Basic Aggregation, groupByKey and FlatMapGroupsWithState

Author: jaceklaskowski

docs/CheckAnalysis.md

@@ -69,7 +69,7 @@ In the end, `checkAnalysis` [marks the entire logical plan as analyzed](logical-
 * `CheckAnalysis` is requested to [checkSubqueryExpression](#checkSubqueryExpression)
 * Catalyst DSL's [analyze](catalyst-dsl/DslLogicalPlan.md#analyze) operator is used
 * `ExpressionEncoder` is requested to [resolveAndBind](ExpressionEncoder.md#resolveAndBind)
-* [RelationalGroupedDataset.as](RelationalGroupedDataset.md#as) operator is used
+* [RelationalGroupedDataset.as](basic-aggregation/RelationalGroupedDataset.md#as) operator is used
 
 ## <span id="checkShowPartitions"> checkShowPartitions
 

docs/Column.md

@@ -307,7 +307,7 @@ generateAlias(e: Expression): String
 `generateAlias` is used when:
 
 * `Column` is requested to <<named, named>>
-* `RelationalGroupedDataset` is requested to [alias](RelationalGroupedDataset.md#alias)
+* `RelationalGroupedDataset` is requested to [alias](basic-aggregation/RelationalGroupedDataset.md#alias)
 
 === [[named]] `named` Method
 
@@ -321,4 +321,4 @@ named: NamedExpression
 `named` is used when the following operators are used:
 
 * [Dataset.select](spark-sql-dataset-operators.md#select)
-* [KeyValueGroupedDataset.agg](KeyValueGroupedDataset.md#agg)
+* [KeyValueGroupedDataset.agg](basic-aggregation/KeyValueGroupedDataset.md#agg)

docs/Dataset-untyped-transformations.md

@@ -1,6 +1,6 @@
 # Dataset API — Untyped Transformations
 
-**Untyped transformations** are part of the Dataset API for transforming a `Dataset` to a [DataFrame](DataFrame.md), a [Column](Column.md), a [RelationalGroupedDataset](RelationalGroupedDataset.md), a [DataFrameNaFunctions](spark-sql-DataFrameNaFunctions.md) or a [DataFrameStatFunctions](spark-sql-DataFrameStatFunctions.md) (and hence _untyped_).
+**Untyped transformations** are part of the Dataset API for transforming a `Dataset` to a [DataFrame](DataFrame.md), a [Column](Column.md), a [RelationalGroupedDataset](basic-aggregation/RelationalGroupedDataset.md), a [DataFrameNaFunctions](spark-sql-DataFrameNaFunctions.md) or a [DataFrameStatFunctions](spark-sql-DataFrameStatFunctions.md) (and hence _untyped_).
 
 !!! note
     Untyped transformations are the methods in the `Dataset` Scala class that are grouped in `untypedrel` group name, i.e. `@group untypedrel`.

docs/Dataset.md

@@ -35,7 +35,7 @@ When created, `Dataset` requests [QueryExecution](#queryExecution) to [assert an
 
 * [Dataset.select](spark-sql-Dataset-typed-transformations.md#select), [Dataset.randomSplit](spark-sql-Dataset-typed-transformations.md#randomSplit) and [Dataset.mapPartitions](spark-sql-Dataset-typed-transformations.md#mapPartitions) typed transformations are used
 
-* [KeyValueGroupedDataset.agg](KeyValueGroupedDataset.md#agg) operator is used (that requests `KeyValueGroupedDataset` to [aggUntyped](KeyValueGroupedDataset.md#aggUntyped))
+* [KeyValueGroupedDataset.agg](basic-aggregation/KeyValueGroupedDataset.md#agg) operator is used (that requests `KeyValueGroupedDataset` to [aggUntyped](basic-aggregation/KeyValueGroupedDataset.md#aggUntyped))
 
 * [SparkSession.emptyDataset](SparkSession.md#emptyDataset) and [SparkSession.range](SparkSession.md#range) operators are used
 
@@ -550,7 +550,7 @@ Internally, `ofRows` SessionState.md#executePlan[prepares the input `logicalPlan
 
 * `Dataset` is requested to execute <<checkpoint, checkpoint>>, `mapPartitionsInR`, <<withPlan, untyped transformations>> and <<withSetOperator, set-based typed transformations>>
 
-* `RelationalGroupedDataset` is requested to [create a DataFrame from aggregate expressions](RelationalGroupedDataset.md#toDF), `flatMapGroupsInR` and `flatMapGroupsInPandas`
+* `RelationalGroupedDataset` is requested to [create a DataFrame from aggregate expressions](basic-aggregation/RelationalGroupedDataset.md#toDF), `flatMapGroupsInR` and `flatMapGroupsInPandas`
 
 * `SparkSession` is requested to <<SparkSession.md#baseRelationToDataFrame, create a DataFrame from a BaseRelation>>, <<SparkSession.md#createDataFrame, createDataFrame>>, <<SparkSession.md#internalCreateDataFrame, internalCreateDataFrame>>, <<SparkSession.md#sql, sql>> and <<SparkSession.md#table, table>>
 

docs/ExpressionEncoder.md

@@ -95,7 +95,7 @@ tuple(
 `tuple` is used when:
 
 * `Dataset` is requested to [selectUntyped](Dataset.md#selectUntyped), [select](Dataset.md#select), [joinWith](Dataset.md#joinWith)
-* `KeyValueGroupedDataset` is requested to [aggUntyped](KeyValueGroupedDataset.md#aggUntyped)
+* `KeyValueGroupedDataset` is requested to [aggUntyped](basic-aggregation/KeyValueGroupedDataset.md#aggUntyped)
 * `Encoders` utility is used to [tuple](Encoders.md#tuple)
 * `ReduceAggregator` is requested for `bufferEncoder`
 

docs/KeyValueGroupedDataset.md

@@ -24,7 +24,7 @@ val qe = new QueryExecution(sparkSession, plan)
 `QueryExecution` is created when:
 
 * [Dataset.ofRows](Dataset.md#ofRows) and [Dataset.selectUntyped](Dataset.md#selectUntyped) are executed
-* `KeyValueGroupedDataset` is requested to [aggUntyped](KeyValueGroupedDataset.md#aggUntyped)
+* `KeyValueGroupedDataset` is requested to [aggUntyped](basic-aggregation/KeyValueGroupedDataset.md#aggUntyped)
 * `CommandUtils` utility is requested to [computeColumnStats](CommandUtils.md#computeColumnStats) and [computePercentiles](CommandUtils.md#computePercentiles)
 * `BaseSessionStateBuilder` is requested to [create a QueryExecution for a LogicalPlan](BaseSessionStateBuilder.md#createQueryExecution)