GitHub user travishegner opened a pull request:
https://github.com/apache/spark/pull/19191
[SPARK-21958][ML] Word2VecModel save: transform data in the cluster
## What changes were proposed in this pull request?
Change a data transformation while saving a Word2VecModel
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/9495#issuecomment-154423022
Thanks @yhuai for taking care of this!
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GitHub user travishegner opened a pull request:
https://github.com/apache/spark/pull/9495
Oracle dialect to handle nonspecific numeric types
This is the alternative/agreed upon solution to PR #8780.
Creating an OracleDialect to handle the nonspecific numeric types that can
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-154087900
Please see PR #9495 for the oracle dialect solution proposed above.
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Github user travishegner closed the pull request at:
https://github.com/apache/spark/pull/8780
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Github user travishegner commented on a diff in the pull request:
https://github.com/apache/spark/pull/8780#discussion_r41172742
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/DecimalType.scala ---
@@ -140,7 +140,12 @@ object DecimalType extends AbstractDataType
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-145609065
@cloud-fan @bdolbeare @davies I'm certainly open to doing this in an oracle
specific way if that is what is required. I was simply hoping to solve my
problem while
Github user travishegner commented on a diff in the pull request:
https://github.com/apache/spark/pull/8780#discussion_r41171411
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
---
@@ -66,9 +66,7 @@ private[sql] object JDBCRDD
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-144054401
So any thoughts on merging this?
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Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-142282068
I'm making sure the new version builds, but here are the rules:
```scala
private[sql] def bounded(precision: Int, scale: Int): DecimalType
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-142004449
Working on a new patch... Would it ever be possible to have a case where
precision is 0 (essentially undefined), but scale is still intentionally set
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-142045620
But a negative scale is inherently less than a defined precision... or do
you mean precision should never be less than the absolute value of scale
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-142100699
OK, after looking at this a little further, it seems that
DecimalType.bounded() should be called regardless of precision and scale values
in JDBCRDD.scala
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-141462484
That is exactly what I was afraid of. Would the patch make more sense to
*only* check precision for a zero value? Does it ever make sense to have a
precision
GitHub user travishegner opened a pull request:
https://github.com/apache/spark/pull/8780
[SPARK-10648] Proposed bug fix when oracle returns -127 as a scale to a
numeric type
In my environment, the precision and scale are undefined in the oracle
database, but spark is detecting
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-140913028
Yes, that is the intention. Is this the proper way to address that issue?
On Wed, Sep 16, 2015, 5:14 PM Holden Karau <notificati...@github.com>
Github user travishegner commented on the pull request:
https://github.com/apache/spark/pull/8780#issuecomment-140936357
I'm not sure if oracle can be associated with anything *reasonable*, but
sometimes you have to play the hand you are dealt. :)
I can only answer your
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