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Commit 4f83e442 authored by Zheng RuiFeng's avatar Zheng RuiFeng Committed by Reynold Xin
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[MINOR][DOC] Minor typo fixes

## What changes were proposed in this pull request?
Minor typo fixes

## How was this patch tested?
local build

Author: Zheng RuiFeng <ruifengz@foxmail.com>

Closes #12755 from zhengruifeng/fix_doc_dataset.
parent cabd54d9
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......@@ -97,7 +97,7 @@ private[sql] object Dataset {
* the following creates a new Dataset by applying a filter on the existing one:
* {{{
* val names = people.map(_.name) // in Scala; names is a Dataset[String]
* Dataset<String> names = people.map((Person p) -> p.name, Encoders.STRING) // in Java 8
* Dataset<String> names = people.map((Person p) -> p.name, Encoders.STRING)) // in Java 8
* }}}
*
* Dataset operations can also be untyped, through various domain-specific-language (DSL)
......@@ -191,7 +191,7 @@ class Dataset[T] private[sql](
}
/**
* An unresolved version of the internal encoder for the type of this [[Dataset]]. This one is
* An unresolved version of the internal encoder for the type of this [[Dataset]]. This one is
* marked implicit so that we can use it when constructing new [[Dataset]] objects that have the
* same object type (that will be possibly resolved to a different schema).
*/
......@@ -329,7 +329,7 @@ class Dataset[T] private[sql](
}
/**
* Converts this strongly typed collection of data to generic Dataframe. In contrast to the
* Converts this strongly typed collection of data to generic Dataframe. In contrast to the
* strongly typed objects that Dataset operations work on, a Dataframe returns generic [[Row]]
* objects that allow fields to be accessed by ordinal or name.
*
......@@ -342,13 +342,13 @@ class Dataset[T] private[sql](
/**
* :: Experimental ::
* Returns a new [[Dataset]] where each record has been mapped on to the specified type. The
* Returns a new [[Dataset]] where each record has been mapped on to the specified type. The
* method used to map columns depend on the type of `U`:
* - When `U` is a class, fields for the class will be mapped to columns of the same name
* (case sensitivity is determined by `spark.sql.caseSensitive`)
* (case sensitivity is determined by `spark.sql.caseSensitive`).
* - When `U` is a tuple, the columns will be be mapped by ordinal (i.e. the first column will
* be assigned to `_1`).
* - When `U` is a primitive type (i.e. String, Int, etc). then the first column of the
* - When `U` is a primitive type (i.e. String, Int, etc), then the first column of the
* [[DataFrame]] will be used.
*
* If the schema of the [[Dataset]] does not match the desired `U` type, you can use `select`
......@@ -1002,7 +1002,7 @@ class Dataset[T] private[sql](
}
/**
* Internal helper function for building typed selects that return tuples. For simplicity and
* Internal helper function for building typed selects that return tuples. For simplicity and
* code reuse, we do this without the help of the type system and then use helper functions
* that cast appropriately for the user facing interface.
*/
......@@ -1125,7 +1125,7 @@ class Dataset[T] private[sql](
}
/**
* Groups the [[Dataset]] using the specified columns, so we can run aggregation on them. See
* Groups the [[Dataset]] using the specified columns, so we can run aggregation on them. See
* [[RelationalGroupedDataset]] for all the available aggregate functions.
*
* {{{
......@@ -1237,7 +1237,7 @@ class Dataset[T] private[sql](
/**
* :: Experimental ::
* (Java-specific)
* Reduces the elements of this Dataset using the specified binary function. The given `func`
* Reduces the elements of this Dataset using the specified binary function. The given `func`
* must be commutative and associative or the result may be non-deterministic.
*
* @group action
......@@ -1553,7 +1553,7 @@ class Dataset[T] private[sql](
/**
* :: Experimental ::
* (Scala-specific) Returns a new [[Dataset]] where each row has been expanded to zero or more
* rows by the provided function. This is similar to a `LATERAL VIEW` in HiveQL. The columns of
* rows by the provided function. This is similar to a `LATERAL VIEW` in HiveQL. The columns of
* the input row are implicitly joined with each row that is output by the function.
*
* The following example uses this function to count the number of books which contain
......@@ -1596,7 +1596,7 @@ class Dataset[T] private[sql](
/**
* :: Experimental ::
* (Scala-specific) Returns a new [[Dataset]] where a single column has been expanded to zero
* or more rows by the provided function. This is similar to a `LATERAL VIEW` in HiveQL. All
* or more rows by the provided function. This is similar to a `LATERAL VIEW` in HiveQL. All
* columns of the input row are implicitly joined with each value that is output by the function.
*
* {{{
......@@ -1730,7 +1730,7 @@ class Dataset[T] private[sql](
/**
* Returns a new [[Dataset]] with a column dropped.
* This version of drop accepts a Column rather than a name.
* This is a no-op if the Datasetdoesn't have a column
* This is a no-op if the Dataset doesn't have a column
* with an equivalent expression.
*
* @group untypedrel
......@@ -1969,7 +1969,7 @@ class Dataset[T] private[sql](
/**
* :: Experimental ::
* (Java-specific)
* Returns a new [[Dataset]] that contains the result of applying `func` to each partition.
* Returns a new [[Dataset]] that contains the result of applying `f` to each partition.
*
* @group func
* @since 1.6.0
......@@ -2028,7 +2028,7 @@ class Dataset[T] private[sql](
def foreach(func: ForeachFunction[T]): Unit = foreach(func.call(_))
/**
* Applies a function f to each partition of this [[Dataset]].
* Applies a function `f` to each partition of this [[Dataset]].
*
* @group action
* @since 1.6.0
......@@ -2283,7 +2283,7 @@ class Dataset[T] private[sql](
def javaRDD: JavaRDD[T] = toJavaRDD
/**
* Registers this [[Dataset]] as a temporary table using the given name. The lifetime of this
* Registers this [[Dataset]] as a temporary table using the given name. The lifetime of this
* temporary table is tied to the [[SQLContext]] that was used to create this Dataset.
*
* @group basic
......
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