# How do I implement a reducer in Ray?

**URL:** <https://discuss.ray.io/t/how-do-i-implement-a-reducer-in-ray/10249>\
**Category:** Uncategorized\
**Created:** [April 15, 2023, 9:42pm UTC](https://discuss.ray.io/t/how-do-i-implement-a-reducer-in-ray/10249 "2023-04-15T21:42:50Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![wpm](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/wpm/32/4241_2.png) [@wpm](https://discuss.ray.io/u/wpm)\
**Post date:** [April 15, 2023, 9:42pm UTC](https://discuss.ray.io/t/how-do-i-implement-a-reducer-in-ray/10249/1 "2023-04-15T21:42:50Z")

</div>

I’m new to Ray and finding it great, but there’s one giant gap in my understanding: how do I use to core Ray functionality to implement the reduce step of a MapReduce algorithm?

MapReduce is such a fundamental concurrency algorithm that I’d expect this to be really obvious. Like there would be core Ray functions called “reducer”, the Getting Started part of the documentation would have a word count example, etc. But there’s almost no mention of MapReduce either in the documentation or online. The top Google result I get for “ray mapreduce” is a link to a [long-abandoned Ray design patterns page](https://docs.ray.io/en/releases-1.10.0/ray-design-patterns/map-reduce.html) from version 1.10.1. This surprises me.

To make things concrete, here’s a simple problem. I have a bunch of number lists, each of which has a unique name A, B, C etc.

```auto
A: 10, 3, 5, 7, 19
B: 2, 4, 6, 7, 5, 100
C: 10, 9, 5, 3, 2, 1
...

```

I want to transform this into lists with the same names where each number has been incremented by one, running the “increment by one” operation in parallel.

```auto
A: 11, 4, 6, 8, 20
B: 3, 5, 7, 8, 6, 101
C: 11, 10, 6, 4, 3, 2
...

```

I’m confident that I can come up with a scalable map step of this process in an idiomatically Ray-like fashion, but I’m not sure how to use Ray to make the reduce step scalable. The best strategy I’ve seen is in the blog post [Executing a distributed shuffle without a MapReduce system](https://medium.com/distributed-computing-with-ray/executing-a-distributed-shuffle-without-a-mapreduce-system-d5856379426c), but that uses the kind of complicated programming that I want Ray to do for me.

Am I misunderstanding something fundamental about Ray’s design?