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提交 7e07ad2d 作者: 925993793@qq.com
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逻辑优化；去除无用逻辑

上级 0ded4c00
正在显示 包含 243 行增加 和 39 行删除
pom.xml
......@@ -314,5 +314,12 @@
<profile.name>nacos</profile.name>
</properties>
</profile>
<profile>
<id>label</id>
<properties>
<!--克虏宝测试环境-->
<profile.name>label</profile.name>
</properties>
</profile>
</profiles>
</project>
src/main/java/com/zzsn/event/controller/EventAnalysisController.java
......@@ -266,7 +266,9 @@ public class EventAnalysisController {
* 热词共现
*
* @param eventId 事件id
* @param startTime 开始时间
* @param endTime 结束时间
* @param versionId 版本id
* @author lkg
* @date 2025/7/9
*/
......
src/main/java/com/zzsn/event/controller/EventManageController.java
......@@ -308,10 +308,6 @@ public class EventManageController {
CompletableFuture.runAsync(() -> {
EventVO eventVO = eventService.queryInfo(id);
iXxlJobInfoService.deleteByInfosourceCode(eventVO.getEventCode());
//删除关键词
keyWordsService.removeBaseAndMap(id);
//删除流程绑定
clbModelArrangeSubjectMapService.remove(Wrappers.<ClbModelArrangeSubjectMap>lambdaQuery().eq(ClbModelArrangeSubjectMap::getSubjectId, id));
});
return Result.OK();
}
......@@ -335,8 +331,6 @@ public class EventManageController {
for (String id : idArr) {
EventVO eventVO = eventService.queryInfo(id);
iXxlJobInfoService.deleteByInfosourceCode(eventVO.getEventCode());
//删除关键词
keyWordsService.removeBaseAndMap(id);
}
});
return Result.OK();
......
src/main/java/com/zzsn/event/service/impl/AnalysisServiceImpl.java
......@@ -60,8 +60,6 @@ public class AnalysisServiceImpl implements AnalysisService {
@Autowired
private EventAnalysisVersionRecordService eventAnalysisVersionRecordService;
@Autowired
private EventContextService eventContextService;
@Autowired
private SysDictItemService dictItemService;
@Autowired
private ObsUtil obsUtil;
......@@ -228,7 +226,12 @@ public class AnalysisServiceImpl implements AnalysisService {
List<CountVO> groupKeyWord = esService.groupByTerm(searchCondition, "groupKeyWord", "keyWordsList.keyword", false, size);
Map<String, Long> wordFrequencyMap = groupKeyWord.stream().collect(Collectors.toMap(CountVO::getName, CountVO::getValue));
Map<String, Integer> map = HotWordUtil.calculateCoOccurrence_list(wordList);
Map<String, Integer> filterMap = map.entrySet().stream().filter(e -> e.getValue() > 10).collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue));
//根据共现次数过滤，支取次数大于等于10的
//Map<String, Integer> filterMap = map.entrySet().stream().filter(e -> e.getValue() >= 10).collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue));
//根据共现次数倒序排序，并取前100
LinkedHashMap<String, Integer> filterMap = map.entrySet().stream().sorted(Map.Entry.comparingByValue(Comparator.reverseOrder()))
.limit(100)
.collect(Collectors.toMap(Map.Entry::getKey, Map.Entry::getValue, (oldValue, newValue) -> oldValue, LinkedHashMap::new));
for (Map.Entry<String, Integer> entry : filterMap.entrySet()) {
CoOccurrenceVO coOccurrenceVO = new CoOccurrenceVO();
String key = entry.getKey();
......
src/main/java/com/zzsn/event/service/impl/EventServiceImpl.java
......@@ -388,10 +388,6 @@ public class EventServiceImpl extends ServiceImpl<EventMapper, Event> implements
endTime = cn.hutool.core.date.DateUtil.offsetWeek(addEventParam.getStartTime(), 3);
}
event.setEndTime(endTime);
//事件专题的默认分析规则参数-必填
event.setIncreAnaRule(20);
event.setTotalAnaRule(50);
event.setTimeAnaRule(5);
String subjectCode = codeGenerateUtil.geneCodeNo(CodePrefixEnum.EVENT_DEFAULT.getValue());
event.setEventCode(subjectCode);
//默认发布
......@@ -420,7 +416,7 @@ public class EventServiceImpl extends ServiceImpl<EventMapper, Event> implements
List<RegionVO> regionList = addEventParam.getRegionList();
addRegionMap(eventId, regionList);
//默认绑定搜索引擎、模型
saveDefaultMap(eventId);
//saveDefaultMap(eventId);
} catch (Exception e) {
log.error("事件配置异常:{}",e.getMessage(),e);
throw new RuntimeException(e);
......@@ -479,8 +475,6 @@ public class EventServiceImpl extends ServiceImpl<EventMapper, Event> implements
CompletableFuture.runAsync(() -> {
//删除与信息源的关联关系
iSubjectInfoSourceMapService.delete(id);
//删除与关键词组的关联关系
iSubjectKeywordsMapService.delete(id);
//删除地域关系
eventRegionMapService.remove(Wrappers.<EventRegionMap>lambdaQuery().eq(EventRegionMap::getEventId, id));
//删除专题-类别绑定关系
......@@ -489,14 +483,18 @@ public class EventServiceImpl extends ServiceImpl<EventMapper, Event> implements
iProjectSubjectMapService.deleteBySubjectId(id);
//删除事件标签
eventTagService.remove(Wrappers.<EventTag>lambdaQuery().eq(EventTag::getEventId, id));
//删除事件-模型关系
//删除关键词
keyWordsService.removeBaseAndMap(id);
//删除流程绑定
clbModelArrangeSubjectMapService.remove(Wrappers.<ClbModelArrangeSubjectMap>lambdaQuery().eq(ClbModelArrangeSubjectMap::getSubjectId, id));
/*//删除事件-模型关系
subjectModelMapService.remove(Wrappers.<SubjectModelMap>lambdaQuery().eq(SubjectModelMap::getSubjectId, id));
//删除事件-搜索引擎关系
subjectSearchEnginesMapService.remove(Wrappers.<SubjectSearchEnginesMap>lambdaQuery().eq(SubjectSearchEnginesMap::getSubjectId, id));
//删除事件 观点分析、事件脉络数据
subjectAnalysisService.remove(Wrappers.<SubjectAnalysis>lambdaQuery().eq(SubjectAnalysis::getSubjectId,id));
//删除事件 分析报告数据
eventAnalysisReportService.delete(id);
eventAnalysisReportService.delete(id);*/
});
}
......@@ -823,36 +821,30 @@ public class EventServiceImpl extends ServiceImpl<EventMapper, Event> implements
}
private void saveMapMain(Event subject, AddEventParam addEventParam) {
if (StringUtils.isNotEmpty(addEventParam.getSubjectTypeId())) {
log.info("事件专题类别id：{}-事件专题id:{}", addEventParam.getSubjectTypeId(),subject.getId());
SubjectTypeMap subjectTypeMap = new SubjectTypeMap();
subjectTypeMap.setSubjectId(subject.getId());
subjectTypeMap.setUpdateBy(subject.getUpdateBy());
subjectTypeMap.setUpdateTime(subject.getUpdateTime());
subjectTypeMap.setTypeId(addEventParam.getSubjectTypeId());
iSubjectTypeMapService.save(subjectTypeMap);
}else {
log.info("事件专题类别id：{}-事件专题id:{}", addEventParam.getSubjectTypeId(),subject.getId());
//事件-分类关系
String subjectTypeId = addEventParam.getSubjectTypeId();
if (StringUtils.isEmpty(subjectTypeId)) {
//分类默认 研究中心
subjectTypeId = "1802619433932296193";
}
log.info("事件专题类别id：{}-事件专题id:{}", subjectTypeId,subject.getId());
SubjectTypeMap subjectTypeMap = new SubjectTypeMap();
subjectTypeMap.setSubjectId(subject.getId());
subjectTypeMap.setTypeId(subjectTypeId);
subjectTypeMap.setUpdateBy(subject.getUpdateBy());
subjectTypeMap.setUpdateTime(subject.getUpdateTime());
subjectTypeMap.setTypeId("1802619433932296193");
iSubjectTypeMapService.save(subjectTypeMap);
//事件-项目关系
String projectId = addEventParam.getProjectId();
if (StringUtils.isNotEmpty(projectId)) {
//项目默认 研究中心
projectId = "1476527644425682945";
}
if (StringUtils.isNotEmpty(addEventParam.getProjectId())) {
log.info("项目id：{}-事件专题id:{}", addEventParam.getProjectId(),subject.getId());
log.info("项目id：{}-事件专题id:{}", projectId,subject.getId());
ProjectSubjectMap projectSubjectMap = new ProjectSubjectMap();
projectSubjectMap.setProjectId(addEventParam.getProjectId());
projectSubjectMap.setProjectId(projectId);
projectSubjectMap.setSubjectId(subject.getId());
iProjectSubjectMapService.save(projectSubjectMap);
}else {
log.info("项目id：{}-事件专题id:{}", addEventParam.getProjectId(),subject.getId());
ProjectSubjectMap projectSubjectMap = new ProjectSubjectMap();
projectSubjectMap.setProjectId("1476527644425682945");
projectSubjectMap.setSubjectId(subject.getId());
iProjectSubjectMapService.save(projectSubjectMap);
}
}
@Override
......
src/main/resources/application-label.yml 0 → 100644
spring:
servlet:
multipart:
max-request-size: 1024MB
max-file-size: 100MB
web:
resources:
static-locations:
- file:${user.dir}/icon/
freemarker:
template-loader-path:
- classpath:/template
datasource:
druid:
stat-view-servlet:
enabled: true
loginUsername: admin
loginPassword: 123456667
allow:
web-stat-filter:
enabled: true
dynamic:
druid: # 全局druid参数，绝大部分值和默认保持一致。(现已支持的参数如下,不清楚含义不要乱设置)
# 连接池的配置信息
# 初始化大小，最小，最大
initial-size: 5
min-idle: 10
maxActive: 100
# 配置获取连接等待超时的时间
maxWait: 60000
# 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒
timeBetweenEvictionRunsMillis: 60000
# 配置一个连接在池中最小生存的时间，单位是毫秒
minEvictableIdleTimeMillis: 600000
validationQuery: SELECT 1 FROM DUAL
testWhileIdle: true
testOnBorrow: false
testOnReturn: false
# 打开PSCache，并且指定每个连接上PSCache的大小
poolPreparedStatements: true
maxPoolPreparedStatementPerConnectionSize: 20
# 配置监控统计拦截的filters，去掉后监控界面sql无法统计，'wall'用于防火墙
filters: stat,wall,slf4j
# 通过connectProperties属性来打开mergeSql功能；慢SQL记录
connectionProperties: druid.stat.mergeSql\=true;druid.stat.slowSqlMillis\=5000
datasource:
master:
url: jdbc:mysql://1.95.78.131:3306/clb_project_label?useUnicode=true&characterEncoding=utf-8&AllowPublicKeyRetrieval=True&serverTimezone=Asia/Shanghai&autoReconnect=true&rewriteBatchedStatements=true
username: ciglobal
password: qwer@9988&zzsn
driver-class-name: com.mysql.cj.jdbc.Driver
multi-datasource1:
url: jdbc:mysql://1.95.78.131:3306/clb_xxl_job_label?characterEncoding=UTF-8&useUnicode=true&useSSL=false&tinyInt1isBit=false&allowPublicKeyRetrieval=true&serverTimezone=Asia/Shanghai
username: ciglobal
password: qwer@9988&zzsn
driver-class-name: com.mysql.cj.jdbc.Driver
multi-datasource2:
url: jdbc:mysql://1.95.78.131:3306/clb_system_label?characterEncoding=UTF-8&useUnicode=true&useSSL=false&tinyInt1isBit=false&allowPublicKeyRetrieval=true&serverTimezone=Asia/Shanghai
username: ciglobal
password: qwer@9988&zzsn
driver-class-name: com.mysql.cj.jdbc.Driver
elasticsearch:
# uris: ["1.95.69.2:9200"]
uris: ["1.95.38.69:9700","1.95.3.121:9200","1.95.87.177:9700"]
username: elastic
# password: elastic
password: zzsn9988
connection-timeout: 300000
socket-timeout: 300000
cloud:
stream:
kafka:
binder:
brokers: 1.95.78.131:17092
zkNodes: 1.95.78.131:12181
requiredAcks: 1
redis:
database: 7
host: 1.95.69.2
lettuce:
pool:
max-active: 8 #最大连接数据库连接数,设 0 为没有限制
max-idle: 8 #最大等待连接中的数量,设 0 为没有限制
max-wait: -1ms #最大建立连接等待时间。如果超过此时间将接到异常。设为-1表示无限制。
min-idle: 0 #最小等待连接中的数量,设 0 为没有限制
shutdown-timeout: 100ms
port: 6379
password: zzsn9988
kafka:
bootstrap-servers: 1.95.78.131:17092
producer: # 生产者
retries: 3 # 设置大于0的值，则客户端会将发送失败的记录重新发送
batch-size: 16384
#缓存大小,默认32M
buffer-memory: 335544324
acks: 1
# 指定消息key和消息体的编解码方式
key-serializer: org.apache.kafka.common.serialization.StringSerializer
value-serializer: org.apache.kafka.common.serialization.StringSerializer
consumer:
#用于标识此使用者所属的使用者组的唯一字符串
group-id: event-analysis-group-test-label
#当Kafka中没有初始偏移量或者服务器上不再存在当前偏移量时该怎么办，默认值为latest，表示自动将偏移重置为最新的偏移量
#可选的值为latest, earliest, none
auto-offset-reset: latest
#消费者的偏移量将在后台定期提交，默认值为true
enable-auto-commit: true
#如果'enable-auto-commit'为true，则消费者偏移自动提交给Kafka的频率（以毫秒为单位），默认值为5000。
auto-commit-interval: 100
#密钥的反序列化器类，实现类实现了接口org.apache.kafka.common.serialization.Deserializer
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
#值的反序列化器类，实现类实现了接口org.apache.kafka.common.serialization.Deserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
properties:
security:
protocol: SASL_PLAINTEXT
sasl:
mechanism: PLAIN
jaas:
config: org.apache.kafka.common.security.plain.PlainLoginModule required username="admin" password="admin-zzsn9988";
main:
allow-circular-references: true
mybatis-plus:
mapper-locations: classpath*:com/zzsn/event/**/xml/*.xml
configuration:
# log-impl: org.apache.ibatis.logging.stdout.StdOutImpl
map-underscore-to-camel-case: true
obs:
ak: VEHN7D0TJ9316H8AHCAV
sk: heR353lvSWVPNU8pe2QxDtd8GDsO5L6PGH5eUoQY
endPoint: https://obs.cn-north-1.myhuaweicloud.com
scheduling:
enable: false
yjzxEnable: false
serviceProject:
url: https://clb.ciglobal.cn/clb-api/datapull/
scoreRule:
weekScore: 10
monthScore: 5
yearScore: 3
beforeYearScore: 1
translate:
url: http://114.116.116.241:8018/translate/getTranslateInfoWithTag
python:
#python打分接口-弃用
scoreModelUrl: http://114.116.36.231:8080/score
#python开始执行接口--弃用
subjectProcessorUrl: http://114.116.36.231:8085/subject/subject_processor
#判重
judgeDuplicateUrl: http://1.95.13.40:8080/subject/judg_duplicate
#抽取关键词
keyWordsExtractUrl: http://1.95.91.200:7006/get_phrase/
#清空去重服务历史数据
clearDuplicateHistoryUrl: http://1.95.13.40:8080/subject/delete_history_data
hot-crawler: http://139.9.144.106:5000/data?option=OPTION
jeecg:
shiro:
excludeUrls: info/subjectPageListGroupByLabel,/subject/simple/queryInfoNoSign,/subject/manage/visiblePageListNoSign
kafka:
topic:
subject:
run: subjectModelTest
event:
run: eventSubjectModelTest
clb:
subject:
default:
processing:
advanceMonth: 6
data-permit:
dataPermitGetQueryEntityTest: http://1.95.77.159:10089/permission/
dataPermitGetQueryEntityProd: http://1.95.14.24:8060/
infoSource:
pageList: http://1.95.79.85:8823/baseSourceInfo/api/infoSource/pageList
columnList: http://1.95.79.85:8823/baseSourceInfo/api/infoSource/columnList
add: http://1.95.79.85:8823/baseSourceInfo/api/infoSource/addInfoSourceTask
waitInfoRemove: http://1.95.79.85:8823/baseSourceInfo/api/infoSource/waitInfoRemove
columnListByWait: http://1.95.79.85:8823/baseSourceInfo/api/infoSource/columnListByWait
columnDetail: http://1.95.79.85:8823/baseSourceInfo/api/infoSource/columnDetail
model:
default-modelType: zhipu
configs:
- modelType: zhipu
modelTypeName: 智谱
url: https://open.bigmodel.cn/api/paas/v4/chat/completions
api-key: c5a53bd5f95a4e37a8997deb5d0c6031.orXyRRPNvZiqRaxF
default-model: glm-4-flash #免费
web-search: true
- modelType: qwen
modelTypeName: 千问
url: https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
api-key: sk-01ee9a6efa394178993a950b768e3753
default-model: qwen-plus #收费
- modelType: deepseek
modelTypeName: deepseek
url: https://api.deepseek.com/v1/chat/completions
api-key: sk-656a8ec451dc47aaad3dacf24fe36f20
default-model: deepseek-chat #收费
- modelType: doubao
modelTypeName: 豆包
url: https://ark.cn-beijing.volces.com/api/v3/chat/completions
api-key: ab54c534-4f3c-41b9-9b27-132cb7954b6f
default-model: doubao-1-5-pro-32k-250115 # Doubao-1.5-pro-32k #收费
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