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Add back the APIs that are removed in SQLContext
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sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala

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@@ -611,6 +611,289 @@ class SQLContext private[sql](val sparkSession: SparkSession)
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sessionState.catalog.listTables(databaseName).map(_.table).toArray
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}
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////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////
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// Deprecated methods
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////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////
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/**
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* @deprecated As of 1.3.0, replaced by `createDataFrame()`.
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*/
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@deprecated("Use createDataFrame instead.", "1.3.0")
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def applySchema(rowRDD: RDD[Row], schema: StructType): DataFrame = {
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createDataFrame(rowRDD, schema)
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}
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/**
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* @deprecated As of 1.3.0, replaced by `createDataFrame()`.
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*/
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@deprecated("Use createDataFrame instead.", "1.3.0")
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def applySchema(rowRDD: JavaRDD[Row], schema: StructType): DataFrame = {
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createDataFrame(rowRDD, schema)
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}
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/**
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* @deprecated As of 1.3.0, replaced by `createDataFrame()`.
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*/
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@deprecated("Use createDataFrame instead.", "1.3.0")
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def applySchema(rdd: RDD[_], beanClass: Class[_]): DataFrame = {
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createDataFrame(rdd, beanClass)
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}
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/**
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* @deprecated As of 1.3.0, replaced by `createDataFrame()`.
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*/
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@deprecated("Use createDataFrame instead.", "1.3.0")
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def applySchema(rdd: JavaRDD[_], beanClass: Class[_]): DataFrame = {
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createDataFrame(rdd, beanClass)
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}
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/**
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* Loads a Parquet file, returning the result as a `DataFrame`. This function returns an empty
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* `DataFrame` if no paths are passed in.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().parquet()`.
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*/
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@deprecated("Use read.parquet() instead.", "1.4.0")
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@scala.annotation.varargs
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def parquetFile(paths: String*): DataFrame = {
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if (paths.isEmpty) {
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emptyDataFrame
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} else {
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read.parquet(paths : _*)
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}
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}
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/**
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* Loads a JSON file (one object per line), returning the result as a `DataFrame`.
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* It goes through the entire dataset once to determine the schema.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonFile(path: String): DataFrame = {
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read.json(path)
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}
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/**
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* Loads a JSON file (one object per line) and applies the given schema,
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* returning the result as a `DataFrame`.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonFile(path: String, schema: StructType): DataFrame = {
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read.schema(schema).json(path)
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}
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/**
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonFile(path: String, samplingRatio: Double): DataFrame = {
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read.option("samplingRatio", samplingRatio.toString).json(path)
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}
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/**
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* Loads an RDD[String] storing JSON objects (one object per record), returning the result as a
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* `DataFrame`.
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* It goes through the entire dataset once to determine the schema.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonRDD(json: RDD[String]): DataFrame = read.json(json)
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/**
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* Loads an RDD[String] storing JSON objects (one object per record), returning the result as a
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* `DataFrame`.
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* It goes through the entire dataset once to determine the schema.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonRDD(json: JavaRDD[String]): DataFrame = read.json(json)
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/**
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* Loads an RDD[String] storing JSON objects (one object per record) and applies the given schema,
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* returning the result as a `DataFrame`.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonRDD(json: RDD[String], schema: StructType): DataFrame = {
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read.schema(schema).json(json)
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}
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/**
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* Loads an JavaRDD[String] storing JSON objects (one object per record) and applies the given
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* schema, returning the result as a `DataFrame`.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonRDD(json: JavaRDD[String], schema: StructType): DataFrame = {
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read.schema(schema).json(json)
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}
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/**
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* Loads an RDD[String] storing JSON objects (one object per record) inferring the
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* schema, returning the result as a `DataFrame`.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonRDD(json: RDD[String], samplingRatio: Double): DataFrame = {
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read.option("samplingRatio", samplingRatio.toString).json(json)
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}
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/**
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* Loads a JavaRDD[String] storing JSON objects (one object per record) inferring the
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* schema, returning the result as a `DataFrame`.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().json()`.
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*/
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@deprecated("Use read.json() instead.", "1.4.0")
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def jsonRDD(json: JavaRDD[String], samplingRatio: Double): DataFrame = {
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read.option("samplingRatio", samplingRatio.toString).json(json)
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}
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/**
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* Returns the dataset stored at path as a DataFrame,
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* using the default data source configured by spark.sql.sources.default.
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*
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* @group genericdata
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* @deprecated As of 1.4.0, replaced by `read().load(path)`.
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*/
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@deprecated("Use read.load(path) instead.", "1.4.0")
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def load(path: String): DataFrame = {
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read.load(path)
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}
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/**
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* Returns the dataset stored at path as a DataFrame, using the given data source.
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*
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* @group genericdata
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* @deprecated As of 1.4.0, replaced by `read().format(source).load(path)`.
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*/
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@deprecated("Use read.format(source).load(path) instead.", "1.4.0")
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def load(path: String, source: String): DataFrame = {
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read.format(source).load(path)
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}
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/**
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* (Java-specific) Returns the dataset specified by the given data source and
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* a set of options as a DataFrame.
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*
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* @group genericdata
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* @deprecated As of 1.4.0, replaced by `read().format(source).options(options).load()`.
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*/
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@deprecated("Use read.format(source).options(options).load() instead.", "1.4.0")
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def load(source: String, options: java.util.Map[String, String]): DataFrame = {
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read.options(options).format(source).load()
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}
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/**
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* (Scala-specific) Returns the dataset specified by the given data source and
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* a set of options as a DataFrame.
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*
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* @group genericdata
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* @deprecated As of 1.4.0, replaced by `read().format(source).options(options).load()`.
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*/
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@deprecated("Use read.format(source).options(options).load() instead.", "1.4.0")
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def load(source: String, options: Map[String, String]): DataFrame = {
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read.options(options).format(source).load()
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}
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/**
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* (Java-specific) Returns the dataset specified by the given data source and
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* a set of options as a DataFrame, using the given schema as the schema of the DataFrame.
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*
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* @group genericdata
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* @deprecated As of 1.4.0, replaced by
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* `read().format(source).schema(schema).options(options).load()`.
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*/
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@deprecated("Use read.format(source).schema(schema).options(options).load() instead.", "1.4.0")
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def load(
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source: String,
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schema: StructType,
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options: java.util.Map[String, String]): DataFrame = {
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read.format(source).schema(schema).options(options).load()
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}
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/**
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* (Scala-specific) Returns the dataset specified by the given data source and
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* a set of options as a DataFrame, using the given schema as the schema of the DataFrame.
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*
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* @group genericdata
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* @deprecated As of 1.4.0, replaced by
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* `read().format(source).schema(schema).options(options).load()`.
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*/
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@deprecated("Use read.format(source).schema(schema).options(options).load() instead.", "1.4.0")
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def load(source: String, schema: StructType, options: Map[String, String]): DataFrame = {
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read.format(source).schema(schema).options(options).load()
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}
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/**
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* Construct a `DataFrame` representing the database table accessible via JDBC URL
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* url named table.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().jdbc()`.
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*/
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@deprecated("Use read.jdbc() instead.", "1.4.0")
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def jdbc(url: String, table: String): DataFrame = {
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read.jdbc(url, table, new Properties)
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}
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/**
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* Construct a `DataFrame` representing the database table accessible via JDBC URL
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* url named table. Partitions of the table will be retrieved in parallel based on the parameters
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* passed to this function.
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*
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* @param columnName the name of a column of integral type that will be used for partitioning.
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* @param lowerBound the minimum value of `columnName` used to decide partition stride
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* @param upperBound the maximum value of `columnName` used to decide partition stride
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* @param numPartitions the number of partitions. the range `minValue`-`maxValue` will be split
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* evenly into this many partitions
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().jdbc()`.
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*/
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@deprecated("Use read.jdbc() instead.", "1.4.0")
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def jdbc(
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url: String,
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table: String,
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columnName: String,
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lowerBound: Long,
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upperBound: Long,
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numPartitions: Int): DataFrame = {
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read.jdbc(url, table, columnName, lowerBound, upperBound, numPartitions, new Properties)
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}
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/**
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* Construct a `DataFrame` representing the database table accessible via JDBC URL
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* url named table. The theParts parameter gives a list expressions
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* suitable for inclusion in WHERE clauses; each one defines one partition
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* of the `DataFrame`.
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*
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* @group specificdata
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* @deprecated As of 1.4.0, replaced by `read().jdbc()`.
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*/
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@deprecated("Use read.jdbc() instead.", "1.4.0")
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def jdbc(url: String, table: String, theParts: Array[String]): DataFrame = {
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read.jdbc(url, table, theParts, new Properties)
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}
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}
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/**

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