[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/20234 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...
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. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...
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. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #20234: [SPARK-19732] [Follow-up] Document behavior chang...
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: gatorsmileDate: 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 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org