A much better one-liner (easier to understand the UI because it will be 1
simple job with 2 stages):
```
spark.read.text("README.md").repartition(2).take(1)
```
Attila Zsolt Piros wrote
> No, it won't be reused.
> You should reuse the dateframe for reusing the shuffle blocks (and cached
> data).
>
> I know this because the two actions will lead to building a two separate
> DAGs, but I will show you a way how you could check this on your own (with
> a
> small simple spark application).
>
> For this you can even use the spark-shell. Start it in directory where a
> simple text file available ("README.md" in my case).
>
> After this the one-liner is:
>
> ```
> scala> spark.read.text("README.md").selectExpr("length(value) as l",
> "value").groupBy("l").count
> .take(1)
> ```
>
> Now if you check Stages tab on the UI you will see 3 stages.
> After re-executing the same line of code in the Stages tab you can see the
> number of stages are doubled.
>
> So shuffle files are not reused.
>
> Finally you can delete the file and re-execute our small test. Now it will
> produce:
>
> ```
> org.apache.spark.sql.AnalysisException: Path does not exist:
> file:/Users/attilazsoltpiros/git/attilapiros/spark/README.md;
> ```
>
> So the file would have been opened again for loading the data (even in the
> 3rd run).
>
>
>
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```
```
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