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[KC-108] ai api batch 작업중

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teddy
2026-01-12 22:28:38 +09:00
parent 49f2efeb1e
commit 2b8af3215d
9 changed files with 557 additions and 360 deletions
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132
src/main/java/com/kamco/cd/kamcoback/inference/dto/InferenceDetailDto.java
View File

@@ -29,20 +29,22 @@ public class InferenceDetailDto {
private String dataName;
private Long mapSheepNum;
private Long detectingCnt;
@JsonFormatDttm private ZonedDateTime analStrtDttm;
@JsonFormatDttm private ZonedDateTime analEndDttm;
@JsonFormatDttm
private ZonedDateTime analStrtDttm;
@JsonFormatDttm
private ZonedDateTime analEndDttm;
private Long analSec;
private String analState;
public Basic(
Long id,
String dataName,
Long mapSheepNum,
Long detectingCnt,
ZonedDateTime analStrtDttm,
ZonedDateTime analEndDttm,
Long analSec,
String analState) {
Long id,
String dataName,
Long mapSheepNum,
Long detectingCnt,
ZonedDateTime analStrtDttm,
ZonedDateTime analEndDttm,
Long analSec,
String analState) {
this.id = id;
this.dataName = dataName;
this.mapSheepNum = mapSheepNum;
@@ -61,8 +63,10 @@ public class InferenceDetailDto {
private Long id;
private String analTitle;
private Long detectingCnt;
@JsonFormatDttm private ZonedDateTime analStrtDttm;
@JsonFormatDttm private ZonedDateTime analEndDttm;
@JsonFormatDttm
private ZonedDateTime analStrtDttm;
@JsonFormatDttm
private ZonedDateTime analEndDttm;
private Long analSec;
private Long analPredSec;
private String analState;
@@ -70,16 +74,16 @@ public class InferenceDetailDto {
private String gukyuinUsed;
public AnalResList(
Long id,
String analTitle,
Long detectingCnt,
ZonedDateTime analStrtDttm,
ZonedDateTime analEndDttm,
Long analSec,
Long analPredSec,
String analState,
String analStateNm,
String gukyuinUsed) {
Long id,
String analTitle,
Long detectingCnt,
ZonedDateTime analStrtDttm,
ZonedDateTime analEndDttm,
Long analSec,
Long analPredSec,
String analState,
String analStateNm,
String gukyuinUsed) {
this.id = id;
this.analTitle = analTitle;
this.detectingCnt = detectingCnt;
@@ -102,8 +106,10 @@ public class InferenceDetailDto {
private String modelInfo;
private Integer targetYyyy;
private Integer compareYyyy;
@JsonFormatDttm private ZonedDateTime analStrtDttm;
@JsonFormatDttm private ZonedDateTime analEndDttm;
@JsonFormatDttm
private ZonedDateTime analStrtDttm;
@JsonFormatDttm
private ZonedDateTime analEndDttm;
private Long analSec;
private Long analPredSec;
private String resultUrl;
@@ -113,20 +119,20 @@ public class InferenceDetailDto {
private String analStateNm;
public AnalResSummary(
Long id,
String analTitle,
String modelInfo,
Integer targetYyyy,
Integer compareYyyy,
ZonedDateTime analStrtDttm,
ZonedDateTime analEndDttm,
Long analSec,
Long analPredSec,
String resultUrl,
Long detectingCnt,
Double accuracy,
String analState,
String analStateNm) {
Long id,
String analTitle,
String modelInfo,
Integer targetYyyy,
Integer compareYyyy,
ZonedDateTime analStrtDttm,
ZonedDateTime analEndDttm,
Long analSec,
Long analPredSec,
String resultUrl,
Long detectingCnt,
Double accuracy,
String analState,
String analStateNm) {
this.id = id;
this.analTitle = analTitle;
this.modelInfo = modelInfo;
@@ -183,16 +189,17 @@ public class InferenceDetailDto {
private Clazzes target;
private MapSheet mapSheet;
private Coordinate center;
@JsonFormatDttm private ZonedDateTime updatedDttm;
@JsonFormatDttm
private ZonedDateTime updatedDttm;
public DetailListEntity(
UUID uuid,
Double detectionScore,
Clazzes compare,
Clazzes target,
MapSheet mapSheet,
Coordinate center,
ZonedDateTime updatedDttm) {
UUID uuid,
Double detectionScore,
Clazzes compare,
Clazzes target,
MapSheet mapSheet,
Coordinate center,
ZonedDateTime updatedDttm) {
this.code = new Uid(uuid);
this.detectionScore = detectionScore;
this.compare = compare;
@@ -233,7 +240,8 @@ public class InferenceDetailDto {
private String code;
private String name;
@JsonIgnore private Double score;
@JsonIgnore
private Double score;
public Clazz(String code, Double score) {
this.code = code;
@@ -300,21 +308,23 @@ public class InferenceDetailDto {
String classAfterName;
Double classAfterProb;
Long mapSheetNum;
@JsonIgnore String gemoStr;
@JsonIgnore String geomCenterStr;
@JsonIgnore
String gemoStr;
@JsonIgnore
String geomCenterStr;
JsonNode gemo;
JsonNode geomCenter;
public Geom(
Integer compareYyyy,
Integer targetYyyy,
String classBeforeCd,
Double classBeforeProb,
String classAfterCd,
Double classAfterProb,
Long mapSheetNum,
String gemoStr,
String geomCenterStr) {
Integer compareYyyy,
Integer targetYyyy,
String classBeforeCd,
Double classBeforeProb,
String classAfterCd,
Double classAfterProb,
Long mapSheetNum,
String gemoStr,
String geomCenterStr) {
this.compareYyyy = compareYyyy;
this.targetYyyy = targetYyyy;
this.classBeforeCd = classBeforeCd;
@@ -385,7 +395,7 @@ public class InferenceDetailDto {
String[] sortParams = sort.split(",");
String property = sortParams[0];
Sort.Direction direction =
sortParams.length > 1 ? Sort.Direction.fromString(sortParams[1]) : Sort.Direction.ASC;
sortParams.length > 1 ? Sort.Direction.fromString(sortParams[1]) : Sort.Direction.ASC;
return PageRequest.of(page, size, Sort.by(direction, property));
}
return PageRequest.of(page, size);
@@ -399,10 +409,14 @@ public class InferenceDetailDto {
public static class InferenceBatchSheet {
private Long id;
private UUID uuid;
private Long m1BatchId;
private Long m2BatchId;
private Long m3BatchId;
private String status;
private String runningModelType;
private UUID m1ModelUuid;
private UUID m2ModelUuid;
private UUID m3ModelUuid;
}
}

52
src/main/java/com/kamco/cd/kamcoback/inference/dto/InferenceProgressDto.java
View File

@@ -11,36 +11,36 @@ import lombok.Setter;
public class InferenceProgressDto {
private InferenceProgressDto.pred_requests_areas pred_requests_areas;
private String model1_version;
private String model2_version;
private String model3_version;
private String cd_model_path;
private String cd_model_config;
private String cls_model_path;
private String cls_model_version;
private String cd_model_type;
private String modelVersion;
private String cdModelPath;
private String cdModelFileName;
private String cdModelConfigPath;
private String cdModelConfigFileName;
private String cdModelClsPath;
private String cdModelClsFileName;
private String clsModelVersion;
private Integer priority;
public InferenceProgressDto(
InferenceProgressDto.pred_requests_areas pred_requests_areas,
String model1_version,
String model2_version,
String model3_version,
String cd_model_path,
String cd_model_config,
String cls_model_path,
String cls_model_version,
String cd_model_type,
Integer priority) {
InferenceProgressDto.pred_requests_areas pred_requests_areas,
String modelVersion,
String cdModelPath,
String cdModelFileName,
String cdModelConfigPath,
String cdModelConfigFileName,
String cdModelClsPath,
String cdModelClsFileName,
String clsModelVersion,
Integer priority) {
this.pred_requests_areas = pred_requests_areas;
this.model1_version = model1_version;
this.model2_version = model2_version;
this.model3_version = model3_version;
this.cd_model_path = cd_model_path;
this.cd_model_config = cd_model_config;
this.cls_model_path = cls_model_path;
this.cls_model_version = cls_model_version;
this.cd_model_type = cd_model_type;
this.modelVersion = modelVersion;
this.cdModelPath = cdModelPath;
this.cdModelFileName = cdModelFileName;
this.cdModelConfigPath = cdModelConfigPath;
this.cdModelConfigFileName = cdModelConfigFileName;
this.cdModelClsPath = cdModelClsPath;
this.cdModelClsFileName = cdModelClsFileName;
this.clsModelVersion = clsModelVersion;
this.priority = priority;
}

92
src/main/java/com/kamco/cd/kamcoback/inference/dto/InferenceResultDto.java
View File

@@ -22,7 +22,9 @@ import org.springframework.data.domain.Pageable;
public class InferenceResultDto {
/** 목록조회 dto */
/**
* 목록조회 dto
*/
@Getter
@Setter
@AllArgsConstructor
@@ -34,11 +36,15 @@ public class InferenceResultDto {
private String status;
private String mapSheetCnt;
private Long detectingCnt;
@JsonFormatDttm private ZonedDateTime startTime;
@JsonFormatDttm private ZonedDateTime endTime;
@JsonFormatDttm private ZonedDateTime elapsedTime;
@JsonFormatDttm
private ZonedDateTime startTime;
@JsonFormatDttm
private ZonedDateTime endTime;
@JsonFormatDttm
private ZonedDateTime elapsedTime;
private Boolean applyYn;
@JsonFormatDttm private ZonedDateTime applyDttm;
@JsonFormatDttm
private ZonedDateTime applyDttm;
@JsonProperty("statusName")
public String statusName() {
@@ -46,7 +52,9 @@ public class InferenceResultDto {
}
}
/** 목록조회 검색 조건 dto */
/**
* 목록조회 검색 조건 dto
*/
@Getter
@Setter
@NoArgsConstructor
@@ -68,7 +76,9 @@ public class InferenceResultDto {
}
}
/** 탐지 데이터 옵션 dto */
/**
* 탐지 데이터 옵션 dto
*/
@Getter
@AllArgsConstructor
public enum MapSheetScope implements EnumType {
@@ -89,7 +99,9 @@ public class InferenceResultDto {
}
}
/** 분석대상 도엽 enum */
/**
* 분석대상 도엽 enum
*/
@Getter
@AllArgsConstructor
public enum DetectOption implements EnumType {
@@ -137,7 +149,9 @@ public class InferenceResultDto {
}
}
/** 변화탐지 실행 정보 저장 요청 정보 */
/**
* 변화탐지 실행 정보 저장 요청 정보
*/
@Getter
@Setter
@NoArgsConstructor
@@ -176,13 +190,13 @@ public class InferenceResultDto {
@Schema(description = "탐지 데이터 옵션 - 추론제외(EXCL), 이전 년도 도엽 사용(PREV)", example = "EXCL")
@NotBlank
@EnumValid(
enumClass = DetectOption.class,
message = "탐지 데이터 옵션은 '추론제외', '이전 년도 도엽 사용' 만 사용 가능합니다.")
enumClass = DetectOption.class,
message = "탐지 데이터 옵션은 '추론제외', '이전 년도 도엽 사용' 만 사용 가능합니다.")
private String detectOption;
@Schema(
description = "5k 도협 번호 목록",
example = "[{\"mapSheetNum\":37914034,\"mapSheetName\":\"죽변\"}]")
description = "5k 도협 번호 목록",
example = "[{\"mapSheetNum\":37914034,\"mapSheetName\":\"죽변\"}]")
@NotNull
private List<MapSheetNumDto> mapSheetNum;
}
@@ -200,13 +214,16 @@ public class InferenceResultDto {
@NoArgsConstructor
@AllArgsConstructor
public static class InferenceStatusDetailDto {
private String title;
private Integer compareYyyy;
private Integer targetYyyy;
private String detectOption;
private String mapSheetScope;
@JsonFormatDttm private ZonedDateTime inferStartDttm;
@JsonFormatDttm private ZonedDateTime inferEndDttm;
@JsonFormatDttm
private ZonedDateTime inferStartDttm;
@JsonFormatDttm
private ZonedDateTime inferEndDttm;
private Long detectingCnt;
private String model1Ver;
@@ -214,17 +231,17 @@ public class InferenceResultDto {
private String model3Ver;
public InferenceStatusDetailDto(
String title,
Integer compareYyyy,
Integer targetYyyy,
String detectOption,
String mapSheetScope,
ZonedDateTime inferStartDttm,
ZonedDateTime inferEndDttm,
Long detectingCnt,
String model1Ver,
String model2Ver,
String model3Ver) {
String title,
Integer compareYyyy,
Integer targetYyyy,
String detectOption,
String mapSheetScope,
ZonedDateTime inferStartDttm,
ZonedDateTime inferEndDttm,
Long detectingCnt,
String model1Ver,
String model2Ver,
String model3Ver) {
this.title = title;
this.compareYyyy = compareYyyy;
this.targetYyyy = targetYyyy;
@@ -248,12 +265,16 @@ public class InferenceResultDto {
private String model4VerStatusName = "진행중";
public String getDetectOptionName() {
if (this.detectOption.equals("EXCL")) return "추론제외";
if (this.detectOption.equals("EXCL")) {
return "추론제외";
}
return "이전 년도 도엽 사용";
}
public String getMapSheetScopeName() {
if (this.detectOption.equals("ALL")) return "전체";
if (this.detectOption.equals("ALL")) {
return "전체";
}
return "부분";
}
}
@@ -265,9 +286,12 @@ public class InferenceResultDto {
public static class InferenceServerStatusDto {
private String serverName;
@JsonIgnore private float cpu_user;
@JsonIgnore private float cpu_system;
@JsonIgnore private float memused;
@JsonIgnore
private float cpu_user;
@JsonIgnore
private float cpu_system;
@JsonIgnore
private float memused;
private Long kbmemused;
private float gpuUtil;
@@ -372,7 +396,13 @@ public class InferenceResultDto {
private String status;
private String type;
private ZonedDateTime inferStartDttm;
private ZonedDateTime inferEndDttm;
private Long detectEndCnt;
private String modelComparePath;
private String modelTargetPath;
private String modelModelPath;
private ZonedDateTime modelStartDttm;
private ZonedDateTime modelEndDttm;
private Long updateUid;
}
}

79
src/main/java/com/kamco/cd/kamcoback/inference/service/InferenceResultService.java
View File

@@ -96,7 +96,7 @@ public class InferenceResultService {
// 기준년도 조회
List<MngListDto> targetList =
mapSheetMngCoreService.getHstMapSheetList(req.getTargetYyyy(), mapTargetIds);
mapSheetMngCoreService.getHstMapSheetList(req.getTargetYyyy(), mapTargetIds);
req.setMapSheetNum(this.createdMngDto(req, targetList));
}
@@ -109,19 +109,19 @@ public class InferenceResultService {
// 비교년도 탐지 제이터 옵션 별로 조회하여 req에 적용
private List<MapSheetNumDto> createdMngDto(
InferenceResultDto.RegReq req, List<MngListDto> targetList) {
InferenceResultDto.RegReq req, List<MngListDto> targetList) {
List<String> mapTargetIds = new ArrayList<>();
targetList.forEach(
hstMapSheet -> {
// 비교년도는 target 년도 기준으로 가져옴 파라미터 만들기
mapTargetIds.add(hstMapSheet.getMapSheetNum());
});
hstMapSheet -> {
// 비교년도는 target 년도 기준으로 가져옴 파라미터 만들기
mapTargetIds.add(hstMapSheet.getMapSheetNum());
});
// 비교년도 조회
List<String> mapCompareIds = new ArrayList<>();
List<MngListCompareDto> compareList =
mapSheetMngCoreService.getByHstMapSheetCompareList(req.getCompareYyyy(), mapTargetIds);
mapSheetMngCoreService.getByHstMapSheetCompareList(req.getCompareYyyy(), mapTargetIds);
for (MngListCompareDto dto : compareList) {
// 추론 제외일때 이전년도 파일이 없으면 제외
@@ -136,35 +136,35 @@ public class InferenceResultService {
}
Set<String> compareSet =
mapCompareIds.stream()
.filter(Objects::nonNull)
.map(String::trim) // 공백/개행 방지
.collect(Collectors.toSet());
mapCompareIds.stream()
.filter(Objects::nonNull)
.map(String::trim) // 공백/개행 방지
.collect(Collectors.toSet());
// target 기준 compare 비교하여 서로 있는것만 저장
List<String> commonIds =
mapTargetIds.stream()
.filter(Objects::nonNull)
.map(String::trim)
.filter(compareSet::contains)
.toList();
mapTargetIds.stream()
.filter(Objects::nonNull)
.map(String::trim)
.filter(compareSet::contains)
.toList();
Set<String> commonIdSet =
commonIds.stream().filter(Objects::nonNull).map(String::trim).collect(Collectors.toSet());
commonIds.stream().filter(Objects::nonNull).map(String::trim).collect(Collectors.toSet());
// 저장하기위해 파라미터 다시 구성
List<MapSheetNumDto> mapSheetNum =
targetList.stream()
.filter(dto -> dto.getMapSheetNum() != null)
.filter(dto -> commonIdSet.contains(dto.getMapSheetNum().trim()))
.map(
dto -> {
MapSheetNumDto mapSheetNumDto = new MapSheetNumDto();
mapSheetNumDto.setMapSheetNum(dto.getMapSheetNum());
mapSheetNumDto.setMapSheetName(dto.getMapSheetName());
return mapSheetNumDto;
})
.toList();
targetList.stream()
.filter(dto -> dto.getMapSheetNum() != null)
.filter(dto -> commonIdSet.contains(dto.getMapSheetNum().trim()))
.map(
dto -> {
MapSheetNumDto mapSheetNumDto = new MapSheetNumDto();
mapSheetNumDto.setMapSheetNum(dto.getMapSheetNum());
mapSheetNumDto.setMapSheetName(dto.getMapSheetName());
return mapSheetNumDto;
})
.toList();
return mapSheetNum;
}
@@ -184,9 +184,9 @@ public class InferenceResultService {
}
String modelComparePath =
this.getSceneInference(String.valueOf(req.getCompareYyyy()), mapSheetNumList);
this.getSceneInference(String.valueOf(req.getCompareYyyy()), mapSheetNumList);
String modelTargetPath =
this.getSceneInference(String.valueOf(req.getTargetYyyy()), mapSheetNumList);
this.getSceneInference(String.valueOf(req.getTargetYyyy()), mapSheetNumList);
pred_requests_areas predRequestsAreas = new pred_requests_areas();
predRequestsAreas.setInput1_year(req.getCompareYyyy());
@@ -212,6 +212,7 @@ public class InferenceResultService {
saveInferenceAiDto.setInferStartDttm(ZonedDateTime.now());
saveInferenceAiDto.setModelComparePath(modelComparePath);
saveInferenceAiDto.setModelTargetPath(modelTargetPath);
saveInferenceAiDto.setModelStartDttm(ZonedDateTime.now());
inferenceResultCoreService.update(saveInferenceAiDto);
}
@@ -240,7 +241,7 @@ public class InferenceResultService {
}
ExternalCallResult<String> result =
externalHttpClient.call(inferenceUrl, HttpMethod.POST, dto, headers, String.class);
externalHttpClient.call(inferenceUrl, HttpMethod.POST, dto, headers, String.class);
int status = result.statusCode();
String body = result.body();
@@ -253,7 +254,8 @@ public class InferenceResultService {
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();
@@ -352,7 +354,7 @@ public class InferenceResultService {
* @return
*/
public Page<InferenceDetailDto.Geom> getInferenceResultGeomList(
Long id, InferenceDetailDto.SearchGeoReq searchGeoReq) {
Long id, InferenceDetailDto.SearchGeoReq searchGeoReq) {
return inferenceResultCoreService.getInferenceResultGeomList(id, searchGeoReq);
}
@@ -363,7 +365,7 @@ public class InferenceResultService {
* @return
*/
public Page<InferenceDetailDto.DetailListEntity> listInferenceResultWithGeom(
@NotNull Long id, InferenceDetailDto.SearchGeoReq searchReq) {
@NotNull Long id, InferenceDetailDto.SearchGeoReq searchReq) {
return inferenceResultCoreService.listInferenceResultWithGeom(id, searchReq);
}
@@ -408,12 +410,15 @@ public class InferenceResultService {
public InferenceStatusDetailDto getInferenceStatus(UUID uuid) {
List<InferenceServerStatusDto> servers =
inferenceResultCoreService.getInferenceServerStatusList();
inferenceResultCoreService.getInferenceServerStatusList();
String serverNames = "";
for (InferenceServerStatusDto server : servers) {
if (serverNames.equals("")) serverNames = server.getServerName();
else serverNames = serverNames + "," + server.getServerName();
if (serverNames.equals("")) {
serverNames = server.getServerName();
} else {
serverNames = serverNames + "," + server.getServerName();
}
}
InferenceStatusDetailDto dto = inferenceResultCoreService.getInferenceStatus(uuid);

121
src/main/java/com/kamco/cd/kamcoback/postgres/core/InferenceResultCoreService.java
View File

@@ -6,6 +6,7 @@ import com.kamco.cd.kamcoback.inference.dto.InferenceDetailDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceDetailDto.Dashboard;
import com.kamco.cd.kamcoback.inference.dto.InferenceDetailDto.InferenceBatchSheet;
import com.kamco.cd.kamcoback.inference.dto.InferenceDetailDto.MapSheet;
import com.kamco.cd.kamcoback.inference.dto.InferenceProgressDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceResultDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceResultDto.InferenceServerStatusDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceResultDto.InferenceStatusDetailDto;
@@ -24,6 +25,7 @@ import com.kamco.cd.kamcoback.postgres.repository.scene.MapInkx5kRepository;
import jakarta.persistence.EntityManager;
import jakarta.persistence.EntityNotFoundException;
import jakarta.validation.constraints.NotNull;
import java.time.ZonedDateTime;
import java.util.ArrayList;
import java.util.List;
import java.util.Set;
@@ -63,11 +65,11 @@ public class InferenceResultCoreService {
*/
public UUID saveInferenceInfo(InferenceResultDto.RegReq req) {
String mapSheetName =
req.getMapSheetNum().get(0).getMapSheetName() + " 외 " + req.getMapSheetNum().size() + "건";
req.getMapSheetNum().get(0).getMapSheetName() + " 외 " + req.getMapSheetNum().size() + "건";
if (req.getMapSheetNum().size() == 1) {
mapSheetName =
req.getMapSheetNum().get(0).getMapSheetName() + " " + req.getMapSheetNum().size() + "건";
req.getMapSheetNum().get(0).getMapSheetName() + " " + req.getMapSheetNum().size() + "건";
}
MapSheetLearnEntity mapSheetLearnEntity = new MapSheetLearnEntity();
@@ -115,22 +117,22 @@ public class InferenceResultCoreService {
// 청크 번호 추출 in 조건 만들기
List<String> chunkNums =
buffer.stream().map(e -> String.valueOf(e.getMapSheetNum())).distinct().toList();
buffer.stream().map(e -> String.valueOf(e.getMapSheetNum())).distinct().toList();
// 추론 제외
List<MapInkx5kEntity> usedEntities =
mapInkx5kRepository.findByMapSheetNumInAndUseInference(chunkNums, CommonUseStatus.USE);
mapInkx5kRepository.findByMapSheetNumInAndUseInference(chunkNums, CommonUseStatus.USE);
// TODO 추론 제외 했으면 파일 있는지도 확인 해야함
// 조회 결과에서 번호만 Set으로
Set<String> usedSet =
usedEntities.stream()
.map(MapInkx5kEntity::getMapidcdNo)
.collect(java.util.stream.Collectors.toSet());
usedEntities.stream()
.map(MapInkx5kEntity::getMapidcdNo)
.collect(java.util.stream.Collectors.toSet());
// 필터 후 저장
List<MapSheetLearn5kEntity> toSave =
buffer.stream().filter(e -> usedSet.contains(String.valueOf(e.getMapSheetNum()))).toList();
buffer.stream().filter(e -> usedSet.contains(String.valueOf(e.getMapSheetNum()))).toList();
if (!toSave.isEmpty()) {
mapSheetLearn5kRepository.saveAll(toSave);
@@ -150,9 +152,9 @@ public class InferenceResultCoreService {
*/
public InferenceDetailDto.AnalResSummary getInferenceResultSummary(Long id) {
InferenceDetailDto.AnalResSummary summary =
mapSheetAnalDataRepository
.getInferenceResultSummary(id)
.orElseThrow(() -> new EntityNotFoundException("요약정보를 찾을 수 없습니다. " + id));
mapSheetAnalDataRepository
.getInferenceResultSummary(id)
.orElseThrow(() -> new EntityNotFoundException("요약정보를 찾을 수 없습니다. " + id));
return summary;
}
@@ -173,7 +175,7 @@ public class InferenceResultCoreService {
* @return
*/
public Page<InferenceDetailDto.Geom> getInferenceResultGeomList(
Long id, InferenceDetailDto.SearchGeoReq searchGeoReq) {
Long id, InferenceDetailDto.SearchGeoReq searchGeoReq) {
return mapSheetAnalDataRepository.getInferenceGeomList(id, searchGeoReq);
}
@@ -185,16 +187,16 @@ public class InferenceResultCoreService {
*/
@Transactional(readOnly = true)
public Page<InferenceDetailDto.DetailListEntity> listInferenceResultWithGeom(
@NotNull Long analyId, InferenceDetailDto.SearchGeoReq searchReq) {
@NotNull Long analyId, InferenceDetailDto.SearchGeoReq searchReq) {
// 분석 ID 에 해당하는 dataids를 가져온다.
List<Long> dataIds =
mapSheetAnalDataRepository.listAnalyGeom(analyId).stream()
.mapToLong(MapSheetAnalDataInferenceEntity::getId)
.boxed()
.toList();
mapSheetAnalDataRepository.listAnalyGeom(analyId).stream()
.mapToLong(MapSheetAnalDataInferenceEntity::getId)
.boxed()
.toList();
// 해당데이터의 폴리곤데이터를 가져온다
Page<MapSheetAnalDataInferenceGeomEntity> mapSheetAnalDataGeomEntities =
mapSheetAnalDataRepository.listInferenceResultWithGeom(dataIds, searchReq);
mapSheetAnalDataRepository.listInferenceResultWithGeom(dataIds, searchReq);
return mapSheetAnalDataGeomEntities.map(MapSheetAnalDataInferenceGeomEntity::toEntity);
}
@@ -211,34 +213,64 @@ public class InferenceResultCoreService {
@Transactional(readOnly = true)
public List<MapSheet> listGetScenes5k(Long analyId) {
List<String> sceneCodes =
mapSheetAnalDataRepository.listAnalyGeom(analyId).stream()
.mapToLong(MapSheetAnalDataInferenceEntity::getMapSheetNum)
.mapToObj(String::valueOf)
.toList();
mapSheetAnalDataRepository.listAnalyGeom(analyId).stream()
.mapToLong(MapSheetAnalDataInferenceEntity::getMapSheetNum)
.mapToObj(String::valueOf)
.toList();
return mapInkx5kRepository.listGetScenes5k(sceneCodes).stream()
.map(MapInkx5kEntity::toEntity)
.toList();
.map(MapInkx5kEntity::toEntity)
.toList();
}
public void update(SaveInferenceAiDto request) {
MapSheetLearnEntity entity =
mapSheetLearnRepository
.getInferenceResultByUuid(request.getUuid())
.orElseThrow(() -> new EntityNotFoundException());
mapSheetLearnRepository
.getInferenceResultByUuid(request.getUuid())
.orElseThrow(() -> new EntityNotFoundException());
if (request.getType().equals("M1")) {
entity.setM1ModelBatchId(request.getBatchId());
if (request.getModelStartDttm() != null) {
entity.setM1ModelStartDttm(request.getModelStartDttm());
}
if (request.getModelEndDttm() != null) {
entity.setM1ModelEndDttm(request.getModelEndDttm());
}
} else if (request.getType().equals("M2")) {
entity.setM2ModelBatchId(request.getBatchId());
if (request.getModelStartDttm() != null) {
entity.setM2ModelStartDttm(request.getModelStartDttm());
}
if (request.getModelEndDttm() != null) {
entity.setM2ModelEndDttm(request.getModelEndDttm());
}
} else if (request.getType().equals("M3")) {
entity.setM3ModelBatchId(request.getBatchId());
if (request.getModelStartDttm() != null) {
entity.setM3ModelStartDttm(request.getModelStartDttm());
}
if (request.getModelEndDttm() != null) {
entity.setM3ModelEndDttm(request.getModelEndDttm());
}
}
if (request.getInferStartDttm() != null) {
entity.setInferStartDttm(request.getInferStartDttm());
}
if (request.getInferEndDttm() != null) {
entity.setInferEndDttm(request.getInferEndDttm());
}
if (request.getModelComparePath() != null) {
entity.setModelComparePath(request.getModelComparePath());
}
@@ -247,8 +279,24 @@ public class InferenceResultCoreService {
entity.setModelTargetPath(request.getModelTargetPath());
}
entity.setRunningModelType(request.getType());
entity.setStatus(request.getStatus());
if (request.getDetectEndCnt() != null) {
entity.setDetectEndCnt(request.getDetectEndCnt());
}
if (request.getType() != null) {
entity.setRunningModelType(request.getType());
}
if (request.getStatus() != null) {
entity.setStatus(request.getStatus());
}
if (request.getUpdateUid() != null) {
entity.setUpdatedUid(request.getUpdateUid());
}
entity.setUpdatedDttm(ZonedDateTime.now());
}
public List<InferenceServerStatusDto> getInferenceServerStatusList() {
@@ -257,23 +305,26 @@ public class InferenceResultCoreService {
public InferenceBatchSheet getInferenceResultByStatus(String status) {
MapSheetLearnEntity entity =
mapSheetLearnRepository
.getInferenceResultByStatus(status)
.orElseThrow(() -> new EntityNotFoundException(status));
mapSheetLearnRepository
.getInferenceResultByStatus(status)
.orElseThrow(() -> new EntityNotFoundException(status));
InferenceBatchSheet inferenceBatchSheet = new InferenceBatchSheet();
inferenceBatchSheet.setId(entity.getId());
inferenceBatchSheet.setUuid(entity.getUuid());
inferenceBatchSheet.setM1BatchId(entity.getM1ModelBatchId());
inferenceBatchSheet.setM2BatchId(entity.getM2ModelBatchId());
inferenceBatchSheet.setM3BatchId(entity.getM3ModelBatchId());
inferenceBatchSheet.setStatus(entity.getStatus());
inferenceBatchSheet.setRunningModelType(entity.getRunningModelType());
inferenceBatchSheet.setM1ModelUuid(entity.getM1ModelUuid());
inferenceBatchSheet.setM2ModelUuid(entity.getM2ModelUuid());
inferenceBatchSheet.setM3ModelUuid(entity.getM3ModelUuid());
return inferenceBatchSheet;
}
public SaveInferenceAiDto getInferenceAiResultById(Long id) {
return null;
public InferenceProgressDto getInferenceAiResultById(Long id, String type, UUID modelUuid) {
return mapSheetLearnRepository.getInferenceAiResultById(id, modelUuid);
}
public InferenceStatusDetailDto getInferenceStatus(UUID uuid) {

39
src/main/java/com/kamco/cd/kamcoback/postgres/entity/MapSheetLearnEntity.java
View File

@@ -25,9 +25,9 @@ public class MapSheetLearnEntity {
@Id
@GeneratedValue(strategy = GenerationType.SEQUENCE, generator = "tb_map_sheet_learn_id_gen")
@SequenceGenerator(
name = "tb_map_sheet_learn_id_gen",
sequenceName = "tb_map_sheet_learn_uid",
allocationSize = 1)
name = "tb_map_sheet_learn_id_gen",
sequenceName = "tb_map_sheet_learn_uid",
allocationSize = 1)
@Column(name = "id", nullable = false)
private Long id;
@@ -124,17 +124,30 @@ public class MapSheetLearnEntity {
@Column(name = "model_target_path")
private String modelTargetPath;
@Column(name = "m1_model_start_dttm")
private ZonedDateTime m1ModelStartDttm;
@Column(name = "m2_model_start_dttm")
private ZonedDateTime m2ModelStartDttm;
@Column(name = "m3_model_start_dttm")
private ZonedDateTime m3ModelStartDttm;
@Column(name = "m1_model_end_dttm")
private ZonedDateTime m1ModelEndDttm;
@Column(name = "m2_model_end_dttm")
private ZonedDateTime m2ModelEndDttm;
@Column(name = "m3_model_end_dttm")
private ZonedDateTime m3ModelEndDttm;
public InferenceResultDto.ResultList toDto() {
return new InferenceResultDto.ResultList(
this.uuid,
this.title,
this.status,
this.mapSheetCnt,
this.detectingCnt,
this.inferStartDttm,
this.inferEndDttm,
this.elapsedTime,
this.applyYn,
this.applyDttm);
this.uuid,
this.title,
this.status,
this.mapSheetCnt,
this.detectingCnt,
this.inferStartDttm,
this.inferEndDttm,
this.elapsedTime,
this.applyYn,
this.applyDttm);
}
}

2
src/main/java/com/kamco/cd/kamcoback/postgres/repository/Inference/MapSheetLearnRepositoryCustom.java
View File

@@ -20,7 +20,7 @@ public interface MapSheetLearnRepositoryCustom {
Optional<MapSheetLearnEntity> getInferenceResultByStatus(String status);
Optional<InferenceProgressDto> getInferenceAiResultById(Long id);
InferenceProgressDto getInferenceAiResultById(Long id, UUID modelUuid);
public InferenceStatusDetailDto getInferenceStatus(UUID uuid);
}

221
src/main/java/com/kamco/cd/kamcoback/postgres/repository/Inference/MapSheetLearnRepositoryImpl.java
View File

@@ -40,7 +40,7 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
BooleanBuilder builder = new BooleanBuilder();
NumberExpression<Integer> statusOrder =
new CaseBuilder().when(mapSheetLearnEntity.status.eq("Y")).then(0).otherwise(1);
new CaseBuilder().when(mapSheetLearnEntity.status.eq("Y")).then(0).otherwise(1);
// 국유인 반영 여부
if (StringUtils.isNotBlank(req.getApplyYn())) {
@@ -54,10 +54,10 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
// 국유인 반영일
if (req.getStrtDttm() != null && req.getEndDttm() != null) {
builder.and(
mapSheetLearnEntity
.applyDttm
.goe(DateRange.start(req.getStrtDttm()))
.and(mapSheetLearnEntity.applyDttm.lt(DateRange.end(req.getEndDttm()))));
mapSheetLearnEntity
.applyDttm
.goe(DateRange.start(req.getStrtDttm()))
.and(mapSheetLearnEntity.applyDttm.lt(DateRange.end(req.getEndDttm()))));
}
// 제목
@@ -66,21 +66,21 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
}
List<MapSheetLearnEntity> content =
queryFactory
.select(mapSheetLearnEntity)
.from(mapSheetLearnEntity)
.where(builder)
.offset(pageable.getOffset())
.limit(pageable.getPageSize())
.orderBy(statusOrder.asc())
.fetch();
queryFactory
.select(mapSheetLearnEntity)
.from(mapSheetLearnEntity)
.where(builder)
.offset(pageable.getOffset())
.limit(pageable.getPageSize())
.orderBy(statusOrder.asc())
.fetch();
Long total =
queryFactory
.select(mapSheetLearnEntity.count())
.from(mapSheetLearnEntity)
.where(builder)
.fetchOne();
queryFactory
.select(mapSheetLearnEntity.count())
.from(mapSheetLearnEntity)
.where(builder)
.fetchOne();
return new PageImpl<>(content, pageable, total == null ? 0L : total);
}
@@ -88,10 +88,10 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
@Override
public Optional<MapSheetLearnEntity> getInferenceResultByUuid(UUID uuid) {
return Optional.ofNullable(
queryFactory
.selectFrom(mapSheetLearnEntity)
.where(mapSheetLearnEntity.uuid.eq(uuid))
.fetchOne());
queryFactory
.selectFrom(mapSheetLearnEntity)
.where(mapSheetLearnEntity.uuid.eq(uuid))
.fetchOne());
}
@Override
@@ -100,41 +100,41 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
BooleanBuilder builder = new BooleanBuilder();
List<Integer> latestIds =
queryFactory
.select(systemMetricEntity.id1.max())
.from(systemMetricEntity)
.groupBy(systemMetricEntity.serverName)
.fetch();
queryFactory
.select(systemMetricEntity.id1.max())
.from(systemMetricEntity)
.groupBy(systemMetricEntity.serverName)
.fetch();
List<Integer> latestGpuIds =
queryFactory
.select(gpuMetricEntity.id1.max())
.from(gpuMetricEntity)
.groupBy(gpuMetricEntity.serverName)
.fetch();
queryFactory
.select(gpuMetricEntity.id1.max())
.from(gpuMetricEntity)
.groupBy(gpuMetricEntity.serverName)
.fetch();
List<InferenceServerStatusDto> foundContent =
queryFactory
.select(
Projections.constructor(
InferenceServerStatusDto.class,
systemMetricEntity.serverName,
systemMetricEntity.cpuUser,
systemMetricEntity.cpuSystem,
systemMetricEntity.memused,
systemMetricEntity.kbmemused,
gpuMetricEntity.gpuUtil))
.from(systemMetricEntity)
.leftJoin(gpuMetricEntity)
.on(
gpuMetricEntity
.id1
.in(latestGpuIds)
.and(gpuMetricEntity.serverName.eq(systemMetricEntity.serverName)))
.where(systemMetricEntity.id1.in(latestIds)) // In 절 사용
.orderBy(systemMetricEntity.serverName.asc())
.limit(4)
.fetch();
queryFactory
.select(
Projections.constructor(
InferenceServerStatusDto.class,
systemMetricEntity.serverName,
systemMetricEntity.cpuUser,
systemMetricEntity.cpuSystem,
systemMetricEntity.memused,
systemMetricEntity.kbmemused,
gpuMetricEntity.gpuUtil))
.from(systemMetricEntity)
.leftJoin(gpuMetricEntity)
.on(
gpuMetricEntity
.id1
.in(latestGpuIds)
.and(gpuMetricEntity.serverName.eq(systemMetricEntity.serverName)))
.where(systemMetricEntity.id1.in(latestIds)) // In 절 사용
.orderBy(systemMetricEntity.serverName.asc())
.limit(4)
.fetch();
return foundContent;
}
@@ -142,11 +142,11 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
@Override
public Optional<MapSheetLearnEntity> getInferenceResultByStatus(String status) {
return Optional.ofNullable(
queryFactory
.selectFrom(mapSheetLearnEntity)
.where(mapSheetLearnEntity.status.eq(status))
.limit(1)
.fetchOne());
queryFactory
.selectFrom(mapSheetLearnEntity)
.where(mapSheetLearnEntity.status.eq(status))
.limit(1)
.fetchOne());
}
@Override
@@ -159,61 +159,64 @@ public class MapSheetLearnRepositoryImpl implements MapSheetLearnRepositoryCusto
QModelMngEntity m3Model = new QModelMngEntity("m3Model");
InferenceStatusDetailDto foundContent =
queryFactory
.select(
Projections.constructor(
InferenceStatusDetailDto.class,
mapSheetLearnEntity.title,
mapSheetLearnEntity.compareYyyy,
mapSheetLearnEntity.targetYyyy,
mapSheetLearnEntity.detectOption,
mapSheetLearnEntity.mapSheetScope,
mapSheetLearnEntity.inferStartDttm,
mapSheetLearnEntity.inferEndDttm,
mapSheetLearnEntity.detectingCnt,
m1Model.modelVer.as("model1Ver"),
m2Model.modelVer.as("model2Ver"),
m3Model.modelVer.as("model3Ver")))
.from(mapSheetLearnEntity)
.leftJoin(m1Model)
.on(m1Model.uuid.eq(mapSheetLearnEntity.m1ModelUuid))
.leftJoin(m2Model)
.on(m2Model.uuid.eq(mapSheetLearnEntity.m2ModelUuid))
.leftJoin(m3Model)
.on(m3Model.uuid.eq(mapSheetLearnEntity.m3ModelUuid))
.where(mapSheetLearnEntity.uuid.eq(uuid))
.fetchOne();
queryFactory
.select(
Projections.constructor(
InferenceStatusDetailDto.class,
mapSheetLearnEntity.title,
mapSheetLearnEntity.compareYyyy,
mapSheetLearnEntity.targetYyyy,
mapSheetLearnEntity.detectOption,
mapSheetLearnEntity.mapSheetScope,
mapSheetLearnEntity.inferStartDttm,
mapSheetLearnEntity.inferEndDttm,
mapSheetLearnEntity.detectingCnt,
m1Model.modelVer.as("model1Ver"),
m2Model.modelVer.as("model2Ver"),
m3Model.modelVer.as("model3Ver")))
.from(mapSheetLearnEntity)
.leftJoin(m1Model)
.on(m1Model.uuid.eq(mapSheetLearnEntity.m1ModelUuid))
.leftJoin(m2Model)
.on(m2Model.uuid.eq(mapSheetLearnEntity.m2ModelUuid))
.leftJoin(m3Model)
.on(m3Model.uuid.eq(mapSheetLearnEntity.m3ModelUuid))
.where(mapSheetLearnEntity.uuid.eq(uuid))
.fetchOne();
return foundContent;
}
@Override
public Optional<InferenceProgressDto> getInferenceAiResultById(Long id) {
// InferenceProgressDto dto =
// queryFactory
// .select(
// Projections.constructor(
// InferenceProgressDto.class,
// Projections.constructor(
// InferenceProgressDto.pred_requests_areas.class,
// mapSheetLearnEntity.compareYyyy,
// mapSheetLearnEntity.targetYyyy,
// mapSheetLearnEntity.modelComparePath,
// mapSheetLearnEntity.modelTargetPath
// ),
// modelMngEntity.uuid.eq(mapSheetLearnEntity.m1ModelUuid).as("m1ModelUuid"),
// modelMngEntity.uuid.eq(mapSheetLearnEntity.m2ModelUuid).as("m2ModelUuid"),
// mapSheetLearnEntity.cdModelPath,
// mapSheetLearnEntity.cdModelConfig,
// mapSheetLearnEntity.clsModelPath,
// mapSheetLearnEntity.clsModelVersion,
// mapSheetLearnEntity.cdModelType,
// mapSheetLearnEntity.priority
// )
// )
// .from(mapSheetLearnEntity)
// .where(mapSheetLearnEntity.id.eq(id))
// .fetchOne();
return Optional.empty();
public InferenceProgressDto getInferenceAiResultById(Long id, UUID modelUuid) {
QModelMngEntity model = new QModelMngEntity("model");
InferenceProgressDto dto =
queryFactory
.select(
Projections.constructor(
InferenceProgressDto.class,
Projections.constructor(
InferenceProgressDto.pred_requests_areas.class,
mapSheetLearnEntity.compareYyyy,
mapSheetLearnEntity.targetYyyy,
mapSheetLearnEntity.modelComparePath,
mapSheetLearnEntity.modelTargetPath),
model.modelVer.as("modelVer"),
model.cdModelPath.as("cdModelPath"),
model.cdModelFileName.as("cdModelFileName"),
model.cdModelConfigPath.as("cdModelConfigPath"),
model.cdModelConfigFileName.as("cdModelConfigFileName"),
model.clsModelPath,
model.clsModelFileName,
model.clsModelVersion
))
.from(mapSheetLearnEntity)
.join(model)
.on(model.uuid.eq(modelUuid))
.where(mapSheetLearnEntity.id.eq(id))
.fetchOne();
return dto;
}
}

179
src/main/java/com/kamco/cd/kamcoback/scheduler/service/MapSheetInferenceJobService.java
View File

@@ -1,19 +1,30 @@
package com.kamco.cd.kamcoback.scheduler.service;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.kamco.cd.kamcoback.common.exception.CustomApiException;
import com.kamco.cd.kamcoback.config.resttemplate.ExternalHttpClient;
import com.kamco.cd.kamcoback.config.resttemplate.ExternalHttpClient.ExternalCallResult;
import com.kamco.cd.kamcoback.inference.dto.InferenceDetailDto.InferenceBatchSheet;
import com.kamco.cd.kamcoback.inference.dto.InferenceProgressDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceResultDto.SaveInferenceAiDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceResultDto.Status;
import com.kamco.cd.kamcoback.inference.dto.InferenceSendDto;
import com.kamco.cd.kamcoback.inference.dto.InferenceSendDto.pred_requests_areas;
import com.kamco.cd.kamcoback.postgres.core.InferenceResultCoreService;
import com.kamco.cd.kamcoback.scheduler.dto.JobStatusDto;
import jakarta.transaction.Transactional;
import java.time.ZonedDateTime;
import java.util.List;
import java.util.Map;
import java.util.UUID;
import lombok.RequiredArgsConstructor;
import lombok.extern.log4j.Log4j2;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.http.HttpHeaders;
import org.springframework.http.HttpMethod;
import org.springframework.http.HttpStatus;
import org.springframework.http.MediaType;
import org.springframework.scheduling.annotation.Scheduled;
import org.springframework.stereotype.Service;
@@ -31,7 +42,14 @@ public class MapSheetInferenceJobService {
@Value("${inference.batch-url}")
private String batchUrl;
@Value("${spring.profiles.active}")
private String profile;
@Value("${inference.url}")
private String inferenceUrl;
@Scheduled(fixedDelay = 60_000)
@Transactional
public void runBatch() {
log.info("1분 배치 시작");
@@ -39,7 +57,7 @@ public class MapSheetInferenceJobService {
// TODO: 배치 로직 작성
InferenceBatchSheet batchSheet =
inferenceResultCoreService.getInferenceResultByStatus(Status.IN_PROGRESS.getId());
inferenceResultCoreService.getInferenceResultByStatus(Status.IN_PROGRESS.getId());
if (batchSheet == null) {
return;
@@ -66,7 +84,7 @@ public class MapSheetInferenceJobService {
String url = batchUrl + "/" + batchId;
ExternalCallResult<String> result =
externalHttpClient.call(url, HttpMethod.GET, null, headers, String.class);
externalHttpClient.call(url, HttpMethod.GET, null, headers, String.class);
int status = result.statusCode();
if (status < 200 || status >= 300) {
@@ -80,19 +98,34 @@ public class MapSheetInferenceJobService {
String type = batchSheet.getRunningModelType();
if (type.equals("M1")) {
// M1 완료되었으면 M2 실행
this.startInference(batchSheet.getId(), batchSheet.getUuid(), "M2", batchSheet.getM2ModelUuid());
// 종료시간
this.updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M1");
} else if (type.equals("M2")) {
// M1 완료되었으면 M3 실행
this.startInference(batchSheet.getId(), batchSheet.getUuid(), "M3", batchSheet.getM3ModelUuid());
// 종료시간
this.updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M2");
} else if (type.equals("M3")) {
// 완료
SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
saveInferenceAiDto.setUuid(batchSheet.getUuid());
saveInferenceAiDto.setStatus(Status.END.getId());
saveInferenceAiDto.setInferEndDttm(ZonedDateTime.now());
inferenceResultCoreService.update(saveInferenceAiDto);
// 종료시간
this.updateProcessingEndTimeByModel(batchSheet.getUuid(), ZonedDateTime.now(), "M3");
}
} else {
SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
saveInferenceAiDto.setUuid(batchSheet.getUuid());
saveInferenceAiDto.setStatus(Status.IN_PROGRESS.getId());
saveInferenceAiDto.setDetectEndCnt(dto.getCompletedJobs().longValue());
inferenceResultCoreService.update(saveInferenceAiDto);
}
System.out.println(dto);
Thread.sleep(3000); // 예시: 처리 시간 3초
} catch (InterruptedException | JsonProcessingException e) {
} catch (JsonProcessingException e) {
Thread.currentThread().interrupt();
log.error("배치 중 인터럽트 발생", e);
}
@@ -100,44 +133,92 @@ public class MapSheetInferenceJobService {
log.info("1분 배치 종료");
}
private void startInference(Long id, String type) {
// InferenceResultDto.SaveInferenceAiDto req
// inferenceResultCoreService.getInferenceResultByU
//
// List<MapSheetNumDto> mapSheetNum = req.getMapSheetNum();
// List<String> mapSheetNumList = new ArrayList<>();
//
// for (MapSheetNumDto mapSheetDto : mapSheetNum) {
// mapSheetNumList.add(mapSheetDto.getMapSheetNum());
// }
//
// String modelComparePath =
// this.getSceneInference(String.valueOf(req.getCompareYyyy()), mapSheetNumList);
// String modelTargetPath =
// this.getSceneInference(String.valueOf(req.getTargetYyyy()), mapSheetNumList);
//
// pred_requests_areas predRequestsAreas = new pred_requests_areas();
// predRequestsAreas.setInput1_year(req.getCompareYyyy());
// predRequestsAreas.setInput2_year(req.getTargetYyyy());
// predRequestsAreas.setInput1_scene_path(modelComparePath);
// predRequestsAreas.setInput2_scene_path(modelTargetPath);
//
// InferenceSendDto m1 = this.getModelInfo(req.getModel1Uuid());
// InferenceSendDto m2 = this.getModelInfo(req.getModel2Uuid());
// InferenceSendDto m3 = this.getModelInfo(req.getModel3Uuid());
//
// m1.setPred_requests_areas(predRequestsAreas);
// m2.setPred_requests_areas(predRequestsAreas);
// m3.setPred_requests_areas(predRequestsAreas);
//
// Long batchId = this.ensureAccepted(m1);
//
// SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
// saveInferenceAiDto.setUuid(uuid);
// saveInferenceAiDto.setBatchId(batchId);
// saveInferenceAiDto.setStatus(Status.IN_PROGRESS.getId());
// saveInferenceAiDto.setType("M1");
// saveInferenceAiDto.setInferStartDttm(ZonedDateTime.now());
// inferenceResultCoreService.update(saveInferenceAiDto);
private void startInference(Long id, UUID uuid, String type, UUID modelUuid) {
InferenceProgressDto progressDto = inferenceResultCoreService.getInferenceAiResultById(id, type, modelUuid);
pred_requests_areas predRequestsAreas = new 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());
predRequestsAreas.setInput2_scene_path(progressDto.getPred_requests_areas().getInput2_scene_path());
InferenceSendDto m = new InferenceSendDto();
m.setModel_version(progressDto.getModelVersion());
m.setCd_model_path(progressDto.getCdModelPath() + "/" + progressDto.getCdModelFileName());
m.setCd_model_config(progressDto.getCdModelConfigPath() + "/" + progressDto.getCdModelConfigFileName());
m.setCls_model_path(progressDto.getCdModelClsPath() + "/" + progressDto.getCdModelClsFileName());
m.setCls_model_version(progressDto.getClsModelVersion());
m.setCd_model_type(type);
m.setPriority(progressDto.getPriority());
// 추론 다음모델 실행
Long batchId = this.ensureAccepted(m);
SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
saveInferenceAiDto.setUuid(uuid);
saveInferenceAiDto.setBatchId(batchId);
saveInferenceAiDto.setStatus(Status.IN_PROGRESS.getId());
saveInferenceAiDto.setType(type);
saveInferenceAiDto.setModelStartDttm(ZonedDateTime.now());
inferenceResultCoreService.update(saveInferenceAiDto);
}
private Long ensureAccepted(InferenceSendDto dto) {
log.info("dto null? {}", dto == null);
ObjectMapper om = new ObjectMapper();
try {
log.info("dto json={}", om.writeValueAsString(dto));
} catch (Exception e) {
log.error(e.getMessage());
}
HttpHeaders headers = new HttpHeaders();
headers.setContentType(MediaType.APPLICATION_JSON);
headers.setAccept(List.of(MediaType.APPLICATION_JSON));
// TODO 추후 삭제
if ("local".equals(profile)) {
dto.getPred_requests_areas().setInput1_scene_path("/kamco-nfs/requests/2023_local.geojson");
dto.getPred_requests_areas().setInput2_scene_path("/kamco-nfs/requests/2024_local.geojson");
}
ExternalCallResult<String> result =
externalHttpClient.call(inferenceUrl, HttpMethod.POST, dto, headers, String.class);
int status = result.statusCode();
String body = result.body();
if (status < 200 || status >= 300) {
throw new CustomApiException("BAD_GATEWAY", HttpStatus.BAD_GATEWAY);
}
Long batchId = 0L;
try {
List<Map<String, Object>> list =
om.readValue(body, new TypeReference<List<Map<String, Object>>>() {
});
Integer batchIdInt = (Integer) list.get(0).get("batch_id");
batchId = batchIdInt.longValue();
if (list.isEmpty()) {
throw new IllegalStateException("Inference response is empty");
}
} catch (Exception e) {
log.error(e.getMessage());
}
return batchId;
}
private void updateProcessingEndTimeByModel(UUID uuid, ZonedDateTime dateTime, String type) {
SaveInferenceAiDto saveInferenceAiDto = new SaveInferenceAiDto();
saveInferenceAiDto.setUuid(uuid);
saveInferenceAiDto.setUpdateUid(0L);
saveInferenceAiDto.setModelEndDttm(dateTime);
saveInferenceAiDto.setType(type);
inferenceResultCoreService.update(saveInferenceAiDto);
}
}