补充MapReduce测试用例

src/main/java/com/example/snailjob/job/TestMapReduceJobExecutor.java

@@ -4,12 +4,23 @@ import com.aizuda.snailjob.client.job.core.dto.MapArgs;
 import com.aizuda.snailjob.client.job.core.dto.ReduceArgs;
 import com.aizuda.snailjob.client.job.core.executor.AbstractMapReduceExecutor;
 import com.aizuda.snailjob.client.model.ExecuteResult;
-import com.aizuda.snailjob.common.core.constant.SystemConstants;
+import com.aizuda.snailjob.common.core.util.JsonUtil;
+import com.example.snailjob.job.TestMapReduceJobExecutor.MonthMap.SubTask;
 import com.google.common.collect.Lists;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.Getter;
 import org.springframework.stereotype.Component;
 
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Objects;
+import java.util.Random;
+
 
 /**
+ * 以下是一个统计某电商公司商家的一年的营业额的计算过程
+ *
  * @author: opensnail
  * @date : 2024-06-13
  * @since : sj_1.1.0
@@ -19,14 +30,22 @@ public class TestMapReduceJobExecutor extends AbstractMapReduceExecutor {
 
     @Override
     public ExecuteResult doJobMapExecute(MapArgs mapArgs) {
-        if (mapArgs.getTaskName().equals(SystemConstants.MAP_ROOT)) {
+        MapEnum mapEnum = MapEnum.ofMap(mapArgs.getTaskName());
-            doMap(Lists.newArrayList(Lists.newArrayList(1, 2, 3), Lists.newArrayList(4, 5, 6)), "TWO_MAP");
+        if (Objects.nonNull(mapEnum)) {
-            return ExecuteResult.success();
+            Map map = mapEnum.getMap();
-        } else if (mapArgs.getTaskName().equals("TWO_MAP")) {
+            return doMap(map.map(mapArgs), mapEnum.name());
-            return ExecuteResult.success(mapArgs.getArgsStr());
-        } else {
-            return ExecuteResult.success();
         }
+
+        // 未找到map的任务，则说明当前需要进行处理
+        String mapResult = mapArgs.getMapResult();
+
+        // 获取最后一次map的信息.
+        SubTask subTask = JsonUtil.parseObject(mapResult, SubTask.class);
+        // 此处可以统计数据或者做其他的事情
+        // 模拟统计营业额
+        int turnover = new Random().nextInt(1000000);
+        return ExecuteResult.success(turnover);
+
     }
 
     @Override
@@ -38,4 +57,103 @@ public class TestMapReduceJobExecutor extends AbstractMapReduceExecutor {
     protected ExecuteResult doMergeReduceExecute(ReduceArgs reduceArgs) {
         return ExecuteResult.success(reduceArgs.getMapResult());
     }
+
+    @Getter
+    private enum MapEnum {
+        MAP_ROOT(new RootMap()),
+        MONTH_MAP(new MonthMap())
+        ;
+
+        private final Map map;
+
+        MapEnum(Map map) {
+            this.map = map;
+        }
+
+        public static MapEnum ofMap(String taskName) {
+            for (final MapEnum value : MapEnum.values()) {
+                if (value.name().equals(taskName)) {
+                    return value;
+                }
+            }
+
+            return null;
+        }
+
+    }
+
+    private static class RootMap implements Map  {
+
+        @Override
+        public List map(MapArgs args) {
+            // 第一层按照商家ID分片
+            // 假设总共有一百万商家 每个分片处理10万商家
+            List<List<Long>> ranges = doSharding(1L, 1000000L, 100000);
+            return ranges;
+        }
+    }
+
+    public static class MonthMap implements Map  {
+
+        @Override
+        public List map(MapArgs args) {
+
+            // 第二层按照月分片
+            // 4个季度
+            List<Long> lists = JsonUtil.parseList(args.getMapResult(), Long.class);
+            List<SubTask> list = new ArrayList<>();
+            for (final Long id : lists) {
+                for (int i = 1; i <= 4; i++) {
+                    list.add(new SubTask(id, i));
+                }
+            }
+
+            return list;
+        }
+
+        @Data
+        @AllArgsConstructor
+        public static class SubTask {
+            // 商家id
+            private Long id;
+
+            // 需要处理的月份
+            private Integer quarter;
+
+        }
+    }
+
+    interface Map{
+        List<Object> map(MapArgs args);
+    }
+
+    public static List<List<Long>> doSharding(Long min, Long max, int interval) {
+
+        if (max.equals(min)) {
+            return new ArrayList<>();
+        }
+
+        // 总数量
+        long total = max - min + 1;
+
+        // 计算分页总页数
+        Long totalPages = total / interval;
+        if (total % interval != 0) {
+            totalPages++;
+        }
+
+        List<List<Long>> partitions = new ArrayList<>();
+        for (Long index = 0L; index < totalPages; index++) {
+
+            // 计算起始点 因为是从min开始所以每次需要加上一个min
+            Long start = index * interval + min;
+
+            // 结算结束点 若最后一个 start + interval - 1 > max 取max
+            // 减一是保证 [start, end] 都是闭区间
+            Long end = Math.min(start + interval - 1, max);
+            partitions.add(Lists.newArrayList(start, end));
+        }
+
+        return partitions;
+    }
 }

src/main/java/com/example/snailjob/job/TestWorkflowAnnoJobExecutor.java

@@ -8,6 +8,8 @@ import com.aizuda.snailjob.common.log.SnailJobLog;
 import com.example.snailjob.po.FailOrderPo;
 import org.springframework.stereotype.Component;
 
+import java.util.Random;
+
 /**
  * @author www.byteblogs.com
  * @date 2023-09-28 22:54:07
@@ -18,11 +20,12 @@ import org.springframework.stereotype.Component;
 public class TestWorkflowAnnoJobExecutor {
 
     public ExecuteResult jobExecute(JobArgs jobArgs) throws InterruptedException {
-//        for (int i = 0; i < 30; i++) {
-//            SnailJobLog.REMOTE.info("任务执行开始. [{}]", i + "" + JsonUtil.toJsonString(jobArgs));
-//        }
         FailOrderPo failOrderPo = new FailOrderPo();
         failOrderPo.setOrderId("xiaowoniu");
+        // 测试上下文传递
+        int i = new Random().nextInt(1000);
+        jobArgs.appendContext("name" + i, "小蜗牛" + i);
+        jobArgs.appendContext("age", 18);
         return ExecuteResult.success(failOrderPo);
     }