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Posted to commits@spark.apache.org by rx...@apache.org on 2015/02/05 04:52:01 UTC
spark git commit: [SQL][DataFrame] Minor cleanup.
Repository: spark
Updated Branches:
refs/heads/master dba98bf69 -> 6b4c7f080
[SQL][DataFrame] Minor cleanup.
1. Removed LocalHiveContext in Python.
2. Reduced DSL UDF support from 22 arguments to 10 arguments so JavaDoc/ScalaDoc look nicer.
Author: Reynold Xin <rx...@databricks.com>
Closes #4374 from rxin/df-style and squashes the following commits:
e493342 [Reynold Xin] [SQL][DataFrame] Minor cleanup.
Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/6b4c7f08
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/6b4c7f08
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/6b4c7f08
Branch: refs/heads/master
Commit: 6b4c7f08068b6099145ab039d0499e3fef68e2e9
Parents: dba98bf
Author: Reynold Xin <rx...@databricks.com>
Authored: Wed Feb 4 19:51:48 2015 -0800
Committer: Reynold Xin <rx...@databricks.com>
Committed: Wed Feb 4 19:51:48 2015 -0800
----------------------------------------------------------------------
python/pyspark/sql.py | 11 --
.../main/scala/org/apache/spark/sql/Dsl.scala | 196 +------------------
2 files changed, 2 insertions(+), 205 deletions(-)
----------------------------------------------------------------------
http://git-wip-us.apache.org/repos/asf/spark/blob/6b4c7f08/python/pyspark/sql.py
----------------------------------------------------------------------
diff --git a/python/pyspark/sql.py b/python/pyspark/sql.py
index 417db34..3ac8ea5 100644
--- a/python/pyspark/sql.py
+++ b/python/pyspark/sql.py
@@ -1683,17 +1683,6 @@ class HiveContext(SQLContext):
return self._jvm.HiveContext(self._jsc.sc())
-class LocalHiveContext(HiveContext):
-
- def __init__(self, sparkContext, sqlContext=None):
- HiveContext.__init__(self, sparkContext, sqlContext)
- warnings.warn("LocalHiveContext is deprecated. "
- "Use HiveContext instead.", DeprecationWarning)
-
- def _get_hive_ctx(self):
- return self._jvm.LocalHiveContext(self._jsc.sc())
-
-
def _create_row(fields, values):
row = Row(*values)
row.__FIELDS__ = fields
http://git-wip-us.apache.org/repos/asf/spark/blob/6b4c7f08/sql/core/src/main/scala/org/apache/spark/sql/Dsl.scala
----------------------------------------------------------------------
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/Dsl.scala b/sql/core/src/main/scala/org/apache/spark/sql/Dsl.scala
index 9afe496..6bf21dd 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/Dsl.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/Dsl.scala
@@ -209,7 +209,7 @@ object Dsl {
// scalastyle:off
/* Use the following code to generate:
- (0 to 22).map { x =>
+ (0 to 10).map { x =>
val types = (1 to x).foldRight("RT")((i, s) => {s"A$i, $s"})
val typeTags = (1 to x).map(i => s"A$i: TypeTag").foldLeft("RT: TypeTag")(_ + ", " + _)
println(s"""
@@ -222,7 +222,7 @@ object Dsl {
}""")
}
- (0 to 22).map { x =>
+ (0 to 10).map { x =>
val args = (1 to x).map(i => s"arg$i: Column").mkString(", ")
val fTypes = Seq.fill(x + 1)("_").mkString(", ")
val argsInUdf = (1 to x).map(i => s"arg$i.expr").mkString(", ")
@@ -325,102 +325,6 @@ object Dsl {
UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
}
- /**
- * Defines a user-defined function of 11 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag](f: Function11[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 12 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag](f: Function12[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 13 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag](f: Function13[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 14 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag](f: Function14[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 15 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag](f: Function15[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 16 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag](f: Function16[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 17 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag](f: Function17[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 18 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag](f: Function18[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 19 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag](f: Function19[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 20 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag, A20: TypeTag](f: Function20[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 21 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag, A20: TypeTag, A21: TypeTag](f: Function21[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
- /**
- * Defines a user-defined function of 22 arguments as user-defined function (UDF).
- * The data types are automatically inferred based on the function's signature.
- */
- def udf[RT: TypeTag, A1: TypeTag, A2: TypeTag, A3: TypeTag, A4: TypeTag, A5: TypeTag, A6: TypeTag, A7: TypeTag, A8: TypeTag, A9: TypeTag, A10: TypeTag, A11: TypeTag, A12: TypeTag, A13: TypeTag, A14: TypeTag, A15: TypeTag, A16: TypeTag, A17: TypeTag, A18: TypeTag, A19: TypeTag, A20: TypeTag, A21: TypeTag, A22: TypeTag](f: Function22[A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, A22, RT]): UserDefinedFunction = {
- UserDefinedFunction(f, ScalaReflection.schemaFor(typeTag[RT]).dataType)
- }
-
//////////////////////////////////////////////////////////////////////////////////////////////////
/**
@@ -511,101 +415,5 @@ object Dsl {
ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr))
}
- /**
- * Call a Scala function of 11 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function11[_, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr))
- }
-
- /**
- * Call a Scala function of 12 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function12[_, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr))
- }
-
- /**
- * Call a Scala function of 13 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function13[_, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr))
- }
-
- /**
- * Call a Scala function of 14 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function14[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr))
- }
-
- /**
- * Call a Scala function of 15 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function15[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr))
- }
-
- /**
- * Call a Scala function of 16 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function16[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr))
- }
-
- /**
- * Call a Scala function of 17 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function17[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column, arg17: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr, arg17.expr))
- }
-
- /**
- * Call a Scala function of 18 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function18[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column, arg17: Column, arg18: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr, arg17.expr, arg18.expr))
- }
-
- /**
- * Call a Scala function of 19 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function19[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column, arg17: Column, arg18: Column, arg19: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr, arg17.expr, arg18.expr, arg19.expr))
- }
-
- /**
- * Call a Scala function of 20 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function20[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column, arg17: Column, arg18: Column, arg19: Column, arg20: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr, arg17.expr, arg18.expr, arg19.expr, arg20.expr))
- }
-
- /**
- * Call a Scala function of 21 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function21[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column, arg17: Column, arg18: Column, arg19: Column, arg20: Column, arg21: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr, arg17.expr, arg18.expr, arg19.expr, arg20.expr, arg21.expr))
- }
-
- /**
- * Call a Scala function of 22 arguments as user-defined function (UDF). This requires
- * you to specify the return data type.
- */
- def callUDF(f: Function22[_, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _, _], returnType: DataType, arg1: Column, arg2: Column, arg3: Column, arg4: Column, arg5: Column, arg6: Column, arg7: Column, arg8: Column, arg9: Column, arg10: Column, arg11: Column, arg12: Column, arg13: Column, arg14: Column, arg15: Column, arg16: Column, arg17: Column, arg18: Column, arg19: Column, arg20: Column, arg21: Column, arg22: Column): Column = {
- ScalaUdf(f, returnType, Seq(arg1.expr, arg2.expr, arg3.expr, arg4.expr, arg5.expr, arg6.expr, arg7.expr, arg8.expr, arg9.expr, arg10.expr, arg11.expr, arg12.expr, arg13.expr, arg14.expr, arg15.expr, arg16.expr, arg17.expr, arg18.expr, arg19.expr, arg20.expr, arg21.expr, arg22.expr))
- }
-
// scalastyle:on
}
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