MLWriter

abstract def saveImpl(path: String): Unit

save() handles overwriting and then calls this method.

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean = false): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

final def isInstanceOf[T0]: Boolean

def isTraceEnabled(): Boolean

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

final def notify(): Unit

final def notifyAll(): Unit

def option(key: String, value: String): MLWriter.this.type

Adds an option to the underlying MLWriter.

val optionMap: Map[String, String]

Map to store extra options for this writer.

def overwrite(): MLWriter.this.type

Overwrites if the output path already exists.

def save(path: String): Unit

Saves the ML instances to the input path.

final def sc: SparkContext

Returns the underlying SparkContext.

def session(sparkSession: SparkSession): MLWriter.this.type

Sets the Spark Session to use for saving/loading.

var shouldOverwrite: Boolean

final def sparkSession: SparkSession

Returns the user-specified Spark Session or the default.

final def sqlContext: SQLContext

Returns the user-specified SQL context or the default.

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def context(sqlContext: SQLContext): MLWriter.this.type

Sets the Spark SQLContext to use for saving/loading.