streaming.dsl.mmlib.algs.python.ResourceManager.scala Maven / Gradle / Ivy

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/*
 * 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 streaming.dsl.mmlib.algs.python

import org.apache.spark.sql.SparkSession
import streaming.common.HDFSOperator
import streaming.dsl.mmlib.algs.{Functions, SQLPythonAlg, SQLPythonFunc}
import streaming.log.{Logging, WowLog}

class ResourceManager(params: Map[String, String]) extends Logging with WowLog {
  def loadResourceInTrain = {
    var resourceParams = Map.empty[String, String]
    if (params.keys.map(_.split("\\.")(0)).toSet.contains("resource")) {
      val resources = Functions.mapParams(s"resource", params)
      resources.foreach {
        case (resourceName, resourcePath) =>
          val tempResourceLocalPath = SQLPythonFunc.getLocalTempResourcePath(resourcePath, resourceName)
          var msg = s"resource paramter found,system will load resource ${resourcePath} in ${tempResourceLocalPath} in executor."
          logInfo(format(msg))
          HDFSOperator.copyToLocalFile(tempResourceLocalPath, resourcePath, true)
          resourceParams += (resourceName -> tempResourceLocalPath)
          msg = s"resource loaded."
          logInfo(format(msg))

      }
    }
    resourceParams
  }

  def loadResourceInRegister(sparkSession: SparkSession, modelMeta: ModelMeta) = {
    val algIndex = params.getOrElse("algIndex", "-1").toInt
    // load resource
    val fitParam = SQLPythonAlg.arrayParamsWithIndex("fitParam", modelMeta.trainParams)
    val selectedFitParam = if (algIndex == -1) Map[String, String]() else fitParam(algIndex)._2
    val loadResource = selectedFitParam.keys.map(_.split("\\.")(0)).toSet.contains("resource")
    var resourceParams = Map.empty[String, String]
    var modelHDFSToLocalPath = Map.empty[String, String]
    // make sure every executor have the model in local directory.
    // we should unregister manually
    modelMeta.modelEntityPaths.foreach { modelPath =>
      val tempModelLocalPath = SQLPythonFunc.getLocalTempModelPath(modelPath)
      modelHDFSToLocalPath += (modelPath -> tempModelLocalPath)
      SQLPythonAlg.distributeResource(sparkSession, modelPath, tempModelLocalPath)

      if (loadResource) {
        val resources = Functions.mapParams(s"resource", selectedFitParam)
        resources.foreach {
          case (resourceName, resourcePath) =>
            val tempResourceLocalPath = SQLPythonFunc.getLocalTempResourcePath(resourcePath, resourceName)
            resourceParams += (resourceName -> tempResourceLocalPath)
            SQLPythonAlg.distributeResource(sparkSession, resourcePath, tempResourceLocalPath)
        }
      }

    }
    (selectedFitParam, resourceParams, modelHDFSToLocalPath)
  }
}