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shp파일 생성 수정, 미사용 소스 제거

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teddy
2026-01-23 11:47:01 +09:00
parent ae031e35ca
commit 3f4cf070cd
4 changed files with 33 additions and 41 deletions
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47
src/main/java/com/kamco/cd/kamcoback/scheduler/service/MapSheetInferenceJobService.java
View File

@@ -58,9 +58,7 @@ public class MapSheetInferenceJobService {
@Value("${file.dataset-dir}")
private String datasetDir;
/**
* 추론 진행 배치 1분 60_000
*/
/** 추론 진행 배치 1분 60_000 */
@Scheduled(fixedDelay = 60_000)
public void runBatch() {
if (isLocalProfile()) {
@@ -145,7 +143,7 @@ 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) {
@@ -170,7 +168,7 @@ public class MapSheetInferenceJobService {
String url = inferenceUrl + "/" + jobId;
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) {
@@ -328,28 +326,28 @@ 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());
@@ -417,7 +415,7 @@ 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());
@@ -427,8 +425,7 @@ 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");
@@ -456,11 +453,9 @@ public class MapSheetInferenceJobService {
return "local".equalsIgnoreCase(profile);
}
/**
* 모델별 추론 종료 update
*/
/** 모델별 추론 종료 update */
private void updateProcessingEndTimeByModel(
BatchStatusDto dto, UUID uuid, ZonedDateTime dateTime, String type) {
BatchStatusDto dto, UUID uuid, ZonedDateTime dateTime, String type) {
SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
saveInferenceAiDto.setUuid(uuid);
saveInferenceAiDto.setUpdateUid(0L);
@@ -494,16 +489,16 @@ public class MapSheetInferenceJobService {
/**
* 도엽별 실패여부 업데이트
*
* @param dto batch 정보
* @param dto batch 정보
* @param uuid uuid
* @param type 모델 타입
*/
private void saveFail5k(BatchStatusDto dto, UUID uuid, String type) {
List<Long> failedIds =
Optional.ofNullable(dto.getFailedIds()).orElse(List.of()).stream()
.map(Long::valueOf)
.toList();
Optional.ofNullable(dto.getFailedIds()).orElse(List.of()).stream()
.map(Long::valueOf)
.toList();
List<Long> jobIds = inferenceResultCoreService.findFail5kList(uuid, failedIds, type);
@@ -528,16 +523,16 @@ public class MapSheetInferenceJobService {
/**
* 도엽별 job id 저장
*
* @param dto batch 정보
* @param dto batch 정보
* @param uuid uuid
* @param type 모델 타입
*/
private void saveCompleted5k(BatchStatusDto dto, UUID uuid, String type) {
List<Long> completedIds =
Optional.ofNullable(dto.getCompletedIds()).orElse(List.of()).stream()
.map(Long::valueOf)
.toList();
Optional.ofNullable(dto.getCompletedIds()).orElse(List.of()).stream()
.map(Long::valueOf)
.toList();
List<Long> jobIds = inferenceResultCoreService.findCompleted5kList(uuid, completedIds, type);

3
src/main/java/com/kamco/cd/kamcoback/scheduler/service/ShpPipelineService.java
View File

@@ -16,8 +16,7 @@ public class ShpPipelineService {
private final ShpKeyLock shpKeyLock;
@Async("shpExecutor")
public void runPipeline(
String jarPath, String datasetDir, String batchId, String inferenceId) {
public void runPipeline(String jarPath, String datasetDir, String batchId, String inferenceId) {
// inferenceId 기준 동시 실행 제한
if (!shpKeyLock.tryLock(inferenceId)) {