abstract class MLWriter extends BaseReadWrite with Logging
Abstract class for utility classes that can save ML instances in Spark's internal format.
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- @Since( "1.6.0" )
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- ReadWrite.scala
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- new MLWriter()
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abstract
def
saveImpl(path: String): Unit
save()handles overwriting and then calls this method.save()handles overwriting and then calls this method. Subclasses should override this method to implement the actual saving of the instance.- Attributes
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def
initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
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def
initializeLogIfNecessary(isInterpreter: Boolean): Unit
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def
isTraceEnabled(): Boolean
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def
log: Logger
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def
logDebug(msg: ⇒ String, throwable: Throwable): Unit
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def
logDebug(msg: ⇒ String): Unit
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def
logError(msg: ⇒ String, throwable: Throwable): Unit
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def
logError(msg: ⇒ String): Unit
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def
logInfo(msg: ⇒ String, throwable: Throwable): Unit
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def
logInfo(msg: ⇒ String): Unit
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def
logName: String
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def
logTrace(msg: ⇒ String, throwable: Throwable): Unit
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def
logTrace(msg: ⇒ String): Unit
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def
logWarning(msg: ⇒ String, throwable: Throwable): Unit
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def
logWarning(msg: ⇒ String): Unit
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def
notify(): Unit
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def
notifyAll(): Unit
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def
option(key: String, value: String): MLWriter.this.type
Adds an option to the underlying MLWriter.
Adds an option to the underlying MLWriter. See the documentation for the specific model's writer for possible options. The option name (key) is case-insensitive.
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- @Since( "2.3.0" )
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val
optionMap: Map[String, String]
Map to store extra options for this writer.
Map to store extra options for this writer.
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def
overwrite(): MLWriter.this.type
Overwrites if the output path already exists.
Overwrites if the output path already exists.
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- @Since( "1.6.0" )
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def
save(path: String): Unit
Saves the ML instances to the input path.
Saves the ML instances to the input path.
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final
def
sc: SparkContext
Returns the underlying
SparkContext.Returns the underlying
SparkContext.- Attributes
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- BaseReadWrite
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def
session(sparkSession: SparkSession): MLWriter.this.type
Sets the Spark Session to use for saving/loading.
Sets the Spark Session to use for saving/loading.
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- MLWriter → BaseReadWrite
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var
shouldOverwrite: Boolean
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final
def
sparkSession: SparkSession
Returns the user-specified Spark Session or the default.
Returns the user-specified Spark Session or the default.
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final
def
sqlContext: SQLContext
Returns the user-specified SQL context or the default.
Returns the user-specified SQL context or the default.
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def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
wait(arg0: Long, arg1: Int): Unit
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finalize(): Unit
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