XDContext

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

def addJar(path: String): Unit

Add JAR file from XD Driver to the context

lazy val analyzer: Analyzer

def applySchemaToPythonRDD(rdd: RDD[Array[Any]], schema: StructType): DataFrame

def applySchemaToPythonRDD(rdd: RDD[Array[Any]], schemaString: String): DataFrame

final def asInstanceOf[T0]: T0

def baseRelationToDataFrame(baseRelation: BaseRelation): DataFrame

val cacheManager: execution.CacheManager

def cacheTable(tableName: String): Unit

lazy val catalog: XDCatalog

def checkCatalogConnection: Boolean

Check if there is Connection with the catalog

def clearCache(): Unit

def clone(): AnyRef

lazy val conf: SQLConf

def createDataFrame(rows: Seq[Row], schema: StructType): DataFrame

def createDataFrame(data: List[_], beanClass: Class[_]): DataFrame

def createDataFrame(rdd: JavaRDD[_], beanClass: Class[_]): DataFrame

def createDataFrame(rdd: RDD[_], beanClass: Class[_]): DataFrame

def createDataFrame(rows: List[Row], schema: StructType): DataFrame

def createDataFrame(rowRDD: JavaRDD[Row], schema: StructType): DataFrame

def createDataFrame(rowRDD: RDD[Row], schema: StructType): DataFrame

def createDataFrame[A <: Product](data: Seq[A])(implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[A]): DataFrame

def createDataFrame[A <: Product](rdd: RDD[A])(implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[A]): DataFrame

def createDataset[T](data: List[T])(implicit arg0: Encoder[T]): Dataset[T]

def createDataset[T](data: RDD[T])(implicit arg0: Encoder[T]): Dataset[T]

def createDataset[T](data: Seq[T])(implicit arg0: Encoder[T]): Dataset[T]

def createExternalTable(tableName: String, source: String, schema: StructType, options: Map[String, String]): DataFrame

def createExternalTable(tableName: String, source: String, schema: StructType, options: Map[String, String]): DataFrame

def createExternalTable(tableName: String, source: String, options: Map[String, String]): DataFrame

def createExternalTable(tableName: String, source: String, options: Map[String, String]): DataFrame

def createExternalTable(tableName: String, path: String, source: String): DataFrame

def createExternalTable(tableName: String, path: String): DataFrame

val ddlParser: XDDdlParser

def dialectClassName: String

def dropAllTables(): Unit

Drops all tables in the persistent catalog.

def dropTable(tableIdentifier: TableIdentifier): Unit

Drops the table in the persistent catalog.

def dropTempTable(tableName: String): Unit

lazy val emptyDataFrame: DataFrame

lazy val emptyResult: RDD[InternalRow]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def executePlan(plan: LogicalPlan): execution.QueryExecution

def executeSql(sql: String): execution.QueryExecution

val experimental: ExperimentalMethods

def finalize(): Unit

lazy val functionRegistry: FunctionRegistry

def getAllConfs: Map[String, String]

final def getClass(): Class[_]

def getConf(key: String, defaultValue: String): String

def getConf(key: String): String

def getSQLDialect(): ParserDialect

def getSchema(beanClass: Class[_]): Seq[AttributeReference]

def hashCode(): Int

def importTables(datasource: String, opts: Map[String, String]): Unit

Imports tables from a DataSource in the persistent catalog.

def isCached(tableName: String): Boolean

final def isInstanceOf[T0]: Boolean

val isRootContext: Boolean

def isTraceEnabled(): Boolean

lazy val listenerManager: ExecutionListenerManager

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit

def logTrace(msg: ⇒ String): Unit

def logWarning(msg: ⇒ String, throwable: Throwable): Unit

def logWarning(msg: ⇒ String): Unit

final def ne(arg0: AnyRef): Boolean

def newSession(): SQLContext

final def notify(): Unit

final def notifyAll(): Unit

lazy val optimizer: Optimizer

def parseDataType(dataTypeString: String): DataType

def parseSql(sql: String): LogicalPlan

val planner: execution.SparkPlanner

val prepareForExecution: RuleExecutor[SparkPlan]

def range(start: Long, end: Long, step: Long, numPartitions: Int): DataFrame

def range(start: Long, end: Long): DataFrame

def range(end: Long): DataFrame

def read: DataFrameReader

val sc: SparkContext

A SparkContext.

lazy val securityManager: security.SecurityManager

def setConf(key: String, value: String): Unit

def setConf(props: Properties): Unit

val sparkContext: SparkContext

def sql(sqlText: String): DataFrame

val sqlParser: SparkSQLParser

lazy val streamingCatalog: Option[XDStreamingCatalog]

final def synchronized[T0](arg0: ⇒ T0): T0

def table(tableName: String): DataFrame

def tableNames(databaseName: String): Array[String]

def tableNames(): Array[String]

def tables(databaseName: String): DataFrame

def tables(): DataFrame

def toString(): String

val udf: UDFRegistration

def uncacheTable(tableName: String): Unit

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

def applySchema(rdd: JavaRDD[_], beanClass: Class[_]): DataFrame

def applySchema(rdd: RDD[_], beanClass: Class[_]): DataFrame

def applySchema(rowRDD: JavaRDD[Row], schema: StructType): DataFrame

def applySchema(rowRDD: RDD[Row], schema: StructType): DataFrame

def jdbc(url: String, table: String, theParts: Array[String]): DataFrame

def jdbc(url: String, table: String, columnName: String, lowerBound: Long, upperBound: Long, numPartitions: Int): DataFrame

def jdbc(url: String, table: String): DataFrame

def jsonFile(path: String, samplingRatio: Double): DataFrame

def jsonFile(path: String, schema: StructType): DataFrame

def jsonFile(path: String): DataFrame

def jsonRDD(json: JavaRDD[String], samplingRatio: Double): DataFrame

def jsonRDD(json: RDD[String], samplingRatio: Double): DataFrame

def jsonRDD(json: JavaRDD[String], schema: StructType): DataFrame

def jsonRDD(json: RDD[String], schema: StructType): DataFrame

def jsonRDD(json: JavaRDD[String]): DataFrame

def jsonRDD(json: RDD[String]): DataFrame

def load(source: String, schema: StructType, options: Map[String, String]): DataFrame

def load(source: String, schema: StructType, options: Map[String, String]): DataFrame

def load(source: String, options: Map[String, String]): DataFrame

def load(source: String, options: Map[String, String]): DataFrame

def load(path: String, source: String): DataFrame

def load(path: String): DataFrame

def parquetFile(paths: String*): DataFrame