Fix doc (replace T with V)

Author: sryza

core/src/main/scala/org/apache/spark/api/java/JavaPairRDD.scala

@@ -231,7 +231,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])
   /**
    * Aggregate the values of each key, using given combine functions and a neutral "zero value".
    * This function can return a different result type, U, than the type of the values in this RDD,
-   * V. Thus, we need one operation for merging a T into a U and one operation for merging two U's,
+   * V. Thus, we need one operation for merging a V into a U and one operation for merging two U's,
    * as in scala.TraversableOnce. The former operation is used for merging values within a partition,
    * and the latter is used for merging values between partitions. To avoid memory allocation, both
    * of these functions are allowed to modify and return their first argument instead of creating a
@@ -246,7 +246,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])
   /**
    * Aggregate the values of each key, using given combine functions and a neutral "zero value".
    * This function can return a different result type, U, than the type of the values in this RDD,
-   * V. Thus, we need one operation for merging a T into a U and one operation for merging two U's,
+   * V. Thus, we need one operation for merging a V into a U and one operation for merging two U's,
    * as in scala.TraversableOnce. The former operation is used for merging values within a partition,
    * and the latter is used for merging values between partitions. To avoid memory allocation, both
    * of these functions are allowed to modify and return their first argument instead of creating a
@@ -261,7 +261,7 @@ class JavaPairRDD[K, V](val rdd: RDD[(K, V)])
   /**
    * Aggregate the values of each key, using given combine functions and a neutral "zero value".
    * This function can return a different result type, U, than the type of the values in this RDD,
-   * V. Thus, we need one operation for merging a T into a U and one operation for merging two U's.
+   * V. Thus, we need one operation for merging a V into a U and one operation for merging two U's.
    * The former operation is used for merging values within a partition, and the latter is used for
    * merging values between partitions. To avoid memory allocation, both of these functions are
    * allowed to modify and return their first argument instead of creating a new U.

core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala

@@ -121,7 +121,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
   /**
    * Aggregate the values of each key, using given combine functions and a neutral "zero value".
    * This function can return a different result type, U, than the type of the values in this RDD,
-   * V. Thus, we need one operation for merging a T into a U and one operation for merging two U's,
+   * V. Thus, we need one operation for merging a V into a U and one operation for merging two U's,
    * as in scala.TraversableOnce. The former operation is used for merging values within a partition,
    * and the latter is used for merging values between partitions. To avoid memory allocation, both
    * of these functions are allowed to modify and return their first argument instead of creating a
@@ -143,7 +143,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
   /**
    * Aggregate the values of each key, using given combine functions and a neutral "zero value".
    * This function can return a different result type, U, than the type of the values in this RDD,
-   * V. Thus, we need one operation for merging a T into a U and one operation for merging two U's,
+   * V. Thus, we need one operation for merging a V into a U and one operation for merging two U's,
    * as in scala.TraversableOnce. The former operation is used for merging values within a partition,
    * and the latter is used for merging values between partitions. To avoid memory allocation, both
    * of these functions are allowed to modify and return their first argument instead of creating a
@@ -157,7 +157,7 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
   /**
    * Aggregate the values of each key, using given combine functions and a neutral "zero value".
    * This function can return a different result type, U, than the type of the values in this RDD,
-   * V. Thus, we need one operation for merging a T into a U and one operation for merging two U's,
+   * V. Thus, we need one operation for merging a V into a U and one operation for merging two U's,
    * as in scala.TraversableOnce. The former operation is used for merging values within a partition,
    * and the latter is used for merging values between partitions. To avoid memory allocation, both
    * of these functions are allowed to modify and return their first argument instead of creating a

python/pyspark/rdd.py

@@ -1183,7 +1183,7 @@ def aggregateByKey(self, zeroValue, seqFunc, combFunc, numPartitions=None):
         """
         Aggregate the values of each key, using given combine functions and a neutral "zero value".
         This function can return a different result type, U, than the type of the values in this RDD,
-        V. Thus, we need one operation for merging a T into a U and one operation for merging two U's,
+        V. Thus, we need one operation for merging a V into a U and one operation for merging two U's,
         The former operation is used for merging values within a partition, and the latter is used
         for merging values between partitions. To avoid memory allocation, both of these functions are
         allowed to modify and return their first argument instead of creating a new U.