Scala LoggerFactory类代码示例

//设置package包名称以及导入依赖的类
package au.csiro.data61.magda.registry

import akka.http.scaladsl.marshallers.sprayjson.SprayJsonSupport
import akka.http.scaladsl.testkit.ScalatestRouteTest
import akka.testkit.TestProbe
import ch.qos.logback.classic.{Level, Logger}
import org.flywaydb.core.Flyway
import org.scalatest.Matchers
import org.scalatest.fixture.FunSpec
import org.slf4j.LoggerFactory

import scala.concurrent.duration._
import scalikejdbc._

abstract class ApiSpec extends FunSpec with ScalatestRouteTest with Matchers with Protocols with SprayJsonSupport {
  case class FixtureParam(api: Api, webHookActorProbe: TestProbe)

  val databaseUrl = Option(System.getenv("npm_package_config_databaseUrl")).getOrElse("jdbc:postgresql://localhost:5432/postgres")

  // Stop Flyway from producing so much spam that Travis terminates the process.
  LoggerFactory.getLogger("org.flywaydb").asInstanceOf[Logger].setLevel(Level.WARN)

  val flyway = new Flyway()
  flyway.setDataSource(databaseUrl, "postgres", "")
  flyway.setSchemas("test")
  flyway.setLocations("classpath:/sql")

  override def testConfigSource =
    s"""
      |db.default.url = "${databaseUrl}?currentSchema=test"
      |authorization.skip = true
      |akka.loglevel = INFO
    """.stripMargin

  override def withFixture(test: OneArgTest) = {
    val webHookActorProbe = TestProbe()
    val api = new Api(webHookActorProbe.ref, testConfig, system, executor, materializer)

    webHookActorProbe.expectMsg(1 millis, WebHookActor.Process)

    DB localTx { implicit session =>
      sql"DROP SCHEMA IF EXISTS test CASCADE".update.apply()
      sql"CREATE SCHEMA test".update.apply()
    }

    flyway.migrate()

    super.withFixture(test.toNoArgTest(FixtureParam(api, webHookActorProbe)))
  }
} 

//设置package包名称以及导入依赖的类
package controllers

import javax.inject._

import org.slf4j.LoggerFactory
import play.api.libs.concurrent.Execution.Implicits.defaultContext
import play.api.libs.json.{JsObject, JsValue, Json}
import play.api.mvc._
import play.modules.reactivemongo._
import play.modules.reactivemongo.json._
import play.modules.reactivemongo.json.collection.{JSONCollection, _}
import reactivemongo.api.Cursor

import scala.concurrent.Future

@Singleton
class HomeController  @Inject() (val reactiveMongoApi: ReactiveMongoApi)
  extends Controller with MongoController with ReactiveMongoComponents {

  val logger = LoggerFactory.getLogger(this.getClass)

  def collection: JSONCollection = db.collection[JSONCollection]("scrawler1")

  def index = Action {
    Ok(views.html.index(""))
  }

  def query = Action.async { request =>
    val body = request.body
    val query = body.asFormUrlEncoded.get("query")

    val querySet = query.toSet[String]

    val keywords = querySet.flatMap({ string: String =>
      string.split(" ")
    })

    val searchQuery = Json.obj("keywords" -> Json.obj("$in" -> Json.toJson(keywords)))
    logger.info(s"Internal query from client: $searchQuery")
    val cursor: Cursor[JsObject] = collection.find(searchQuery).cursor[JsObject]

    val result: Future[List[JsObject]] = cursor.collect[List]()

    val resultJson: Future[JsValue] =
      result.map { persons => Json.toJson(persons) }

    resultJson.map { results =>
      val title = results \\ "title"
      val url = results \\ "url"
      val description = results \\ "body"
      val queryData: Seq[((JsValue, JsValue), JsValue)] = title.zip(url).zip(description)
      Ok(views.html.result(queryData))
    }
  }
} 

//设置package包名称以及导入依赖的类
package com.oradian.autofuture

import org.slf4j.LoggerFactory

import scalax.file._

object AutoFutureRunner extends App {
  if (args.isEmpty) {
    System.err.println("Usage: java -jar autofuture.jar [file1] [directory1] ... [directoryN]")
    sys.exit(1)
  }

  val logger = LoggerFactory.getLogger("auto-future")

  args foreach { arg =>
    val path = Path.apply(arg.replace('\\', '/'), '/').toAbsolute
    logger.info("Gathering sources from path: {}", path.path)
    for (source <- (path ** "*.scala").par if source.isFile) {
      logger.trace("Examining Scala source: {}", source.path)
      AutoFuture(source.string) match {
        case AutoFuture.Result.Success(body) =>
          logger.debug("Auto-Futuring Scala source: {}", source.path)
          source.write(body)
        case AutoFuture.Result.Error(error) =>
          logger.warn("Error while parsing Scala source: {}\n{}", source.path: Any, error: Any)
        case AutoFuture.Result.Noop =>
          logger.trace("Noop on: {}", source.path)
      }
    }
  }

  sys.exit(0)
} 

//设置package包名称以及导入依赖的类
package biz.meetmatch.modules.util

import biz.meetmatch.modules.Module
import biz.meetmatch.util.Utils
import com.google.gson.Gson
import org.apache.spark.sql.SparkSession
import org.rogach.scallop.Scallop
import org.slf4j.LoggerFactory

import scalaj.http.Http

object WarmupZeppelin extends Module {

  override def execute(scallopts: Scallop)(implicit sparkSession: SparkSession): Unit = {
    val interpreterId = Utils.getConfig("zeppelin.interpreter.id")

    logger.info(s"Restarting the spark interpreter using url http://localhost:8080/api/interpreter/setting/restart/$interpreterId...")
    val interpreterResponse = Http(s"http://localhost:8080/api/interpreter/setting/restart/$interpreterId")
      .method("put")
      .timeout(connTimeoutMs = 10000, readTimeoutMs = 60000)
      .asParamMap
    logger.info("Response code: " + interpreterResponse.code)

    if (interpreterResponse.code == 200) {
      val bootstrapNotebookId = Utils.getConfig("zeppelin.bootstrapNotebookId.id")

      logger.info(s"Executing the Bootstrap notebook using url http://localhost:8080/api/notebook/job/$bootstrapNotebookId...")
      val notebookResponse = Http(s"http://localhost:8080/api/notebook/job/$bootstrapNotebookId")
        .postForm
        .timeout(connTimeoutMs = 10000, readTimeoutMs = 60000)
        .asParamMap
      logger.info("Response code: " + notebookResponse.code)

      if (notebookResponse.code == 200) {
        def stillRunningParagraphs(): Boolean = {
          logger.info("Checking if the Bootstrap notebook has finished...")
          val checkNotebookResponse = Http("http://localhost:8080/api/notebook/job/2BKFC4D5W")
            .timeout(connTimeoutMs = 10000, readTimeoutMs = 120000)
            .asString
          logger.info("Response code: " + checkNotebookResponse.code)
          val notebookJobResponse = new Gson().fromJson(checkNotebookResponse.body, classOf[GetNotebookJobResponse])
          notebookJobResponse.body.exists(_.status != "FINISHED")
        }

        while (stillRunningParagraphs()) {
          logger.info("Keep on polling...")
          Thread.sleep(5000)
        }
        logger.info("The Bootstrap notebook has finished.")
      }
    }
  }

  case class GetNotebookJobResponse(status: String, body: Array[ParagraphStatus])

  case class ParagraphStatus(id: String, started: String, finished: String, status: String)

  override protected val logger = LoggerFactory.getLogger(this.getClass)
} 

//设置package包名称以及导入依赖的类
package com.hivehome.kafka.connect.sqs

import java.time.Instant

import org.scalatest.{FunSuite, Matchers}
import org.slf4j.LoggerFactory

import scala.concurrent.ExecutionContext.Implicits.global
import scala.concurrent.Future


class E2ESpec extends FunSuite with Matchers with SQSSupport {
  val logger = LoggerFactory.getLogger(getClass.getName)
  private val KafkaTopic: String = "connect-test"
  override val queueName = "test-sqs" // kafka connect should be setup with this SQS
  queueUrl = sqs.getQueueUrl(queueName).getQueueUrl

  private val props = Map(
    "bootstrap.servers" -> sys.env.getOrElse("KAFKA", "localhost:9092"),
    "schema.registry.url" -> sys.env.getOrElse("SCHEMA_REGISTRY", "http://localhost:8081"))

  val consumer = KafkaAvroConsumer[String, String](props, topicName = KafkaTopic)

  // Test is ignored because it does not run without dependent services
  ignore("should route message SQS -> Kafka") {
    Future {
      // sleep is required so that the message to SQS
      // is sent after the consumer is listening on the kafka topic
      Thread.sleep(500)
      logger.debug("sending message..")
      sendMessage(Instant.now().toString)
      logger.debug("sent message..")
    }

    val msgs = consumer.poll(1, accept = _ => true)

    msgs should have size 1
  }
} 

//设置package包名称以及导入依赖的类
package ie.zalando.pipeline.backbone.concurrent

import scala.concurrent.{ ExecutionContext, Future }
import scala.util.Try
import scala.util.control.NonFatal

import org.slf4j.LoggerFactory

import cats.data.Xor
import ie.zalando.pipeline.backbone.Backbone
import ie.zalando.pipeline.backbone.Phases.{ LocalReleasePhase, TransformationPipelineFailure }

class ExecutionContextBackboneCoordinator[DA](backbone: Backbone[DA], executionContext: ExecutionContext) {

  import ExecutionContextBackboneCoordinator._

  val localInitPhases = backbone.initializeTopLevelContexts

  def process(datum: DA): Future[Xor[TransformationPipelineFailure, DA]] = {
    Future {
      val (dataPhases, releasePhases) = backbone.initializeInLocalContext(-1, localInitPhases).unzip
      try {
        backbone.transformDatum(backbone.createStateMonad(dataPhases), datum)
      } finally {
        releasePhases.foreach((phase: LocalReleasePhase) => {
          Try({ phase.releaseLocalResources() }).recover { case NonFatal(ex) => log.warn(s"Release phase $phase failed:", ex) }
        })
      }
    }(executionContext)
  }

}

object ExecutionContextBackboneCoordinator {
  val log = LoggerFactory.getLogger(classOf[ExecutorServiceBackboneCoordinator[_]])
} 

//设置package包名称以及导入依赖的类
package org.dl4scala.examples.nlp.word2vec

import org.datavec.api.util.ClassPathResource
import org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
import org.deeplearning4j.text.sentenceiterator.BasicLineIterator
import org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CommonPreprocessor
import org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
import org.slf4j.LoggerFactory


object Word2VecRawTextExample {
  private val log = LoggerFactory.getLogger(Word2VecRawTextExample.getClass)

  def main(args: Array[String]): Unit = {
    // Gets Path to Text file
    val filePath: String = new ClassPathResource("raw_sentences.txt").getFile.getAbsolutePath

    log.info("Load & Vectorize Sentences....")
    // Strip white space before and after for each line
    val iter = new BasicLineIterator(filePath)
    // Split on white spaces in the line to get words
    val t = new DefaultTokenizerFactory

    t.setTokenPreProcessor(new CommonPreprocessor)

    import org.deeplearning4j.models.word2vec.Word2Vec

    log.info("Building model....")
    val vec: Word2Vec = new Word2Vec.Builder()
      .minWordFrequency(5)
      .iterations(1)
      .layerSize(100)
      .seed(42)
      .windowSize(5)
      .iterate(iter)
      .tokenizerFactory(t)
      .build

    log.info("Fitting Word2Vec model....")
    vec.fit()

    log.info("Writing word vectors to text file....")
    // Write word vectors to file
    WordVectorSerializer.writeWordVectors(vec, "pathToWriteto.txt")
    // Prints out the closest 10 words to "day". An example on what to do with these Word Vectors.
    log.info("Closest Words:")
    val lst = vec.wordsNearest("day", 10)
    System.out.println("10 Words closest to 'day': " + lst)
  }
} 

//设置package包名称以及导入依赖的类
package org.dl4scala.examples.nlp.paragraphvectors

import org.datavec.api.util.ClassPathResource
import org.deeplearning4j.models.embeddings.loader.WordVectorSerializer
import org.deeplearning4j.text.tokenization.tokenizer.preprocessor.CommonPreprocessor
import org.deeplearning4j.text.tokenization.tokenizerfactory.DefaultTokenizerFactory
import org.nd4j.linalg.ops.transforms.Transforms
import org.slf4j.LoggerFactory


object ParagraphVectorsInferenceExample {
  private val log = LoggerFactory.getLogger(ParagraphVectorsInferenceExample.getClass)

  def main(args: Array[String]): Unit = {
    val resource = new ClassPathResource("/paravec/simple.pv")
    val t = new DefaultTokenizerFactory
    t.setTokenPreProcessor(new CommonPreprocessor)

    // we load externally originated model
    val vectors = WordVectorSerializer.readParagraphVectors(resource.getFile)
    vectors.setTokenizerFactory(t)
    vectors.getConfiguration.setIterations(1) // please note, we set iterations to 1 here, just to speedup inference

    val inferredVectorA = vectors.inferVector("This is my world .")
    val inferredVectorA2 = vectors.inferVector("This is my world .")
    val inferredVectorB = vectors.inferVector("This is my way .")

    // high similarity expected here, since in underlying corpus words WAY and WORLD have really close context
    log.info("Cosine similarity A/B: {}", Transforms.cosineSim(inferredVectorA, inferredVectorB))

    // equality expected here, since inference is happening for the same sentences
    log.info("Cosine similarity A/A2: {}", Transforms.cosineSim(inferredVectorA, inferredVectorA2))
  }
} 

//设置package包名称以及导入依赖的类
package info.unterstein.akka.persistence.api

import com.google.gson._
import java.lang.reflect.Type

import com.google.gson.reflect.TypeToken
import org.slf4j.LoggerFactory

import scala.collection.JavaConverters._


case class PersistentActorMessage(messageType: String, scheduleDate: Long, originalMessage: Map[String, String])

object PersistentActorMessage {

  private val mapToken = new TypeToken[java.util.Map[String, String]](){}.getType

  private val log = LoggerFactory.getLogger(PersistentActorMessage.getClass)

  private val gson = new GsonBuilder()
    .registerTypeAdapter(classOf[Map[String, String]], new MapSerializer())
    .create()

  private class MapSerializer extends JsonSerializer[Map[String, String]] with JsonDeserializer[Map[String, String]] {

    override def serialize(src: Map[String, String], typeOfSrc: Type, context: JsonSerializationContext): JsonElement = {
      gson.toJsonTree(src.asJava)
    }

    override def deserialize(json: JsonElement, typeOfT: Type, context: JsonDeserializationContext): Map[String, String] = {
      val result: java.util.Map[String, String] = gson.fromJson(json, mapToken)
      result.asScala.toMap
    }
  }

  def jsonToMap(json: String): Map[String, String] = {
    try {
      val result: java.util.Map[String, String] = gson.fromJson(json, mapToken)
      result.asScala.toMap
    } catch {
      case o_O: Exception =>
        log.error("Deserialization failed for " + json, o_O)
        throw new RuntimeException("Deserialization failed!", o_O)
    }
  }

  def mapToJson(map: Map[String, String]): String = gson.toJson(map.asJava)
} 

//设置package包名称以及导入依赖的类
package com.scalaio.http.monitoring

import akka.actor.ActorSystem
import akka.http.scaladsl.Http
import akka.http.scaladsl.model.ContentTypes._
import akka.http.scaladsl.model.{HttpEntity, HttpResponse, StatusCodes, Uri}
import akka.http.scaladsl.model.StatusCodes._
import akka.http.scaladsl.server.Directives._
import akka.http.scaladsl.server._
import akka.stream.Materializer
import com.typesafe.config.Config
import com.yammer.metrics.HealthChecks
import com.yammer.metrics.core.HealthCheckRegistry
import org.slf4j.LoggerFactory
import play.api.libs.json.{JsArray, Json}

import scala.util.{Failure, Success}
import scala.collection.convert.wrapAsScala._

object MonitoringServer {

  lazy val logger = LoggerFactory.getLogger(getClass)

  def handleHealthchecks(registry: HealthCheckRegistry): Route = {
    path("health") {
      get {
        complete {
          val checks = registry.runHealthChecks
          val payload = JsArray(checks.map {
            case (name, result) =>
              Json.obj(
                "name" -> name,
                "healthy" -> result.isHealthy,
                "message" -> result.getMessage
              )
          }.toSeq)
          val status = if (checks.values().forall(_.isHealthy)) OK else InternalServerError
          HttpResponse(entity = HttpEntity(`application/json`, Json.stringify(payload)), status = status)
        }
      }
    }
  }

  def start(serverConfig: Config, registry: HealthCheckRegistry = HealthChecks.defaultRegistry())
           (implicit system: ActorSystem, materializer: Materializer): Unit = {
    val host = serverConfig.getString("host")
    val port = serverConfig.getInt("port")
    logger.info(s"Starting monitoring server at: $host:$port")

    val routes = handleHealthchecks(registry) ~ redirect(Uri("/health"), StatusCodes.SeeOther)
    import system.dispatcher
    Http()
      .bindAndHandle(routes, host, port).onComplete {
      case Success(Http.ServerBinding(address)) =>
        logger.info(s"Monitoring server started at :$address")
      case Failure(t) =>
        logger.error("Error while trying to start monitoring server", t)
    }
  }
} 

//设置package包名称以及导入依赖的类
package akka.stream.alpakka.geode.scaladsl

import akka.stream.scaladsl.Sink
import org.slf4j.LoggerFactory

import scala.concurrent.Await
import scala.concurrent.duration.DurationInt
import scala.language.postfixOps

class GeodeFiniteSourceSpec extends GeodeBaseSpec {

  private val log = LoggerFactory.getLogger(classOf[GeodeFiniteSourceSpec])

  "Geode finite source" should {
    it { geodeSettings =>
      "retrieves finite elements from geode" in {

        val reactiveGeode = new ReactiveGeode(geodeSettings)

        //#query
        val source =
          reactiveGeode
            .query[Person](s"select * from /persons order by id")
            .runWith(Sink.foreach(e => log.debug(s"$e")))
        //#query
        Await.ready(source, 10 seconds)

        val animals =
          reactiveGeode
            .query[Animal](s"select * from /animals order by id")
            .runWith(Sink.foreach(e => log.debug(s"$e")))

        Await.ready(animals, 10 seconds)

        val complexes =
          reactiveGeode
            .query[Complex](s"select * from /complexes order by id")
            .runWith(Sink.foreach(e => log.debug(s"$e")))

        Await.ready(complexes, 10 seconds)

        reactiveGeode.close()
      }
    }
  }
} 

//设置package包名称以及导入依赖的类
package ru.fediq.scrapingkit

import java.util.concurrent.TimeUnit

import akka.actor.ActorSystem
import akka.http.scaladsl.model.{HttpMethods, Uri}
import com.codahale.metrics.Slf4jReporter
import com.codahale.metrics.Slf4jReporter.LoggingLevel
import com.typesafe.config.ConfigFactory
import org.scalatest.FlatSpec
import org.slf4j.LoggerFactory
import ru.fediq.scrapingkit.backend.{InMemoryFifoLinksQueue, InMemoryLinksHistory, NoOpFeedExporter, NoOpPageCache}
import ru.fediq.scrapingkit.model.PageRef
import ru.fediq.scrapingkit.scraper.HtmlCrawlingScraper
import ru.fediq.scrapingkit.util.Metrics

class ScrapingKitReactorTest extends FlatSpec {

  "Reactor" should "crawl something" in {
    val scraperName = "crawl"
    val scrapers = Map(scraperName -> new HtmlCrawlingScraper(scraperName))

    val config = ConfigFactory.load()
    implicit val system = ActorSystem("reactor-test", config)

    val linksQueue = new InMemoryFifoLinksQueue()
    val linksHistory = new InMemoryLinksHistory()
    val pageCache = new NoOpPageCache()
    val exporter = new NoOpFeedExporter()

    val reactor = new ScrapingKitReactor(linksQueue, linksHistory, pageCache, exporter, scrapers)
    linksQueue.enqueue(PageRef(Uri("http://quotes.toscrape.com/"), HttpMethods.GET, scraperName))

    Slf4jReporter
      .forRegistry(Metrics.metricRegistry)
      .withLoggingLevel(LoggingLevel.INFO)
      .outputTo(LoggerFactory.getLogger("METRICS"))
      .convertDurationsTo(TimeUnit.MILLISECONDS)
      .convertRatesTo(TimeUnit.SECONDS)
      .build()
      .start(10, TimeUnit.SECONDS)

    Thread.sleep(10000)

    reactor.close()
  }
} 

//设置package包名称以及导入依赖的类
package transformation

import org.apache.kafka.streams.KeyValue
import org.apache.kafka.streams.kstream.Transformer
import org.apache.kafka.streams.processor.ProcessorContext
import org.apache.kafka.streams.state.KeyValueStore
import org.slf4j.{Logger, LoggerFactory}

abstract class CollectTransformer[INPUT_K, INPUT_V, STORE_V, OUTPUT_K, OUTPUT_V](storeName: String)
  extends Transformer[INPUT_K, INPUT_V, KeyValue[OUTPUT_K, OUTPUT_V]] {

  val log: Logger = LoggerFactory.getLogger(this.getClass)

  var ctx: ProcessorContext = _
  var store: KeyValueStore[INPUT_K, STORE_V] = _

  override def init(context: ProcessorContext): Unit = {
    log.debug(s"Init ...")

    ctx = context
    store = ctx.getStateStore(storeName).asInstanceOf[KeyValueStore[INPUT_K, STORE_V]]

    ctx.schedule(100)
    
  }

  override def punctuate(timestamp: Long): KeyValue[OUTPUT_K, OUTPUT_V] = {
    log.debug(s"Punctuating ...")
    null
  }

  override def transform(key: INPUT_K, value: INPUT_V): KeyValue[OUTPUT_K, OUTPUT_V] = {
    log.debug(s"Transforming event : $value")

    val currentStoreValue = store.get(key)
    if (currentStoreValue != null && collectComplete(currentStoreValue, value)) {
      collectOutput(key, currentStoreValue, value)
    } else {
      store.put(key, appendToStore(currentStoreValue, value))
      null
    }
  }

  def appendToStore(storeValue: STORE_V, appendValue: INPUT_V): STORE_V

  def collectComplete(storeValue: STORE_V, appendValue: INPUT_V): Boolean

  def collectOutput(inputKey: INPUT_K, storeValue: STORE_V, mergeValue: INPUT_V): KeyValue[OUTPUT_K, OUTPUT_V]

  override def close(): Unit = {
    log.debug(s"Close ...")
  }
} 

//设置package包名称以及导入依赖的类
package org.wex.cmsfs.lagom.service.discovery.consul

import java.net.URI

import com.lightbend.lagom.internal.client.CircuitBreakers
import com.lightbend.lagom.scaladsl.api.Descriptor.Call
import com.lightbend.lagom.scaladsl.api.ServiceLocator
import com.lightbend.lagom.scaladsl.client.{CircuitBreakerComponents, CircuitBreakingServiceLocator}
import org.slf4j.{Logger, LoggerFactory}
import play.api.Configuration
import scala.concurrent.{ExecutionContext, Future}

trait ConsulServiceLocatorComponents extends CircuitBreakerComponents {
  lazy val serviceLocator: ServiceLocator = new ConsulServiceLocator(configuration, circuitBreakers)(executionContext)
}

class ConsulServiceLocator(configuration: Configuration, circuitBreakers: CircuitBreakers)(implicit ec: ExecutionContext)
  extends CircuitBreakingServiceLocator(circuitBreakers) {

  private val logger: Logger = LoggerFactory.getLogger(this.getClass)

  private val consulServiceExtract = new ConsulServiceExtract(configuration)

  override def locate(name: String, serviceCall: Call[_, _]): Future[Option[URI]] = Future {
    logger.debug(s"request Service Name: ${name}.")
    consulServiceExtract.getService(name)
  }
} 

//设置package包名称以及导入依赖的类
package cloud.hw.actors

import akka.actor.{Actor, Props}
import akka.routing.BalancingPool
import cloud.hw.app.ErrorCase
import cloud.hw.util.GitSourceDownloader
import com.typesafe.scalalogging.Logger
import org.slf4j.LoggerFactory


class GitSourceDownloaderActor extends Actor{
  val logger = Logger(LoggerFactory.getLogger(this.getClass))

  def receive = {
    case GitSourceReceiver(metadata) =>
      logger.info("Download git project and send to ElasticsearchAdderActor")
      val GitRepoZip = GitSourceDownloader.fromUrl(metadata("downloadUrl"))
      var unzippedRepo = GitRepoZip.asInstanceOf[GitSourceDownloader].download

      // Creates a balance pool of actors to split up the work.
      val router = context.actorOf(BalancingPool(4).props(Props(new ElasticsearchAdderActor())))

      // Run through all the lines and give each actor 15 entries to insert into
      // Elasticsearch. We used 15 because more than that and we were basically DDOS
      // the Elasticsearch server.
      while(!unzippedRepo.isEmpty) {
        logger.info("Taking 15 entries")
        router ! AddGitProjectToElasticsearch(metadata("projectName"), unzippedRepo.take(15))
        unzippedRepo = unzippedRepo.drop(15)
      }

    // Not a Git repo, then don't do anything.
    case ErrorCase => logger.info("Error with Git repo download")
    case _ => logger.info("Not a vaild message to GitSourceDownloaderActor")
  }
}