erikerlandson

import scala.language.higherKinds

object nat {

trait Nat {
  /** The type of this Nat object. */
  type Self <: Nat

  /** Add another Nat to this one. */
  type + [_ <: Nat] <: Nat

erikerlandson

val local:ThreadLocal[String] = new InheritableThreadLocal[String]

local.set("value")

println(s"${local.get()}")

erikerlandson

import scala.concurrent._
import ExecutionContext.Implicits.global

val local1:ThreadLocal[String] = new InheritableThreadLocal[String]
val local2:ThreadLocal[String] = new ThreadLocal[String]

local1.set("foo")
local2.set("bar")

println(s"main: local1= ${local1.get()}")

erikerlandson

import scala.concurrent._
import ExecutionContext.Implicits.global

// global ThreadLocal structures
val local1:ThreadLocal[String] = new InheritableThreadLocal[String]
val local2:ThreadLocal[String] = new ThreadLocal[String]

local1.set("foo")
local2.set("bar")

erikerlandson

import scala.concurrent._
import ExecutionContext.Implicits.global

// global ThreadLocal structures
val local1:ThreadLocal[String] = new InheritableThreadLocal[String]
val local2:ThreadLocal[String] = new ThreadLocal[String]

local1.set("foo")
local2.set("bar")

erikerlandson

import scala.concurrent._
import ExecutionContext.Implicits.global

// ThreadLocal structures as class members
class Context {
  private val local: ThreadLocal[String] = new InheritableThreadLocal[String] {
    override protected def childValue(parent: String): String = {
      println(s"cloning parent ${parent}")
      s"(${parent})"
    }

erikerlandson

[eje@localhost spark]$ scala
Welcome to Scala version 2.10.3-20130923-e2fec6b28dfd73482945ffab85d9b582d0cb9f17 (OpenJDK 64-Bit Server VM, Java 1.7.0_71).
Type in expressions to have them evaluated.
Type :help for more information.

scala> import java.util.Properties
import java.util.Properties

scala> val p = new Properties
p: java.util.Properties = {}

erikerlandson

// A formalism that might be defined using different axiom systems
// Not intended to be instantiated directly
trait Formalism {
  // from axiom system A/B
  def A: Unit
  def B: Unit

  // from axiom system C/D
  def C: Unit

erikerlandson

// starting Spark REPL at top of source tree:
// $ cd ~/git/spark
// $ ./bin/spark-shell
//
import org.apache.spark.mllib.tree.RandomForest
import org.apache.spark.mllib.util.MLUtils
// Load and parse the data file. 
val data = MLUtils.loadLibSVMFile(sc, "data/mllib/sample_libsvm_data.txt") 
// Split the data into training and test sets (30% held out for testing) 
val splits = data.randomSplit(Array(0.7, 0.3)) 

erikerlandson

  def kMedoids[T :ClassTag, U >: T :ClassTag](
      data: RDD[T],
      k: Int,
      metric: (U,U) => Double,
      sampleSize: Int = 10000,
      maxIterations: Int = 10,
      resampleInterval: Int = 3
    ): (Seq[T], Double) = {

    val n = data.count