[SPARK-31086][SQL] Add Back the Deprecated SQLContext methods

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

@@ -611,6 +611,289 @@ class SQLContext private[sql](val sparkSession: SparkSession)
     sessionState.catalog.listTables(databaseName).map(_.table).toArray
   }
 
+  ////////////////////////////////////////////////////////////////////////////
+  ////////////////////////////////////////////////////////////////////////////
+  // 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)
+  }
 }
 
 /**

sql/core/src/test/scala/org/apache/spark/sql/DeprecatedAPISuite.scala

@@ -0,0 +1,106 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.sql
+
+import org.apache.spark.sql.test.SharedSparkSession
+import org.apache.spark.sql.types.{IntegerType, StringType, StructField, StructType}
+
+class DeprecatedAPISuite extends QueryTest with SharedSparkSession {
+
+  test("SQLContext.applySchema") {
+    val rowRdd = sparkContext.parallelize(Seq(Row("Jack", 20), Row("Marry", 18)))
+    val schema = StructType(StructField("name", StringType, false) ::
+      StructField("age", IntegerType, true) :: Nil)
+    val sqlContext = spark.sqlContext
+    checkAnswer(sqlContext.applySchema(rowRdd, schema), Row("Jack", 20) :: Row("Marry", 18) :: Nil)
+    checkAnswer(sqlContext.applySchema(rowRdd.toJavaRDD(), schema),
+      Row("Jack", 20) :: Row("Marry", 18) :: Nil)
+  }
+
+  test("SQLContext.parquetFile") {
+    val sqlContext = spark.sqlContext
+    withTempDir { dir =>
+      val parquetFile = s"${dir.toString}/${System.currentTimeMillis()}"
+      val expectDF = spark.range(10).toDF()
+      expectDF.write.parquet(parquetFile)
+      val parquetDF = sqlContext.parquetFile(parquetFile)
+      checkAnswer(parquetDF, expectDF)
+    }
+  }
+
+  test("SQLContext.jsonFile") {
+    val sqlContext = spark.sqlContext
+    withTempDir { dir =>
+      val jsonFile = s"${dir.toString}/${System.currentTimeMillis()}"
+      val expectDF = spark.range(10).toDF()
+      expectDF.write.json(jsonFile)
+      var jsonDF = sqlContext.jsonFile(jsonFile)
+      checkAnswer(jsonDF, expectDF)
+      assert(jsonDF.schema === expectDF.schema.asNullable)
+
+      var schema = expectDF.schema
+      jsonDF = sqlContext.jsonFile(jsonFile, schema)
+      checkAnswer(jsonDF, expectDF)
+      assert(jsonDF.schema === schema.asNullable)
+
+      jsonDF = sqlContext.jsonFile(jsonFile, 0.9)
+      checkAnswer(jsonDF, expectDF)
+
+      val jsonRDD = sparkContext.parallelize(Seq("{\"name\":\"Jack\",\"age\":20}",
+        "{\"name\":\"Marry\",\"age\":18}"))
+      jsonDF = sqlContext.jsonRDD(jsonRDD)
+      checkAnswer(jsonDF, Row(18, "Marry") :: Row(20, "Jack") :: Nil)
+      jsonDF = sqlContext.jsonRDD(jsonRDD.toJavaRDD())
+      checkAnswer(jsonDF, Row(18, "Marry") :: Row(20, "Jack") :: Nil)
+
+      schema = StructType(StructField("name", StringType, false) ::
+        StructField("age", IntegerType, false) :: Nil)
+      jsonDF = sqlContext.jsonRDD(jsonRDD, schema)
+      checkAnswer(jsonDF, Row("Jack", 20) :: Row("Marry", 18) :: Nil)
+      jsonDF = sqlContext.jsonRDD(jsonRDD.toJavaRDD(), schema)
+      checkAnswer(jsonDF, Row("Jack", 20) :: Row("Marry", 18) :: Nil)
+
+
+      jsonDF = sqlContext.jsonRDD(jsonRDD, 0.9)
+      checkAnswer(jsonDF, Row(18, "Marry") :: Row(20, "Jack") :: Nil)
+      jsonDF = sqlContext.jsonRDD(jsonRDD.toJavaRDD(), 0.9)
+      checkAnswer(jsonDF, Row(18, "Marry") :: Row(20, "Jack") :: Nil)
+    }
+  }
+
+  test("SQLContext.load") {
+    withTempDir { dir =>
+      val path = s"${dir.toString}/${System.currentTimeMillis()}"
+      val expectDF = spark.range(10).toDF()
+      expectDF.write.parquet(path)
+      val sqlContext = spark.sqlContext
+
+      var loadDF = sqlContext.load(path)
+      checkAnswer(loadDF, expectDF)
+
+      loadDF = sqlContext.load(path, "parquet")
+      checkAnswer(loadDF, expectDF)
+
+      loadDF = sqlContext.load("parquet", Map("path" -> path))
+      checkAnswer(loadDF, expectDF)
+
+      loadDF = sqlContext.load("parquet", expectDF.schema, Map("path" -> path))
+      checkAnswer(loadDF, expectDF)
+    }
+  }
+}