package org.dromara.job.snailjob;
import cn.hutool.core.thread.ThreadUtil;
import cn.hutool.extra.spring.SpringUtil;
import com.aizuda.snailjob.client.job.core.MapHandler;
import com.aizuda.snailjob.client.job.core.annotation.JobExecutor;
import com.aizuda.snailjob.client.job.core.annotation.MapExecutor;
import com.aizuda.snailjob.client.job.core.annotation.ReduceExecutor;
import com.aizuda.snailjob.client.job.core.dto.MapArgs;
import com.aizuda.snailjob.client.job.core.dto.ReduceArgs;
import com.aizuda.snailjob.common.log.SnailJobLog;
import com.aizuda.snailjob.model.dto.ExecuteResult;
import org.springframework.stereotype.Component;
import java.util.List;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
/**
* MapReduce任务 动态分配 分片后合并结果
*
*
* @author 老马
*/
@Component
@JobExecutor(name = "testMapReduceAnnotation1")
public class TestMapReduceAnnotation1 {
@MapExecutor
public ExecuteResult rootMapExecute(MapArgs mapArgs, MapHandler mapHandler) {
int partitionSize = 50;
List> partition = IntStream.rangeClosed(1, 200)
.boxed()
.collect(Collectors.groupingBy(i -> (i - 1) / partitionSize))
.values()
.stream()
.toList();
SnailJobLog.REMOTE.info("端口:{}完成分配任务", SpringUtil.getProperty("server.port"));
return mapHandler.doMap(partition, "doCalc");
}
@MapExecutor(taskName = "doCalc")
public ExecuteResult doCalc(MapArgs mapArgs) {
List sourceList = (List) mapArgs.getMapResult();
// 遍历sourceList的每一个元素,计算出一个累加值partitionTotal
int partitionTotal = sourceList.stream().mapToInt(i -> i).sum();
// 打印日志到服务器
ThreadUtil.sleep(3, TimeUnit.SECONDS);
SnailJobLog.REMOTE.info("端口:{},partitionTotal:{}", SpringUtil.getProperty("server.port"), partitionTotal);
return ExecuteResult.success(partitionTotal);
}
@ReduceExecutor
public ExecuteResult reduceExecute(ReduceArgs reduceArgs) {
int reduceTotal = reduceArgs.getMapResult().stream().mapToInt(i -> Integer.parseInt((String) i)).sum();
SnailJobLog.REMOTE.info("端口:{},reduceTotal:{}", SpringUtil.getProperty("server.port"), reduceTotal);
return ExecuteResult.success(reduceTotal);
}
}