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java高并发下数据入库
该服务利用线程池并结合缓存类来处理高并发下数据入库问题，做到实时数据存入redis和数据批量入库，使用的时候需要修改为自己的业务数据，该模块是根据下面的设置进行高并发处理。 1、达到设置的超时时间。 2、达到最大批次。
代码语言：javascript复制package io.jack.service.impl;
import com.alibaba.fastjson.JSON;
import com.alibaba.fastjson.JSONArray;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Component;
import javax.annotation.Resource;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
/** * <pre> * 数据批量入库服务 * </pre> * Created by RuiXing Hou on 2021-08-05. * * @since 1.0 */
@Component
@Slf4j
public class BatchDataStorageService implements InitializingBean
{
/** * 最大批次数量 */
@Value("${app.db.maxBatchCount:800}")
private int maxBatchCount;
/** * 最大线程数 */
@Value("${app.db.maxBatchThreads:100}")
private int maxBatchThreads;
/** * 超时时间 */
@Value("${app.db.batchTimeout:3000}")
private int batchTimeout;
/** * 批次数量 */
private int batchCount = 0;
/** * 批次号 */
private static long batchNo = 0;
/** * 线程池定义接口 */
private ExecutorService executorService = null;
/** * 服务器缓存工具类，下面提供源码 */
@Resource
private CacheService cacheService;
/** * 业务接口 */
@Resource
private DeviceRealTimeService deviceRealTimeService;
/** * redis工具类 */
@Resource
private RedisUtils redisUtils;
@Override
public void afterPropertiesSet() {
this.executorService = Executors.newFixedThreadPool(this.maxBatchThreads, r -> {
Thread thread = new Thread(r);
if (r instanceof BatchWorker) {
thread.setName("batch-worker-" ((BatchWorker) r).batchKey);
}
return thread;
});
}
/** * 需要做高并发处理的类只需要调用该方法 （我用的是rabbitMq） * * @param deviceRealTimeDTO */
public void saveRealTimeData(DeviceRealTimeDTO deviceRealTimeDTO) {
final String failedCacheKey = "device:real_time:failed_records";
try {
String durationKey = "device:real_time:batchDuration" batchNo;
String batchKey = "device:real_time:batch" batchNo;
if (!cacheService.exists(durationKey)) {
cacheService.put(durationKey, System.currentTimeMillis());
new BatchTimeoutCommitThread(batchKey, durationKey, failedCacheKey).start();
}
cacheService.lPush(batchKey, deviceRealTimeDTO);
if ( batchCount >= maxBatchCount) {
// 达到最大批次，执行入库逻辑
dataStorage(durationKey, batchKey, failedCacheKey);
}
} catch (Exception ex) {
log.warn("[DB:FAILED] 设备上报记录入批处理集合异常: " ex.getMessage() ", DeviceRealTimeDTO: " JSON.toJSONString(deviceRealTimeDTO), ex);
cacheService.lPush(failedCacheKey, deviceRealTimeDTO);
} finally {
updateRealTimeData(deviceRealTimeDTO);
}
}
/** * 更新实时数据 * @param deviceRealTimeDTO 业务POJO */
private void updateRealTimeData(DeviceRealTimeDTO deviceRealTimeDTO) {
redisUtils.set("real_time:" deviceRealTimeDTO.getDeviceId(), JSONArray.toJSONString(deviceRealTimeDTO));
}
/** * * @param durationKey 持续时间标识 * @param batchKey 批次标识 * @param failedCacheKey 错误标识 */
private void dataStorage(String durationKey, String batchKey, String failedCacheKey) {
batchNo ;
batchCount = 0;
cacheService.del(durationKey);
if (batchNo >= Long.MAX_VALUE) {
batchNo = 0;
}
executorService.execute(new BatchWorker(batchKey, failedCacheKey));
}
private class BatchWorker implements Runnable
{
private final String failedCacheKey;
private final String batchKey;
public BatchWorker(String batchKey, String failedCacheKey) {
this.batchKey = batchKey;
this.failedCacheKey = failedCacheKey;
}
@Override
public void run() {
final List<DeviceRealTimeDTO> deviceRealTimeDTOList = new ArrayList<>();
try {
DeviceRealTimeDTO deviceRealTimeDTO = cacheService.lPop(batchKey);
while(deviceRealTimeDTO != null) {
deviceRealTimeDTOList.add(deviceRealTimeDTO);
deviceRealTimeDTO = cacheService.lPop(batchKey);
}
long timeMillis = System.currentTimeMillis();
try {
List<DeviceRealTimeEntity> deviceRealTimeEntityList = ConvertUtils.sourceToTarget(deviceRealTimeDTOList, DeviceRealTimeEntity.class);
deviceRealTimeService.insertBatch(deviceRealTimeEntityList);
} finally {
cacheService.del(batchKey);
log.info("[DB:BATCH_WORKER] 批次：" batchKey "，保存设备上报记录数：" deviceRealTimeDTOList.size() ", 耗时：" (System.currentTimeMillis() - timeMillis) "ms");
}
} catch (Exception e) {
log.warn("[DB:FAILED] 设备上报记录批量入库失败：" e.getMessage() ", DeviceRealTimeDTO: " deviceRealTimeDTOList.size(), e);
for (DeviceRealTimeDTO deviceRealTimeDTO : deviceRealTimeDTOList) {
cacheService.lPush(failedCacheKey, deviceRealTimeDTO);
}
}
}
}
class BatchTimeoutCommitThread extends Thread {
private final String batchKey;
private final String durationKey;
private final String failedCacheKey;
public BatchTimeoutCommitThread(String batchKey, String durationKey, String failedCacheKey) {
this.batchKey = batchKey;
this.durationKey = durationKey;
this.failedCacheKey = failedCacheKey;
this.setName("batch-thread-" batchKey);
}
public void run() {
try {
Thread.sleep(batchTimeout);
} catch (InterruptedException e) {
log.error("[DB] 内部错误，直接提交：" e.getMessage());
}
if (cacheService.exists(durationKey)) {
// 达到最大批次的超时间，执行入库逻辑
dataStorage(durationKey, batchKey, failedCacheKey);
}
}
}
}package io.jack.service;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.context.annotation.Scope;
import org.springframework.stereotype.Component;
import java.util.HashMap;
import java.util.LinkedList;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
@Component
@Scope("singleton")
public class CacheService implements InitializingBean {
private Map<String, Object> objectCache = new ConcurrentHashMap<>();
private Map<String, AtomicLong> statCache = new ConcurrentHashMap<>();
@Override
public void afterPropertiesSet() {
statCache.put("terminals", new AtomicLong(0));
statCache.put("connections", new AtomicLong(0));
}
public long incr(String statName) {
if (!statCache.containsKey(statName))
statCache.put(statName, new AtomicLong(0));
return statCache.get(statName).incrementAndGet();
}
public long decr(String statName) {
if (!statCache.containsKey(statName))
statCache.put(statName, new AtomicLong(0));
return statCache.get(statName).decrementAndGet();
}
public long stat(String statName) {
if (!statCache.containsKey(statName))
statCache.put(statName, new AtomicLong(0));
return statCache.get(statName).get();
}
public <T> void put(String key, T object) {
objectCache.put(key, object);
}
public <T> T get(String key) {
return (T) objectCache.get(key);
}
public void remove(String key) {
objectCache.remove(key);
}
public void hSet(String key, String subkey, Object value) {
synchronized (objectCache) {
HashMap<String, Object> submap = (HashMap<String, Object>) objectCache.get(key);
if (submap == null) {
submap = new HashMap<>();
objectCache.put(key, submap);
}
submap.put(subkey, value);
}
}
public <T> T hGet(String key, String subkey) {
synchronized (objectCache) {
HashMap<String, Object> submap = (HashMap<String, Object>) objectCache.get(key);
if (submap != null) {
return (T) submap.get(subkey);
}
return null;
}
}
public boolean hExists(String key, String subkey) {
synchronized (objectCache) {
HashMap<String, Object> submap = (HashMap<String, Object>) objectCache.get(key);
if (submap != null) {
return submap.containsKey(subkey);
}
return false;
}
}
public void lPush(String key, Object value) {
synchronized (objectCache) {
LinkedList queue = (LinkedList) objectCache.get (key);
if (queue == null) {
queue = new LinkedList();
objectCache.put(key, queue);
}
queue.addLast(value);
}
}
public <T> T lPop(String key) {
synchronized (objectCache) {
LinkedList queue = (LinkedList) objectCache.get (key);
if (queue != null) {
if (!queue.isEmpty()) {
return (T)queue.removeLast();
}
objectCache.remove(key);
}
return null;
}
}
public void del(String key) {
objectCache.remove(key);
}
public boolean exists(String key) {
return objectCache.containsKey(key);
}
public void dump() {
}
}发布者：全栈程序员栈长，转载请注明出处：https://javaforall.cn/144596.html原文链接：https://javaforall.cn
