Github user tgravescs commented on a diff in the pull request:

    https://github.com/apache/spark/pull/204#discussion_r11389264
  
    --- Diff: 
core/src/main/scala/org/apache/spark/deploy/history/HistoryServer.scala ---
    @@ -0,0 +1,265 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.deploy.history
    +
    +import javax.servlet.http.HttpServletRequest
    +
    +import scala.collection.mutable
    +import scala.concurrent._
    +import scala.concurrent.ExecutionContext.Implicits.global
    +
    +import org.apache.hadoop.fs.{FileStatus, Path}
    +import org.eclipse.jetty.servlet.ServletContextHandler
    +
    +import org.apache.spark.{Logging, SecurityManager, SparkConf}
    +import org.apache.spark.deploy.SparkUIContainer
    +import org.apache.spark.ui.SparkUI
    +import org.apache.spark.ui.JettyUtils._
    +import org.apache.spark.util.Utils
    +import org.apache.spark.scheduler.{ApplicationEventListener, 
ReplayListenerBus}
    +
    +/**
    + * A web server that renders SparkUIs of finished applications.
    + *
    + * For the standalone mode, MasterWebUI already achieves this 
functionality. Thus, the
    + * main use case of the HistoryServer is in other deploy modes (e.g. Yarn 
or Mesos).
    + *
    + * The logging directory structure is as follows: Within the given base 
directory, each
    + * application's event logs are maintained in the application's own 
sub-directory. This
    + * is the same structure as maintained in the event log write code path in
    + * EventLoggingListener.
    + *
    + * @param baseLogDir The base directory in which event logs are found
    + * @param requestedPort The requested port to which this server is to be 
bound
    + */
    +class HistoryServer(
    +    val baseLogDir: String,
    +    requestedPort: Int,
    +    conf: SparkConf)
    +  extends SparkUIContainer("History Server") with Logging {
    +
    +  import HistoryServer._
    +
    +  private val fileSystem = Utils.getHadoopFileSystem(baseLogDir)
    +  private val bindHost = Utils.localHostName()
    +  private val publicHost = 
Option(System.getenv("SPARK_PUBLIC_DNS")).getOrElse(bindHost)
    +  private val port = requestedPort
    +  private val securityManager = new SecurityManager(conf)
    +  private val indexPage = new IndexPage(this)
    +
    +  // A timestamp of when the disk was last accessed to check for log 
updates
    +  private var lastLogCheck = -1L
    +
    +  private val handlers = Seq[ServletContextHandler](
    +    createStaticHandler(STATIC_RESOURCE_DIR, "/static"),
    +    createServletHandler("/",
    +      (request: HttpServletRequest) => indexPage.render(request), 
securityMgr = securityManager)
    +  )
    +
    +  // A mapping of application ID to its history information, which 
includes the rendered UI
    +  val appIdToInfo = mutable.HashMap[String, ApplicationHistoryInfo]()
    +
    +  // A set of recently removed applications that the server should avoid 
re-rendering
    +  val appIdBlacklist = mutable.HashSet[String]()
    --- End diff --
    
    This isn't ideal for scaling.  At some point this is going to get huge 
unless the application history logs are cleaned up.  Perhaps we leave that for 
a follow on improvement though since I think you are limited by the way its 
storing them now.  The first thing that came to mind was just to list by date 
and choose the latest x but hadoop filesystem doesn't give you that filter 
without doing stat on each one afterwards. 


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