Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/17874
yea that example looks very weird and we should fix it, thanks!
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Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17874
@cloud-fan Since you all concern about breaking existing applications, I'd
close this. But I think we should not add missing attributes though subqueries
like I showed above. I'll create another PR
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17874
Maybe another point of view is, we can split `df.select("y").where("x=1")`
to two different DataFrames:
val onlyY = df.select("y") // The schema of onlyY is just "y" attribute
Github user viirya commented on the issue:
https://github.com/apache/spark/pull/17874
`select a from t where b > 0` works. However, it can be seen logically as:
Project [a]
Filter [b > 0]
Relation t [a, b]
It seems to me Spark also parses the
Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/17874
in postgres, `select a from t where b > 0` can work, I think it's
reasonable if `df.select("y").where("x=1")` works in spark.
```
Seq(1).toDF("c1").createOrReplaceTempView("onerow")
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/17874
Merged build finished. Test PASSed.
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/17874
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Github user SparkQA commented on the issue:
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