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https://issues.apache.org/jira/browse/FLINK-8828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16384761#comment-16384761
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Jelmer Kuperus commented on FLINK-8828:
---------------------------------------
You are right. Infact the fact that there is already a method defined called
collect() seems to be biting me :(. TableSourceITCase is not compiling because
the implicit conversions defined in
[org.apache.flink.table.api.scala._|https://github.com/apache/flink/blob/master/flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/scala/package.scala]
now think the no args collect method is ambiguous.
And there does not seem to be a good way to make this class compile this
without renaming method I introduced to something else.
The problem is that scala developers expect this method to be called collect..
As an aside I think using implicit conversions in the way
[org.apache.flink.table.api.scala._|https://github.com/apache/flink/blob/master/flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/scala/package.scala]
does is frowned upon a little in the scala world. A slightly more explicit
that will give less unexpected surprises like this one might look something like
{noformat}
implicit class RichTable[T](table: Table) {
def asRowDataSet: DataSet[Row] = {
val tableEnv = table.tableEnv.asInstanceOf[ScalaBatchTableEnv]
tableEnv.toDataSet[Row](table)
}
def asRowDataStream: DataStream[Row] = {
val tableEnv = table.tableEnv.asInstanceOf[ScalaStreamTableEnv]
tableEnv.toAppendStream[Row](table)
}
}{noformat}
Then this code
{noformat}
val results = tEnv.scan("T")
.select('name, 'rtime, 'val)
.collect(){noformat}
Could be rewritten as
{noformat}
val results = tEnv.scan("T")
.select('name, 'rtime, 'val)
.asRowDataSet
.collect(){noformat}
> Add collect method to DataStream / DataSet scala api
> ----------------------------------------------------
>
> Key: FLINK-8828
> URL: https://issues.apache.org/jira/browse/FLINK-8828
> Project: Flink
> Issue Type: Improvement
> Components: Core, DataSet API, DataStream API, Scala API
> Affects Versions: 1.4.0
> Reporter: Jelmer Kuperus
> Priority: Major
>
> A collect function is a method that takes a Partial Function as its parameter
> and applies it to all the elements in the collection to create a new
> collection which satisfies the Partial Function.
> It can be found on all [core scala collection
> classes|http://www.scala-lang.org/api/2.9.2/scala/collection/TraversableLike.html]
> as well as on spark's [rdd
> interface|https://spark.apache.org/docs/2.2.0/api/scala/index.html#org.apache.spark.rdd.RDD]
> To understand its utility imagine the following scenario :
> Given a DataStream that produces events of type _Purchase_ and _View_
> Transform this stream into a stream of purchase amounts over 1000 euros.
> Currently an implementation might look like
> {noformat}
> val x = dataStream
> .filter(_.isInstanceOf[Purchase])
> .map(_.asInstanceOf[Purchase])
> .filter(_.amount > 1000)
> .map(_.amount){noformat}
> Or alternatively you could do this
> {noformat}
> dataStream.flatMap(_ match {
> case p: Purchase if p.amount > 1000 => Some(p.amount)
> case _ => None
> }){noformat}
> But with collect implemented it could look like
> {noformat}
> dataStream.collect {
> case p: Purchase if p.amount > 1000 => p.amount
> }{noformat}
>
> Which is a lot nicer to both read and write
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