Are we using the advantage of "Map & Reduce" ?

[wyzer]

Hello,

We are new on Databricks and we would like to know if our working method are good.

Currently, we are working like this :

spark.sql("CREATE TABLE Temp (SELECT avg(***), sum(***) FROM aaa LEFT JOIN bbb WHERE *** >= ***)")

With this method, are we using the full capacity of Databricks, like "Map & Reduce" ?

Thanks.

[Kaniz]

Hi @Salah K.​ ! My name is Kaniz, and I'm the technical moderator here. Great to meet you, and thanks for your question! Let's see if your peers in the community have an answer to your question first. Or else I will get back to you soon. Thanks.

[-werners- · Accepted solution]

Spark will handle the map/reduce for you.

So as long as you use Spark provided functions, be it in scala, python or sql (or even R) you will be using distributed processing.

You just care about what you want as a result.

And afterwards when you are more familiar with Spark you can start tuning (f.e. trying to avoid shuffles, other join types etc)

[wyzer]

Thank you.