process information about you that may
be subject to data protection laws. For more information about how we use and
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www.gs.com/privacy-notices<http://www.gs.com/privacy-notices>
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. All rights reserved*.
>
> See http://www.gs.com/disclaimer/global_email for important risk
> disclosures, conflicts of interest and other terms and conditions
> relating to this e-mail and your reliance on information contained in
> it. This message may contain confidential or privileged information.
> If you are not the intended recipient, please advise us immediately
> and delete this message. See http://www.gs.com/disclaimer/email for
> further information on confidentiality and the risks of non-secure
> electronic communication. If you cannot access these links, please
> notify us by reply message and we will send the contents to you.
>
>
>
>
>
>
> Your Personal Data: We may collect and process information about you
> that may be subject to data protection laws. For more information
> about how we use and disclose your personal data, how we protect your
> information, our legal basis to use your information, your rights and
> who you can contact, please refer to: www.gs.com/privacy-notices
>
signature.asc
Description: OpenPGP digital signature
Table API: Joining on Tables of Complex Types
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. All rights reserved.
See http://www.gs.com/disclaimer/global_email for important risk disclosures,
conflicts of interest and other terms and conditions relating to this e-mail
and your reliance on information contained in it. This message may contain
confidential or privileged information. If you are not the intended recipient,
please advise us immediately and delete this message. See
http://www.gs.com/disclaimer/email for further information on confidentiality
and the risks of non-secure electronic communication. If you cannot access
these links, please notify us by reply message and we will send the contents to
you.
Your Personal Data: We may collect and process information about you that may
be subject to data protection laws. For more information about how we use and
disclose your personal data, how we protect your information, our legal basis
to use your information, your rights and who you can contact, please refer to:
www.gs.com/privacy-notices
