Fixed coding style issues in Spark SQL

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/ScalaReflection.scala

@@ -0,0 +1,69 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+package catalyst
+
+import org.apache.spark.sql.catalyst.expressions.Attribute
+import org.apache.spark.sql.catalyst.expressions.AttributeReference
+import org.apache.spark.sql.catalyst.plans.logical.LocalRelation
+import org.apache.spark.sql.catalyst.types._
+
+/**
+ * Provides experimental support for generating catalyst schemas for scala objects.
+ */
+object ScalaReflection {
+  import scala.reflect.runtime.universe._
+
+  /** Returns a Sequence of attributes for the given case class type. */
+  def attributesFor[T: TypeTag]: Seq[Attribute] = schemaFor[T] match {
+    case s: StructType =>
+      s.fields.map(f => AttributeReference(f.name, f.dataType, nullable = true)())
+  }
+
+  /** Returns a catalyst DataType for the given Scala Type using reflection. */
+  def schemaFor[T: TypeTag]: DataType = schemaFor(typeOf[T])
+
+  /** Returns a catalyst DataType for the given Scala Type using reflection. */
+  def schemaFor(tpe: `Type`): DataType = tpe match {
+    case t if t <:< typeOf[Product] =>
+      val params = t.member("<init>": TermName).asMethod.paramss
+      StructType(
+        params.head.map(p => StructField(p.name.toString, schemaFor(p.typeSignature), true)))
+    case t if t <:< typeOf[Seq[_]] =>
+      val TypeRef(_, _, Seq(elementType)) = t
+      ArrayType(schemaFor(elementType))
+    case t if t <:< typeOf[String] => StringType
+    case t if t <:< definitions.IntTpe => IntegerType
+    case t if t <:< definitions.LongTpe => LongType
+    case t if t <:< definitions.DoubleTpe => DoubleType
+    case t if t <:< definitions.ShortTpe => ShortType
+    case t if t <:< definitions.ByteTpe => ByteType
+  }
+
+  implicit class CaseClassRelation[A <: Product : TypeTag](data: Seq[A]) {
+
+    /**
+     * Implicitly added to Sequences of case class objects.  Returns a catalyst logical relation
+     * for the the data in the sequence.
+     */
+    def asRelation: LocalRelation = {
+      val output = attributesFor[A]
+      LocalRelation(output, data)
+    }
+  }
+}

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/SqlParser.scala

@@ -17,32 +17,28 @@
 
 package org.apache.spark.sql.catalyst
 
-import scala.util.matching.Regex
-import scala.util.parsing.combinator._
+import scala.util.parsing.combinator.lexical.StdLexical
+import scala.util.parsing.combinator.syntactical.StandardTokenParsers
 import scala.util.parsing.input.CharArrayReader.EofCh
-import lexical._
-import syntactical._
-import token._
 
-import analysis._
-import expressions._
-import plans._
-import plans.logical._
-import types._
+import org.apache.spark.sql.catalyst.analysis._
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.types._
 
 /**
- * A very simple SQL parser.  Based loosly on:
+ * A very simple SQL parser.  Based loosely on:
  * https://github.com/stephentu/scala-sql-parser/blob/master/src/main/scala/parser.scala
  *
  * Limitations:
  *  - Only supports a very limited subset of SQL.
  *  - Keywords must be capital.
  *
  * This is currently included mostly for illustrative purposes.  Users wanting more complete support
- * for a SQL like language should checkout the HiveQL support in the sql/hive subproject.
+ * for a SQL like language should checkout the HiveQL support in the sql/hive sub-project.
  */
 class SqlParser extends StandardTokenParsers {
-
   def apply(input: String): LogicalPlan = {
     phrase(query)(new lexical.Scanner(input)) match {
       case Success(r, x) => r
@@ -196,7 +192,7 @@ class SqlParser extends StandardTokenParsers {
 
   protected lazy val from: Parser[LogicalPlan] = FROM ~> relations
 
-  // Based very loosly on the MySQL Grammar.
+  // Based very loosely on the MySQL Grammar.
   // http://dev.mysql.com/doc/refman/5.0/en/join.html
   protected lazy val relations: Parser[LogicalPlan] =
     relation ~ "," ~ relation ^^ { case r1 ~ _ ~ r2 => Join(r1, r2, Inner, None) } |
@@ -261,9 +257,9 @@ class SqlParser extends StandardTokenParsers {
     andExpression * (OR ^^^ { (e1: Expression, e2: Expression) => Or(e1,e2) })
 
   protected lazy val andExpression: Parser[Expression] =
-    comparisionExpression * (AND ^^^ { (e1: Expression, e2: Expression) => And(e1,e2) })
+    comparisonExpression * (AND ^^^ { (e1: Expression, e2: Expression) => And(e1,e2) })
 
-  protected lazy val comparisionExpression: Parser[Expression] =
+  protected lazy val comparisonExpression: Parser[Expression] =
     termExpression ~ "=" ~ termExpression ^^ { case e1 ~ _ ~ e2 => Equals(e1, e2) } |
     termExpression ~ "<" ~ termExpression ^^ { case e1 ~ _ ~ e2 => LessThan(e1, e2) } |
     termExpression ~ "<=" ~ termExpression ^^ { case e1 ~ _ ~ e2 => LessThanOrEqual(e1, e2) } |

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala

@@ -19,9 +19,10 @@ package org.apache.spark.sql
 package catalyst
 package analysis
 
-import expressions._
-import plans.logical._
-import rules._
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.rules._
+
 
 /**
  * A trivial [[Analyzer]] with an [[EmptyCatalog]] and [[EmptyFunctionRegistry]]. Used for testing

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Catalog.scala

@@ -19,9 +19,10 @@ package org.apache.spark.sql
 package catalyst
 package analysis
 
-import plans.logical.{LogicalPlan, Subquery}
 import scala.collection.mutable
 
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Subquery}
+
 /**
  * An interface for looking up relations by name.  Used by an [[Analyzer]].
  */

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 package catalyst
 package analysis
 
-import expressions._
+import org.apache.spark.sql.catalyst.expressions.Expression
 
 /** A catalog for looking up user defined functions, used by an [[Analyzer]]. */
 trait FunctionRegistry {

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/HiveTypeCoercion.scala

@@ -19,10 +19,10 @@ package org.apache.spark.sql
 package catalyst
 package analysis
 
-import expressions._
-import plans.logical._
-import rules._
-import types._
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.logical.{LogicalPlan, Project, Union}
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.types._
 
 /**
  * A collection of [[catalyst.rules.Rule Rules]] that can be used to coerce differing types that

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/MultiInstanceRelation.scala

@@ -18,14 +18,14 @@
 package org.apache.spark.sql.catalyst
 package analysis
 
-import plans.logical.LogicalPlan
-import rules._
+import org.apache.spark.sql.catalyst.rules.Rule
+import org.apache.spark.sql.catalyst.plans.logical.LogicalPlan
 
 /**
  * A trait that should be mixed into query operators where an single instance might appear multiple
  * times in a logical query plan.  It is invalid to have multiple copies of the same attribute
- * produced by distinct operators in a query tree as this breaks the gurantee that expression
- * ids, which are used to differentate attributes, are unique.
+ * produced by distinct operators in a query tree as this breaks the guarantee that expression
+ * ids, which are used to differentiate attributes, are unique.
  *
  * Before analysis, all operators that include this trait will be asked to produce a new version
  * of itself with globally unique expression ids.

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/package.scala

@@ -15,6 +15,7 @@
  * limitations under the License.
  */
 
+package org.apache.spark.sql
 package catalyst
 
 /**

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala

@@ -19,9 +19,9 @@ package org.apache.spark.sql
 package catalyst
 package analysis
 
-import expressions._
-import plans.logical.BaseRelation
-import trees.TreeNode
+import org.apache.spark.sql.catalyst.expressions.{Alias, Attribute, Expression, NamedExpression}
+import org.apache.spark.sql.catalyst.plans.logical.BaseRelation
+import org.apache.spark.sql.catalyst.trees.TreeNode
 
 /**
  * Thrown when an invalid attempt is made to access a property of a tree that has yet to be fully
@@ -95,7 +95,7 @@ case class Star(
       // If there is no table specified, use all input attributes.
       case None => input
       // If there is a table, pick out attributes that are part of this table.
-      case Some(table) => input.filter(_.qualifiers contains table)
+      case Some(t) => input.filter(_.qualifiers contains t)
     }
     val mappedAttributes = expandedAttributes.map(mapFunction).zip(input).map {
       case (n: NamedExpression, _) => n

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/dsl/package.scala

@@ -19,58 +19,12 @@ package org.apache.spark.sql
 package catalyst
 
 import scala.language.implicitConversions
-import scala.reflect.runtime.universe.TypeTag
 
-import analysis.UnresolvedAttribute
-import expressions._
-import plans._
-import plans.logical._
-import types._
-
-/**
- * Provides experimental support for generating catalyst schemas for scala objects.
- */
-object ScalaReflection {
-  import scala.reflect.runtime.universe._
-
-  /** Returns a Sequence of attributes for the given case class type. */
-  def attributesFor[T: TypeTag]: Seq[Attribute] = schemaFor[T] match {
-    case s: StructType =>
-      s.fields.map(f => AttributeReference(f.name, f.dataType, nullable = true)())
-  }
-
-  /** Returns a catalyst DataType for the given Scala Type using reflection. */
-  def schemaFor[T: TypeTag]: DataType = schemaFor(typeOf[T])
-
-  /** Returns a catalyst DataType for the given Scala Type using reflection. */
-  def schemaFor(tpe: `Type`): DataType = tpe match {
-    case t if t <:< typeOf[Product] =>
-      val params = t.member("<init>": TermName).asMethod.paramss
-      StructType(
-        params.head.map(p => StructField(p.name.toString, schemaFor(p.typeSignature), true)))
-    case t if t <:< typeOf[Seq[_]] =>
-      val TypeRef(_, _, Seq(elementType)) = t
-      ArrayType(schemaFor(elementType))
-    case t if t <:< typeOf[String] => StringType
-    case t if t <:< definitions.IntTpe => IntegerType
-    case t if t <:< definitions.LongTpe => LongType
-    case t if t <:< definitions.DoubleTpe => DoubleType
-    case t if t <:< definitions.ShortTpe => ShortType
-    case t if t <:< definitions.ByteTpe => ByteType
-  }
-
-  implicit class CaseClassRelation[A <: Product : TypeTag](data: Seq[A]) {
-
-    /**
-     * Implicitly added to Sequences of case class objects.  Returns a catalyst logical relation
-     * for the the data in the sequence.
-     */
-    def asRelation: LocalRelation = {
-      val output = attributesFor[A]
-      LocalRelation(output, data)
-    }
-  }
-}
+import org.apache.spark.sql.catalyst.analysis.UnresolvedAttribute
+import org.apache.spark.sql.catalyst.expressions._
+import org.apache.spark.sql.catalyst.plans.logical._
+import org.apache.spark.sql.catalyst.plans.{Inner, JoinType}
+import org.apache.spark.sql.catalyst.types._
 
 /**
  * A collection of implicit conversions that create a DSL for constructing catalyst data structures.

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/errors/package.scala

@@ -18,15 +18,16 @@
 package org.apache.spark.sql
 package catalyst
 
-import trees._
+import org.apache.spark.sql.catalyst.trees.TreeNode
 
 /**
  * Functions for attaching and retrieving trees that are associated with errors.
  */
 package object errors {
 
-  class TreeNodeException[TreeType <: TreeNode[_]]
-    (tree: TreeType, msg: String, cause: Throwable) extends Exception(msg, cause) {
+  class TreeNodeException[TreeType <: TreeNode[_]](
+      tree: TreeType, msg: String, cause: Throwable)
+    extends Exception(msg, cause) {
 
     // Yes, this is the same as a default parameter, but... those don't seem to work with SBT
     // external project dependencies for some reason.

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/BoundAttribute.scala

@@ -19,10 +19,9 @@ package org.apache.spark.sql
 package catalyst
 package expressions
 
-import rules._
-import errors._
-
-import catalyst.plans.QueryPlan
+import org.apache.spark.sql.catalyst.errors.attachTree
+import org.apache.spark.sql.catalyst.plans.QueryPlan
+import org.apache.spark.sql.catalyst.rules.Rule
 
 /**
  * A bound reference points to a specific slot in the input tuple, allowing the actual value

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 package catalyst
 package expressions
 
-import types._
+import org.apache.spark.sql.catalyst.types._
 
 /** Cast the child expression to the target data type. */
 case class Cast(child: Expression, dataType: DataType) extends UnaryExpression {
@@ -40,7 +40,7 @@ case class Cast(child: Expression, dataType: DataType) extends UnaryExpression {
     case (StringType, ShortType) => a: Any => castOrNull(a, _.toShort)
     case (StringType, ByteType) => a: Any => castOrNull(a, _.toByte)
     case (StringType, DecimalType) => a: Any => castOrNull(a, BigDecimal(_))
-    case (BooleanType, ByteType) => a: Any => a match {
+    case (BooleanType, ByteType) => {
       case null => null
       case true => 1.toByte
       case false => 0.toByte

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Expression.scala

@@ -19,9 +19,9 @@ package org.apache.spark.sql
 package catalyst
 package expressions
 
-import errors._
-import trees._
-import types._
+import org.apache.spark.sql.catalyst.trees.TreeNode
+import org.apache.spark.sql.catalyst.types.{DataType, FractionalType, IntegralType, NumericType}
+import org.apache.spark.sql.catalyst.errors.TreeNodeException
 
 abstract class Expression extends TreeNode[Expression] {
   self: Product =>

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Rand.scala

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 package catalyst
 package expressions
 
-import types.DoubleType
+import org.apache.spark.sql.catalyst.types.DoubleType
 
 case object Rand extends LeafExpression {
   def dataType = DoubleType

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Row.scala

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 package catalyst
 package expressions
 
-import types._
+import org.apache.spark.sql.catalyst.types.NativeType
 
 /**
  * Represents one row of output from a relational operator.  Allows both generic access by ordinal,

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUdf.scala

@@ -19,7 +19,7 @@ package org.apache.spark.sql
 package catalyst
 package expressions
 
-import types._
+import org.apache.spark.sql.catalyst.types.DataType
 
 case class ScalaUdf(function: AnyRef, dataType: DataType, children: Seq[Expression])
   extends Expression {

sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/WrapDynamic.scala

@@ -21,7 +21,7 @@ package expressions
 
 import scala.language.dynamics
 
-import types._
+import org.apache.spark.sql.catalyst.types.DataType
 
 case object DynamicType extends DataType