优化的批量分支计算

epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/batch/BatchScoreCalculator.java

@@ -17,16 +17,20 @@ public class BatchScoreCalculator {
      * 执行计算
      * @return 每一条都是一个指标的，所有样本对应的，得分值
      */
-    public List<IndexOutputVO> exec(List<IndexInputVO> indexVOS) {
-        this.indexVOS = indexVOS;
+    public List<IndexOutputVO> exec(List<IndexInputVO> indexInputVOS) {
+        this.indexVOS = indexInputVOS;
 
-        return indexVOS.stream().map(i -> {
+        return indexInputVOS.stream().map(i -> {
             String indexId = i.getIndexId();
-            List indexValues = i.getIndexValues();
+            List<SampleValue> indexValueVOs = i.getIndexValueVOs();
             BigDecimal weight = i.getWeight();
             ScoreCalculator scoreCalculator = i.getScoreCalculator();
 
-            List scores4OneIndex = scoreCalculator.normalize(indexValues, weight);
+            // 循环同一个指标内的多个样本值的SampleValue列表
+            List<SampleScore> scores4OneIndex = indexValueVOs.stream().map(vo -> {
+                BigDecimal score = scoreCalculator.normalize(vo.getSampleValue(), weight);
+                return new SampleScore(vo.getSampleId(), score);
+            }).collect(Collectors.toList());
 
             return new IndexOutputVO(indexId, scores4OneIndex);
         }).collect(Collectors.toList());

epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/batch/IndexInputVO.java

@@ -22,7 +22,7 @@ public class IndexInputVO<T> {
     /**
      * 指标的样本值
      */
-    private List<T> indexValues;
+    private List<SampleValue<T>> indexValueVOs;
 
     /**
      * 权重
@@ -31,8 +31,8 @@ public class IndexInputVO<T> {
 
     private ScoreCalculator<T> scoreCalculator;
 
-    public IndexInputVO(List<T> indexValues, BigDecimal weight, ScoreCalculator<T> scoreCalculator) {
-        this.indexValues = indexValues;
+    public IndexInputVO(List<SampleValue<T>> indexValueVOs, BigDecimal weight, ScoreCalculator<T> scoreCalculator) {
+        this.indexValueVOs = indexValueVOs;
         this.weight = weight;
         this.scoreCalculator = scoreCalculator;
     }

epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/batch/IndexOutputVO.java

@@ -8,7 +8,7 @@ import java.util.List;
 
 @Data
 @AllArgsConstructor
-public class IndexOutputVO<T> {
+public class IndexOutputVO {
 
     /**
      * 指标标记，由使用者传入，用以标记该条指标的独有特性，一般用id或者code
@@ -19,5 +19,5 @@ public class IndexOutputVO<T> {
     /**
      * 指标的样本值
      */
-    private List<BigDecimal> indexScores;
+    private List<SampleScore> indexScoreVOs;
 }

epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/batch/SampleScore.java

@@ -0,0 +1,19 @@
+package com.epmet.support.normalizing.batch;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+
+import java.math.BigDecimal;
+
+/**
+ * 样本得分对象
+ */
+@Data
+@AllArgsConstructor
+public class SampleScore {
+
+    private String sampleId;
+
+    private BigDecimal sampleScore;
+
+}

epmet-module/data-statistical/data-statistical-server/src/main/java/com/epmet/support/normalizing/batch/SampleValue.java

@@ -0,0 +1,17 @@
+package com.epmet.support.normalizing.batch;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+
+/**
+ * 样本值对象
+ */
+@Data
+@AllArgsConstructor
+public class SampleValue<T> {
+
+    private String sampleId;
+
+    private T sampleValue;
+
+}

epmet-module/data-statistical/data-statistical-server/src/test/java/com/epmet/stats/test/normalizing/DemoScoreCal.java

@@ -4,6 +4,7 @@ import com.epmet.support.normalizing.*;
 import com.epmet.support.normalizing.batch.BatchScoreCalculator;
 import com.epmet.support.normalizing.batch.IndexInputVO;
 import com.epmet.support.normalizing.batch.IndexOutputVO;
+import com.epmet.support.normalizing.batch.SampleValue;
 import org.junit.Test;
 
 import java.math.BigDecimal;
@@ -24,10 +25,8 @@ public class DemoScoreCal {
     @Test
     public void demoInteger() {
         Integer[] iArray = {4, 8, 1, 3, 2};
-        BigDecimal minScore = new BigDecimal(5);
-        BigDecimal maxScore = new BigDecimal(10);
 
-        ScoreCalculator sc = new IntegerScoreCalculator(iArray, minScore, maxScore, Correlation.NEGATIVE);
+        ScoreCalculator sc = new IntegerScoreCalculator(iArray, ScoreConstants.MIN_SCORE, ScoreConstants.MAX_SCORE, Correlation.NEGATIVE);
         BigDecimal[] scores = sc.normalize(iArray);
         Arrays.stream(scores).forEach(s -> System.out.println(s));
     }
@@ -38,10 +37,8 @@ public class DemoScoreCal {
     @Test
     public void demoIntegerPartical() {
         Integer[] iArray = {4, 1, 8};
-        BigDecimal minScore = new BigDecimal(5);
-        BigDecimal maxScore = new BigDecimal(10);
 
-        ScoreCalculator sc = new IntegerScoreCalculator(1, 8, minScore, maxScore, Correlation.NEGATIVE);
+        ScoreCalculator sc = new IntegerScoreCalculator(1, 8, ScoreConstants.MIN_SCORE, ScoreConstants.MAX_SCORE, Correlation.NEGATIVE);
         BigDecimal[] scores = sc.normalize(iArray);// 此处也可以直接使用list参数的重载方法，计算阶段没有任何区别，区别在于new IntegerScoreCalculator()阶段
         Arrays.stream(scores).forEach(s -> System.out.println(s));
     }
@@ -76,9 +73,12 @@ public class DemoScoreCal {
         ScoreCalculator<Integer> sc1 = new IntegerScoreCalculator(1, 8, ScoreConstants.MIN_SCORE, ScoreConstants.MAX_SCORE, Correlation.NEGATIVE);
         ScoreCalculator<Integer> sc2 = new IntegerScoreCalculator(1, 8, ScoreConstants.MIN_SCORE, ScoreConstants.MAX_SCORE, Correlation.NEGATIVE);
 
+        List<SampleValue<Integer>> index1SampleValues = Arrays.asList(new SampleValue<>("id1", 4), new SampleValue<>("id2", 1), new SampleValue<>("id3", 8));
+        List<SampleValue<Integer>> index2SampleValues = Arrays.asList(new SampleValue<>("id1", 1), new SampleValue<>("id2", 8), new SampleValue<>("id3", 3));
+
         // 每个指标的信息，包括样本列表，权重，指标标记
-        IndexInputVO<Integer> index1VO = new IndexInputVO<>("aaa", Arrays.asList(4, 1, 8), new BigDecimal(1), sc1);
-        IndexInputVO<Integer> index2VO = new IndexInputVO<>("bbb", Arrays.asList(1, 8, 3), new BigDecimal(1), sc2);
+        IndexInputVO<Integer> index1VO = new IndexInputVO<>("aaa", index1SampleValues, new BigDecimal(1), sc1);
+        IndexInputVO<Integer> index2VO = new IndexInputVO<>("bbb", index2SampleValues, new BigDecimal(1), sc2);
 
         List<IndexInputVO> indexInputVOS = Arrays.asList(index1VO, index2VO);