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org.apache.spark.ml.odkl.JacksonParam.scala Maven / Gradle / Ivy
package org.apache.spark.ml.odkl
import com.fasterxml.jackson.core.{JsonGenerator, JsonParser}
import com.fasterxml.jackson.databind.deser.std.PrimitiveArrayDeserializers
import com.fasterxml.jackson.databind.module.SimpleModule
import com.fasterxml.jackson.databind._
import com.fasterxml.jackson.module.scala.DefaultScalaModule
import odkl.analysis.spark.util.Logging
import org.apache.spark.ml.param.Param
import org.apache.spark.ml.util.Identifiable
import org.apache.spark.mllib.linalg.DenseVector
import scala.reflect.ClassTag
/**
* ml.odkl is an extension to Spark ML package with intention to
* 1. Provide a modular structure with shared and tested common code
* 2. Add ability to create train-only transformation (for better prediction performance)
* 3. Unify extra information generation by the model fitters
* 4. Support combined models with option for parallel training.
*
* This particular file contains utility for serializing complex parameters using jackson (handles few
* types automatically which can not be handled by json4s)
*/
class JacksonParam[T] (
parent: String,
name: String,
doc: String,
isValid: T => Boolean,
default: Option[T]
)(implicit ct: ClassTag[T])
extends Param[T](parent, name, doc, isValid) with Logging {
def this(parent: Identifiable, name: String, doc: String, isValid: T => Boolean)(implicit ct: ClassTag[T]) = {
this(parent.uid, name, doc, isValid, None)
}
def this(parent: String, name: String, doc: String)(implicit ct: ClassTag[T]) = {
this(parent, name, doc, (x: T) => true, None)
}
def this(parent: Identifiable, name: String, doc: String)(implicit ct: ClassTag[T]) = {
this(parent.uid, name, doc)
}
override def jsonEncode(value: T): String = {
JacksonParam.objectMapper.writeValueAsString(value)
}
override def jsonDecode(json: String): T = {
try {
JacksonParam.objectMapper.readValue[T](json, ct.runtimeClass.asInstanceOf[Class[T]])
} catch {
case e: Throwable =>
logError(s"Failed to read param $name from data $json due error", e)
default.get
}
}
}
object JacksonParam extends Serializable {
def apply[T](parent: Identifiable, name: String, doc: String,
isValid: (T) => Boolean = (x: T) => true,
default: Option[T] = None)(implicit ct: ClassTag[T]) = {
new JacksonParam[T](parent.uid, name, doc, isValid, default)
}
def mapParam[V](parent: Identifiable, name: String, doc: String,
isValid: (Map[String, V]) => Boolean = (x: Map[String, V]) => true,
default: Option[Map[String, V]] = Some(Map[String,V]()))(implicit ct: ClassTag[Map[String, V]]) = {
new JacksonParam[Map[String, V]](parent.uid, name, doc, isValid, default)
}
def arrayParam[V](parent: Identifiable, name: String, doc: String)(implicit ct: ClassTag[Array[V]], cv: ClassTag[V]) = {
new JacksonParam[Array[V]](parent.uid, name, doc, (x : Array[V]) => true, Some[Array[V]](Array[V]()))
}
lazy val objectMapper: ObjectMapper = createDefaultMapper
private def createDefaultMapper: ObjectMapper = {
val m = new ObjectMapper()
m.registerModule(DefaultScalaModule)
m.registerModule(sparkModule)
m
}
def sparkModule: Module = {
val module = new SimpleModule("SparkJson")
module.addSerializer(classOf[DenseVector], DenseVectorSerializer)
module.addDeserializer(classOf[DenseVector], DenseVectorDeserializer)
module
}
private object DenseVectorSerializer extends JsonSerializer[DenseVector] {
override def serialize(value: DenseVector, gen: JsonGenerator, serializers: SerializerProvider): Unit = {
gen.writeStartArray(value.size)
for (i <- 0 until value.size) gen.writeNumber(value(i))
gen.writeEndArray()
}
}
private object DenseVectorDeserializer extends JsonDeserializer[DenseVector] {
private val arrayDeserializer = PrimitiveArrayDeserializers.forType(java.lang.Double.TYPE)
override def deserialize(p: JsonParser, ctxt: DeserializationContext): DenseVector = {
val array = arrayDeserializer.deserialize(p, ctxt).asInstanceOf[Array[Double]]
new DenseVector(array)
}
}
}