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 <b>DecimalType(38,0)*</b>, 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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