Github user clockfly commented on a diff in the pull request:
https://github.com/apache/spark/pull/13637#discussion_r66885663
--- 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 --
Oh, I missed several fix.
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
