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Thanks, merged to master.
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@@ -42,47 +42,27 @@ abstract class Generator exte
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*/
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seed: Int =
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*/
obje
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@marmbrus updated, can you review it again?
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Github user marmbrus commented on the pull request:
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I think that if you just make them arguments to the constructor then all of
the work to keep them consistent will come for free.
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Github user chenghao-intel commented on the pull request:
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Yea, that's quite headache, all of the output attribute are created within
the `Generate`, and will be bundled by its parent nodes later, the difficulty
is to keep
Github user marmbrus commented on the pull request:
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Sorry for the delay. I did a quick pass and I think the biggest comment is
the mutable state for the output of `Generate`. My initial version had tons of
bugs, so I'd
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@@ -700,12 +700,15 @@ class DataFrame private[sql](
*/
def explode[A
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cc @yhuai @marmbrus @liancheng can you review the code? I've finished the
code refactoring and the bug fixing as we discussed above.
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--- Diff:
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@@ -34,24 +35,12 @@ import org.apache.spark.sql.catalyst.expression
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@yhuai @marmbrus this is a bug fixing, it will be great if you can give
more comments on this, and I agree with @yhuai we need to refactor the UDTF
expression impl
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@yhuai please ignore my previous comment. I was thinking some other
possibilities.
I agree with you we can move the output column names into the logical plan
n
Github user chenghao-intel commented on the pull request:
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The `generator` is not like the normal expression, which can output
multiple columns, in current implementation, the logical plan node `Generate`
is for that purpo
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@chenghao-intel After another look of the code, I think it may be better to
remove aliases from the `generator`. Then, `MultiAlias` can be used to assign
the names to the o
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/cc @marmbrus @yhuai Any comment on this?
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Github user chenghao-intel commented on the pull request:
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retest this please.
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Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/4602#issuecomment-74628619
Thank you @yhuai , I've updated the description and rebased the code.
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Github user SparkQA commented on the pull request:
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Github user yhuai commented on the pull request:
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I tried the following
```
val rdd = sc.parallelize((1 to 10).map(i => s"""{"a":$i, "b":"str${i}"}"""))
sqlContext.jsonRDD(rdd).registerTempTable("jt")
sqlCon
Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/4602#issuecomment-74402072
@marmbrus any more comments on this?
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Github user chenghao-intel commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala ---
@@ -34,17 +36,22 @@ import org.apache.spark.sql.catalyst.expression
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--- Diff:
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@@ -137,6 +137,11 @@ class Analyzer(catalog: Catalog,
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--- Diff:
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Github user marmbrus commented on a diff in the pull request:
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--- Diff:
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@@ -137,6 +137,11 @@ class Analyzer(catalog: Catalog,
Github user marmbrus commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala ---
@@ -34,17 +36,22 @@ import org.apache.spark.sql.catalyst.expressions._
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