前往小程序,Get更优阅读体验!
立即前往
首页
学习
活动
专区
工具
TVP
发布
社区首页 >专栏 >聊聊storm的AggregateProcessor的execute及finishBatch方法

聊聊storm的AggregateProcessor的execute及finishBatch方法

作者头像
code4it
发布2018-12-13 18:04:44
6230
发布2018-12-13 18:04:44
举报

本文主要研究一下storm的AggregateProcessor的execute及finishBatch方法

实例

        TridentTopology topology = new TridentTopology();
        topology.newStream("spout1", spout)
                .groupBy(new Fields("user"))
                .aggregate(new Fields("user","score"),new UserCountAggregator(),new Fields("val"))
                .toStream()
                .parallelismHint(1)
                .each(new Fields("val"),new PrintEachFunc(),new Fields());

TridentBoltExecutor

storm-core-1.2.2-sources.jar!/org/apache/storm/trident/topology/TridentBoltExecutor.java

    private void checkFinish(TrackedBatch tracked, Tuple tuple, TupleType type) {
        if(tracked.failed) {
            failBatch(tracked);
            _collector.fail(tuple);
            return;
        }
        CoordCondition cond = tracked.condition;
        boolean delayed = tracked.delayedAck==null &&
                              (cond.commitStream!=null && type==TupleType.COMMIT
                               || cond.commitStream==null);
        if(delayed) {
            tracked.delayedAck = tuple;
        }
        boolean failed = false;
        if(tracked.receivedCommit && tracked.reportedTasks == cond.expectedTaskReports) {
            if(tracked.receivedTuples == tracked.expectedTupleCount) {
                finishBatch(tracked, tuple);                
            } else {
                //TODO: add logging that not all tuples were received
                failBatch(tracked);
                _collector.fail(tuple);
                failed = true;
            }
        }
        
        if(!delayed && !failed) {
            _collector.ack(tuple);
        }
        
    }

   private boolean finishBatch(TrackedBatch tracked, Tuple finishTuple) {
        boolean success = true;
        try {
            _bolt.finishBatch(tracked.info);
            String stream = COORD_STREAM(tracked.info.batchGroup);
            for(Integer task: tracked.condition.targetTasks) {
                _collector.emitDirect(task, stream, finishTuple, new Values(tracked.info.batchId, Utils.get(tracked.taskEmittedTuples, task, 0)));
            }
            if(tracked.delayedAck!=null) {
                _collector.ack(tracked.delayedAck);
                tracked.delayedAck = null;
            }
        } catch(FailedException e) {
            failBatch(tracked, e);
            success = false;
        }
        _batches.remove(tracked.info.batchId.getId());
        return success;
    }

    public static class TrackedBatch {
        int attemptId;
        BatchInfo info;
        CoordCondition condition;
        int reportedTasks = 0;
        int expectedTupleCount = 0;
        int receivedTuples = 0;
        Map<Integer, Integer> taskEmittedTuples = new HashMap<>();
        //......
    }
  • 用户的spout以及groupBy操作最后都是被包装为TridentBoltExecutor,而groupBy的TridentBoltExecutor则是包装了SubtopologyBolt
  • TridentBoltExecutor在checkFinish方法里头会调用finishBatch操作(另外接收到REGULAR类型的tuple时,在tracked.condition.expectedTaskReports==0的时候也会调用finishBatch操作,对于spout来说tracked.condition.expectedTaskReports为0,因为它是数据源,所以不用接收COORD_STREAM更新expectedTaskReports以及expectedTupleCount),而该操作会往COORD_STREAM这个stream发送new Values(tracked.info.batchId, Utils.get(tracked.taskEmittedTuples, task, 0)),也就是new Fields("id", "count"),即batchId以及发送给目的task的tuple数量,告知下游的它给task发送了多少tuple(taskEmittedTuples数据在CoordinatedOutputCollector的emit及emitDirect方法里头维护)
  • 下游也是TridentBoltExecutor,它在接收到COORD_STREAM发来的数据时,更新expectedTupleCount,而每个TridentBoltExecutor在checkFinish方法里头会判断,如果receivedTuples等于expectedTupleCount则表示完整接收完上游发过来的tuple,然后触发finishBatch操作

SubtopologyBolt

storm-core-1.2.2-sources.jar!/org/apache/storm/trident/planner/SubtopologyBolt.java

public class SubtopologyBolt implements ITridentBatchBolt {
    //......
    @Override
    public void execute(BatchInfo batchInfo, Tuple tuple) {
        String sourceStream = tuple.getSourceStreamId();
        InitialReceiver ir = _roots.get(sourceStream);
        if(ir==null) {
            throw new RuntimeException("Received unexpected tuple " + tuple.toString());
        }
        ir.receive((ProcessorContext) batchInfo.state, tuple);
    }

    @Override
    public void finishBatch(BatchInfo batchInfo) {
        for(TridentProcessor p: _myTopologicallyOrdered.get(batchInfo.batchGroup)) {
            p.finishBatch((ProcessorContext) batchInfo.state);
        }
    }

    @Override
    public Object initBatchState(String batchGroup, Object batchId) {
        ProcessorContext ret = new ProcessorContext(batchId, new Object[_nodes.size()]);
        for(TridentProcessor p: _myTopologicallyOrdered.get(batchGroup)) {
            p.startBatch(ret);
        }
        return ret;
    }

    @Override
    public void cleanup() {
        for(String bg: _myTopologicallyOrdered.keySet()) {
            for(TridentProcessor p: _myTopologicallyOrdered.get(bg)) {
                p.cleanup();
            }   
        }
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        for(Node n: _nodes) {
            declarer.declareStream(n.streamId, TridentUtils.fieldsConcat(new Fields("$batchId"), n.allOutputFields));
        }        
    }

    @Override
    public Map<String, Object> getComponentConfiguration() {
        return null;
    }

    protected static class InitialReceiver {
        List<TridentProcessor> _receivers = new ArrayList<>();
        RootFactory _factory;
        ProjectionFactory _project;
        String _stream;
        
        public InitialReceiver(String stream, Fields allFields) {
            // TODO: don't want to project for non-batch bolts...???
            // how to distinguish "batch" streams from non-batch streams?
            _stream = stream;
            _factory = new RootFactory(allFields);
            List<String> projected = new ArrayList<>(allFields.toList());
            projected.remove(0);
            _project = new ProjectionFactory(_factory, new Fields(projected));
        }
        
        public void receive(ProcessorContext context, Tuple tuple) {
            TridentTuple t = _project.create(_factory.create(tuple));
            for(TridentProcessor r: _receivers) {
                r.execute(context, _stream, t);
            }            
        }
        
        public void addReceiver(TridentProcessor p) {
            _receivers.add(p);
        }
        
        public Factory getOutputFactory() {
            return _project;
        }
    }
}
  • groupBy操作被包装为一个SubtopologyBolt,它的outputFields的第一个field为$batchId
  • execute方法会获取对应的InitialReceiver,然后调用receive方法;InitialReceiver的receive方法调用_receivers的execute,这里的receive为AggregateProcessor
  • finishBatch方法挨个调用_myTopologicallyOrdered.get(batchInfo.batchGroup)返回的TridentProcessor的finishBatch方法,这里就是AggregateProcessor及EachProcessor;BatchInfo,包含batchId、processorContext及batchGroup信息,这里将processorContext(包含TransactionAttempt类型的batchId以及Object数组state,state里头包含GroupCollector、aggregate累加结果等)传递给finishBatch方法

AggregateProcessor

storm-core-1.2.2-sources.jar!/org/apache/storm/trident/planner/processor/AggregateProcessor.java

public class AggregateProcessor implements TridentProcessor {
    Aggregator _agg;
    TridentContext _context;
    FreshCollector _collector;
    Fields _inputFields;
    ProjectionFactory _projection;

    public AggregateProcessor(Fields inputFields, Aggregator agg) {
        _agg = agg;
        _inputFields = inputFields;
    }
    
    @Override
    public void prepare(Map conf, TopologyContext context, TridentContext tridentContext) {
        List<Factory> parents = tridentContext.getParentTupleFactories();
        if(parents.size()!=1) {
            throw new RuntimeException("Aggregate operation can only have one parent");
        }
        _context = tridentContext;
        _collector = new FreshCollector(tridentContext);
        _projection = new ProjectionFactory(parents.get(0), _inputFields);
        _agg.prepare(conf, new TridentOperationContext(context, _projection));
    }

    @Override
    public void cleanup() {
        _agg.cleanup();
    }

    @Override
    public void startBatch(ProcessorContext processorContext) {
        _collector.setContext(processorContext);
        processorContext.state[_context.getStateIndex()] = _agg.init(processorContext.batchId, _collector);
    }    

    @Override
    public void execute(ProcessorContext processorContext, String streamId, TridentTuple tuple) {
        _collector.setContext(processorContext);
        _agg.aggregate(processorContext.state[_context.getStateIndex()], _projection.create(tuple), _collector);
    }
    
    @Override
    public void finishBatch(ProcessorContext processorContext) {
        _collector.setContext(processorContext);
        _agg.complete(processorContext.state[_context.getStateIndex()], _collector);
    }
 
    @Override
    public Factory getOutputFactory() {
        return _collector.getOutputFactory();
    }
}
  • AggregateProcessor在prepare创建了FreshCollector以及ProjectionFactory
  • 对于GroupBy操作来说,这里的agg为GroupedAggregator,agg.prepare传递的context为TridentOperationContext
  • finishBatch方法这里调用agg.complete方法,传入的arr数组,第一个元素为GroupCollector,第二元素为aggregator的累加值;传入的collector为FreshCollector

GroupedAggregator

storm-core-1.2.2-sources.jar!/org/apache/storm/trident/operation/impl/GroupedAggregator.java

public class GroupedAggregator implements Aggregator<Object[]> {
    ProjectionFactory _groupFactory;
    ProjectionFactory _inputFactory;
    Aggregator _agg;
    ComboList.Factory _fact;
    Fields _inFields;
    Fields _groupFields;
    
    public GroupedAggregator(Aggregator agg, Fields group, Fields input, int outSize) {
        _groupFields = group;
        _inFields = input;
        _agg = agg;
        int[] sizes = new int[2];
        sizes[0] = _groupFields.size();
        sizes[1] = outSize;
        _fact = new ComboList.Factory(sizes);
    }
    
    @Override
    public void prepare(Map conf, TridentOperationContext context) {
        _inputFactory = context.makeProjectionFactory(_inFields);
        _groupFactory = context.makeProjectionFactory(_groupFields);
        _agg.prepare(conf, new TridentOperationContext(context, _inputFactory));
    }

    @Override
    public Object[] init(Object batchId, TridentCollector collector) {
        return new Object[] {new GroupCollector(collector, _fact), new HashMap(), batchId};
    }

    @Override
    public void aggregate(Object[] arr, TridentTuple tuple, TridentCollector collector) {
        GroupCollector groupColl = (GroupCollector) arr[0];
        Map<List, Object> val = (Map) arr[1];
        TridentTuple group = _groupFactory.create((TridentTupleView) tuple);
        TridentTuple input = _inputFactory.create((TridentTupleView) tuple);
        Object curr;
        if(!val.containsKey(group)) {
            curr = _agg.init(arr[2], groupColl);
            val.put((List) group, curr);
        } else {
            curr = val.get(group);
        }
        groupColl.currGroup = group;
        _agg.aggregate(curr, input, groupColl);
        
    }

    @Override
    public void complete(Object[] arr, TridentCollector collector) {
        Map<List, Object> val = (Map) arr[1];        
        GroupCollector groupColl = (GroupCollector) arr[0];
        for(Entry<List, Object> e: val.entrySet()) {
            groupColl.currGroup = e.getKey();
            _agg.complete(e.getValue(), groupColl);
        }
    }

    @Override
    public void cleanup() {
        _agg.cleanup();
    }
    
}
  • aggregate方法的arr[0]为GroupCollector;arr[1]为map,key为group字段的TridentTupleView,value为_agg的init返回值用于累加;arr[2]为TransactionAttempt
  • agg这里为ChainedAggregatorImpl,aggregate首先获取tuple的group字段以及输入的tuple,然后判断arr[1]是否有该group的值,没有就调用agg的init初始化一个并添加到map
  • aggregate方法最后调用_agg.aggregate进行累加

ChainedAggregatorImpl

storm-core-1.2.2-sources.jar!/org/apache/storm/trident/operation/impl/ChainedAggregatorImpl.java

public class ChainedAggregatorImpl implements Aggregator<ChainedResult> {
    Aggregator[] _aggs;
    ProjectionFactory[] _inputFactories;
    ComboList.Factory _fact;
    Fields[] _inputFields;
    
    
    
    public ChainedAggregatorImpl(Aggregator[] aggs, Fields[] inputFields, ComboList.Factory fact) {
        _aggs = aggs;
        _inputFields = inputFields;
        _fact = fact;
        if(_aggs.length!=_inputFields.length) {
            throw new IllegalArgumentException("Require input fields for each aggregator");
        }
    }
    
    public void prepare(Map conf, TridentOperationContext context) {
        _inputFactories = new ProjectionFactory[_inputFields.length];
        for(int i=0; i<_inputFields.length; i++) {
            _inputFactories[i] = context.makeProjectionFactory(_inputFields[i]);
            _aggs[i].prepare(conf, new TridentOperationContext(context, _inputFactories[i]));
        }
    }
    
    public ChainedResult init(Object batchId, TridentCollector collector) {
        ChainedResult initted = new ChainedResult(collector, _aggs.length);
        for(int i=0; i<_aggs.length; i++) {
            initted.objs[i] = _aggs[i].init(batchId, initted.collectors[i]);
        }
        return initted;
    }
    
    public void aggregate(ChainedResult val, TridentTuple tuple, TridentCollector collector) {
        val.setFollowThroughCollector(collector);
        for(int i=0; i<_aggs.length; i++) {
            TridentTuple projected = _inputFactories[i].create((TridentTupleView) tuple);
            _aggs[i].aggregate(val.objs[i], projected, val.collectors[i]);
        }
    }
    
    public void complete(ChainedResult val, TridentCollector collector) {
        val.setFollowThroughCollector(collector);
        for(int i=0; i<_aggs.length; i++) {
            _aggs[i].complete(val.objs[i], val.collectors[i]);
        }
        if(_aggs.length > 1) { // otherwise, tuples were emitted directly
            int[] indices = new int[val.collectors.length];
            for(int i=0; i<indices.length; i++) {
                indices[i] = 0;
            }
            boolean keepGoing = true;
            //emit cross-join of all emitted tuples
            while(keepGoing) {
                List[] combined = new List[_aggs.length];
                for(int i=0; i< _aggs.length; i++) {
                    CaptureCollector capturer = (CaptureCollector) val.collectors[i];
                    combined[i] = capturer.captured.get(indices[i]);
                }
                collector.emit(_fact.create(combined));
                keepGoing = increment(val.collectors, indices, indices.length - 1);
            }
        }
    }
    
    //return false if can't increment anymore
    private boolean increment(TridentCollector[] lengths, int[] indices, int j) {
        if(j==-1) return false;
        indices[j]++;
        CaptureCollector capturer = (CaptureCollector) lengths[j];
        if(indices[j] >= capturer.captured.size()) {
            indices[j] = 0;
            return increment(lengths, indices, j-1);
        }
        return true;
    }
    
    public void cleanup() {
       for(Aggregator a: _aggs) {
           a.cleanup();
       } 
    } 
}
  • init方法返回的是ChainedResult,它的objs字段存放每个_aggs对应的init结果
  • 这里的_agg如果是Aggregator类型,则为用户在groupBy之后aggregate方法传入的aggregator;如果是CombinerAggregator类型,它会被CombinerAggregatorCombineImpl包装一下
  • ChainedAggregatorImpl的complete方法,aggs挨个调用complete,传入的第一个参数为val.objs[i],即每个agg对应的累加值

小结

  • groupBy被包装为一个SubtopologyBolt,它的execute方法会触发InitialReceiver的receive方法,而receive方法会触发receivers的execute方法,第一个receivers为AggregateProcessor
  • AggregateProcessor包装了GroupedAggregator,而GroupedAggregator包装了ChainedAggregatorImpl,而ChainedAggregatorImpl包装了Aggregator数组,本实例只有一个,即在groupBy之后aggregate方法传入的aggregator
  • TridentBoltExecutor会从coordinator那里接收COORD_STREAM_PREFIX发送过来的应该接收到的tuple的count,然后更新expectedTupleCount,然后进行checkFinish判断,当receivedTuples(每次接收到spout的batch的一个tuple就更新该值)等于expectedTupleCount的时候,会触发finishBatch操作,该操作会调用SubtopologyBolt.finishBatch,进而调用AggregateProcessor.finishBatch,进而调用GroupedAggregator.complete,进而调用ChainedAggregatorImpl.complete,进而调用用户的aggregator的complete
  • 对于包装了TridentSpoutExecutor的TridentBoltExecutor来说,它的tracked.condition.expectedTaskReports为0,因为它是数据源,所以不用接收COORD_STREAM更新expectedTaskReports以及expectedTupleCount;当它在execute方法接收到MasterBatchCoordinator的MasterBatchCoordinator.BATCH_STREAM_ID($batch)发来的tuple的时候,调用TridentSpoutExecutor的execute方法,之后就由于tracked.condition.expectedTaskReports==0(本实例两个TridentBoltExecutor的TrackedBatch的condition.commitStream为null,因而receivedCommit为true),就立即调用finishBatch(里头会调用TridentSpoutExecutor的finishBatch方法,之后通过COORD_STREAM给下游TridentBoltExecutor的task发送batchId及taskEmittedTuples数量;而对于下游TridentBoltExecutor它的expectedTaskReports不为0,则需要在收到COORD_STREAM的tuple的时候才能checkFinish,判断是否可以finishBatch)
  • TridentSpoutExecutor的execute会调用emitter(最后调用用户的spout)发射一个batch;而finishBatch方法目前为空,没有做任何操作;也就是说对于包装了TridentSpoutExecutor的TridentBoltExecutor来说,它接收到发射一个batch的指令之后,调用完TridentSpoutExecutor.execute通过emitter发射一个batch,就立马执行finishBatch操作(发射[id,count]给下游的TridentBoltExecutor,下游TridentBoltExecutor在接收到[id,count]数据时更新expectedTupleCount,然后进行checkFinish判断,如果receivedTuples等于expectedTupleCount,就触发finishBatch操作,进而触发AggregateProcessor的finishBatch操作)

doc

  • Windowing Support in Core Storm
  • 聊聊storm TridentTopology的构建
  • 聊聊storm trident的coordinator
本文参与 腾讯云自媒体分享计划,分享自微信公众号。
原始发表:2018-11-15,如有侵权请联系 cloudcommunity@tencent.com 删除

本文分享自 码匠的流水账 微信公众号,前往查看

如有侵权,请联系 cloudcommunity@tencent.com 删除。

本文参与 腾讯云自媒体分享计划  ,欢迎热爱写作的你一起参与!

评论
登录后参与评论
0 条评论
热度
最新
推荐阅读
目录
  • 实例
  • TridentBoltExecutor
  • SubtopologyBolt
  • AggregateProcessor
  • GroupedAggregator
  • ChainedAggregatorImpl
  • 小结
  • doc
领券
问题归档专栏文章快讯文章归档关键词归档开发者手册归档开发者手册 Section 归档