针对SKN加分

@@ -62,10 +62,12 @@ public class FunctionScoreSearchHelper {
 
 	private static final float BRAND_INCREASE_SCORE_WEIGHT = 1.1f;// 品类列表默认针对某些品牌加分
 	private static final float BRAND_SORT_INCREASE_SCORE_WEIGHT = 1.1f; // 针对特定的【品牌+品类】加分
+	private static final float SKN_INCREASE_SCORE_WEIGHT = 1.1f;
 
 	private static final float BREAK_PRODUCT_WEIGHT = 0.50f;// 断码区商品得分
 	private static final float GLOABL_DEFUT_WEIGHT = 0.50f;// 全球购得分
 	private static final float PROBLEM_GOODS_WEIGHT = 0.2f;// 一高三低商品降分
+	
 
 	public QueryBuilder buildFunctionScoreQueryBuild(QueryBuilder queryBuilder, BoolQueryBuilder boolQueryBuilder, Map<String, String> paramMap) {
 		FunctionScoreQueryBuilder functionScoreQueryBuilder = new FunctionScoreQueryBuilder(queryBuilder);
@@ -97,6 +99,10 @@ public class FunctionScoreSearchHelper {
 
 		// 7、新品到着的人气值排序，使用人气值当分数，并且针对30天以内的商品做降分
 		this.addNewArriveHeatDescSearch(functionScoreQueryBuilder, paramMap);
+		
+		// 8、针对SKN加分
+		this.addIncreaseScoreSkns(functionScoreQueryBuilder);
+		
 
 		functionScoreQueryBuilder.boostMode(CombineFunction.MULT);
 		return functionScoreQueryBuilder;
@@ -207,6 +213,16 @@ public class FunctionScoreSearchHelper {
 			logger.warn("Parse score rule [" + ruleValue + "] failed!", e);
 		}
 	}
+	
+	//对skn加分
+	private void addIncreaseScoreSkns(FunctionScoreQueryBuilder functionScoreQueryBuilder) {
+		String skns = dynamicConfig.getIncreaseScoreSkns();
+		if (StringUtils.isBlank(skns) || "-1".equals(skns)) {
+			return;
+		}
+		String[] sknsArr = skns.split(",");
+		functionScoreQueryBuilder.add(QueryBuilders.termsQuery(ProductIndexEsField.productSkn, sknsArr), ScoreFunctionBuilders.weightFactorFunction(SKN_INCREASE_SCORE_WEIGHT));
+	}
 
 	// 针对问题商品降分【非新品，且是一高三低0交际】
 	private void addProblemProductSearch(FunctionScoreQueryBuilder functionScoreQueryBuilder, Map<String, String> paramMap) {