Will you elaborate on your use case? It would help to find out where Flink shines. IMO, its a great project, but needs more differentiation from Spark.

On Thu, Apr 23, 2015 at 7:25 AM, LINZ, Arnaud <ALINZ@bouyguestelecom.fr> wrote:



After a quite successful benchmark yesterday (Flink being about twice faster than Spark on my use cases), I’ve turned instantly from spark-fan to flink-fan – great job, committers!

So I’ve decided to port my existing Spark tools to Flink. Happily, most of the difficulty was renaming classes, packages and variables with “spark” in them to something more neutral J


However there is one easy thing in Spark I’m still wondering how to do in Flink : generic keys.


I’m trying to make a framework on which my applications are built. That framework thus manipulate “generic types” representing the data, inheriting from an abstract class with a common contract, let’s call it “Bean”.


Among other things Bean exposes an abstract method

public Key getKey();   


Key being one of my core types used in several java algorithms.


Let’s say I have the class :

public class Framework<T extends Bean> implements Serializable {


public DataSet<T> doCoolStuff(final DataSet<T> inputDataset) {

        // Group lines according to a key

        final UnsortedGrouping<YT> groupe = inputDataset.groupBy(new KeySelector<T, Key>() {


            public Key getKey(T record)  {

                return record.getKey();







With Spark, a mapToPair works fine because all I have to do is implements correctly hashCode() and equals() on my Key type.

With Flink, Key is not recognized as a POJO object (well it is not) and that does not work.


I have tried to expose something like public Tuple getKeyAsTuple(); in Key but Flink does not accept generic Tuples. I’ve tried to parameterize my Tuple but Flink does not know how to infer

the generic type value.


So I’m wondering what is the best way to implement it.

For now I have exposed something like public String getKeyAsString(); and turned my generic treatment into :

final UnsortedGrouping<YT> groupe = inputDataset.groupBy(new KeySelector<T, String>() {


            public String getKey(T record)  {

                return record.getKey().getKeyAsString();



But that “ASCII” representation is suboptimal.


I thought of passing a key to tuple conversion lambda upon creation of the Framework class but that would be boiler-plate code on the user’s end, which I’m not fond of.


So my questions are :

-          Is there a smarter way to do this ?

-          What kind of objects can be passed as a Key ? Is there an Interface to respect ?

-          In the worst case, is byte[]  ok as a Key ? (I can code the serialization on the framework side…)



Best regards,



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