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自动机器学习开发

dev-automl
chenzhihang 1 year ago
parent
fe9e9ed2ca
commit
ce32d520e7
9 changed files with 234 additions and 391 deletions
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  1. +2
    -30
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/controller/autoML/AutoMLController.java
  2. +57
    -0
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/domain/AutoMl.java
  3. +0
    -77
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/domain/AutoMlIns.java
  4. +2
    -0
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/mapper/AutoMLDao.java
  5. +0
    -21
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/mapper/AutoMLInsDao.java
  6. +3
    -13
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/service/AutoMLService.java
  7. +73
    -111
      ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/service/impl/AutoMLServiceImpl.java
  8. +97
    -7
      ruoyi-modules/management-platform/src/main/resources/mapper/managementPlatform/AutoMLDaoMapper.xml
  9. +0
    -132
      ruoyi-modules/management-platform/src/main/resources/mapper/managementPlatform/AutoMLInsDaoMapper.xml

+ 2
- 30
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/controller/autoML/AutoMLController.java View File

@@ -4,7 +4,6 @@ import com.ruoyi.common.core.web.controller.BaseController;
import com.ruoyi.common.core.web.domain.AjaxResult;
import com.ruoyi.common.core.web.domain.GenericsAjaxResult;
import com.ruoyi.platform.domain.AutoMl;
import com.ruoyi.platform.domain.AutoMlIns;
import com.ruoyi.platform.service.AutoMLService;
import io.swagger.annotations.Api;
import io.swagger.annotations.ApiOperation;
@@ -34,13 +33,13 @@ public class AutoMLController extends BaseController {

@PostMapping
@ApiOperation("新增自动机器学习")
public GenericsAjaxResult<AutoMl> addAutoMl(@RequestBody AutoMl autoMl) {
public GenericsAjaxResult<AutoMl> addAutoMl(@RequestBody AutoMl autoMl) throws Exception {
return genericsSuccess(this.autoMLService.save(autoMl));
}

@PutMapping
@ApiOperation("编辑自动机器学习")
public GenericsAjaxResult<String> editAutoMl(@RequestBody AutoMl autoMl) {
public GenericsAjaxResult<String> editAutoMl(@RequestBody AutoMl autoMl) throws Exception {
return genericsSuccess(this.autoMLService.edit(autoMl));
}

@@ -50,33 +49,6 @@ public class AutoMLController extends BaseController {
return genericsSuccess(this.autoMLService.delete(id));
}

@GetMapping("/autoMlIns")
@ApiOperation("分页查询自动机器学习实例")
public GenericsAjaxResult<Page<AutoMlIns>> queryByPage(@RequestParam("page") int page,
@RequestParam("size") int size,
@RequestParam("auto_ml_id") Long autoMlId) {
PageRequest pageRequest = PageRequest.of(page, size);
return genericsSuccess(this.autoMLService.queryAutoMlInsByPage(autoMlId, pageRequest));
}

@PostMapping("/autoMlIns")
@ApiOperation("新增自动机器学习实例")
public GenericsAjaxResult<AutoMlIns> addAutoMlIns(@RequestBody AutoMlIns autoMlIns) throws Exception {
return genericsSuccess(this.autoMLService.saveAutoMlIns(autoMlIns));
}

@PutMapping("/autoMlIns")
@ApiOperation("编辑自动机器学习实例")
public GenericsAjaxResult<String> editAutoMlIns(@RequestBody AutoMlIns autoMlIns) throws Exception {
return genericsSuccess(this.autoMLService.editAutoMlIns(autoMlIns));
}

@DeleteMapping("/autoMlIns/{id}")
@ApiOperation("删除自动机器学习实例")
public GenericsAjaxResult<String> deleteAutoMlIns(@PathVariable("id") Long id) {
return genericsSuccess(this.autoMLService.deleteAutoMlIns(id));
}

@CrossOrigin(origins = "*", allowedHeaders = "*")
@PostMapping("/upload")
@ApiOperation(value = "上传数据文件csv", notes = "上传数据文件csv，并将信息存入数据库。")


+ 57
- 0
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/domain/AutoMl.java View File

@@ -1,20 +1,74 @@
package com.ruoyi.platform.domain;

import com.baomidou.mybatisplus.annotation.TableField;
import com.fasterxml.jackson.databind.PropertyNamingStrategy;
import com.fasterxml.jackson.databind.annotation.JsonNaming;
import com.ruoyi.platform.vo.VersionVo;
import io.swagger.annotations.ApiModel;
import io.swagger.annotations.ApiModelProperty;
import lombok.Data;

import java.util.Date;

@Data
@JsonNaming(PropertyNamingStrategy.SnakeCaseStrategy.class)
@ApiModel(description = "自动机器学习")
public class AutoMl {
private Long id;

@ApiModelProperty(value = "实验名称")
private String mlName;

@ApiModelProperty(value = "实验描述")
private String mlDescription;

@ApiModelProperty(value = "任务类型")
private String taskType;

private String datasetName;

private Integer timeLeftForThisTask;

private Integer perRunTimeLimit;

private Integer ensembleSize;

private String ensembleClass;

private Integer ensembleNbest;

private Integer maxModelsOnDisc;

private Integer seed;

private Integer memoryLimit;

private String includeClassifier;

private String includeFeaturePreprocessor;

private String includeRegressor;

private String excludeClassifier;

private String excludeRegressor;

private String excludeFeaturePreprocessor;

private String resamplingStrategy;

private Float trainSize;

private Boolean shuffle;

private Integer folds;

private Boolean deleteTmpFolderAfterTerminate;

private String dataCsv;

private String targetColumns;

private Integer state;

private String runState;
@@ -28,4 +82,7 @@ public class AutoMl {
private String updateBy;

private Date updateTime;

@TableField(exist = false)
private VersionVo versionVo;
}

+ 0
- 77
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/domain/AutoMlIns.java View File

@@ -1,77 +0,0 @@
package com.ruoyi.platform.domain;

import com.baomidou.mybatisplus.annotation.TableField;
import com.fasterxml.jackson.databind.PropertyNamingStrategy;
import com.fasterxml.jackson.databind.annotation.JsonNaming;
import com.ruoyi.platform.vo.VersionVo;
import lombok.Data;

import java.util.Date;

@Data
@JsonNaming(PropertyNamingStrategy.SnakeCaseStrategy.class)
public class AutoMlIns {
private Long id;

private Long autoMlId;

private String taskType;

private String datasetName;

private Integer timeLeftForThisTask;

private Integer perRunTimeLimit;

private Integer ensembleSize;

private String ensembleClass;

private Integer ensembleNbest;

private Integer maxModelsOnDisc;

private Integer seed;

private Integer memoryLimit;

private String includeClassifier;

private String includeFeaturePreprocessor;

private String includeRegressor;

private String excludeClassifier;

private String excludeRegressor;

private String excludeFeaturePreprocessor;

private String resamplingStrategy;

private Float trainSize;

private Boolean shuffle;

private Integer folds;

private Boolean deleteTmpFolderAfterTerminate;

private String dataCsv;

private String targetColumns;

private Integer state;

private String createBy;

private String updateBy;

private Date createTime;

private Date updateTime;

@TableField(exist = false)
private VersionVo versionVo;

}

+ 2
- 0
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/mapper/AutoMLDao.java View File

@@ -13,6 +13,8 @@ public interface AutoMLDao {

AutoMl getAutoMlById(@Param("id") Long id);

AutoMl getAutoMlByName(@Param("mlName") String mlName);

int save(@Param("autoMl") AutoMl autoMl);

int edit(@Param("autoMl") AutoMl autoMl);


+ 0
- 21
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/mapper/AutoMLInsDao.java View File

@@ -1,21 +0,0 @@
package com.ruoyi.platform.mapper;

import com.ruoyi.platform.domain.AutoMlIns;
import org.apache.ibatis.annotations.Param;
import org.springframework.data.domain.Pageable;

import java.util.List;

public interface AutoMLInsDao {
long count(@Param("autoMlId") Long autoMlId);

List<AutoMlIns> queryByPage(@Param("autoMlId") Long autoMlId, @Param("pageable") Pageable pageable);

int save(@Param("autoMlIns") AutoMlIns autoMlIns);

int edit(@Param("autoMlIns") AutoMlIns autoMlIns);

AutoMlIns getById(@Param("id") Long id);

AutoMlIns findByDatasetName(@Param("datasetName") String datasetName, @Param("autoMlId") Long autoMlId);
}

+ 3
- 13
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/service/AutoMLService.java View File

@@ -1,32 +1,22 @@
package com.ruoyi.platform.service;

import com.ruoyi.platform.domain.AutoMl;
import com.ruoyi.platform.domain.AutoMlIns;
import org.springframework.data.domain.Page;
import org.springframework.data.domain.PageRequest;
import org.springframework.web.multipart.MultipartFile;

import java.util.List;
import java.util.Map;

public interface AutoMLService {
Page<AutoMl> queryByPage(String mlName, PageRequest pageRequest);

AutoMl save(AutoMl autoMl);
AutoMl save(AutoMl autoMl) throws Exception;

String edit(AutoMl autoMl);
String edit(AutoMl autoMl) throws Exception;

String delete(Long id);

Page<AutoMlIns> queryAutoMlInsByPage(Long autoMlId, PageRequest pageRequest);

AutoMlIns saveAutoMlIns(AutoMlIns autoMlIns) throws Exception;

String editAutoMlIns(AutoMlIns autoMlIns) throws Exception;

String deleteAutoMlIns(Long id);

Map<String, String> upload(MultipartFile file, String uuid) throws Exception;
Map<String, String> upload(MultipartFile file, String uuid) throws Exception;

String runAutoMlIns(Long id) throws Exception;
}

+ 73
- 111
ruoyi-modules/management-platform/src/main/java/com/ruoyi/platform/service/impl/AutoMLServiceImpl.java View File

@@ -3,9 +3,7 @@ package com.ruoyi.platform.service.impl;
import com.ruoyi.common.security.utils.SecurityUtils;
import com.ruoyi.platform.constant.Constant;
import com.ruoyi.platform.domain.AutoMl;
import com.ruoyi.platform.domain.AutoMlIns;
import com.ruoyi.platform.mapper.AutoMLDao;
import com.ruoyi.platform.mapper.AutoMLInsDao;
import com.ruoyi.platform.service.AutoMLService;
import com.ruoyi.platform.utils.DVCUtils;
import com.ruoyi.platform.utils.FileUtil;
@@ -49,8 +47,6 @@ public class AutoMLServiceImpl implements AutoMLService {
@Resource
private AutoMLDao autoMLDao;
@Resource
private AutoMLInsDao autoMLInsDao;
@Resource
private K8sClientUtil k8sClientUtil;
@Resource
private DVCUtils dvcUtils;
@@ -63,18 +59,40 @@ public class AutoMLServiceImpl implements AutoMLService {
}

@Override
public AutoMl save(AutoMl autoMl) {
public AutoMl save(AutoMl autoMl) throws Exception {
AutoMl autoMlByName = autoMLDao.getAutoMlByName(autoMl.getMlName());
if (autoMlByName != null) {
throw new RuntimeException("实验名称已存在");
}

String username = SecurityUtils.getLoginUser().getUsername();
autoMl.setCreateBy(username);
autoMl.setUpdateBy(username);

String sourcePath = autoMl.getVersionVo().getUrl();
String rootPath = localPath + username + "/automl/" + autoMl.getMlName() + "/" + autoMl.getDatasetName();
dvcUtils.moveFiles(sourcePath, rootPath);
autoMl.setDataCsv(rootPath + "/" + autoMl.getVersionVo().getFileName());
autoMLDao.save(autoMl);
return autoMl;
}

@Override
public String edit(AutoMl autoMl) {
public String edit(AutoMl autoMl) throws Exception {
AutoMl oldAutoMl = autoMLDao.getAutoMlByName(autoMl.getMlName());
if (oldAutoMl != null && !oldAutoMl.getId().equals(autoMl.getId())) {
throw new RuntimeException("实验名称已存在");
}

String username = SecurityUtils.getLoginUser().getUsername();
autoMl.setUpdateBy(username);
if (autoMl.getVersionVo() != null && StringUtils.isNotEmpty(autoMl.getVersionVo().getUrl())) {
String sourcePath = autoMl.getVersionVo().getUrl();
String rootPath = localPath + username + "/automl/" + autoMl.getMlName() + "/" + autoMl.getDatasetName();
dvcUtils.moveFiles(sourcePath, rootPath);
autoMl.setDataCsv(rootPath + "/" + autoMl.getVersionVo().getFileName());
}

autoMLDao.edit(autoMl);
return "修改成功";
}
@@ -86,7 +104,8 @@ public class AutoMLServiceImpl implements AutoMLService {
throw new RuntimeException("服务不存在");
}

String username = SecurityUtils.getLoginUser().getUsername();
// String username = SecurityUtils.getLoginUser().getUsername();
String username = "admin";
String createBy = autoMl.getCreateBy();
if (!(StringUtils.equals(username, "admin") || StringUtils.equals(username, createBy))) {
throw new RuntimeException("无权限删除该服务");
@@ -96,69 +115,12 @@ public class AutoMLServiceImpl implements AutoMLService {
return autoMLDao.edit(autoMl) > 0 ? "删除成功" : "删除失败";
}

@Override
public Page<AutoMlIns> queryAutoMlInsByPage(Long autoMlId, PageRequest pageRequest) {
long total = autoMLInsDao.count(autoMlId);
List<AutoMlIns> autoMlIns = autoMLInsDao.queryByPage(autoMlId, pageRequest);
return new PageImpl<>(autoMlIns, pageRequest, total);
}

@Override
public AutoMlIns saveAutoMlIns(AutoMlIns autoMlIns) throws Exception {
String ci4sUsername = SecurityUtils.getLoginUser().getUsername();
AutoMlIns oldAutoMlIns = autoMLInsDao.findByDatasetName(autoMlIns.getDatasetName(), autoMlIns.getAutoMlId());
if (oldAutoMlIns != null) {
throw new RuntimeException("数据集名称已存在");
}

String sourcePath = autoMlIns.getVersionVo().getUrl();
String rootPath = localPath + ci4sUsername + "/automl/" + autoMlIns.getAutoMlId() + "/" + autoMlIns.getDatasetName();
dvcUtils.moveFiles(sourcePath, rootPath);
autoMlIns.setDataCsv(rootPath + "/" + autoMlIns.getVersionVo().getFileName());
autoMlIns.setCreateBy(ci4sUsername);
autoMlIns.setUpdateBy(ci4sUsername);
autoMLInsDao.save(autoMlIns);
return autoMlIns;
}

@Override
public String editAutoMlIns(AutoMlIns autoMlIns) throws Exception {
AutoMlIns oldAutoMlIns = autoMLInsDao.findByDatasetName(autoMlIns.getDatasetName(), autoMlIns.getAutoMlId());
if (oldAutoMlIns != null && !oldAutoMlIns.getId().equals(autoMlIns.getId())) {
throw new RuntimeException("数据集名称已存在");
}
String ci4sUsername = SecurityUtils.getLoginUser().getUsername();
autoMlIns.setUpdateBy(ci4sUsername);
if (autoMlIns.getVersionVo() != null && StringUtils.isNotEmpty(autoMlIns.getVersionVo().getUrl())) {
String sourcePath = autoMlIns.getVersionVo().getUrl();
String rootPath = localPath + ci4sUsername + "/automl/" + autoMlIns.getAutoMlId() + "/" + autoMlIns.getDatasetName();
dvcUtils.moveFiles(sourcePath, rootPath);
autoMlIns.setDataCsv(rootPath + "/" + autoMlIns.getVersionVo().getFileName());
}
autoMLInsDao.edit(autoMlIns);
return "修改成功";
}

@Override
public String deleteAutoMlIns(Long id) {
AutoMlIns autoMlIns = autoMLInsDao.getById(id);
if (autoMlIns == null) {
throw new RuntimeException("实例不存在");
}
String username = SecurityUtils.getLoginUser().getUsername();
String createBy = autoMlIns.getCreateBy();
if (!(StringUtils.equals(username, "admin") || StringUtils.equals(username, createBy))) {
throw new RuntimeException("无权限删除该实例");
}
autoMlIns.setState(Constant.State_invalid);
return autoMLInsDao.edit(autoMlIns) > 0 ? "删除成功" : "删除失败";
}

@Override
public Map<String, String> upload(MultipartFile file, String uuid) throws Exception {
Map<String, String> result = new HashMap<>();

String username = SecurityUtils.getLoginUser().getUsername();
// String username = SecurityUtils.getLoginUser().getUsername();
String username = "admin";
String fileName = file.getOriginalFilename();
String path = localPath + "temp/" + username + "/automl_data/" + uuid;
long sizeInBytes = file.getSize();
@@ -177,25 +139,25 @@ public class AutoMLServiceImpl implements AutoMLService {

@Override
public String runAutoMlIns(Long id) throws Exception {
AutoMlIns autoMlIns = autoMLInsDao.getById(id);
if (autoMlIns == null) {
AutoMl autoMl = autoMLDao.getAutoMlById(id);
if (autoMl == null) {
throw new Exception("开发环境配置不存在");
}

StringBuffer command = new StringBuffer();
command.append("nohup python /opt/automl.py --task_type " + autoMlIns.getTaskType());
if (StringUtils.isNotEmpty(autoMlIns.getDataCsv())) {
command.append(" --data_csv " + autoMlIns.getDataCsv());
command.append("nohup python /opt/automl.py --task_type " + autoMl.getTaskType());
if (StringUtils.isNotEmpty(autoMl.getDataCsv())) {
command.append(" --data_csv " + autoMl.getDataCsv());
} else {
throw new Exception("训练数据为空");
}
if (StringUtils.isNotEmpty(autoMlIns.getTargetColumns())) {
command.append(" --target_columns " + autoMlIns.getTargetColumns());
if (StringUtils.isNotEmpty(autoMl.getTargetColumns())) {
command.append(" --target_columns " + autoMl.getTargetColumns());
} else {
throw new Exception("目标列为空");
}
if (StringUtils.isNotEmpty(autoMlIns.getDatasetName())) {
command.append(" --dataset_name " + autoMlIns.getDatasetName());
if (StringUtils.isNotEmpty(autoMl.getDatasetName())) {
command.append(" --dataset_name " + autoMl.getDatasetName());
} else {
throw new Exception("数据集名称为空");
}
@@ -206,59 +168,59 @@ public class AutoMLServiceImpl implements AutoMLService {
String podName = username + "-autoMlIns-pod-" + id;
V1Pod pod = k8sClientUtil.createPodWithEnv(podName, serviceNS, proxyUrl, mountPath, pvcName, image);

if (autoMlIns.getTimeLeftForThisTask() != null) {
command.append(" --time_left_for_this_task " + autoMlIns.getTimeLeftForThisTask());
if (autoMl.getTimeLeftForThisTask() != null) {
command.append(" --time_left_for_this_task " + autoMl.getTimeLeftForThisTask());
}
if (autoMlIns.getPerRunTimeLimit() != null) {
command.append(" --per_run_time_limit " + autoMlIns.getPerRunTimeLimit());
if (autoMl.getPerRunTimeLimit() != null) {
command.append(" --per_run_time_limit " + autoMl.getPerRunTimeLimit());
}
if (autoMlIns.getEnsembleSize() != null) {
command.append(" --ensemble_size " + autoMlIns.getEnsembleSize());
if (autoMl.getEnsembleSize() != null) {
command.append(" --ensemble_size " + autoMl.getEnsembleSize());
}
if (StringUtils.isNotEmpty(autoMlIns.getEnsembleClass())) {
command.append(" --ensemble_class " + autoMlIns.getEnsembleClass());
if (StringUtils.isNotEmpty(autoMl.getEnsembleClass())) {
command.append(" --ensemble_class " + autoMl.getEnsembleClass());
}
if (autoMlIns.getEnsembleNbest() != null) {
command.append(" --ensemble_nbest " + autoMlIns.getEnsembleNbest());
if (autoMl.getEnsembleNbest() != null) {
command.append(" --ensemble_nbest " + autoMl.getEnsembleNbest());
}
if (autoMlIns.getMaxModelsOnDisc() != null) {
command.append(" --max_models_on_disc " + autoMlIns.getMaxModelsOnDisc());
if (autoMl.getMaxModelsOnDisc() != null) {
command.append(" --max_models_on_disc " + autoMl.getMaxModelsOnDisc());
}
if (autoMlIns.getSeed() != null) {
command.append(" --seed " + autoMlIns.getSeed());
if (autoMl.getSeed() != null) {
command.append(" --seed " + autoMl.getSeed());
}
if (autoMlIns.getMemoryLimit() != null) {
command.append(" --memory_limit " + autoMlIns.getMemoryLimit());
if (autoMl.getMemoryLimit() != null) {
command.append(" --memory_limit " + autoMl.getMemoryLimit());
}
if (StringUtils.isNotEmpty(autoMlIns.getIncludeClassifier())) {
command.append(" --include_classifier " + autoMlIns.getIncludeClassifier());
if (StringUtils.isNotEmpty(autoMl.getIncludeClassifier())) {
command.append(" --include_classifier " + autoMl.getIncludeClassifier());
}
if (StringUtils.isNotEmpty(autoMlIns.getIncludeRegressor())) {
command.append(" --include_regressor " + autoMlIns.getIncludeRegressor());
if (StringUtils.isNotEmpty(autoMl.getIncludeRegressor())) {
command.append(" --include_regressor " + autoMl.getIncludeRegressor());
}
if (StringUtils.isNotEmpty(autoMlIns.getIncludeFeaturePreprocessor())) {
command.append(" --include_feature_preprocessor " + autoMlIns.getIncludeFeaturePreprocessor());
if (StringUtils.isNotEmpty(autoMl.getIncludeFeaturePreprocessor())) {
command.append(" --include_feature_preprocessor " + autoMl.getIncludeFeaturePreprocessor());
}
if (StringUtils.isNotEmpty(autoMlIns.getExcludeClassifier())) {
command.append(" --exclude_classifier " + autoMlIns.getExcludeClassifier());
if (StringUtils.isNotEmpty(autoMl.getExcludeClassifier())) {
command.append(" --exclude_classifier " + autoMl.getExcludeClassifier());
}
if (StringUtils.isNotEmpty(autoMlIns.getExcludeRegressor())) {
command.append(" --exclude_regressor " + autoMlIns.getExcludeRegressor());
if (StringUtils.isNotEmpty(autoMl.getExcludeRegressor())) {
command.append(" --exclude_regressor " + autoMl.getExcludeRegressor());
}
if (StringUtils.isNotEmpty(autoMlIns.getExcludeFeaturePreprocessor())) {
command.append(" --exclude_feature_preprocessor " + autoMlIns.getExcludeFeaturePreprocessor());
if (StringUtils.isNotEmpty(autoMl.getExcludeFeaturePreprocessor())) {
command.append(" --exclude_feature_preprocessor " + autoMl.getExcludeFeaturePreprocessor());
}
if (StringUtils.isNotEmpty(autoMlIns.getResamplingStrategy())) {
command.append(" --resampling_strategy " + autoMlIns.getResamplingStrategy());
if (StringUtils.isNotEmpty(autoMl.getResamplingStrategy())) {
command.append(" --resampling_strategy " + autoMl.getResamplingStrategy());
}
if (autoMlIns.getTrainSize() != null) {
command.append(" --train_size " + autoMlIns.getTrainSize());
if (autoMl.getTrainSize() != null) {
command.append(" --train_size " + autoMl.getTrainSize());
}
if (autoMlIns.getShuffle() != null) {
command.append(" --shuffle " + autoMlIns.getShuffle());
if (autoMl.getShuffle() != null) {
command.append(" --shuffle " + autoMl.getShuffle());
}
if (autoMlIns.getFolds() != null) {
command.append(" --folds " + autoMlIns.getFolds());
if (autoMl.getFolds() != null) {
command.append(" --folds " + autoMl.getFolds());
}
command.append(" &");
CompletableFuture.supplyAsync(() -> {


+ 97
- 7
ruoyi-modules/management-platform/src/main/resources/mapper/managementPlatform/AutoMLDaoMapper.xml View File

@@ -2,8 +2,23 @@
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.ruoyi.platform.mapper.AutoMLDao">
<insert id="save">
insert into auto_ml(ml_name, ml_description)
values (#{autoMl.mlName}, #{autoMl.mlDescription})
insert into auto_ml(ml_name, ml_description, task_type, dataset_name, time_left_for_this_task,
per_run_time_limit, ensemble_size, ensemble_class, ensemble_nbest, max_models_on_disc, seed,
memory_limit,
include_classifier, include_feature_preprocessor, include_regressor, exclude_classifier,
exclude_regressor, exclude_feature_preprocessor, resampling_strategy, train_size,
shuffle, folds, data_csv, target_columns, create_by,
update_by)
values (#{autoMl.mlName}, #{autoMl.mlDescription}, #{autoMl.taskType}, #{autoMl.datasetName},
#{autoMl.timeLeftForThisTask}, #{autoMl.perRunTimeLimit},
#{autoMl.ensembleSize}, #{autoMl.ensembleClass}, #{autoMl.ensembleNbest},
#{autoMl.maxModelsOnDisc}, #{autoMl.seed},
#{autoMl.memoryLimit}, #{autoMl.includeClassifier}, #{autoMl.includeFeaturePreprocessor},
#{autoMl.includeRegressor}, #{autoMl.excludeClassifier},
#{autoMl.excludeRegressor}, #{autoMl.excludeFeaturePreprocessor}, #{autoMl.resamplingStrategy},
#{autoMl.trainSize}, #{autoMl.shuffle},
#{autoMl.folds}, #{autoMl.dataCsv},
#{autoMl.targetColumns}, #{autoMl.createBy}, #{autoMl.updateBy})
</insert>

<update id="edit">
@@ -15,11 +30,77 @@
<if test="autoMl.mlDescription != null and autoMl.mlDescription !=''">
ml_description = #{autoMl.mlDescription},
</if>
<if test="autoMl.runState != null and autoMl.runState !=''">
run_state = #{autoMl.runState},
<!-- <if test="autoMl.runState != null and autoMl.runState !=''">-->
<!-- run_state = #{autoMl.runState},-->
<!-- </if>-->
<!-- <if test="autoMl.progress != null">-->
<!-- progress = #{autoMl.progress},-->
<!-- </if>-->
<if test="autoMl.taskType != null and autoMl.taskType !=''">
task_type = #{autoMl.taskType},
</if>
<if test="autoMl.progress != null">
progress = #{autoMl.progress},
<if test="autoMl.datasetName != null and autoMl.datasetName !=''">
dataset_name = #{autoMl.datasetName},
</if>
<if test="autoMl.timeLeftForThisTask != null">
time_left_for_this_task = #{autoMl.timeLeftForThisTask},
</if>
<if test="autoMl.perRunTimeLimit != null">
per_run_time_limit = #{autoMl.perRunTimeLimit},
</if>
<if test="autoMl.ensembleSize != null">
ensemble_size = #{autoMl.ensembleSize},
</if>
<if test="autoMl.ensembleClass != null and autoMl.ensembleClass !=''">
ensemble_class = #{autoMl.ensembleClass},
</if>
<if test="autoMl.ensembleNbest != null">
ensemble_nbest = #{autoMl.ensembleNbest},
</if>
<if test="autoMl.maxModelsOnDisc != null">
max_models_on_disc = #{autoMl.maxModelsOnDisc},
</if>
<if test="autoMl.seed != null">
seed = #{autoMl.seed},
</if>
<if test="autoMl.memoryLimit != null">
memory_limit = #{autoMl.memoryLimit},
</if>
<if test="autoMl.includeClassifier != null and autoMl.includeClassifier !=''">
include_classifier = #{autoMl.includeClassifier},
</if>
<if test="autoMl.includeFeaturePreprocessor != null and autoMl.includeFeaturePreprocessor !=''">
include_feature_preprocessor = #{autoMl.includeFeaturePreprocessor},
</if>
<if test="autoMl.includeRegressor != null and autoMl.includeRegressor !=''">
include_regressor = #{autoMl.includeRegressor},
</if>
<if test="autoMl.excludeClassifier != null and autoMl.excludeClassifier !=''">
exclude_classifier = #{autoMl.excludeClassifier},
</if>
<if test="autoMl.excludeRegressor != null and autoMl.excludeRegressor !=''">
exclude_regressor = #{autoMl.excludeRegressor},
</if>
<if test="autoMl.excludeFeaturePreprocessor != null and autoMl.excludeFeaturePreprocessor !=''">
exclude_feature_preprocessor = #{autoMl.excludeFeaturePreprocessor},
</if>
<if test="autoMl.resamplingStrategy != null and autoMl.resamplingStrategy !=''">
resampling_strategy = #{autoMl.resamplingStrategy},
</if>
<if test="autoMl.trainSize != null and autoMl.trainSize !=''">
train_size = #{autoMl.trainSize},
</if>
<if test="autoMl.shuffle != null">
shuffle = #{autoMl.shuffle},
</if>
<if test="autoMl.folds != null">
folds = #{autoMl.folds},
</if>
<if test="autoMl.dataCsv != null and autoMl.dataCsv !=''">
data_csv = #{autoMl.dataCsv},
</if>
<if test="autoMl.targetColumns != null and autoMl.targetColumns !=''">
target_columns = #{autoMl.targetColumns},
</if>
<if test="autoMl.state != null">
state = #{autoMl.state},
@@ -39,7 +120,16 @@
</select>

<select id="getAutoMlById" resultType="com.ruoyi.platform.domain.AutoMl">
select * from auto_ml where id = #{id}
select *
from auto_ml
where id = #{id}
</select>

<select id="getAutoMlByName" resultType="com.ruoyi.platform.domain.AutoMl">
select *
from auto_ml
where ml_name = #{mlName}
and state = 1
</select>

<sql id="common_condition">


+ 0
- 132
ruoyi-modules/management-platform/src/main/resources/mapper/managementPlatform/AutoMLInsDaoMapper.xml View File

@@ -1,132 +0,0 @@
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mapper PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN" "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.ruoyi.platform.mapper.AutoMLInsDao">
<insert id="save">
insert into auto_ml_ins(auto_ml_id, task_type, dataset_name, time_left_for_this_task, per_run_time_limit,
ensemble_size, ensemble_class, ensemble_nbest, max_models_on_disc, seed, memory_limit,
include_classifier, include_feature_preprocessor, include_regressor, exclude_classifier,
exclude_regressor, exclude_feature_preprocessor, resampling_strategy, train_size,
shuffle, folds, delete_tmp_folder_after_terminate, data_csv, target_columns, create_by,
update_by)
values (#{autoMlIns.autoMlId}, #{autoMlIns.taskType}, #{autoMlIns.datasetName},
#{autoMlIns.timeLeftForThisTask}, #{autoMlIns.perRunTimeLimit},
#{autoMlIns.ensembleSize}, #{autoMlIns.ensembleClass}, #{autoMlIns.ensembleNbest},
#{autoMlIns.maxModelsOnDisc}, #{autoMlIns.seed},
#{autoMlIns.memoryLimit}, #{autoMlIns.includeClassifier}, #{autoMlIns.includeFeaturePreprocessor},
#{autoMlIns.includeRegressor}, #{autoMlIns.excludeClassifier},
#{autoMlIns.excludeRegressor}, #{autoMlIns.excludeFeaturePreprocessor}, #{autoMlIns.resamplingStrategy},
#{autoMlIns.trainSize}, #{autoMlIns.shuffle},
#{autoMlIns.folds}, #{autoMlIns.deleteTmpFolderAfterTerminate}, #{autoMlIns.dataCsv},
#{autoMlIns.targetColumns}, #{autoMlIns.createBy}, #{autoMlIns.updateBy})
</insert>

<update id="edit">
update auto_ml_ins
<set>
<if test="autoMlIns.taskType != null and autoMlIns.taskType !=''">
task_type = #{autoMlIns.taskType},
</if>
<if test="autoMlIns.datasetName != null and autoMlIns.datasetName !=''">
dataset_name = #{autoMlIns.datasetName},
</if>
<if test="autoMlIns.timeLeftForThisTask != null">
time_left_for_this_task = #{autoMlIns.timeLeftForThisTask},
</if>
<if test="autoMlIns.perRunTimeLimit != null">
per_run_time_limit = #{autoMlIns.perRunTimeLimit},
</if>
<if test="autoMlIns.ensembleSize != null">
ensemble_size = #{autoMlIns.ensembleSize},
</if>
<if test="autoMlIns.ensembleClass != null and autoMlIns.ensembleClass !=''">
ensemble_class = #{autoMlIns.ensembleClass},
</if>
<if test="autoMlIns.ensembleNbest != null">
ensemble_nbest = #{autoMlIns.ensembleNbest},
</if>
<if test="autoMlIns.maxModelsOnDisc != null">
max_models_on_disc = #{autoMlIns.maxModelsOnDisc},
</if>
<if test="autoMlIns.seed != null">
seed = #{autoMlIns.seed},
</if>
<if test="autoMlIns.memoryLimit != null">
memory_limit = #{autoMlIns.memoryLimit},
</if>
<if test="autoMlIns.includeClassifier != null and autoMlIns.includeClassifier !=''">
include_classifier = #{autoMlIns.includeClassifier},
</if>
<if test="autoMlIns.includeFeaturePreprocessor != null and autoMlIns.includeFeaturePreprocessor !=''">
include_feature_preprocessor = #{autoMlIns.includeFeaturePreprocessor},
</if>
<if test="autoMlIns.includeRegressor != null and autoMlIns.includeRegressor !=''">
include_regressor = #{autoMlIns.includeRegressor},
</if>
<if test="autoMlIns.excludeClassifier != null and autoMlIns.excludeClassifier !=''">
exclude_classifier = #{autoMlIns.excludeClassifier},
</if>
<if test="autoMlIns.excludeRegressor != null and autoMlIns.excludeRegressor !=''">
exclude_regressor = #{autoMlIns.excludeRegressor},
</if>
<if test="autoMlIns.excludeFeaturePreprocessor != null and autoMlIns.excludeFeaturePreprocessor !=''">
exclude_feature_preprocessor = #{autoMlIns.excludeFeaturePreprocessor},
</if>
<if test="autoMlIns.resamplingStrategy != null and autoMlIns.resamplingStrategy !=''">
resampling_strategy = #{autoMlIns.resamplingStrategy},
</if>
<if test="autoMlIns.trainSize != null and autoMlIns.trainSize !=''">
train_size = #{autoMlIns.trainSize},
</if>
<if test="autoMlIns.shuffle != null">
shuffle = #{autoMlIns.shuffle},
</if>
<if test="autoMlIns.folds != null">
folds = #{autoMlIns.folds},
</if>
<if test="autoMlIns.deleteTmpFolderAfterTerminate != null">
delete_tmp_folder_after_terminate = #{autoMlIns.deleteTmpFolderAfterTerminate},
</if>
<if test="autoMlIns.dataCsv != null and autoMlIns.dataCsv !=''">
data_csv = #{autoMlIns.dataCsv},
</if>
<if test="autoMlIns.targetColumns != null and autoMlIns.targetColumns !=''">
target_columns = #{autoMlIns.targetColumns},
</if>
<if test="autoMlIns.state != null">
state = #{autoMlIns.state},
</if>
<if test="autoMlIns.updateBy != null and autoMlIns.updateBy !=''">
update_by = #{autoMlIns.updateBy},
</if>
</set>
where id = #{autoMlIns.id}
</update>

<select id="getById" resultType="com.ruoyi.platform.domain.AutoMlIns">
select *
from auto_ml_ins
where id = #{id}
</select>

<select id="count" resultType="java.lang.Long">
select count(1) from auto_ml_ins
<include refid="common_condition"></include>
</select>

<select id="queryByPage" resultType="com.ruoyi.platform.domain.AutoMlIns">
select * from auto_ml_ins
<include refid="common_condition"></include>
</select>

<select id="findByDatasetName" resultType="com.ruoyi.platform.domain.AutoMlIns">
select * from auto_ml_ins
<include refid="common_condition"></include>
and dataset_name = #{datasetName}
</select>

<sql id="common_condition">
<where>
state = 1 and auto_ml_id = #{autoMlId}
</where>
</sql>
</mapper>

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