ArtemGr

    val pattern = java.util.regex.Pattern.compile ("""(?xs) ("(.*?)"|) ; ("(.*?)"|) (?: \r?\n | \z ) """)
    val matcher = pattern.matcher (input)
    while (matcher.find) {
      val col1 = matcher.group (2)
      val col2 = matcher.group (4)
      // ...
    }

brikis98

import io.Source
import scala.actors.Actor._

// Regex to pick up external links; very simplified, so it'll miss some
val linkRegex = "(?i)<a.+?href=\"(http.+?)\".*?>(.+?)</a>".r

object PageLoader {
  def load(url: String) = {
    try {
      Source.fromURL(url).mkString

Mistobaan

// Thanks to zeebo on #go-nuts
package main

import (
	"os"
	"os/signal"
	"runtime"
	"syscall"
)

radu-gheorghe

curl -XDELETE localhost:9200/test
curl -XPUT localhost:9200/test -d '{
  "index.mapper.dynamic": false
}'
#{"ok":true,"acknowledged":true}
curl -XPUT localhost:9200/test/test/1 -d '{"foo":"bar"}'
#{"error":"TypeMissingException[[test] type[test] missing: trying to auto create mapping, but dynamic mapping is disabled]","status":404}

jdegoes

object BenchmarkCommon {
  import scala.util.Random
  
  val DatasetSize = 10000
  val Iterations = 10000
  val ArrayPoolSize = 1000
  val ArrayPool = {
    def randomArray(): Array[Int] = {
      val array = new Array[Int](DatasetSize)
      

MLnick

import spark.streaming.StreamingContext._
import spark.streaming.{Seconds, StreamingContext}
import spark.SparkContext._
import spark.storage.StorageLevel
import spark.streaming.examples.twitter.TwitterInputDStream
import com.twitter.algebird.HyperLogLog._
import com.twitter.algebird._

/**
 * Example of using HyperLogLog monoid from Twitter's Algebird together with Spark Streaming's

lukas-vlcek

// create an index with an analyzer "myindex"
curl -X PUT localhost:9200/myindex -d '
{
  "settings" : {`
    "index":{
      "number_of_replicas":0,
      "number_of_shards":1,
      "analysis":{
        "analyzer":{
          "first":{

ankurcha

{
    "home": null,
    "local_dir": null,
    "buffer_size": 65536,
    "kryo": {
        "buffer_size_mb": 10,
        "registrator": null
    },
    "parallelism": null,
    "test": {

ashrithr

Introduction to Kafka

Kafka acts as a kind of write-ahead log (WAL) that records messages to a persistent store (disk) and allows subscribers to read and apply these changes to their own stores in a system appropriate time-frame.

Terminology:

• Producers send messages to brokers
• Consumers read messages from brokers
• Messages are sent to a topic

audreyfeldroy

• Update HISTORY.md
• Commit the changes:

git add HISTORY.md
git commit -m "Changelog for upcoming release 0.1.1."

• Update version number (can also be minor or major)

bumpversion patch