[SPARK-15914][SQL] Add deprecated method back to SQLContext for backward source code compatibility

## What changes were proposed in this pull request?

Revert partial changes in SPARK-12600, and add some deprecated method back to SQLContext for backward source code compatibility.

## How was this patch tested?

Manual test.

Author: Sean Zhong <seanzhong@databricks.com>

Closes #13637 from clockfly/SPARK-15914.

project/MimaExcludes.scala

@@ -778,6 +778,15 @@ object MimaExcludes {
       ) ++ Seq(
         ProblemFilters.exclude[ReversedMissingMethodProblem]("org.apache.spark.mllib.linalg.Vector.asBreeze"),
         ProblemFilters.exclude[ReversedMissingMethodProblem]("org.apache.spark.mllib.linalg.Matrix.asBreeze")
+      ) ++ Seq(
+        // [SPARK-15914] Binary compatibility is broken since consolidation of Dataset and DataFrame
+        // in Spark 2.0. However, source level compatibility is still maintained.
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.load"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.jsonRDD"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.jsonFile"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.jdbc"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.parquetFile"),
+        ProblemFilters.exclude[IncompatibleResultTypeProblem]("org.apache.spark.sql.SQLContext.applySchema")
       )
     case v if v.startsWith("1.6") =>
       Seq(

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

@@ -736,6 +736,290 @@ class SQLContext private[sql](val sparkSession: SparkSession)
   private[sql] def parseDataType(dataTypeString: String): DataType = {
     DataType.fromJson(dataTypeString)
   }
+
+  ////////////////////////////////////////////////////////////////////////////
+  ////////////////////////////////////////////////////////////////////////////
+  // Deprecated methods
+  ////////////////////////////////////////////////////////////////////////////
+  ////////////////////////////////////////////////////////////////////////////
+
+  /**
+   * @deprecated As of 1.3.0, replaced by `createDataFrame()`.
+   */
+  @deprecated("Use createDataFrame instead.", "1.3.0")
+  def applySchema(rowRDD: RDD[Row], schema: StructType): DataFrame = {
+    createDataFrame(rowRDD, schema)
+  }
+
+  /**
+   * @deprecated As of 1.3.0, replaced by `createDataFrame()`.
+   */
+  @deprecated("Use createDataFrame instead.", "1.3.0")
+  def applySchema(rowRDD: JavaRDD[Row], schema: StructType): DataFrame = {
+    createDataFrame(rowRDD, schema)
+  }
+
+  /**
+   * @deprecated As of 1.3.0, replaced by `createDataFrame()`.
+   */
+  @deprecated("Use createDataFrame instead.", "1.3.0")
+  def applySchema(rdd: RDD[_], beanClass: Class[_]): DataFrame = {
+    createDataFrame(rdd, beanClass)
+  }
+
+  /**
+   * @deprecated As of 1.3.0, replaced by `createDataFrame()`.
+   */
+  @deprecated("Use createDataFrame instead.", "1.3.0")
+  def applySchema(rdd: JavaRDD[_], beanClass: Class[_]): DataFrame = {
+    createDataFrame(rdd, beanClass)
+  }
+
+  /**
+   * Loads a Parquet file, returning the result as a [[DataFrame]]. This function returns an empty
+   * [[DataFrame]] if no paths are passed in.
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().parquet()`.
+   */
+  @deprecated("Use read.parquet() instead.", "1.4.0")
+  @scala.annotation.varargs
+  def parquetFile(paths: String*): DataFrame = {
+    if (paths.isEmpty) {
+      emptyDataFrame
+    } else {
+      read.parquet(paths : _*)
+    }
+  }
+
+  /**
+   * Loads a JSON file (one object per line), returning the result as a [[DataFrame]].
+   * It goes through the entire dataset once to determine the schema.
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonFile(path: String): DataFrame = {
+    read.json(path)
+  }
+
+  /**
+   * Loads a JSON file (one object per line) and applies the given schema,
+   * returning the result as a [[DataFrame]].
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonFile(path: String, schema: StructType): DataFrame = {
+    read.schema(schema).json(path)
+  }
+
+  /**
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonFile(path: String, samplingRatio: Double): DataFrame = {
+    read.option("samplingRatio", samplingRatio.toString).json(path)
+  }
+
+  /**
+   * Loads an RDD[String] storing JSON objects (one object per record), returning the result as a
+   * [[DataFrame]].
+   * It goes through the entire dataset once to determine the schema.
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonRDD(json: RDD[String]): DataFrame = read.json(json)
+
+  /**
+   * Loads an RDD[String] storing JSON objects (one object per record), returning the result as a
+   * [[DataFrame]].
+   * It goes through the entire dataset once to determine the schema.
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonRDD(json: JavaRDD[String]): DataFrame = read.json(json)
+
+  /**
+   * Loads an RDD[String] storing JSON objects (one object per record) and applies the given schema,
+   * returning the result as a [[DataFrame]].
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonRDD(json: RDD[String], schema: StructType): DataFrame = {
+    read.schema(schema).json(json)
+  }
+
+  /**
+   * Loads an JavaRDD<String> storing JSON objects (one object per record) and applies the given
+   * schema, returning the result as a [[DataFrame]].
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonRDD(json: JavaRDD[String], schema: StructType): DataFrame = {
+    read.schema(schema).json(json)
+  }
+
+  /**
+   * Loads an RDD[String] storing JSON objects (one object per record) inferring the
+   * schema, returning the result as a [[DataFrame]].
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonRDD(json: RDD[String], samplingRatio: Double): DataFrame = {
+    read.option("samplingRatio", samplingRatio.toString).json(json)
+  }
+
+  /**
+   * Loads a JavaRDD[String] storing JSON objects (one object per record) inferring the
+   * schema, returning the result as a [[DataFrame]].
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().json()`.
+   */
+  @deprecated("Use read.json() instead.", "1.4.0")
+  def jsonRDD(json: JavaRDD[String], samplingRatio: Double): DataFrame = {
+    read.option("samplingRatio", samplingRatio.toString).json(json)
+  }
+
+  /**
+   * Returns the dataset stored at path as a DataFrame,
+   * using the default data source configured by spark.sql.sources.default.
+   *
+   * @group genericdata
+   * @deprecated As of 1.4.0, replaced by `read().load(path)`.
+   */
+  @deprecated("Use read.load(path) instead.", "1.4.0")
+  def load(path: String): DataFrame = {
+    read.load(path)
+  }
+
+  /**
+   * Returns the dataset stored at path as a DataFrame, using the given data source.
+   *
+   * @group genericdata
+   * @deprecated As of 1.4.0, replaced by `read().format(source).load(path)`.
+   */
+  @deprecated("Use read.format(source).load(path) instead.", "1.4.0")
+  def load(path: String, source: String): DataFrame = {
+    read.format(source).load(path)
+  }
+
+  /**
+   * (Java-specific) Returns the dataset specified by the given data source and
+   * a set of options as a DataFrame.
+   *
+   * @group genericdata
+   * @deprecated As of 1.4.0, replaced by `read().format(source).options(options).load()`.
+   */
+  @deprecated("Use read.format(source).options(options).load() instead.", "1.4.0")
+  def load(source: String, options: java.util.Map[String, String]): DataFrame = {
+    read.options(options).format(source).load()
+  }
+
+  /**
+   * (Scala-specific) Returns the dataset specified by the given data source and
+   * a set of options as a DataFrame.
+   *
+   * @group genericdata
+   * @deprecated As of 1.4.0, replaced by `read().format(source).options(options).load()`.
+   */
+  @deprecated("Use read.format(source).options(options).load() instead.", "1.4.0")
+  def load(source: String, options: Map[String, String]): DataFrame = {
+    read.options(options).format(source).load()
+  }
+
+  /**
+   * (Java-specific) Returns the dataset specified by the given data source and
+   * a set of options as a DataFrame, using the given schema as the schema of the DataFrame.
+   *
+   * @group genericdata
+   * @deprecated As of 1.4.0, replaced by
+   *            `read().format(source).schema(schema).options(options).load()`.
+   */
+  @deprecated("Use read.format(source).schema(schema).options(options).load() instead.", "1.4.0")
+  def load(
+      source: String,
+      schema: StructType,
+      options: java.util.Map[String, String]): DataFrame = {
+    read.format(source).schema(schema).options(options).load()
+  }
+
+  /**
+   * (Scala-specific) Returns the dataset specified by the given data source and
+   * a set of options as a DataFrame, using the given schema as the schema of the DataFrame.
+   *
+   * @group genericdata
+   * @deprecated As of 1.4.0, replaced by
+   *            `read().format(source).schema(schema).options(options).load()`.
+   */
+  @deprecated("Use read.format(source).schema(schema).options(options).load() instead.", "1.4.0")
+  def load(source: String, schema: StructType, options: Map[String, String]): DataFrame = {
+    read.format(source).schema(schema).options(options).load()
+  }
+
+  /**
+   * Construct a [[DataFrame]] representing the database table accessible via JDBC URL
+   * url named table.
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().jdbc()`.
+   */
+  @deprecated("Use read.jdbc() instead.", "1.4.0")
+  def jdbc(url: String, table: String): DataFrame = {
+    read.jdbc(url, table, new Properties)
+  }
+
+  /**
+   * Construct a [[DataFrame]] representing the database table accessible via JDBC URL
+   * url named table.  Partitions of the table will be retrieved in parallel based on the parameters
+   * passed to this function.
+   *
+   * @param columnName the name of a column of integral type that will be used for partitioning.
+   * @param lowerBound the minimum value of `columnName` used to decide partition stride
+   * @param upperBound the maximum value of `columnName` used to decide partition stride
+   * @param numPartitions the number of partitions.  the range `minValue`-`maxValue` will be split
+   *                      evenly into this many partitions
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().jdbc()`.
+   */
+  @deprecated("Use read.jdbc() instead.", "1.4.0")
+  def jdbc(
+      url: String,
+      table: String,
+      columnName: String,
+      lowerBound: Long,
+      upperBound: Long,
+      numPartitions: Int): DataFrame = {
+    read.jdbc(url, table, columnName, lowerBound, upperBound, numPartitions, new Properties)
+  }
+
+  /**
+   * Construct a [[DataFrame]] representing the database table accessible via JDBC URL
+   * url named table. The theParts parameter gives a list expressions
+   * suitable for inclusion in WHERE clauses; each one defines one partition
+   * of the [[DataFrame]].
+   *
+   * @group specificdata
+   * @deprecated As of 1.4.0, replaced by `read().jdbc()`.
+   */
+  @deprecated("Use read.jdbc() instead.", "1.4.0")
+  def jdbc(url: String, table: String, theParts: Array[String]): DataFrame = {
+    read.jdbc(url, table, theParts, new Properties)
+  }
 }
 
 /**