AbstractTrainer no longer stores a local copy of dbName.

datumbox · Dec 21, 2016 · 1e76739 · 1e76739
1 parent eb43202
commit 1e76739
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Showing 7 changed files with 35 additions and 33 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,7 +1,7 @@
 CHANGELOG
 =========
 
-Version 0.8.0-SNAPSHOT - Build 20161220
+Version 0.8.0-SNAPSHOT - Build 20161221
 ---------------------------------------
 
 - Improved Validation:
@@ -20,6 +20,7 @@ Version 0.8.0-SNAPSHOT - Build 20161220
 - Removed the AbstractWrapper and Modeler inherits directly from AbstractTrainer. 
 - Created a TrainableBundle to keep track of the Trainables of Modeler, AbstractBoostingBagging and StepwiseRegression.
 - Removed automatic save after fit, now save() must be called.
+- AbstractTrainer no longer stores a local copy of dbName.
 
 Version 0.7.1-SNAPSHOT - Build 20161217
 ---------------------------------------

diff --git a/...-applications/src/main/java/com/datumbox/framework/applications/datamodeling/Modeler.java b/...-applications/src/main/java/com/datumbox/framework/applications/datamodeling/Modeler.java
@@ -194,6 +194,7 @@ public void predict(Dataframe newData) {
     protected void _fit(Dataframe trainingData) {
         TrainingParameters trainingParameters = knowledgeBase.getTrainingParameters();
         Configuration conf = knowledgeBase.getConf();
+        String dbName = knowledgeBase.getDbc().getDatabaseName();
 
         //reset previous entries on the bundle
         resetBundle();
@@ -264,6 +265,7 @@ private void resetBundle() {
     private void initBundle() {
         TrainingParameters trainingParameters = knowledgeBase.getTrainingParameters();
         Configuration conf = knowledgeBase.getConf();
+        String dbName = knowledgeBase.getDbc().getDatabaseName();
 
         if(!bundle.containsKey("dataTransformer")) {
             AbstractTransformer.AbstractTrainingParameters dtParams = trainingParameters.getDataTransformerTrainingParameters();

diff --git a/...main/java/com/datumbox/framework/common/persistentstorage/inmemory/InMemoryConnector.java b/...main/java/com/datumbox/framework/common/persistentstorage/inmemory/InMemoryConnector.java
@@ -42,19 +42,19 @@
  */
 public class InMemoryConnector extends AbstractDatabaseConnector {
 
-    private final String database;
+    private String dbName;
     private final InMemoryConfiguration dbConf;
 
     /** 
-     * @param database
+     * @param dbName
      * @param dbConf
      * @see AbstractDatabaseConnector#AbstractDatabaseConnector()
      */
-    protected InMemoryConnector(String database, InMemoryConfiguration dbConf) {  
+    protected InMemoryConnector(String dbName, InMemoryConfiguration dbConf) {
         super();
-        this.database = database;
+        this.dbName = dbName;
         this.dbConf = dbConf;
-        logger.trace("Opened db "+ database);
+        logger.trace("Opened db {}", dbName);
     }
 
     /** {@inheritDoc} */
@@ -109,9 +109,9 @@ public void close() {
             return; 
         }
         super.close();
-        logger.trace("Closed db "+ database);
+        logger.trace("Closed db {}", dbName);
     }
-        
+
     /** {@inheritDoc} */
     @Override
     public void clear() {
@@ -150,7 +150,7 @@ public <T extends Map> void dropBigMap(String name, T map) {
     /** {@inheritDoc} */
     @Override
     public String getDatabaseName() {
-        return database;
+        return dbName;
     }
 
     private Path getRootPath() {
@@ -161,6 +161,6 @@ private Path getRootPath() {
             outputFolder = System.getProperty("java.io.tmpdir"); //write them to the tmp directory
         }
 
-        return Paths.get(outputFolder + File.separator + database);
+        return Paths.get(outputFolder + File.separator + dbName);
     }
 }
diff --git a/...n/src/main/java/com/datumbox/framework/common/persistentstorage/mapdb/MapDBConnector.java b/...n/src/main/java/com/datumbox/framework/common/persistentstorage/mapdb/MapDBConnector.java
@@ -41,7 +41,7 @@
  */
 public class MapDBConnector extends AbstractDatabaseConnector {
 
-    private final String database;
+    private String dbName;
     private final MapDBConfiguration dbConf;
 
     /**
@@ -77,15 +77,15 @@ private enum DBType {
     private final Map<DBType, DB> dbRegistry = new HashMap<>(); 
 
     /** 
-     * @param database
+     * @param dbName
      * @param dbConf
      * @see AbstractDatabaseConnector#AbstractDatabaseConnector()
      */
-    protected MapDBConnector(String database, MapDBConfiguration dbConf) {  
+    protected MapDBConnector(String dbName, MapDBConfiguration dbConf) {
         super();
-        this.database = database;
+        this.dbName = dbName;
         this.dbConf = dbConf;
-        logger.trace("Opened db "+ database);
+        logger.trace("Opened db {}", dbName);
     }
 
     /** {@inheritDoc} */
@@ -140,7 +140,7 @@ public void close() {
         super.close();
 
         closeDBRegistry();
-        logger.trace("Closed db "+ database);
+        logger.trace("Closed db {}", dbName);
     }
 
     /** {@inheritDoc} */
@@ -256,7 +256,7 @@ public <T extends Map> void dropBigMap(String name, T map) {
     /** {@inheritDoc} */
     @Override
     public String getDatabaseName() {
-        return database;
+        return dbName;
     }
 
     //private methods of connector class
@@ -406,6 +406,6 @@ private Path getRootPath() {
             outputFolder = System.getProperty("java.io.tmpdir"); //write them to the tmp directory
         }
 
-        return Paths.get(outputFolder + File.separator + database);
+        return Paths.get(outputFolder + File.separator + dbName);
     }
 }
diff --git a/...in/java/com/datumbox/framework/core/machinelearning/common/abstracts/AbstractTrainer.java b/...in/java/com/datumbox/framework/core/machinelearning/common/abstracts/AbstractTrainer.java
@@ -107,11 +107,6 @@ public static abstract class AbstractTrainingParameters implements TrainingParam
      */
     protected final Logger logger = LoggerFactory.getLogger(getClass());
 
-    /**
-     * The name of the Database where we persist our data.
-     */
-    protected final String dbName; //FIXME: do we really need the dbName here? Perhaps a temp name is good enough
-
     /**
      * The KnowledgeBase instance of the algorithm. 
      */
@@ -120,23 +115,23 @@ public static abstract class AbstractTrainingParameters implements TrainingParam
     /**
      * Constructor which is called on model initialization before training.
      * 
-     * @param baseDBname
+     * @param dbName
      * @param conf 
      * @param trainingParameters
      */
-    protected AbstractTrainer(String baseDBname, Configuration conf, TP trainingParameters) {
+    protected AbstractTrainer(String dbName, Configuration conf, TP trainingParameters) {
-        dbName = baseDBname + conf.getDbConfig().getDBnameSeparator() + this.getClass().getSimpleName();
+        dbName += conf.getDbConfig().getDBnameSeparator() + this.getClass().getSimpleName();
         knowledgeBase = new KnowledgeBase<>(dbName, conf, trainingParameters);
     }
 
     /**
      * Constructor which is called when we pre-trained load persisted models.
      *
-     * @param baseDBname
+     * @param dbName
      * @param conf
      */
-    protected AbstractTrainer(String baseDBname, Configuration conf) {
+    protected AbstractTrainer(String dbName, Configuration conf) {
-        dbName = baseDBname + conf.getDbConfig().getDBnameSeparator() + this.getClass().getSimpleName();
+        dbName += conf.getDbConfig().getDBnameSeparator() + this.getClass().getSimpleName();;
         knowledgeBase = new KnowledgeBase<>(dbName, conf);
     }
 

diff --git a/...x/framework/core/machinelearning/common/abstracts/algorithms/AbstractBoostingBagging.java b/...x/framework/core/machinelearning/common/abstracts/algorithms/AbstractBoostingBagging.java
@@ -205,6 +205,7 @@ protected void _predict(Dataframe newData) {
     @Override
     protected void _fit(Dataframe trainingData) {
         Configuration conf = knowledgeBase.getConf();
+        DatabaseConnector dbc = knowledgeBase.getDbc();
         TP trainingParameters = knowledgeBase.getTrainingParameters();
         MP modelParameters = knowledgeBase.getModelParameters();
 
@@ -236,7 +237,7 @@ protected void _fit(Dataframe trainingData) {
         //training the weak classifiers
         int t=0;
         int retryCounter = 0;
-        String prefix = dbName+conf.getDbConfig().getDBnameSeparator()+DB_INDICATOR;
+        String prefix = dbc.getDatabaseName()+conf.getDbConfig().getDBnameSeparator()+DB_INDICATOR;
         while(t<totalWeakClassifiers) {
             logger.debug("Training Weak learner {}", t);
 
@@ -343,12 +344,13 @@ private void resetBundle() {
     }
 
     private void initBundle() {
+        Configuration conf = knowledgeBase.getConf();
+        DatabaseConnector dbc = knowledgeBase.getDbc();
         MP modelParameters = knowledgeBase.getModelParameters();
         TP trainingParameters = knowledgeBase.getTrainingParameters();
-        Configuration conf = knowledgeBase.getConf();
 
         //the number of weak classifiers is the minimum between the classifiers that were defined in training parameters AND the number of the weak classifiers that were kept
-        String prefix = dbName+knowledgeBase.getConf().getDbConfig().getDBnameSeparator()+DB_INDICATOR;
+        String prefix = dbc.getDatabaseName()+knowledgeBase.getConf().getDbConfig().getDBnameSeparator()+DB_INDICATOR;
         Class<AbstractClassifier> weakClassifierClass = trainingParameters.getWeakClassifierTrainingParameters().getTClass();
         int totalWeakClassifiers = Math.min(modelParameters.getWeakClassifierWeights().size(), trainingParameters.getMaxWeakClassifiers());
         for(int t=0;t<totalWeakClassifiers;++t) {

diff --git a/.../main/java/com/datumbox/framework/core/machinelearning/regression/StepwiseRegression.java b/.../main/java/com/datumbox/framework/core/machinelearning/regression/StepwiseRegression.java
@@ -168,6 +168,7 @@ protected void _predict(Dataframe newData) {
     protected void _fit(Dataframe trainingData) {
         TrainingParameters trainingParameters = knowledgeBase.getTrainingParameters();
         Configuration conf = knowledgeBase.getConf();
+        String dbName = knowledgeBase.getDbc().getDatabaseName();
 
         //reset previous entries on the bundle
         resetBundle();
@@ -254,6 +255,7 @@ private void resetBundle() {
     private void initBundle() {
         TrainingParameters trainingParameters = knowledgeBase.getTrainingParameters();
         Configuration conf = knowledgeBase.getConf();
+        String dbName = knowledgeBase.getDbc().getDatabaseName();
 
         if(!bundle.containsKey("mlregressor")) {
             AbstractTrainingParameters mlParams = trainingParameters.getRegressionTrainingParameters();
@@ -265,7 +267,7 @@ private void initBundle() {
     private Map<Object, Double> runRegression(Dataframe trainingData) {
         AbstractRegressor mlregressor = MLBuilder.create(
                 knowledgeBase.getTrainingParameters().getRegressionTrainingParameters(),
-                dbName,
+                knowledgeBase.getDbc().getDatabaseName(),
                 knowledgeBase.getConf()
         );
         mlregressor.fit(trainingData);