[MINOR][DOCS] JSON APIs related documentation fixes

## What changes were proposed in this pull request?

This PR proposes corrections related to JSON APIs as below:

- Rendering links in Python documentation
- Replacing `RDD` to `Dataset` in programing guide
- Adding missing description about JSON Lines consistently in `DataFrameReader.json` in Python API
- De-duplicating little bit of `DataFrameReader.json` in Scala/Java API

## How was this patch tested?

Manually build the documentation via `jekyll build`. Corresponding snapstops will be left on the codes.

Note that currently there are Javadoc8 breaks in several places. These are proposed to be handled in apache#17477. So, this PR does not fix those.

Author: hyukjinkwon <[email protected]>

Closes apache#17602 from HyukjinKwon/minor-json-documentation.

docs/sql-programming-guide.md

@@ -883,7 +883,7 @@ Configuration of Parquet can be done using the `setConf` method on `SparkSession
 
 <div data-lang="scala"  markdown="1">
 Spark SQL can automatically infer the schema of a JSON dataset and load it as a `Dataset[Row]`.
-This conversion can be done using `SparkSession.read.json()` on either an RDD of String,
+This conversion can be done using `SparkSession.read.json()` on either a `Dataset[String]`,
 or a JSON file.
 
 Note that the file that is offered as _a json file_ is not a typical JSON file. Each
@@ -897,7 +897,7 @@ For a regular multi-line JSON file, set the `wholeFile` option to `true`.
 
 <div data-lang="java"  markdown="1">
 Spark SQL can automatically infer the schema of a JSON dataset and load it as a `Dataset<Row>`.
-This conversion can be done using `SparkSession.read().json()` on either an RDD of String,
+This conversion can be done using `SparkSession.read().json()` on either a `Dataset<String>`,
 or a JSON file.
 
 Note that the file that is offered as _a json file_ is not a typical JSON file. Each

examples/src/main/java/org/apache/spark/examples/sql/JavaSQLDataSourceExample.java

@@ -215,7 +215,7 @@ private static void runJsonDatasetExample(SparkSession spark) {
     // +------+
 
     // Alternatively, a DataFrame can be created for a JSON dataset represented by
-    // an Dataset[String] storing one JSON object per string.
+    // a Dataset<String> storing one JSON object per string.
     List<String> jsonData = Arrays.asList(
             "{\"name\":\"Yin\",\"address\":{\"city\":\"Columbus\",\"state\":\"Ohio\"}}");
     Dataset<String> anotherPeopleDataset = spark.createDataset(jsonData, Encoders.STRING());

examples/src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala

@@ -139,7 +139,7 @@ object SQLDataSourceExample {
     // +------+
 
     // Alternatively, a DataFrame can be created for a JSON dataset represented by
-    // an Dataset[String] storing one JSON object per string
+    // a Dataset[String] storing one JSON object per string
     val otherPeopleDataset = spark.createDataset(
       """{"name":"Yin","address":{"city":"Columbus","state":"Ohio"}}""" :: Nil)
     val otherPeople = spark.read.json(otherPeopleDataset)

python/pyspark/sql/readwriter.py

@@ -173,8 +173,8 @@ def json(self, path, schema=None, primitivesAsString=None, prefersDecimal=None,
         """
         Loads JSON files and returns the results as a :class:`DataFrame`.
 
-        `JSON Lines <http://jsonlines.org/>`_(newline-delimited JSON) is supported by default.
-        For JSON (one record per file), set the `wholeFile` parameter to ``true``.
+        `JSON Lines <http://jsonlines.org/>`_ (newline-delimited JSON) is supported by default.
+        For JSON (one record per file), set the ``wholeFile`` parameter to ``true``.
 
         If the ``schema`` parameter is not specified, this function goes
         through the input once to determine the input schema.
@@ -634,7 +634,9 @@ def saveAsTable(self, name, format=None, mode=None, partitionBy=None, **options)
 
     @since(1.4)
     def json(self, path, mode=None, compression=None, dateFormat=None, timestampFormat=None):
-        """Saves the content of the :class:`DataFrame` in JSON format at the specified path.
+        """Saves the content of the :class:`DataFrame` in JSON format
+        (`JSON Lines text format or newline-delimited JSON <http://jsonlines.org/>`_) at the
+        specified path.
 
         :param path: the path in any Hadoop supported file system
         :param mode: specifies the behavior of the save operation when data already exists.

python/pyspark/sql/streaming.py

@@ -405,8 +405,8 @@ def json(self, path, schema=None, primitivesAsString=None, prefersDecimal=None,
         """
         Loads a JSON file stream and returns the results as a :class:`DataFrame`.
 
-        `JSON Lines <http://jsonlines.org/>`_(newline-delimited JSON) is supported by default.
-        For JSON (one record per file), set the `wholeFile` parameter to ``true``.
+        `JSON Lines <http://jsonlines.org/>`_ (newline-delimited JSON) is supported by default.
+        For JSON (one record per file), set the ``wholeFile`` parameter to ``true``.
 
         If the ``schema`` parameter is not specified, this function goes
         through the input once to determine the input schema.

sql/core/src/main/scala/org/apache/spark/sql/DataFrameReader.scala

@@ -268,8 +268,8 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
   }
 
   /**
-   * Loads a JSON file (<a href="http://jsonlines.org/">JSON Lines text format or
-   * newline-delimited JSON</a>) and returns the result as a `DataFrame`.
+   * Loads a JSON file and returns the results as a `DataFrame`.
+   *
    * See the documentation on the overloaded `json()` method with varargs for more details.
    *
    * @since 1.4.0