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铭牌的多线程控制， 修改企微画像的tag

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This commit is contained in:
ZLI263
2025-09-19 10:59:32 +08:00
parent 263614258b
commit 2586bb5de1
4 changed files with 31 additions and 19 deletions
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14
ai-analytic-center-biz/src/main/java/com/volvo/ai/analytic/center/config/ExecutorConfig.java
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@@ -20,14 +20,14 @@ public class ExecutorConfig {
@Value("${task.pool.corePoolSize}")
private int corePoolSize;
@Value("${task.pool.maxPoolSize}")
private int maxPoolSize;
// @Value("${task.pool.maxPoolSize}")
private int maxPoolSize=12;
@Value("${task.pool.keepAliveSeconds}")
private int keepAliveSeconds;
// @Value("${task.pool.keepAliveSeconds}")
private int keepAliveSeconds=12000;
@Value("${task.pool.queueCapacity}")
private int queueCapacity;
// @Value("${task.pool.queueCapacity}")
private int queueCapacity=20;
private ThreadPoolTaskExecutor executor;
private ThreadPoolExecutor blockingExecutor;
@@ -38,7 +38,7 @@ public class ExecutorConfig {
executor = new ThreadPoolTaskExecutor();
log.info("Thread-process-pool-Initializing: corePoolSize: {}, maxPoolSize: {}, queueCapacity: {}, keepAliveSeconds: {}",corePoolSize, maxPoolSize, queueCapacity, keepAliveSeconds);
// 设置核心线程数
// 设置核心线程数 Thread-process-pool-Initializing: corePoolSize: 10, maxPoolSize: 300, queueCapacity: 1000, keepAliveSeconds: 60
executor.setCorePoolSize(corePoolSize);
// 设置最大线程数为5
executor.setMaxPoolSize(maxPoolSize);

10
ai-analytic-center-biz/src/main/java/com/volvo/ai/analytic/center/mq/NameplateKafkaConsumer.java
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@@ -19,6 +19,7 @@ import org.springframework.web.bind.annotation.RestController;
import javax.annotation.Resource;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.Semaphore;
/**
* @ClassName NameplateKafkaConsumer
@@ -40,7 +41,7 @@ public class NameplateKafkaConsumer {
@Autowired
@Resource(name = "threadPoolTaskExecutor")
private ThreadPoolTaskExecutor executor;
private Semaphore semaphore = new Semaphore(10); // 限制并发数
@KafkaListener(topics = "${analyticCenterKafka.consumer.topic}", // = smart_assistant_nameplate_topic
groupId = "${analyticCenterKafka.consumer.group}" , //smart_assistant_nameplate_topic_group
@@ -51,12 +52,13 @@ public class NameplateKafkaConsumer {
@Header(KafkaHeaders.OFFSET) Long offset) {
long startTime = System.currentTimeMillis();
log.info("nameplateKafkaConsumer 当前线程: {}, 线程ID: {},计数：{}", Thread.currentThread().getName(), Thread.currentThread().getId());
log.info("nameplateKafkaConsumerMessage总数：{}，消息：{}", recordMessages);
log.info("nameplateKafkaConsumerMessage，消息：{}", recordMessages);
// 初始化绑定 Consumer
if (StringUtils.isEmpty(recordMessages)) {
ack.acknowledge();
return;
}
try {
NameplateTableKafkaDTO tmNameplateCorpus = JSON.parseObject(recordMessages, NameplateTableKafkaDTO.class);
if (!"INSERT".equals(tmNameplateCorpus.getType()) || CollectionUtils.isEmpty(tmNameplateCorpus.getData())) {
@@ -66,9 +68,13 @@ public class NameplateKafkaConsumer {
tmNameplateCorpus.getData().forEach(nameplate ->
CompletableFuture.runAsync(() -> {
try {
semaphore.acquire(); // 获取许可
tmNameplateCorpusService.processItem(nameplate);
} catch (Exception e) {
log.error("corpusPortrait画像铭牌异步任务执行失败", e);
} finally {
log.info("corpusPortrait 释放锁，availablePermits {}", semaphore.availablePermits());
semaphore.release(); // 释放许可
}
}, executor));

19
ai-analytic-center-biz/src/main/java/com/volvo/ai/analytic/center/service/impl/TmNameplateCorpusServiceImpl.java
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@@ -22,8 +22,10 @@ import org.apache.commons.lang3.StringUtils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.cloud.context.config.annotation.RefreshScope;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
import org.springframework.stereotype.Service;
import javax.annotation.Resource;
import java.time.LocalDate;
import java.util.*;
import java.util.concurrent.CompletableFuture;
@@ -73,7 +75,9 @@ public class TmNameplateCorpusServiceImpl extends ServiceImpl<TmNameplateCorpusM
private String aiAnalysisRequestIdFinal = "aiAnalysisRequestId";
// 使用多线程并行执行两个业务场景
ExecutorService executorService = Executors.newFixedThreadPool(6);
@Autowired
@Resource(name = "threadPoolTaskExecutor")
private ThreadPoolTaskExecutor executor;
@Override
public void runNameplateCorpusDifyRetry(String paramJson) {
@@ -169,18 +173,18 @@ public class TmNameplateCorpusServiceImpl extends ServiceImpl<TmNameplateCorpusM
log.info("铭牌语料第1个业务场景， 优先执行。 ");
long startTime = System.currentTimeMillis();
CompletableFuture.runAsync(() -> {
CompletableFuture<Void> summaryTask = CompletableFuture.runAsync(() -> {
//第一个业务场景 开始： 总结和分类业务场景
JSONObject execDifyFlow = diFyService.executeDifyFlow(diFyImageReq, BusinessTypeEnum.SMART_ASSISTANT_NAMEPLATE.getCode(),
JSONObject execDifyFlow = diFyService.executeDifyFlow(diFyImageReq, BusinessTypeEnum.SMART_ASSISTANT_NAMEPLATE.getCode(),
JSONObject.toJSONString(corpusReportDTO), null);
log.info("runDify execDifyFlow ,铭牌语料 ，总结和分类业务，返回： {}", execDifyFlow);
}, executorService);
}, executor);
long endTime = System.currentTimeMillis();
log.info("第一个业务场景（总结和分类）执行时间: {} ms", (endTime - startTime));
//第一个业务场景， 结束
long startTime2 = System.currentTimeMillis();
CompletableFuture.runAsync(() -> {
CompletableFuture<Void> portraitTask = CompletableFuture.runAsync(() -> {
//"analysisScene": "分析类型", // 1、企微会话 2、AI通话录音 3、AI铭牌(客流) 4、AI铭牌(试驾)
DiFyReq diFyImageReq2 = new DiFyReq();
diFyImageReq2.setUser(ConstantStr.corpus_user);
@@ -199,9 +203,12 @@ public class TmNameplateCorpusServiceImpl extends ServiceImpl<TmNameplateCorpusM
updateNameplate(execDifyFlowForPortrait.toJSONString());
log.info("runDify execDifyFlow ,铭牌语料 ,客户画像场景，返回： {}", execDifyFlowForPortrait);
}, executorService);
}, executor);
long endTime2 = System.currentTimeMillis();
log.info("第二个业务场景（用户画像）执行时间: {} ms", (endTime2 - startTime2));
// 等待两个任务完成
CompletableFuture.allOf(summaryTask, portraitTask).join();
} catch (Exception e) {
log.error("nameplate processItem error {}", e);

7
ai-analytic-center-biz/src/main/java/com/volvo/ai/analytic/center/service/impl/TmOdsVdqwMessagearchivingServiceImpl.java
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@@ -210,10 +210,8 @@ public class TmOdsVdqwMessagearchivingServiceImpl extends ServiceImpl<TmOdsVdqwM
String corpusChat = dataMaskingRuleService.runMaskingRule(runMaskingRuleInput);
finalChatList.append(corpusChat).append("***");
chatList2.append(corpusChat).append("####");
chatList3.append(corpusChat).append("\n");
chatList4.append(corpusChat).append("\r");
log.info("第几循环次数{} ，掩码前：{} ,掩码后：{},合并后的总语料数据 ：{}", externalcontactCount.get(), chat,corpusChat, finalChatList);
log.info("chatList2: {} ,chatList3：{} ,chatList4：{},", chatList2, chatList3,chatList4 );
});
if (externalcontactCount.get() < 1) {
log.info("没有客户回复的语料，无需解析");
@@ -329,7 +327,8 @@ public class TmOdsVdqwMessagearchivingServiceImpl extends ServiceImpl<TmOdsVdqwM
DiFyReq diFyImageReq2 = new DiFyReq();
diFyImageReq2.setUser(ConstantStr.corpus_user);
Map<String, Object> inputMap2 = new HashMap<>();
inputMap2.put("businessId", unionId);
inputMap2.put("businessId", unionId+","+corpusReportDTO.getUserId());
inputMap2.put("consultantId", corpusReportDTO.getUserId());//顾问id
inputMap2.put("communicateDate", DateUtil.format(maxMsgTimeItem.getMsgTime(), DatePattern.NORM_DATETIME_PATTERN));
inputMap2.put("analysisScene", "1");
inputMap2.put("version", 2);