hbp-sp8-mip-local/woken/application.conf.in

# Sample configuration for local execution of the woken

akka {
  log-dead-letters = 1
  log-dead-letters-during-shutdown = off
  loglevel = INFO

  actor {
    provider = "akka.cluster.ClusterActorRefProvider"
    debug {
      receive = on
      autoreceive = off
      lifecycle = on
      fsm = on
      unhandled = on
      event-stream = off
    }
  }

  remote {
    log-sent-messages = off
    log-received-messages = off
    log-remote-lifecycle-events = off

    maximum-payload-bytes = 10000000 bytes
    enabled-transports = [ "akka.remote.netty.tcp" ]

    netty.tcp {
      hostname = WOKEN_HOST        # external (logical) hostname
      port = WOKEN_AKKA_PORT       # external (logical) port

      bind-hostname = localhost    # internal (bind) hostname
      bind-port = WOKEN_AKKA_PORT  # internal (bind) port

      message-frame-size = 10000000b
      send-buffer-size = 10000000b
      receive-buffer-size = 10000000b
      maximum-frame-size = 10000000b
    }
  }

  cluster {
    seed-nodes = [ "akka.tcp://woken@WOKEN_HOST:WOKEN_AKKA_PORT" ]

    roles = [ "woken" ]
  }
}

spray.can.server {
  idle-timeout = 300s
  request-timeout = 180s
  ssl-encryption = off
  ssl-tracing = on
}

spray.can.client {
  request-timeout = 20s
  chunkless-streaming = off
  connecting-timeout = 10s
}

spray.can.host-connector {
  max-connections = 5
  host-connector.max-retries = 2
  pipelining = on
}

app {
  systemName = "woken" # Needed LS Old version
  interface = "0.0.0.0" # Needed LS Old version
  port = WOKEN_PORT2 # Needed LS Old version

  clusterSystemName = "woken"
  jobServiceName = "job-service"
  dockerBridgeNetwork = "MIP_PRIVATE_NETWORK"
  networkInterface = "0.0.0.0"
  webServicesPort = WOKEN_PORT2

  master.router {
    actors {
      mining.limit = 5
      experiment.limit = 5
    }
  }

  basicAuth {
    username = "admin"
    password = "WoKeN"
  }
}

jobs {
  node = "localhost"
  owner = "admin@mip.chuv.ch"
  chronosServerUrl = "http://CHRONOS_HOST:CHRONOS_PORT1"
  featuresDb = "DB_NAME2"
  featuresTable = "WOKEN_MAIN_TABLE"
  resultDb = "DB_NAME3"
  metaDb = "DB_NAME1"
}

db {
  woken {
    jdbc_driver = "org.postgresql.Driver"
    jdbc_jar_path = "/usr/lib/R/libraries/postgresql-9.4-1201.jdbc41.jar"
    jdbc_url = "jdbc:postgresql://DB_HOST:DB_PORT/DB_NAME3"
    jdbc_user = "DB_USER3"
    jdbc_password = "DB_PASSWORD3"

    host = "DB_HOST"
    port = DB_PORT
    user = "DB_USER3"
    password = "DB_PASSWORD3"
  }

  features {
    jdbc_driver = "org.postgresql.Driver"
    jdbc_jar_path = "/usr/lib/R/libraries/postgresql-9.4-1201.jdbc41.jar"
    jdbc_url = "jdbc:postgresql://DB_HOST:DB_PORT/DB_NAME2"
    jdbc_user = "DB_USER2"
    jdbc_password = "DB_PASSWORD2"

    host = "DB_HOST"
    port = DB_PORT
    user = "DB_USER2"
    password = "DB_PASSWORD2"
  }

  metadata {
    jdbc_driver = "org.postgresql.Driver"
    jdbc_jar_path = "postgresql-9.4-1201.jdbc41.jar"
    jdbc_url = "jdbc:postgresql://DB_HOST:DB_PORT/DB_NAME1"
    jdbc_user = "DB_USER1"
    jdbc_password = "DB_PASSWORD1"

    host = "DB_HOST"
    port = DB_PORT
    user = "DB_USER1"
    password = "DB_PASSWORD1"
  }
}

defaultSettings { # LSC Whole block for old version
  # Default settings for the request service
  request {
    nodes = {}
    inDb = "features"
    outDb = "woken"
    metaDb = "metadata"
    mainTable = "WOKEN_MAIN_TABLE"

    functions {
      histograms = {
        image = "hbpmip/python-histograms:0.3.6"
        predictive = false
      }

      statisticsSummary = {
        image = "hbpmip/r-summary-stats:2afe249"
        predictive = false
      }

      linearRegression = {
        image = "hbpmip/python-linear-regression:0.0.6"
        predictive = false
      }

      anova = {
        image = "hbpmip/python-anova:0.3.5"
        predictive = false
      }

      knn = {
        image = "hbpmip/java-rapidminer-knn:0.2.1"
        predictive = true
      }

      naiveBayes = {
        image = "hbpmip/java-rapidminer-naivebayes:0.2.0"
        predictive = true
      }

      tSNE = {
        image = "hbpmip/python-tsne:0.3.3"
        predictive = true
      }
    }
  }
}

# The actual Algorithm Library
algorithms {
  histograms = {
    dockerImage = "hbpmip/python-histograms:0.3.6"
    predictive = false
  }

  statisticsSummary = {
    dockerImage = "hbpmip/r-summary-stats:2afe249"
    predictive = false
  }

  anova = {
    dockerImage = "hbpmip/python-anova:0.3.6"
    predictive = false
  }

  linearRegression = {
    dockerImage = "hbpmip/python-linear-regression:0.0.7"
    predictive = false
  }

  knn = {
    dockerImage = "hbpmip/java-rapidminer-knn:0.2.1"
    predictive = true
  }

  naiveBayes = {
    dockerImage = "hbpmip/java-rapidminer-naivebayes:0.2.0"
    predictive = true
  }

  tSNE = {
    dockerImage = "hbpmip/python-tsne:0.3.3"
    predictive = true
    maturity = "experimental"
  }

  ggparci = {
    dockerImage = "hbpmip/r-ggparci:0.2.0"
    predictive = false
    maturity = "experimental"
  }
}