Merge pull request 'feat/infer_dev_260107' (#226) from feat/infer_dev_260107 into develop

Reviewed-on: https://kamco.gitea.gs.dabeeo.com/dabeeo/kamco-dabeeo-backoffice/pulls/226

src/main/java/com/kamco/cd/kamcoback/inference/service/InferenceResultService.java

@@ -96,7 +96,7 @@ public class InferenceResultService {
 
       // 기준년도 조회
       List<MngListDto> targetList = mapSheetMngCoreService.getHstMapSheetList(req.getTargetYyyy());
-      req.setMapSheetNum(this.createdMngDto(req, targetList));
+      req.setMapSheetNum(createdMngDto(req, targetList));
 
     } else {
       // 부분
@@ -107,7 +107,7 @@ public class InferenceResultService {
       // 기준년도 조회
       List<MngListDto> targetList =
           mapSheetMngCoreService.getHstMapSheetList(req.getTargetYyyy(), mapTargetIds);
-      req.setMapSheetNum(this.createdMngDto(req, targetList));
+      req.setMapSheetNum(createdMngDto(req, targetList));
     }
 
     if (req.getMapSheetNum().isEmpty()) {
@@ -116,7 +116,9 @@ public class InferenceResultService {
 
     // 추론 테이블 저장
     UUID uuid = inferenceResultCoreService.saveInferenceInfo(req);
-    this.startInference(req, uuid);
+
+    // 추론 실행 API 호출
+    startInference(req, uuid);
 
     return uuid;
   }
@@ -198,9 +200,9 @@ public class InferenceResultService {
     }
 
     String modelComparePath =
-        this.getSceneInference(String.valueOf(req.getCompareYyyy()), mapSheetNumList);
+        getSceneInference(String.valueOf(req.getCompareYyyy()), mapSheetNumList);
     String modelTargetPath =
-        this.getSceneInference(String.valueOf(req.getTargetYyyy()), mapSheetNumList);
+        getSceneInference(String.valueOf(req.getTargetYyyy()), mapSheetNumList);
 
     pred_requests_areas predRequestsAreas = new pred_requests_areas();
     predRequestsAreas.setInput1_year(req.getCompareYyyy());

src/main/java/com/kamco/cd/kamcoback/postgres/core/InferenceResultCoreService.java

@@ -104,13 +104,13 @@ public class InferenceResultCoreService {
       buffer.add(e);
 
       if (buffer.size() == CHUNK) {
-        this.flushChunk(buffer);
+        flushChunk(buffer);
         buffer.clear();
       }
     }
 
     if (!buffer.isEmpty()) {
-      this.flushChunk(buffer);
+      flushChunk(buffer);
       buffer.clear();
     }
 

src/main/java/com/kamco/cd/kamcoback/postgres/repository/Inference/MapSheetLearnRepositoryImpl.java

@@ -144,8 +144,9 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
     return Optional.ofNullable(
         queryFactory
             .selectFrom(mapSheetLearnEntity)
-            .where(mapSheetLearnEntity.status.eq(status))
+            .where(mapSheetLearnEntity.id.eq(106L))
-            .limit(1)
+            //        .where(mapSheetLearnEntity.status.eq(status))
+            //        .limit(1)
             .fetchOne());
   }
 

src/main/java/com/kamco/cd/kamcoback/scheduler/MapSheetMngFileJobApiController.java

@@ -3,6 +3,7 @@ package com.kamco.cd.kamcoback.scheduler;
 import com.kamco.cd.kamcoback.code.dto.CommonCodeDto;
 import com.kamco.cd.kamcoback.code.service.CommonCodeService;
 import com.kamco.cd.kamcoback.config.api.ApiResponseDto;
+import com.kamco.cd.kamcoback.scheduler.service.MapSheetInferenceJobService;
 import io.swagger.v3.oas.annotations.Operation;
 import io.swagger.v3.oas.annotations.media.Content;
 import io.swagger.v3.oas.annotations.media.Schema;
@@ -10,6 +11,7 @@ import io.swagger.v3.oas.annotations.responses.ApiResponse;
 import io.swagger.v3.oas.annotations.responses.ApiResponses;
 import io.swagger.v3.oas.annotations.tags.Tag;
 import lombok.RequiredArgsConstructor;
+import org.springframework.web.bind.annotation.GetMapping;
 import org.springframework.web.bind.annotation.PutMapping;
 import org.springframework.web.bind.annotation.RequestMapping;
 import org.springframework.web.bind.annotation.RequestParam;
@@ -23,6 +25,7 @@ public class MapSheetMngFileJobApiController {
 
   private final CommonCodeService commonCodeService;
   private final MapSheetMngFileJobController mapSheetMngFileJobController;
+  private final MapSheetInferenceJobService mapSheetInferenceJobService;
 
   @Operation(summary = "영상관리 파일 싱크 스캐쥴러 Start/Stop", description = "영상관리 파일 싱크 스캐쥴러 Start/Stop API")
   @ApiResponses(
@@ -46,4 +49,22 @@ public class MapSheetMngFileJobApiController {
 
     return ApiResponseDto.createOK("OK");
   }
+
+  @GetMapping("/inference-batch")
+  @ApiResponses(
+      value = {
+        @ApiResponse(
+            responseCode = "200",
+            description = "실행 성공",
+            content =
+                @Content(
+                    mediaType = "application/json",
+                    schema = @Schema(implementation = String.class))),
+        @ApiResponse(responseCode = "404", description = "코드를 찾을 수 없음", content = @Content),
+        @ApiResponse(responseCode = "500", description = "서버 오류", content = @Content)
+      })
+  public ApiResponseDto<String> inferenceRunBatch() {
+    //    mapSheetInferenceJobService.runBatch();
+    return ApiResponseDto.createOK("OK");
+  }
 }

src/main/java/com/kamco/cd/kamcoback/scheduler/service/MapSheetInferenceJobService.java

@@ -48,9 +48,7 @@ public class MapSheetInferenceJobService {
   @Value("${inference.url}")
   private String inferenceUrl;
 
-  /**
+  /** 추론 진행 배치 1분 */
-   * 추론 진행 배치 1분
-   */
   @Scheduled(fixedDelay = 60_000)
   @Transactional
   public void runBatch() {
@@ -103,23 +101,23 @@ public class MapSheetInferenceJobService {
       int failedJobs = dto.getFailedJobs();
 
       // 성공, 실패 값 더해서 total 과 같으면 완료
-      String inferStatus = this.setStatus(totalJobs, completedJobs, failedJobs);
+      String inferStatus = setStatus(totalJobs, completedJobs, failedJobs);
 
       if ("COMPLETED".equals(inferStatus)) {
         String type = batchSheet.getRunningModelType();
 
         if (type.equals("M1")) {
           // M1 완료되었으면 M2 실행
-          this.startInference(
+          startInference(
               batchSheet.getId(), batchSheet.getUuid(), "M2", batchSheet.getM2ModelUuid());
           // 종료시간
-          this.updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M1");
+          updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M1");
         } else if (type.equals("M2")) {
           // M2 완료되었으면 M3 실행
-          this.startInference(
+          startInference(
               batchSheet.getId(), batchSheet.getUuid(), "M3", batchSheet.getM3ModelUuid());
           // 종료시간
-          this.updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M2");
+          updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M2");
         } else if (type.equals("M3")) {
           // 완료
           SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
@@ -129,7 +127,7 @@ public class MapSheetInferenceJobService {
           saveInferenceAiDto.setType(type);
           inferenceResultCoreService.update(saveInferenceAiDto);
           // 종료시간
-          this.updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M3");
+          updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M3");
         }
       } else {
         SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
@@ -181,7 +179,7 @@ public class MapSheetInferenceJobService {
     m.setPriority(progressDto.getPriority());
 
     // 추론 다음모델 실행
-    Long batchId = this.ensureAccepted(m);
+    Long batchId = ensureAccepted(m);
 
     SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
     saveInferenceAiDto.setUuid(uuid);
@@ -230,8 +228,7 @@ public class MapSheetInferenceJobService {
 
     try {
       List<Map<String, Object>> list =
-        om.readValue(body, new TypeReference<List<Map<String, Object>>>() {
+          om.readValue(body, new TypeReference<List<Map<String, Object>>>() {});
-        });
 
       Integer batchIdInt = (Integer) list.get(0).get("batch_id");
       batchId = batchIdInt.longValue();