[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[
https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17132743#comment-17132743
]
Everett Rush commented on SPARK-27249:
--
I checked out the code and the design. Thanks for the great effort, but this
doesn't quite meet the need. The transformer contract can still be met with a
transform function that returns a Dataframe.
I would like something more like this.
{{@DeveloperApi}}
{{abstract class MultiColumnTransformer[T<: MultiColumnTransformer[T]]}}
{{ extends Transformer with HasOutputCol with Logging {}}
{{ def setOutputCol(value: String): T = set(outputCol, value).asInstanceOf[T]}}
{{ /** Returns the data type of the output column. */}}
{{ protected def outputDataType: DataType}}
{{ protected def *transformFunc*: Iterator[Row] => Iterator[Row]}}
{{ override def *transformSchema*(schema: StructType): StructType = {}}
{{ }}}
{{ def *transform*(dataset: DataFrame, targetSchema: StructType): DataFrame =
{}}
{{ val targetEncoder = RowEncoder(targetSchema)}}
{{ dataset.mapPartitions(transformFunc)(targetEncoder)}}
{{ }}}
{{ override def *transform*(dataset: Dataset[_]): DataFrame = {}}
{{ val dataframe = dataset.toDF()}}
{{ val targetSchema = transformSchema(dataframe.schema, logging = true)}}
{{ transform(dataframe, targetSchema)}}
{{ }}}
{{ override def copy(extra: ParamMap): T = defaultCopy(extra)}}
{{}}}
> Developers API for Transformers beyond UnaryTransformer
> ---
>
> Key: SPARK-27249
> URL: https://issues.apache.org/jira/browse/SPARK-27249
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Affects Versions: 3.1.0
>Reporter: Everett Rush
>Priority: Minor
> Labels: starter
> Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png
>
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> It would be nice to have a developers' API for dataset transformations that
> need more than one column from a row (ie UnaryTransformer inputs one column
> and outputs one column) or that contain objects too expensive to initialize
> repeatedly in a UDF such as a database connection.
>
> Design:
> Abstract class PartitionTransformer extends Transformer and defines the
> partition transformation function as Iterator[Row] => Iterator[Row]
> NB: This parallels the UnaryTransformer createTransformFunc method
>
> When developers subclass this transformer, they can provide their own schema
> for the output Row in which case the PartitionTransformer creates a row
> encoder and executes the transformation. Alternatively the developer can set
> output Datatype and output col name. Then the PartitionTransformer class will
> create a new schema, a row encoder, and execute the transformation.
--
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[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17129814#comment-17129814 ] Everett Rush commented on SPARK-27249: -- [~nafshartous] Hi Nick, thanks for looping me in. I just got time to look at this. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17104661#comment-17104661 ] Nick Afshartous commented on SPARK-27249: - [~enrush] Hi Everett, can you please chime in on the thread in the PR. There's a question about whether or not the need is covered by existing API's. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17103917#comment-17103917 ] Apache Spark commented on SPARK-27249: -- User 'nafshartous' has created a pull request for this issue: https://github.com/apache/spark/pull/28492 > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17103915#comment-17103915 ] Apache Spark commented on SPARK-27249: -- User 'nafshartous' has created a pull request for this issue: https://github.com/apache/spark/pull/28492 > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[
https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17086029#comment-17086029
]
Nick Afshartous commented on SPARK-27249:
-
[~enrush] Hi Everett,
Using the {{Iterator}} approach would seem to deviate from the existing
{{Transformer}} contract. More specifically, the {{transform}} function should
output a new {{DataFrame}} object. What I would propose is adding a new
function {{Transformer.compose}} to allow the composition of {{Transformers}}.
{code}
def compose(other: Transformer): Transformer = {
new Transformer {
override def transform(dataset: Dataset[_]): DataFrame = {
other.transform(this.transform(dataset));
}
...
{code}
Then one could {{compose}} {{Transformers}} which effectively would enable
multi-column transformations.
{code}
val dataFrame = ...
val transformers = List(transformer1, transformer2, transformer3)
val multiColumnTransformer = transformers.reduce((x, y) => x.compose(y))
multiColumnTransformer.transform(dataFrame)
{code}
I'd be happy to submit a PR if this meets your requirments.
> Developers API for Transformers beyond UnaryTransformer
> ---
>
> Key: SPARK-27249
> URL: https://issues.apache.org/jira/browse/SPARK-27249
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Affects Versions: 3.1.0
>Reporter: Everett Rush
>Priority: Minor
> Labels: starter
> Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png
>
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> It would be nice to have a developers' API for dataset transformations that
> need more than one column from a row (ie UnaryTransformer inputs one column
> and outputs one column) or that contain objects too expensive to initialize
> repeatedly in a UDF such as a database connection.
>
> Design:
> Abstract class PartitionTransformer extends Transformer and defines the
> partition transformation function as Iterator[Row] => Iterator[Row]
> NB: This parallels the UnaryTransformer createTransformFunc method
>
> When developers subclass this transformer, they can provide their own schema
> for the output Row in which case the PartitionTransformer creates a row
> encoder and executes the transformation. Alternatively the developer can set
> output Datatype and output col name. Then the PartitionTransformer class will
> create a new schema, a row encoder, and execute the transformation.
--
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[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17079337#comment-17079337 ] Everett Rush commented on SPARK-27249: -- Hi Nick, I think the solution could make use of the mapPartitions method, but still there should be a multicolumn transformer class. The unary transformer is very limiting. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17078751#comment-17078751 ] Nick Afshartous commented on SPARK-27249: - [~enrush] Hi Everett, checking back on my question in the last comment. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.1.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png > > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[
https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17018329#comment-17018329
]
Nick Afshartous commented on SPARK-27249:
-
[~enrush] Hi Everett,
The {{Dataset}} API has an experimental function {{mapPartitions}} for
transforming {{Dataset}} . Does this satisfy your requirements ?
https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.Dataset
> Developers API for Transformers beyond UnaryTransformer
> ---
>
> Key: SPARK-27249
> URL: https://issues.apache.org/jira/browse/SPARK-27249
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Affects Versions: 3.0.0
>Reporter: Everett Rush
>Priority: Minor
> Labels: starter
> Attachments: Screen Shot 2020-01-17 at 4.20.57 PM.png
>
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> It would be nice to have a developers' API for dataset transformations that
> need more than one column from a row (ie UnaryTransformer inputs one column
> and outputs one column) or that contain objects too expensive to initialize
> repeatedly in a UDF such as a database connection.
>
> Design:
> Abstract class PartitionTransformer extends Transformer and defines the
> partition transformation function as Iterator[Row] => Iterator[Row]
> NB: This parallels the UnaryTransformer createTransformFunc method
>
> When developers subclass this transformer, they can provide their own schema
> for the output Row in which case the PartitionTransformer creates a row
> encoder and executes the transformation. Alternatively the developer can set
> output Datatype and output col name. Then the PartitionTransformer class will
> create a new schema, a row encoder, and execute the transformation.
--
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[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17018105#comment-17018105 ] Nick Afshartous commented on SPARK-27249: - Thanks Everett, and can someone with permission assign this ticket to me. > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[
https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17012229#comment-17012229
]
Everett Rush commented on SPARK-27249:
--
[~nafshartous]
Hi Nick,
I would like to have a "MultiColumnTransformer class" in Spark. I should be
able to subclass this transformer. I would like the api to be similar to
UnaryTranformer. So I provide a transformation function and a new schema. Then
Spark handles the encoding back to a DataFrame and optimizes the computation
however it can.
class ExampleMulticolumn(override val uid: String, envVars: Map[String, String])
extends MultiColumnTransformer[ExampleMulticolumn]
with HasInputCol with DefaultParamsWritable {
def this() = this(Identifiable.randomUID("exampleMulticolumn"), Map())
// developer provides the new schema for dataframe
val newSchema: StructType
override protected def transformFunc: Iterator[Row] => Iterator[Row] = {
iter => {
// connect to database
// iterate over rows in partition
val new_iter = iter.map{
row =>
// do some computation
row
}
new_iter
}
}
override def copy(extra: ParamMap): ExampleMulticolumn = defaultCopy(extra)
}
> Developers API for Transformers beyond UnaryTransformer
> ---
>
> Key: SPARK-27249
> URL: https://issues.apache.org/jira/browse/SPARK-27249
> Project: Spark
> Issue Type: New Feature
> Components: ML
>Affects Versions: 3.0.0
>Reporter: Everett Rush
>Priority: Minor
> Labels: starter
> Original Estimate: 96h
> Remaining Estimate: 96h
>
> It would be nice to have a developers' API for dataset transformations that
> need more than one column from a row (ie UnaryTransformer inputs one column
> and outputs one column) or that contain objects too expensive to initialize
> repeatedly in a UDF such as a database connection.
>
> Design:
> Abstract class PartitionTransformer extends Transformer and defines the
> partition transformation function as Iterator[Row] => Iterator[Row]
> NB: This parallels the UnaryTransformer createTransformFunc method
>
> When developers subclass this transformer, they can provide their own schema
> for the output Row in which case the PartitionTransformer creates a row
> encoder and executes the transformation. Alternatively the developer can set
> output Datatype and output col name. Then the PartitionTransformer class will
> create a new schema, a row encoder, and execute the transformation.
--
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[jira] [Commented] (SPARK-27249) Developers API for Transformers beyond UnaryTransformer
[ https://issues.apache.org/jira/browse/SPARK-27249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=17010756#comment-17010756 ] Nick Afshartous commented on SPARK-27249: - I could try and look into this. Could someone validate that this feature is still needed ? > Developers API for Transformers beyond UnaryTransformer > --- > > Key: SPARK-27249 > URL: https://issues.apache.org/jira/browse/SPARK-27249 > Project: Spark > Issue Type: New Feature > Components: ML >Affects Versions: 3.0.0 >Reporter: Everett Rush >Priority: Minor > Labels: starter > Original Estimate: 96h > Remaining Estimate: 96h > > It would be nice to have a developers' API for dataset transformations that > need more than one column from a row (ie UnaryTransformer inputs one column > and outputs one column) or that contain objects too expensive to initialize > repeatedly in a UDF such as a database connection. > > Design: > Abstract class PartitionTransformer extends Transformer and defines the > partition transformation function as Iterator[Row] => Iterator[Row] > NB: This parallels the UnaryTransformer createTransformFunc method > > When developers subclass this transformer, they can provide their own schema > for the output Row in which case the PartitionTransformer creates a row > encoder and executes the transformation. Alternatively the developer can set > output Datatype and output col name. Then the PartitionTransformer class will > create a new schema, a row encoder, and execute the transformation. -- This message was sent by Atlassian Jira (v8.3.4#803005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
