Fix scaladoc errors due to missing links, which are generating build warnings, from some recent doc changes. We apparently can't generate links outside the module.

Author: srowen

mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala

@@ -73,7 +73,7 @@ class SVD {
    * U is a row-by-row dense matrix
    * S is a simple double array of singular values
    * V is a 2d array matrix
-   * See [[denseSVD]] for more documentation 
+   * See `denseSVD` for more documentation
    */
   def compute(matrix: RDD[Array[Double]]):
   (RDD[Array[Double]], Array[Double], Array[Array[Double]]) = {

sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala

@@ -70,8 +70,8 @@ case class Exchange(newPartitioning: Partitioning, child: SparkPlan) extends Una
 }
 
 /**
- * Ensures that the [[catalyst.plans.physical.Partitioning Partitioning]] of input data meets the
- * [[catalyst.plans.physical.Distribution Distribution]] requirements for each operator by inserting
+ * Ensures that the Partitioning of input data meets the
+ * Distribution requirements for each operator by inserting
  * [[Exchange]] Operators where required.
  */
 object AddExchange extends Rule[SparkPlan] {
@@ -133,4 +133,4 @@ object AddExchange extends Rule[SparkPlan] {
         operator.withNewChildren(repartitionedChildren)
       }
   }
-}
+}

sql/core/src/main/scala/org/apache/spark/sql/execution/Generate.scala

@@ -20,7 +20,7 @@ package org.apache.spark.sql.execution
 import org.apache.spark.sql.catalyst.expressions.{Generator, JoinedRow, Literal, Projection}
 
 /**
- * Applies a [[catalyst.expressions.Generator Generator]] to a stream of input rows, combining the
+ * Applies a Generator to a stream of input rows, combining the
  * output of each into a new stream of rows.  This operation is similar to a `flatMap` in functional
  * programming with one important additional feature, which allows the input rows to be joined with
  * their output.

sql/hive/src/main/scala/org/apache/spark/SparkHadoopWriter.scala

@@ -30,7 +30,7 @@ import org.apache.hadoop.io.Writable
 
 /**
  * Internal helper class that saves an RDD using a Hive OutputFormat.
- * It is based on [[SparkHadoopWriter]].
+ * It is based on SparkHadoopWriter.
  */
 protected[spark]
 class SparkHiveHadoopWriter(

sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala

@@ -137,7 +137,7 @@ class HiveMetastoreCatalog(hive: HiveContext) extends Catalog with Logging {
 
   /**
    * UNIMPLEMENTED: It needs to be decided how we will persist in-memory tables to the metastore.
-   * For now, if this functionality is desired mix in the in-memory [[OverrideCatalog]].
+   * For now, if this functionality is desired mix in the in-memory OverrideCatalog.
    */
   override def registerTable(
       databaseName: Option[String], tableName: String, plan: LogicalPlan): Unit = ???

sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveQl.scala

@@ -122,7 +122,7 @@ object HiveQl {
 
   /**
    * A set of implicit transformations that allow Hive ASTNodes to be rewritten by transformations
-   * similar to [[catalyst.trees.TreeNode]].
+   * similar to TreeNode.
    *
    * Note that this should be considered very experimental and is not indented as a replacement
    * for TreeNode.  Primarily it should be noted ASTNodes are not immutable and do not appear to

sql/hive/src/main/scala/org/apache/spark/sql/hive/hiveUdfs.scala

@@ -359,7 +359,7 @@ case class HiveGenericUdaf(
 
 /**
  * Converts a Hive Generic User Defined Table Generating Function (UDTF) to a
- * [[catalyst.expressions.Generator Generator]].  Note that the semantics of Generators do not allow
+ * Generator.  Note that the semantics of Generators do not allow
  * Generators to maintain state in between input rows.  Thus UDTFs that rely on partitioning
  * dependent operations like calls to `close()` before producing output will not operate the same as
  * in Hive.  However, in practice this should not affect compatibility for most sane UDTFs