Revize 6dc585b4

Re #9049 thread-safety implementation

Server/ServerApp/Predictor/PredictionController.cs

@@ -43 +43 @@
         /// </summary>
         private IPredictor[] Predictors;
 
+        /// <summary>
+        /// A mutual exclusive lock to pro
+        /// </summary>
+        private readonly object predictorsLock = new Object();
+
         /// <summary>
         /// A reference to a data parser.
         /// </summary>
@@ -64 +69 @@
         /// <param name="dataParser">A data parser used to get training data.</param>
         public PredictionController(IJsonParser weatherService, IDataParser dataParser, string pathToConfig = null)
         {
-            // TODO look for existing predictors
             _log.Info("Constructing a new PredictionController instance.");
             this.weatherService = weatherService;
             // load config or get the default one
@@ -85 +89 @@
             }
 
             this.DataParser = dataParser;
-            this.Predictors = new IPredictor[this.Configuration.PredictorCount];
+            var predictors = new IPredictor[this.Configuration.PredictorCount];
             this.FeatureExtractor = new FeatureExtractor(this.DataParser, this.Configuration);
 
             DirectoryInfo di = new DirectoryInfo(Configuration.ModelDataPath);
@@ -100 +104 @@
                 _log.Info("No predictors found, creating new ones");
                 for (int i = 0; i < this.Configuration.PredictorCount; i++)
                 {
-                    Predictors[i] = new NaiveBayesClassifier();
+                    predictors[i] = new NaiveBayesClassifier();
                 }
             }
+            lock (predictorsLock)
+            {
+                this.Predictors = predictors;
+            }
             PredictorConfiguration.SaveConfig(PredictorConfiguration.DEFAULT_CONFIG_PATH, Configuration);
         }
         public List<string> GetPredictors()
@@ -122 +130 @@
                     {
                         newPredictors[i] = new NaiveBayesClassifier(Array.Find(files, f => Regex.IsMatch(f.Name, $"{predictorID}_{i}.zip")).FullName);
                     }
-                    this.Predictors = newPredictors;
                     files = di.GetFiles($"{predictorID}.txt");
-                    this.DataFilenames = File.ReadLines(files[0].FullName);
-                    this.PredictorID = predictorID;
+                    var dataFilenames = File.ReadLines(files[0].FullName); 
+                    lock (predictorsLock)
+                    {
+                        this.Predictors = newPredictors;
+                        this.DataFilenames = dataFilenames;
+                        this.PredictorID = predictorID;
+                    }
                 } catch (FileNotFoundException e)
                 {
                     _log.Error(e.ToString());
@@ -133 +145 @@
                 }
             } else
             {
-                // TODO indicate exception
                 _log.Debug("Could not find predictor with given predictorID");
                 return 1;
             }
@@ -144 +155 @@
         {
             DirectoryInfo di = new DirectoryInfo(Configuration.ModelDataPath);
 
-            for (int i = 0; i < this.Configuration.PredictorCount; i++)
+            lock (predictorsLock)
             {
-                Predictors[i].Save(Path.Combine(di.FullName, $"{PredictorID}_{i}.zip"));
+                for (int i = 0; i < this.Configuration.PredictorCount; i++)
+                {
+                    Predictors[i].Save(Path.Combine(di.FullName, $"{PredictorID}_{i}.zip"));
+                }
+                File.WriteAllLinesAsync(Path.Combine(di.FullName, $"{PredictorID}.txt"), this.DataFilenames);
             }
-            File.WriteAllLinesAsync(Path.Combine(di.FullName, $"{PredictorID}.txt"), this.DataFilenames);
         }
 
         public int Rollback()
@@ -221 +235 @@
                 if (request.useWeather)
                 {
                     _log.Debug("Predicting for requested weather.");
-                    predictedLabels[i] = this.Predictors[i].Predict(new ModelInput
+                    lock (predictorsLock)
                     {
-                        Rain = (float)request.rain,
-                        Temp = (float)request.temperature,
-                        Wind = (float)request.wind,
-                        Hour = predictionTime.Hour,
-                        Time = predictionTime
-                    });
+                        predictedLabels[i] = this.Predictors[i].Predict(new ModelInput
+                        {
+                            Rain = (float)request.rain,
+                            Temp = (float)request.temperature,
+                            Wind = (float)request.wind,
+                            Hour = predictionTime.Hour,
+                            Time = predictionTime
+                        });
+                    }
                 }
                 else
                 {
@@ -241 +258 @@
                     }
                     else
                     {
-                        predictedLabels[i] = this.Predictors[i].Predict(new ModelInput
+                        lock (predictorsLock)
                         {
-                            Rain = weatherInfo.rain,
-                            Temp = (float)weatherInfo.temp,
-                            Wind = (float)weatherInfo.wind,
-                            Hour = predictionTime.Hour,
-                            Time = predictionTime
-                        });
+                            predictedLabels[i] = this.Predictors[i].Predict(new ModelInput
+                            {
+                                Rain = weatherInfo.rain,
+                                Temp = (float)weatherInfo.temp,
+                                Wind = (float)weatherInfo.wind,
+                                Hour = predictionTime.Hour,
+                                Time = predictionTime
+                            });
+                        }
                     }
                 }
             }
@@ -273 +293 @@
         public void Train()
         {
             DataParser.Parse(DateTime.MinValue, DateTime.MaxValue, this.Configuration.TimeResolution, wholeDay: false);
-            for (int i = 0; i < this.Predictors.Length; i++)
+            for (int i = 0; i < this.Configuration.PredictorCount; i++)
             {
                 // train on all available data
                 List<ModelInput> data = FeatureExtractor.PrepareTrainingInput(i);
                 Console.WriteLine("Training predictor with {0} samples.", data.Count);
-                this.Predictors[i].Fit(data);
+                lock (predictorsLock)
+                {
+                    this.Predictors[i].Fit(data);
+                }
+            }
+            lock (predictorsLock)
+            {
+                this.DataFilenames = this.DataParser.WeatherDataUsed.Concat(this.DataParser.ActivityDataUsed);
+                this.PredictorID = DateTime.Now.ToBinary().ToString();
             }
-            this.DataFilenames = this.DataParser.WeatherDataUsed.Concat(this.DataParser.ActivityDataUsed);
-            this.PredictorID = DateTime.Now.ToBinary().ToString();
             this.Save();
         }