Github user gatorsmile commented on the issue:
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Thank you for your investigation! How about generating a user-friendly
error message in these unsupported cases? The error messages from Hive is very
confusing to the external users.
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Github user dongjoon-hyun commented on the issue:
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Hi, @gatorsmile . I investigated the related PRs.
* #12934 `[SPARK-14127][SQL] Makes 'DESC [EXTENDED|FORMATTED] '
support data source tables`
* #12844 `[SPARK-14127][SQL] Native
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Github user dongjoon-hyun commented on a diff in the pull request:
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--- Diff:
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@@ -506,6 +506,25 @@ class HiveDDLSuite
}
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[SPARK-17660] [SQL] DESC FORMATTED for VIEW Lacks View Definition
### What changes were proposed in this pull request?
Before this PR, DESC FORMATTED does not have a section for the view
Github user felixcheung commented on the issue:
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Hmm, thanks.
I thought we had "turn warning to error" in test - any idea why these
didn't error out in the PR before it was merged?
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Let's add some tests for this?
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Github user gatorsmile commented on the issue:
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Partitioned View is another potential issue for this PR.
FYI, just submitted a related PR https://github.com/apache/spark/pull/15168
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Github user HyukjinKwon commented on the issue:
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Sorry, I left and removed a wring comment. Please ignore that. Sure, I will
rather try to add an explicit check before that.
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[SPARK-17659] [SQL] Partitioned View is Not Supported In SHOW CREATE TABLE
### What changes were proposed in this pull request?
`Partitioned View` is not supported by SPARK SQL. For Hive
Github user gatorsmile commented on the issue:
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For `CREATE SHOW TABLE` on global temporary views, we need to always
qualify the database name `global_temp` in the table name, no matter whether
users add it or not.
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Github user dongjoon-hyun commented on the issue:
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Sure. I'll investigate from that. Thank you for the pointer, @gatorsmile .
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Yeah, please change the JIRA to improvement.
I did not check the code of Spark 1.6.2, but, since Spark 2.0, we provide a
native support for `DESC TABLE`. See the PR:
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rebase to master
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Github user HyukjinKwon commented on the issue:
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Sure, I trust your judgement. Coould you please guide me please? (Is there
a common logic to check this?)
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Thanks @HyukjinKwon - Fix looks good. But isn't it better to do the check
before we do the na.omit / as.integer ? Or will that miss some cases ?
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Github user mpjlu commented on the issue:
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Hi @yanboliang , got it. Thanks.
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Github user dongjoon-hyun commented on the issue:
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Actually, I think there was a reason not to do that in Spark 1.6.2. In
Spark 2.0, is there any new way to lookup the partition info from Parquet
Datasource through `SessionCatalog`?
Github user gatorsmile commented on the issue:
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cc @cloud-fan @yhuai
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Github user gatorsmile commented on the issue:
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Yeah, I knew. : ) This PR is to support `DESCRIBE PARTITION`, right? The
other `DESCRIBE` commands can support all the table types. Thus, I believe we
need to support all the cases for `DESCRIBE
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Hi, @gatorsmile .
It's the same behavior with Apache Spark 1.6.2. This PR doesn't make any
regression for Datasource tables. Actually, the error you mentioned is raised
by
Github user cloud-fan commented on the issue:
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has an offline discussion with @wzhfy , here is the result:
1. The current `ColumnStats` is hard to use because most of its fields are
`Option`, some are `Option[Any]`, and we may need a
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Thank you, @gatorsmile . I'll fix that soon.
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cc @felixcheung and @shivaram
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[SPARK-17499][SPARKR][FOLLOWUP] Suppress warnings from is.na in spark.mlp
causing warnings in test results
## What changes were proposed in this pull request?
Some tests in
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retest this please
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FWIW - Python API seems having `path` as optional[1] and Scala API seems
doing this so as well[2].
[1]https://github.com/apache/spark/blob/master/python/pyspark/sql/readwriter.py#L521
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[SPARK-17658][SPARKR] write.df API taking path optionally in SparkR
## What changes were proposed in this pull request?
`write.df` API requires path which is not actually always
Github user chuanlei commented on a diff in the pull request:
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--- Diff:
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@@ -290,8 +284,8 @@ final class DataStreamWriter[T]
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@thunterdb any updates here? Can this be merged?
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Github user asfgit closed the pull request at:
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Github user gatorsmile commented on the issue:
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It sounds like the implementation of this PR does not support data source
tables. Please try the following example.
```Scala
spark
.range(1).select('id as 'a, 'id
Github user yanboliang commented on the issue:
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Merged into master. Thanks for review.
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@mpjlu The most important cause of this change is that the fit/train model
should not dependent on the order of users setting params. In other words,
users should get the same model whether set
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--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/feature/ChiSqSelectorSuite.scala ---
@@ -76,7 +76,7 @@ class ChiSqSelectorSuite extends
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[SPARK-17657] [SQL] Disallow Users to Change Table Type
### What changes were proposed in this pull request?
Hive allows users to change the table type from `Managed` to `External` or
from
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https://github.com/apache/spark/pull/15229
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/15229
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Github user jaceklaskowski commented on the issue:
https://github.com/apache/spark/pull/14808
@sethah I seem to have missed the other comment with the notes what has to
be done to make the PR an example for the change. Sorry.
Since I'm very new to it and the only way to learn
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