[SPARK-15250][SQL] Remove deprecated json API in DataFrameReader

## What changes were proposed in this pull request?

This PR removes the old `json(path: String)` API which is covered by the new `json(paths: String*)`.

## How was this patch tested?

Jenkins tests (existing tests should cover this)

Author: hyukjinkwon <[email protected]>
Author: Hyukjin Kwon <[email protected]>

Closes #13040 from HyukjinKwon/SPARK-15250.

Author: HyukjinKwon

project/MimaExcludes.scala

@@ -348,6 +348,9 @@ object MimaExcludes {
       ) ++ Seq(
         // [SPARK-13686][MLLIB][STREAMING] Add a constructor parameter `reqParam` to (Streaming)LinearRegressionWithSGD
         ProblemFilters.exclude[MissingMethodProblem]("org.apache.spark.mllib.regression.LinearRegressionWithSGD.this")
+      ) ++ Seq(
+        // SPARK-15250 Remove deprecated json API in DataFrameReader
+        ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.sql.DataFrameReader.json")
       ) ++ Seq(
         // SPARK-13920: MIMA checks should apply to @Experimental and @DeveloperAPI APIs
         ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.Aggregator.combineCombinersByKey"),

python/pyspark/sql/readwriter.py

@@ -241,8 +241,8 @@ def json(self, path, schema=None, primitivesAsString=None, prefersDecimal=None,
         if columnNameOfCorruptRecord is not None:
             self.option("columnNameOfCorruptRecord", columnNameOfCorruptRecord)
         if isinstance(path, basestring):
-            return self._df(self._jreader.json(path))
-        elif type(path) == list:
+            path = [path]
+        if type(path) == list:
             return self._df(self._jreader.json(self._sqlContext._sc._jvm.PythonUtils.toSeq(path)))
         elif isinstance(path, RDD):
             def func(iterator):

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

@@ -277,38 +277,6 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
     sparkSession.baseRelationToDataFrame(relation)
   }
 
-  /**
-   * Loads a JSON file (one object per line) and returns the result as a [[DataFrame]].
-   *
-   * This function goes through the input once to determine the input schema. If you know the
-   * schema in advance, use the version that specifies the schema to avoid the extra scan.
-   *
-   * You can set the following JSON-specific options to deal with non-standard JSON files:
-   * <li>`primitivesAsString` (default `false`): infers all primitive values as a string type</li>
-   * <li>`allowComments` (default `false`): ignores Java/C++ style comment in JSON records</li>
-   * <li>`allowUnquotedFieldNames` (default `false`): allows unquoted JSON field names</li>
-   * <li>`allowSingleQuotes` (default `true`): allows single quotes in addition to double quotes
-   * </li>
-   * <li>`allowNumericLeadingZeros` (default `false`): allows leading zeros in numbers
-   * (e.g. 00012)</li>
-   * <li>`mode` (default `PERMISSIVE`): allows a mode for dealing with corrupt records
-   * during parsing.</li>
-   * <ul>
-   *  <li>`PERMISSIVE` : sets other fields to `null` when it meets a corrupted record, and puts the
-   *  malformed string into a new field configured by `columnNameOfCorruptRecord`. When
-   *  a schema is set by user, it sets `null` for extra fields.</li>
-   *  <li>`DROPMALFORMED` : ignores the whole corrupted records.</li>
-   *  <li>`FAILFAST` : throws an exception when it meets corrupted records.</li>
-   * </ul>
-   * <li>`columnNameOfCorruptRecord` (default `_corrupt_record`): allows renaming the new field
-   * having malformed string created by `PERMISSIVE` mode. This overrides
-   * `spark.sql.columnNameOfCorruptRecord`.</li>
-   *
-   * @since 1.4.0
-   */
-  // TODO: Remove this one in Spark 2.0.
-  def json(path: String): DataFrame = format("json").load(path)
-
   /**
    * Loads a JSON file (one object per line) and returns the result as a [[DataFrame]].
    *
@@ -342,6 +310,7 @@ class DataFrameReader private[sql](sparkSession: SparkSession) extends Logging {
    *
    * @since 1.6.0
    */
+  @scala.annotation.varargs
   def json(paths: String*): DataFrame = format("json").load(paths : _*)
 
   /**