Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/13245#issuecomment-220880599
Sorry, it wasn't a good idea of extending SparkSession for RDD. I'm closing
this PR.
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Github user dongjoon-hyun closed the pull request at:
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Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/13245#issuecomment-220814644
Unfortunately, `Dataset` (or `Dataframe`) seems not suitable to achieve the
goal on Python.
```python
>>> spark.parallelize(range(1, 10)).toDS()
...
Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/13245#issuecomment-220813421
I see. Thank you!
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Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/13245#issuecomment-220811972
hm we are trying to avoid returning rdds in the new apis. one thing we can
do is to introduce a parallelize api that returns dataset?
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Github user dongjoon-hyun commented on the pull request:
https://github.com/apache/spark/pull/13245#issuecomment-220801877
Hi, @rxin .
I'm wondering your opinion about this PR.
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GitHub user dongjoon-hyun opened a pull request:
https://github.com/apache/spark/pull/13245
[SPARK-15466][SQL] Make `SparkSession` as the entry point to programming
with RDD too
## What changes were proposed in this pull request?
`SparkSession` greatly reduces the number
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