聊聊storm的CustomStreamGrouping
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本文主要研究一下storm的CustomStreamGrouping
CustomStreamGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/CustomStreamGrouping.java
public interface CustomStreamGrouping extends Serializable { /** * Tells the stream grouping at runtime the tasks in the target bolt. This information should be used in chooseTasks to determine the * target tasks. * * It also tells the grouping the metadata on the stream this grouping will be used on. */ void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks); /** * This function implements a custom stream grouping. It takes in as input the number of tasks in the target bolt in prepare and returns * the tasks to send the tuples to. * * @param values the values to group on */ List<Integer> chooseTasks(int taskId, List<Object> values); }
- 这里定义了prepare以及chooseTasks方法
- GrouperFactory里头定义了FieldsGrouper、GlobalGrouper、NoneGrouper、AllGrouper、BasicLoadAwareCustomStreamGrouping
- 另外org.apache.storm.grouping包里头也定义了ShuffleGrouping、PartialKeyGrouping、LoadAwareShuffleGrouping
FieldsGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class FieldsGrouper implements CustomStreamGrouping { private Fields outFields; private List<List<Integer>> targetTasks; private Fields groupFields; private int numTasks; public FieldsGrouper(Fields outFields, Grouping thriftGrouping) { this.outFields = outFields; this.groupFields = new Fields(Thrift.fieldGrouping(thriftGrouping)); } @Override public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) { this.targetTasks = new ArrayList<List<Integer>>(); for (Integer targetTask : targetTasks) { this.targetTasks.add(Collections.singletonList(targetTask)); } this.numTasks = targetTasks.size(); } @Override public List<Integer> chooseTasks(int taskId, List<Object> values) { int targetTaskIndex = TupleUtils.chooseTaskIndex(outFields.select(groupFields, values), numTasks); return targetTasks.get(targetTaskIndex); } }
- 对选中fields的values通过TupleUtils.chooseTaskIndex选择task下标;chooseTaskIndex主要是采用Arrays.deepHashCode取哈希值然后对numTask向下取模
GlobalGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class GlobalGrouper implements CustomStreamGrouping { private List<Integer> targetTasks; public GlobalGrouper() { } @Override public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) { this.targetTasks = targetTasks; } @Override public List<Integer> chooseTasks(int taskId, List<Object> values) { if (targetTasks.isEmpty()) { return null; } // It's possible for target to have multiple tasks if it reads multiple sources return Collections.singletonList(targetTasks.get(0)); } }
- 这里固定取第一个task,即targetTasks.get(0)
NoneGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class NoneGrouper implements CustomStreamGrouping { private final Random random; private List<Integer> targetTasks; private int numTasks; public NoneGrouper() { random = new Random(); } @Override public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) { this.targetTasks = targetTasks; this.numTasks = targetTasks.size(); } @Override public List<Integer> chooseTasks(int taskId, List<Object> values) { int index = random.nextInt(numTasks); return Collections.singletonList(targetTasks.get(index)); } }
- 这里通过random.nextInt(numTasks)随机取task
AllGrouper
storm-2.0.0/storm-client/src/jvm/org/apache/storm/daemon/GrouperFactory.java
public static class AllGrouper implements CustomStreamGrouping { private List<Integer> targetTasks; @Override public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) { this.targetTasks = targetTasks; } @Override public List<Integer> chooseTasks(int taskId, List<Object> values) { return targetTasks; } }
- 这里返回所有的targetTasks
ShuffleGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/ShuffleGrouping.java
public class ShuffleGrouping implements CustomStreamGrouping, Serializable { private ArrayList<List<Integer>> choices; private AtomicInteger current; @Override public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) { choices = new ArrayList<List<Integer>>(targetTasks.size()); for (Integer i : targetTasks) { choices.add(Arrays.asList(i)); } current = new AtomicInteger(0); Collections.shuffle(choices, new Random()); } @Override public List<Integer> chooseTasks(int taskId, List<Object> values) { int rightNow; int size = choices.size(); while (true) { rightNow = current.incrementAndGet(); if (rightNow < size) { return choices.get(rightNow); } else if (rightNow == size) { current.set(0); return choices.get(0); } } // race condition with another thread, and we lost. try again } }
- 这里在prepare的时候对ArrayList<List<Integer>> choices进行随机化
- 采用current.incrementAndGet()实现round robbin的效果,超过size的时候重置返回第一个,没有超过则返回incr后的index的值
PartialKeyGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/PartialKeyGrouping.java
public class PartialKeyGrouping implements CustomStreamGrouping, Serializable { private static final long serialVersionUID = -1672360572274911808L; private List<Integer> targetTasks; private Fields fields = null; private Fields outFields = null; private AssignmentCreator assignmentCreator; private TargetSelector targetSelector; public PartialKeyGrouping() { this(null); } public PartialKeyGrouping(Fields fields) { this(fields, new RandomTwoTaskAssignmentCreator(), new BalancedTargetSelector()); } public PartialKeyGrouping(Fields fields, AssignmentCreator assignmentCreator) { this(fields, assignmentCreator, new BalancedTargetSelector()); } public PartialKeyGrouping(Fields fields, AssignmentCreator assignmentCreator, TargetSelector targetSelector) { this.fields = fields; this.assignmentCreator = assignmentCreator; this.targetSelector = targetSelector; } @Override public void prepare(WorkerTopologyContext context, GlobalStreamId stream, List<Integer> targetTasks) { this.targetTasks = targetTasks; if (this.fields != null) { this.outFields = context.getComponentOutputFields(stream); } } @Override public List<Integer> chooseTasks(int taskId, List<Object> values) { List<Integer> boltIds = new ArrayList<>(1); if (values.size() > 0) { final byte[] rawKeyBytes = getKeyBytes(values); final int[] taskAssignmentForKey = assignmentCreator.createAssignment(this.targetTasks, rawKeyBytes); final int selectedTask = targetSelector.chooseTask(taskAssignmentForKey); boltIds.add(selectedTask); } return boltIds; } //...... }
- 这里通过RandomTwoTaskAssignmentCreator来选中两个taskId,然后选择使用次数小的那个
LoadAwareCustomStreamGrouping
storm-2.0.0/storm-client/src/jvm/org/apache/storm/grouping/LoadAwareCustomStreamGrouping.java
public interface LoadAwareCustomStreamGrouping extends CustomStreamGrouping { void refreshLoad(LoadMapping loadMapping); }
- 继承了CustomStreamGrouping接口,然后新定义了refreshLoad方法用于刷新负载,这里的负载主要是executor的receiveQueue的负载(
qMetrics.population() / qMetrics.capacity()
) - LoadAwareCustomStreamGrouping有几个实现类,有BasicLoadAwareCustomStreamGrouping以及LoadAwareShuffleGrouping
小结
- storm的CustomStreamGrouping接口定义了chooseTasks方法,用于选择tasks来处理tuples
- ShuffleGrouping类似round robbin,FieldsGrouper则根据所选字段值采用Arrays.deepHashCode取哈希值然后对numTask向下取模,GlobalGrouper返回index为0的taskId,NoneGrouper则随机返回,AllGrouper不做过滤返回所有taskId,PartialKeyGrouping则使用key的哈希值作为seed,采用Random函数来计算两个taskId的下标,然后选择使用次数少的那个task。
- LoadAware的grouping有BasicLoadAwareCustomStreamGrouping以及LoadAwareShuffleGrouping,他们都实现了LoadAwareCustomStreamGrouping接口,该接口定义了refreshLoad方法,用于动态刷新负载,这里的负载主要是executor的receiveQueue的负载(
qMetrics.population() / qMetrics.capacity()
)