Hi Aditya,
thank you for your email. 
There are three Wayang operators: Reduce, ReduceBy, and GlobalReduce. Let me 
first explain the latter two, which have completely different functionality and 
thus output. 

The ReduceByOperator aggregates data based on groups defined by a key. So data 
containing the same key will be aggregated. It's as a groupby followed by an 
aggregation in SQL or as the reduce phase in the wordcount task. In Spark, it 
would be a reducebyKey() operation.

The GlobalReduceOperator performs a total aggregate over all data points. So it 
brings all data in a single place and makes the aggregate. In Spark, it would 
be the respective reduce() operation.

You can take a look at one of their platform implementations to check which 
operators it calls in Spark, for example, or in Java streams.

Now the ReduceOperator was meant more as a convenience operator for users. If 
it is preceded by a GroupByOperator, it's meant to be the ReduceBy, and 
otherwise the GlobalReduce.
However, currently this operator does not have any platform implementation. So 
I would recommend to not use it.
Hope this helps. Let us know if not.
Best
--
Zoi
   Στις Τρίτη 5 Σεπτεμβρίου 2023 στις 09:40:53 μ.μ. CEST, ο χρήστης Aditya Goel 
<[email protected]> έγραψε:  
 
 Dear Wayang Community,

I hope this email finds you well.  I am reaching out to seek clarification 
regarding the usage and differences between the ReduceOperator and 
GlobalReduceOperator classes.

Here are the specific questions I have:


  1.  Use Cases: Could you please explain the typical use cases or scenarios 
where it is appropriate to use the ReduceOperator class, and when it is more 
suitable to use the GlobalReduceOperator class? I want to ensure that we are 
selecting the right operator for our aggregation needs.
  2.  Functionality: What are the key functional differences between these two 
operators? Are there any performance or scalability considerations that should 
inform our choice between them?
  3.  Best Practices: Are there any best practices or recommended patterns for 
configuring and using these operators efficiently? Any tips or pitfalls we 
should be aware of?

Thank you in advance for your time and assistance. I look forward to hearing 
from you and benefiting from your insights.

Best regards,

Aditya Goel

  

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