Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/18005
LGTM - merging to master/2.2. Thanks!
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Github user tpoterba commented on the issue:
https://github.com/apache/spark/pull/18005
Others on my team suggest that the >64k bytecode issue has been fixed
already (and ported to a 2.1 maintenance release as well)
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Github user tpoterba commented on the issue:
https://github.com/apache/spark/pull/18005
I used this script to generate random CSV files:
```python
import uuid
import sys
try:
print('args = ' + str(sys.argv))
filename = sys.argv[1]
cols =
Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/18005
What do you mean by catalyst blew up?
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Github user tpoterba commented on the issue:
https://github.com/apache/spark/pull/18005
Addressed comments.
I tried to get some benchmark stats for this code:
```python
spark.read.csv(text_file).write.mode('overwrite').parquet(parquet_path)
```
I wanted to
Github user hvanhovell commented on the issue:
https://github.com/apache/spark/pull/18005
LGTM pending jenkins
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Github user tpoterba commented on the issue:
https://github.com/apache/spark/pull/18005
Yeah, I can change that - I do hate the standard IndexedSeq implementation
(Vector) though, and want to make sure that the collection is actually a
WrappedArray.
I've actually done more
Github user JoshRosen commented on the issue:
https://github.com/apache/spark/pull/18005
It might be nice to explicitly use the type `IndexedSeq[ValueWriter]` for
`rootFieldWriters` (up on line 61 of this file) since that would capture the
intent behind using an Array and would maybe
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Github user hvanhovell commented on the issue:
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Can you also make sure that we do not use a `Seq` for struct writing?
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Github user hvanhovell commented on the issue:
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ok to test
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Github user AmplabJenkins commented on the issue:
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Can one of the admins verify this patch?
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