[KC-116] shp 파일 생성 기능 수정

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

@@ -53,7 +53,9 @@ public class MapSheetInferenceJobService {
   @Value("${inference.jar-path}")
   private String jarPath;
 
-  /** 추론 진행 배치 1분 */
+  /**
+   * 추론 진행 배치 1분
+   */
   @Scheduled(fixedDelay = 60_000)
   public void runBatch() {
     if (isLocalProfile()) {
@@ -138,7 +140,7 @@ public class MapSheetInferenceJobService {
     String url = batchUrl + "/" + batchId;
 
     ExternalCallResult<String> result =
-        externalHttpClient.call(url, HttpMethod.GET, null, jsonHeaders(), String.class);
+      externalHttpClient.call(url, HttpMethod.GET, null, jsonHeaders(), String.class);
 
     int status = result.statusCode();
     if (status == 404) {
@@ -220,7 +222,7 @@ public class MapSheetInferenceJobService {
     batchIds.add(sheet.getM3BatchId());
 
     List<InferenceResultsTestingDto.ShpDto> resultList =
-        inferenceResultCoreService.getInferenceResults(batchIds);
+      inferenceResultCoreService.getInferenceResults(batchIds);
     String inferenceId = "";
     StringBuilder sb = new StringBuilder();
 
@@ -237,8 +239,10 @@ public class MapSheetInferenceJobService {
     String mapIds = sb.toString();
     String batchId = sheet.getM1BatchId() + "," + sheet.getM2BatchId() + "," + sheet.getM3BatchId();
 
+    // uid 기준 도엽별 shp, geojson 파일 생성
     externalJarRunner.run(jarPath, batchId, inferenceId, mapIds);
 
+    // uid 기준 merge shp, geojson 파일 생성
     externalJarRunner.run(jarPath, batchId, inferenceId, "");
   }
 
@@ -308,28 +312,28 @@ public class MapSheetInferenceJobService {
 
     // 추론 실행 api 파라미터 조회
     InferenceProgressDto progressDto =
-        inferenceResultCoreService.getInferenceAiResultById(id, modelUuid);
+      inferenceResultCoreService.getInferenceAiResultById(id, modelUuid);
 
     // ai 에 맞는 모델 명으로 변경
     String inferenceType = modelToInferenceType(type);
 
     InferenceSendDto.pred_requests_areas predRequestsAreas =
-        new InferenceSendDto.pred_requests_areas();
+      new InferenceSendDto.pred_requests_areas();
     predRequestsAreas.setInput1_year(progressDto.getPred_requests_areas().getInput1_year());
     predRequestsAreas.setInput2_year(progressDto.getPred_requests_areas().getInput2_year());
     predRequestsAreas.setInput1_scene_path(
-        progressDto.getPred_requests_areas().getInput1_scene_path());
+      progressDto.getPred_requests_areas().getInput1_scene_path());
     predRequestsAreas.setInput2_scene_path(
-        progressDto.getPred_requests_areas().getInput2_scene_path());
+      progressDto.getPred_requests_areas().getInput2_scene_path());
 
     InferenceSendDto m = new InferenceSendDto();
     m.setPred_requests_areas(predRequestsAreas);
     m.setModel_version(progressDto.getModelVersion());
     m.setCd_model_path(progressDto.getCdModelPath() + "/" + progressDto.getCdModelFileName());
     m.setCd_model_config(
-        progressDto.getCdModelConfigPath() + "/" + progressDto.getCdModelConfigFileName());
+      progressDto.getCdModelConfigPath() + "/" + progressDto.getCdModelConfigFileName());
     m.setCls_model_path(
-        progressDto.getCdModelClsPath() + "/" + progressDto.getCdModelClsFileName());
+      progressDto.getCdModelClsPath() + "/" + progressDto.getCdModelClsFileName());
     m.setCls_model_version(progressDto.getClsModelVersion());
     m.setCd_model_type(inferenceType);
     m.setPriority(progressDto.getPriority());
@@ -400,7 +404,7 @@ public class MapSheetInferenceJobService {
     headers.setAccept(List.of(MediaType.APPLICATION_JSON));
 
     ExternalCallResult<String> result =
-        externalHttpClient.call(inferenceUrl, HttpMethod.POST, dto, headers, String.class);
+      externalHttpClient.call(inferenceUrl, HttpMethod.POST, dto, headers, String.class);
 
     if (result.statusCode() < 200 || result.statusCode() >= 300) {
       log.error("Inference API failed. status={}, body={}", result.statusCode(), result.body());
@@ -410,7 +414,8 @@ public class MapSheetInferenceJobService {
     // 4) 응답 파싱
     try {
       List<Map<String, Object>> list =
-          objectMapper.readValue(result.body(), new TypeReference<>() {});
+        objectMapper.readValue(result.body(), new TypeReference<>() {
+        });
 
       if (list.isEmpty()) {
         throw new IllegalStateException("Inference response is empty");
@@ -438,9 +443,11 @@ public class MapSheetInferenceJobService {
     return "local".equalsIgnoreCase(profile);
   }
 
-  /** 모델별 추론 종료 update */
+  /**
+   * 모델별 추론 종료 update
+   */
   private void updateProcessingEndTimeByModel(
-      JobStatusDto dto, UUID uuid, ZonedDateTime dateTime, String type) {
+    JobStatusDto dto, UUID uuid, ZonedDateTime dateTime, String type) {
     SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
     saveInferenceAiDto.setUuid(uuid);
     saveInferenceAiDto.setUpdateUid(0L);
@@ -453,9 +460,9 @@ public class MapSheetInferenceJobService {
     inferenceResultCoreService.update(saveInferenceAiDto);
 
     List<Long> failedIds =
-        Optional.ofNullable(dto.getFailedIds()).orElse(List.of()).stream()
+      Optional.ofNullable(dto.getFailedIds()).orElse(List.of()).stream()
-            .map(Long::valueOf)
+        .map(Long::valueOf)
-            .toList();
+        .toList();
 
     // 도엽별 실패여부 업데이트
     inferenceResultCoreService.saveFail5k(uuid, failedIds, type);