[SPARK-13274] Fix Aggregator Links on GroupedDataset Scala API

raelawang · rxin · commit 719973b05ef6 · 2016-02-10T17:00:54.000-08:00
Update Aggregator links to point to #org.apache.spark.sql.expressions.Aggregator Author: raela <raela@databricks.com> Closes #11158 from raelawang/master.
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala b/sql/core/src/main/scala/org/apache/spark/sql/GroupedDataset.scala
@@ -101,7 +101,8 @@ class GroupedDataset[K, V] private[sql](
    *
    * This function does not support partial aggregation, and as a result requires shuffling all
    * the data in the [[Dataset]]. If an application intends to perform an aggregation over each
-   * key, it is best to use the reduce function or an [[Aggregator]].
+   * key, it is best to use the reduce function or an
+   * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].
    *
    * Internally, the implementation will spill to disk if any given group is too large to fit into
    * memory.  However, users must take care to avoid materializing the whole iterator for a group
@@ -128,7 +129,8 @@ class GroupedDataset[K, V] private[sql](
    *
    * This function does not support partial aggregation, and as a result requires shuffling all
    * the data in the [[Dataset]]. If an application intends to perform an aggregation over each
-   * key, it is best to use the reduce function or an [[Aggregator]].
+   * key, it is best to use the reduce function or an
+   * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].
    *
    * Internally, the implementation will spill to disk if any given group is too large to fit into
    * memory.  However, users must take care to avoid materializing the whole iterator for a group
@@ -148,7 +150,8 @@ class GroupedDataset[K, V] private[sql](
    *
    * This function does not support partial aggregation, and as a result requires shuffling all
    * the data in the [[Dataset]]. If an application intends to perform an aggregation over each
-   * key, it is best to use the reduce function or an [[Aggregator]].
+   * key, it is best to use the reduce function or an
+   * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].
    *
    * Internally, the implementation will spill to disk if any given group is too large to fit into
    * memory.  However, users must take care to avoid materializing the whole iterator for a group
@@ -169,7 +172,8 @@ class GroupedDataset[K, V] private[sql](
    *
    * This function does not support partial aggregation, and as a result requires shuffling all
    * the data in the [[Dataset]]. If an application intends to perform an aggregation over each
-   * key, it is best to use the reduce function or an [[Aggregator]].
+   * key, it is best to use the reduce function or an
+   * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].
    *
    * Internally, the implementation will spill to disk if any given group is too large to fit into
    * memory.  However, users must take care to avoid materializing the whole iterator for a group

Original file line number	Diff line number	Diff line change
`@@ -101,7 +101,8 @@ class GroupedDataset[K, V] private[sql](`
`101`	`101`	`*`
`102`	`102`	`* This function does not support partial aggregation, and as a result requires shuffling all`
`103`	`103`	`* the data in the [[Dataset]]. If an application intends to perform an aggregation over each`
`104`		`- * key, it is best to use the reduce function or an [[Aggregator]].`
	`104`	`+ * key, it is best to use the reduce function or an`
	`105`	`+ * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].`
`105`	`106`	`*`
`106`	`107`	`* Internally, the implementation will spill to disk if any given group is too large to fit into`
`107`	`108`	`* memory. However, users must take care to avoid materializing the whole iterator for a group`
`@@ -128,7 +129,8 @@ class GroupedDataset[K, V] private[sql](`
`128`	`129`	`*`
`129`	`130`	`* This function does not support partial aggregation, and as a result requires shuffling all`
`130`	`131`	`* the data in the [[Dataset]]. If an application intends to perform an aggregation over each`
`131`		`- * key, it is best to use the reduce function or an [[Aggregator]].`
	`132`	`+ * key, it is best to use the reduce function or an`
	`133`	`+ * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].`
`132`	`134`	`*`
`133`	`135`	`* Internally, the implementation will spill to disk if any given group is too large to fit into`
`134`	`136`	`* memory. However, users must take care to avoid materializing the whole iterator for a group`
`@@ -148,7 +150,8 @@ class GroupedDataset[K, V] private[sql](`
`148`	`150`	`*`
`149`	`151`	`* This function does not support partial aggregation, and as a result requires shuffling all`
`150`	`152`	`* the data in the [[Dataset]]. If an application intends to perform an aggregation over each`
`151`		`- * key, it is best to use the reduce function or an [[Aggregator]].`
	`153`	`+ * key, it is best to use the reduce function or an`
	`154`	`+ * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].`
`152`	`155`	`*`
`153`	`156`	`* Internally, the implementation will spill to disk if any given group is too large to fit into`
`154`	`157`	`* memory. However, users must take care to avoid materializing the whole iterator for a group`
`@@ -169,7 +172,8 @@ class GroupedDataset[K, V] private[sql](`
`169`	`172`	`*`
`170`	`173`	`* This function does not support partial aggregation, and as a result requires shuffling all`
`171`	`174`	`* the data in the [[Dataset]]. If an application intends to perform an aggregation over each`
`172`		`- * key, it is best to use the reduce function or an [[Aggregator]].`
	`175`	`+ * key, it is best to use the reduce function or an`
	`176`	`+ * [[org.apache.spark.sql.expressions#Aggregator Aggregator]].`
`173`	`177`	`*`
`174`	`178`	`* Internally, the implementation will spill to disk if any given group is too large to fit into`
`175`	`179`	`* memory. However, users must take care to avoid materializing the whole iterator for a group`