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Commit 719973b0 authored by raela's avatar raela Committed by Reynold Xin
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[SPARK-13274] Fix Aggregator Links on GroupedDataset Scala API

Update Aggregator links to point to #org.apache.spark.sql.expressions.Aggregator

Author: raela <raela@databricks.com>

Closes #11158 from raelawang/master.
parent 0902e202
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......@@ -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
......
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