Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/13637#discussion_r66884192
--- Diff: 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()`. This will
be removed in Spark 2.0.
+ */
+ @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()`. This will
be removed in Spark 2.0.
+ */
+ @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()`. This will
be removed in Spark 2.0.
+ */
+ @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()`. This will
be removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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)`. This will
be removed in Spark 2.0.
+ */
+ @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)`.
+ * This will be removed in Spark 2.0.
+ */
+ @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()`.
+ * This will be removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
+ */
+ @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()`. This will be
removed in Spark 2.0.
--- End diff --
what do you mean "this will be removed in Spark 2.0"? We're already
releasing 2.0 right? I think we don't need this line in the comments (same
elsewhere). The deprecation message in the annotation is sufficient.
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