[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...

2018-01-11 Thread asfgit
Github user asfgit closed the pull request at:

https://github.com/apache/spark/pull/20234


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[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...

2018-01-11 Thread gatorsmile
Github user gatorsmile commented on a diff in the pull request:

https://github.com/apache/spark/pull/20234#discussion_r160952123
  
--- Diff: docs/sql-programming-guide.md ---
@@ -1788,12 +1788,10 @@ options.
 Note that, for DecimalType(38,0)*, the table above 
intentionally does not cover all other combinations of scales and precisions 
because currently we only infer decimal type like `BigInteger`/`BigInt`. For 
example, 1.1 is inferred as double type.
   - In PySpark, now we need Pandas 0.19.2 or upper if you want to use 
Pandas related functionalities, such as `toPandas`, `createDataFrame` from 
Pandas DataFrame, etc.
   - In PySpark, the behavior of timestamp values for Pandas related 
functionalities was changed to respect session timezone. If you want to use the 
old behavior, you need to set a configuration 
`spark.sql.execution.pandas.respectSessionTimeZone` to `False`. See 
[SPARK-22395](https://issues.apache.org/jira/browse/SPARK-22395) for details.
-
- - Since Spark 2.3, when either broadcast hash join or broadcast nested 
loop join is applicable, we prefer to broadcasting the table that is explicitly 
specified in a broadcast hint. For details, see the section [Broadcast 
Hint](#broadcast-hint-for-sql-queries) and 
[SPARK-22489](https://issues.apache.org/jira/browse/SPARK-22489).
-
- - Since Spark 2.3, when all inputs are binary, `functions.concat()` 
returns an output as binary. Otherwise, it returns as a string. Until Spark 
2.3, it always returns as a string despite of input types. To keep the old 
behavior, set `spark.sql.function.concatBinaryAsString` to `true`.
-
- - Since Spark 2.3, when all inputs are binary, SQL `elt()` returns an 
output as binary. Otherwise, it returns as a string. Until Spark 2.3, it always 
returns as a string despite of input types. To keep the old behavior, set 
`spark.sql.function.eltOutputAsString` to `true`.
+  - In PySpark, `na.fill()` or `fillna` also accepts boolean and replaces 
NAs with booleans. In prior Spark versions, PySpark just ignores it and returns 
the original Dataset/DataFrame.  
--- End diff --

Sounds good to me.


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[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...

2018-01-11 Thread HyukjinKwon
Github user HyukjinKwon commented on a diff in the pull request:

https://github.com/apache/spark/pull/20234#discussion_r160949121
  
--- Diff: docs/sql-programming-guide.md ---
@@ -1788,12 +1788,10 @@ options.
 Note that, for DecimalType(38,0)*, the table above 
intentionally does not cover all other combinations of scales and precisions 
because currently we only infer decimal type like `BigInteger`/`BigInt`. For 
example, 1.1 is inferred as double type.
   - In PySpark, now we need Pandas 0.19.2 or upper if you want to use 
Pandas related functionalities, such as `toPandas`, `createDataFrame` from 
Pandas DataFrame, etc.
   - In PySpark, the behavior of timestamp values for Pandas related 
functionalities was changed to respect session timezone. If you want to use the 
old behavior, you need to set a configuration 
`spark.sql.execution.pandas.respectSessionTimeZone` to `False`. See 
[SPARK-22395](https://issues.apache.org/jira/browse/SPARK-22395) for details.
-
- - Since Spark 2.3, when either broadcast hash join or broadcast nested 
loop join is applicable, we prefer to broadcasting the table that is explicitly 
specified in a broadcast hint. For details, see the section [Broadcast 
Hint](#broadcast-hint-for-sql-queries) and 
[SPARK-22489](https://issues.apache.org/jira/browse/SPARK-22489).
-
- - Since Spark 2.3, when all inputs are binary, `functions.concat()` 
returns an output as binary. Otherwise, it returns as a string. Until Spark 
2.3, it always returns as a string despite of input types. To keep the old 
behavior, set `spark.sql.function.concatBinaryAsString` to `true`.
-
- - Since Spark 2.3, when all inputs are binary, SQL `elt()` returns an 
output as binary. Otherwise, it returns as a string. Until Spark 2.3, it always 
returns as a string despite of input types. To keep the old behavior, set 
`spark.sql.function.eltOutputAsString` to `true`.
+  - In PySpark, `na.fill()` or `fillna` also accepts boolean and replaces 
NAs with booleans. In prior Spark versions, PySpark just ignores it and returns 
the original Dataset/DataFrame.  
--- End diff --

Shall we say `null` instead of `NA`? I actually think `null` is more 
correct.


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[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...

2018-01-11 Thread gatorsmile
GitHub user gatorsmile opened a pull request:

https://github.com/apache/spark/pull/20234

[SPARK-19732] [Follow-up] Document behavior changes made in na.fill and 
fillna

## What changes were proposed in this pull request?
https://github.com/apache/spark/pull/18164 introduces the behavior changes. 
We need to document it.

## How was this patch tested?
N/A

You can merge this pull request into a Git repository by running:

$ git pull https://github.com/gatorsmile/spark docBehaviorChange

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/20234.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

This closes #20234


commit 89f00867f319cddf5ff49442b9ab38f1cefe837e
Author: gatorsmile 
Date:   2018-01-11T03:10:11Z

fix

commit 09193499f522dee74d99262347e254e028e9d636
Author: gatorsmile 
Date:   2018-01-11T03:10:35Z

clean

commit ff30553092a7bfe8d9aac3fc1f89b99ff679a2aa
Author: gatorsmile 
Date:   2018-01-11T03:11:56Z

fix




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