[GitHub] spark issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarI...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/22054 Please review this PR. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarI...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/22054 PLease review this PR. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #22054: [SPARK-24703][SQL]: To add support to multiply CalendarI...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/22054 PLease review this PR. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #22054: [SPARK-24703][SQL]: To add support to multiply Ca...
GitHub user priyankagargnitk opened a pull request:
https://github.com/apache/spark/pull/22054
[SPARK-24703][SQL]: To add support to multiply CalendarInterval with
Integral Type.
## What changes were proposed in this pull request?
This change adds capability to multiply Calender interval.
Earlier the multiplication was throwing exception as follow:
spark.sql("select interval '1' day * 3").show()
org.apache.spark.sql.AnalysisException: cannot resolve '(interval 1
days * 3)' due to data type mismatch: differing types in '(interval 1 days) *
3' (int and calendarinterval).; line 1 pos 7;
'Project [unresolvedalias((interval 1 days * 3) , None)]
+- OneRowRelation
at
org.apache.spark.sql.catalyst.analysis.package.failAnalysis(package.scala:42)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis1433anonfun1433anonfun.applyOrElse(CheckAnalysis.scala:93)
at
but now, we have added this support.
## How was this patch tested?
Added test case in CalendarIntervalSuite.java,
ArithmeticExpressionSuite.scala and ExpressionTypeCheckingSuite.scala
Also, tested by spark-shell by multiplying calendarinterval with
Integral type.
scala> spark.sql(\"select interval '1' day\").show()
+---+
|interval 1 days|
+---+
|interval 1 days|
+---+
scala> spark.sql(\"select interval '1' day * 3\").show()
+-+
|(interval 1 days * 3)|
+-+
| interval 3 days|
+-+
scala> spark.sql(\"select 3 * interval '1' day * 3\").show()
+---+
|((3 * interval 1 days) * 3)|
+---+
| interval 1 weeks ...|
+---+
scala> spark.sql("select 3 * interval '1' day * 3").collect()
res7: Array[org.apache.spark.sql.Row] = Array([interval 1 weeks 2 days])
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/priyankagargnitk/spark SPARK-24703
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/22054.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 #22054
commit 31312c86f83fbd0aaf6d0d4a706d3469792a23df
Author: Priyanka Garg
Date: 2018-08-09T10:24:27Z
[SPARK-24703][SQL]: To add support to multiply CalendarInterval with
Integral Type.
## What changes were proposed in this pull request?
This change adds capability to multiply Calender interval.
Earlier the multiplication was throwing exception as follow:
spark.sql("select interval '1' day * 3").show()
org.apache.spark.sql.AnalysisException: cannot resolve '(interval 1
days * 3)' due to data type mismatch: differing types in '(interval 1 days) *
3' (int and calendarinterval).; line 1 pos 7;
'Project [unresolvedalias((interval 1 days * 3) , None)]
+- OneRowRelation
at
org.apache.spark.sql.catalyst.analysis.package.failAnalysis(package.scala:42)
at
org.apache.spark.sql.catalyst.analysis.CheckAnalysis1433anonfun1433anonfun.applyOrElse(CheckAnalysis.scala:93)
at
but now, we have added this support.
## How was this patch tested?
Added test case in CalendarIntervalSuite.java,
ArithmeticExpressionSuite.scala and ExpressionTypeCheckingSuite.scala
Also, tested by spark-shell by multiplying calendarinterval with
Integral type.
---
-
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21679: [SPARK-24695] [SQL]: To add support to return Calendar i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/21679 What if i make changes to expose it? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #21679: [SPARK-24695] [SQL]: To add support to return Calendar i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/21679 org.apache.spark.unsafe.types.CalenderInterval is already public, am i missing something. Also, what if i want to do some computation on any data type and return Calender Interval.. How should i solve this problem in current scenario. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #21679: SPARK-24695: To add support to return Calendar in...
GitHub user priyankagargnitk opened a pull request: https://github.com/apache/spark/pull/21679 SPARK-24695: To add support to return Calendar interval from udf. ## What changes were proposed in this pull request? This change adds capability to return Calender interval from udf. Earlier, the udf of Type (String => CalendarInterval) was throwing Exception stating: Schema for type org.apache.spark.unsafe.types.CalendarInterval is not supported java.lang.UnsupportedOperationException: Schema for type org.apache.spark.unsafe.types.CalendarInterval is not supported at org.apache.spark.sql.catalyst.ScalaReflection391anonfun.apply(ScalaReflection.scala:781) ## How was this patch tested? Added test case in ScalaReflectionSuite.scala and ExpressionEncoderSuite.scala Also, tested by creating an udf that returns Calendar interval. jira entry for detail: https://issues.apache.org/jira/browse/SPARK-24695 You can merge this pull request into a Git repository by running: $ git pull https://github.com/priyankagargnitk/spark SPARK-24695 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/21679.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 #21679 commit bd805299cc9802597c165a6de1667a7b02ad48ae Author: Priyanka Garg Date: 2018-06-30T07:23:56Z SPARK-24695: To add support to return Calender interval from udf. ## What changes were proposed in this pull request? This change adds capability to return Calender interval from udf. Earlier, the udf of Type (String => CalendarInterval) was throwing Exception stating: Schema for type org.apache.spark.unsafe.types.CalendarInterval is not supported java.lang.UnsupportedOperationException: Schema for type org.apache.spark.unsafe.types.CalendarInterval is not supported at org.apache.spark.sql.catalyst.ScalaReflection391anonfun.apply(ScalaReflection.scala:781) ## How was this patch tested? Added test case in ScalaReflectionSuite.scala and ExpressionEncoderSuite.scala Also, tested by creating an udf that returns Calendar interval. jira entry for detail: https://issues.apache.org/jira/browse/SPARK-24695 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15479: [SPARK-17884][SQL] To resolve Null pointer except...
Github user priyankagargnitk closed the pull request at: https://github.com/apache/spark/pull/15479 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15479: [SPARK-17884][SQL] To resolve Null pointer exception whe...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15479 Yeah.. closing this. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15609: [SPARK-18048][SQL] To make behaviour of If consis...
Github user priyankagargnitk closed the pull request at: https://github.com/apache/spark/pull/15609 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15609: [SPARK-18048][SQL] To make behaviour of If consistent, i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15609 Sure.. I am closing it... If still face any issues... will raise another.. Thanks for the help. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15609: [SPARK-18048][SQL] To make behaviour of If consistent, i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15609 Hmm... I think that makes sense.. i am trying a couple of more things... Thanks --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15609: [SPARK-18048][SQL] To make behaviour of If consistent, i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15609 Actually our use case is little different, we are not invoking it with the Select queries.. We are using JS to let user type expressions and then we have created out own layer on top of spark that converts this JS to Spark expressions.. So if user writes an expression that returns date in true branch and timestamp in false branch.. Then the IF expression fails... because it internally getting mapped to If(Literal.create(true, BooleanType), Literal.create(identity(1), DateType), Literal.create(identity(2L), TimestampType)) , Which fails. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15609: [SPARK-18048][SQL] To make behaviour of If consistent, i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15609 actually, its not covered in type widening... So, if any of my expression is calling if expression ( in nested) .. its failing because of this issue. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15609: [SPARK-18048][SQL] To make behaviour of If consis...
GitHub user priyankagargnitk opened a pull request: https://github.com/apache/spark/pull/15609 [SPARK-18048][SQL] To make behaviour of If consistent, in case of true expression and false expression are of compatible data types. ## What changes were proposed in this pull request? This change adds a type conversion from false value datatype to true valueâs datatype. Earlier, the expression If(Literal.create(true, BooleanType), Literal.create(identity(1), DateType), Literal.create(identity(2L), TimestampType)) was throwing Exception while the expression If(Literal.create(true, BooleanType), Literal.create(identity(1L), TimestampType), Literal.create(identity(2), DateType)) was working fine. So , if we interchange the true and false expressions, behaviour of the IF expression changes. ## How was this patch tested? Added test case in ConditionalExpressionSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-18048 You can merge this pull request into a Git repository by running: $ git pull https://github.com/priyankagargnitk/spark SPARK-18048 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15609.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 #15609 commit 9a8ef85c9e8924a44b4e7d5639f259c950d03a9c Author: prigarg Date: 2016-10-24T06:34:58Z [SPARK-18048][SQL] To make behaviour of If consistent, in case of true expression and false expression are of compatible data types. ## What changes were proposed in this pull request? This change adds a type conversion from false value datatype to true valueâs datatype. Earlier, the expression If(Literal.create(true, BooleanType), Literal.create(identity(1), DateType), Literal.create(identity(2L), TimestampType)) was throwing Exception while the expression If(Literal.create(true, BooleanType), Literal.create(identity(1L), TimestampType), Literal.create(identity(2), DateType)) was working fine. So , if we interchange the true and false expressions, behaviour of the IF expression changes. ## How was this patch tested? Added test case in ConditionalExpressionSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-18048 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15449: [SPARK-17884][SQL] To resolve Null pointer exception whe...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15449 Done. PR #15479 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15479: [SPARK-17884][SQL] To resolve Null pointer except...
GitHub user priyankagargnitk opened a pull request: https://github.com/apache/spark/pull/15479 [SPARK-17884][SQL] To resolve Null pointer exception when casting from empty string to interval type ## What changes were proposed in this pull request? This change adds a check in castToInterval method of Cast expression , such that if converted value is null , then isNull variable should be set to true. Earlier, the expression Cast(Literal(), CalendarIntervalType) was throwing NullPointerException because of the above mentioned reason. ## How was this patch tested? Added test case in CastSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-17884 You can merge this pull request into a Git repository by running: $ git pull https://github.com/priyankagargnitk/spark cast_empty_string_bug Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15479.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 #15479 commit 6bdbe7d31f7b01727858fe10593b35ac1b2dafad Author: prigarg Date: 2016-10-12T17:14:45Z [SPARK-17884][SQL] To resolve Null pointer exception when casting from empty string to interval type. ## What changes were proposed in this pull request? This change adds a check in castToInterval method of Cast expression , such that if converted value is null , then isNull variable should be set to true. Earlier, the expression Cast(Literal(), CalendarIntervalType) was throwing NullPointerException because of the above mentioned reason. ## How was this patch tested? Added test case in CastSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-17884 Author: prigarg Closes #15449 from priyankagargnitk/SPARK-17884. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15449: [SPARK-17884][SQL] To resolve Null pointer exception whe...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15449 Hi rxin, Can we merge the same change in branch 1.6 as well... As we are still using spark 1.6 and need this change? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15449: [SPARK-17884][SQL] To resolve Null pointer exception whe...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15449 Thanks rxin --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15449: [SPARK-17884][SQL] To resolve Null pointer except...
GitHub user priyankagargnitk opened a pull request: https://github.com/apache/spark/pull/15449 [SPARK-17884][SQL] To resolve Null pointer exception when casting from empty string to interval type. ## What changes were proposed in this pull request? This change adds a check in castToInterval method of Cast expression , such that if converted value is null , then isNull variable should be set to true. Earlier, the expression Cast(Literal(), CalendarIntervalType) was throwing NullPointerException because of the above mentioned reason. ## How was this patch tested? Added test case in CastSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-17884 You can merge this pull request into a Git repository by running: $ git pull https://github.com/priyankagargnitk/spark SPARK-17884 Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15449.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 #15449 commit 9dc99adecfadb60ef402f68e956a0f94734b1226 Author: prigarg Date: 2016-10-12T08:51:13Z [SPARK-17884][SQL] To resolve Null pointer exception when casting from empty string to interval type. ## What changes were proposed in this pull request? This change adds a check in castToInterval method of Cast expression , such that if converted value is null , then isNull variable should be set to true. Earlier, the expression Cast(Literal(), CalendarIntervalType) was throwing NullPointerException because of the above mentioned reason. ## How was this patch tested? Added test case in CastSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-17884 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15294: [SPARK-17619][SQL] To add support for pattern matching i...
Github user priyankagargnitk commented on the issue: https://github.com/apache/spark/pull/15294 Reverted the previous changes that i did in ArrayContains and now a new expression is added as ArrayContainsWithPatternMatch. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15294: [SPARK-17619][SQL] To add support for pattern mat...
Github user priyankagargnitk commented on a diff in the pull request: https://github.com/apache/spark/pull/15294#discussion_r81103845 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/collectionOperations.scala --- @@ -191,11 +193,15 @@ case class SortArray(base: Expression, ascendingOrder: Expression) } /** - * Checks if the array (left) has the element (right) + * Checks if the array (left) has the element (right) and pattern match in + * case left is Array of type string */ + @ExpressionDescription( - usage = "_FUNC_(array, value) - Returns TRUE if the array contains the value.", - extended = " > SELECT _FUNC_(array(1, 2, 3), 2);\n true") + usage = """_FUNC_(array, value) - Returns TRUE if the array contains the value or --- End diff -- So, in that case we can add one more expression , something like ArrayContainsWithPatternMatch? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #15294: [SPARK-17619][SQL] To add support for pattern mat...
GitHub user priyankagargnitk opened a pull request: https://github.com/apache/spark/pull/15294 [SPARK-17619][SQL] To add support for pattern matching in ArrayContains expression ## What changes were proposed in this pull request? This change adds support for pattern matching in arrayContains expression for the string arrays. For eg. a. arrayContains ( Seq ( â\\d\\d\\s-\\s\\d\\dâ, null, "", "pattern"), "12 - 20" ) returns true b. arrayContains ( Seq ( "\\d\\d\\s-\\s\\d\\d", "", "pattern"), "132 - 20" ) ) returns false c. arrayContains ( Seq ( "\\d\\d\\s-\\s\\d\\d", null, ââ, "pattern"), "132 - 20" ) ) returns null This change is completely backward compatible. ## How was this patch tested? Added some more test cases for pattern match use case in the following: a. CollectionFunctionsSuite.scala b. DataFrameFunctionsSuite.scala c. ExpressionToSQLSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-17619 You can merge this pull request into a Git repository by running: $ git pull https://github.com/priyankagargnitk/spark array_contains_with_pattern_match Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/15294.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 #15294 commit 69f63092ddcb04ea10186d71d407b4886dea3245 Author: Priyanka Garg Date: 2016-09-29T08:13:08Z [SPARK-17619][SQL] To add support for pattern matching in ArrayContains Expression. ## What changes were proposed in this pull request? This change adds support for pattern matching in arrayContains expression for the string arrays. For eg. a. arrayContains ( Seq ( â\\d\\d\\s-\\s\\d\\dâ, null, "", "pattern"), "12 - 20" ) returns true b. arrayContains ( Seq ( "\\d\\d\\s-\\s\\d\\d", "", "pattern"), "132 - 20" ) ) returns false c. arrayContains ( Seq ( "\\d\\d\\s-\\s\\d\\d", null, ââ, "pattern"), "132 - 20" ) ) returns null This change is completely backward compatible. ## How was this patch tested? Added some more test cases for pattern match use case in the following: a. CollectionFunctionsSuite.scala b. DataFrameFunctionsSuite.scala c. ExpressionToSQLSuite.scala jira entry for detail: https://issues.apache.org/jira/browse/SPARK-17619 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
