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Why does Java's Stream.reduce method take an identity element instead of a default result?

By : throwaway92838
Date : September 16 2020, 09:00 PM
this will help Look in particular at the third method: Here the accumulation (wrong word, really; this is a conclist more than a conslist, but I hope you follow the meaning here) is a different type than the stream.
For example, you have a stream of strings, and you reduce it into an op that counts up the string lengths; the accumulation is done as an integer.
code :

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In Stream reduce method, must the identity always be 0 for sum and 1 for multiplication?

By : Lisa
Date : March 29 2020, 07:55 AM
I wish did fix the issue. The identity value is a value, such that x op identity = x. This is a concept which is not unique to Java Streams, see for example on Wikipedia.
It lists some examples of identity elements, some of them can be directly expressed in Java code, e.g.
code :
reduce(x->true, Predicate::and)
reduce(x->false, Predicate::or)
reduce(Function.identity(), Function::andThen)

Why does Java stream map reduce count my result twice?

By : nanwil
Date : March 29 2020, 07:55 AM
hope this fix your issue Your are mutating an incoming object in reduce. This is wrong. It doesn’t help that you are creating a new object after modifying the incoming object.
What you want to do, is
code :
.collect(ComparisonResults::new, ComparisonResults::addSingleResult,
         (a,b)->/* code to merge two ComparisonResults instances*/);

Scala equivalent for Javas stream findFirst()

By : Свидарасня Бандеровс
Date : March 29 2020, 07:55 AM
hop of those help? You can simple use lst.find(_ > 5) which will return an Option. This is basically the same as (but more efficient than) writing lst.filter(_ > 5).headOption which will also return an Option or swapping headOption for head (highly discouraged) which will throw an exception if nothing is found.

Why calling the reduce method in the parallel stream with a mutable object as identity does not reserve the order in the

By : Andrew Raketskyi
Date : March 29 2020, 07:55 AM
wish helps you Your diagram is not correct - you assume that each parallel reduction starts with a new StringBuilder. Instead of that each parallel reduction starts with the same identity element - with the same StringBuilder (the one that you create and pass as the first parameter to the reduce method).
Each parallel stream calls StringBuilder.append on the (one and only) StringBuilder that you pass to the reduce method, thereby appending the currently encountered element to it.
code :
List<String> list = Arrays.asList("1","2","3","4","5","6",
String result = list.parallelStream()
   .collect(StringBuilder::new, StringBuilder::append, 

Reduce with identity combiner parallel stream

By : lelong1406
Date : March 29 2020, 07:55 AM
wish help you to fix your issue I have not looked at that link from the comments, but the documentation is pretty clear about identity and it even provides a simple way of testing that:
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