Examples with PartitionNode org.apache.storm.trident.planner.PartitionNode used on opensource projects

Example 1 with PartitionNode

use of org.apache.storm.trident.planner.PartitionNode in project storm by apache.

the class TridentTopology method getOutputStreamBatchGroups.

private static Map<String, String> getOutputStreamBatchGroups(Group g, Map<Node, String> batchGroupMap) {
    Map<String, String> ret = new HashMap<>();
    Set<PartitionNode> externalGroupOutputs = externalGroupOutputs(g);
    for (PartitionNode n : externalGroupOutputs) {
        ret.put(n.streamId, batchGroupMap.get(n));
    }
    return ret;
}

Example 2 with PartitionNode

use of org.apache.storm.trident.planner.PartitionNode in project storm by apache.

the class TridentTopology method uniquedSubscriptions.

private static Collection<PartitionNode> uniquedSubscriptions(Set<PartitionNode> subscriptions) {
    Map<String, PartitionNode> ret = new HashMap<>();
    for (PartitionNode n : subscriptions) {
        PartitionNode curr = ret.get(n.streamId);
        if (curr != null && !curr.thriftGrouping.equals(n.thriftGrouping)) {
            throw new RuntimeException("Multiple subscriptions to the same stream with different groupings. Should be impossible since that is explicitly guarded against.");
        }
        ret.put(n.streamId, n);
    }
    return ret.values();
}

Example 3 with PartitionNode

use of org.apache.storm.trident.planner.PartitionNode in project storm by apache.

the class TridentTopology method build.

public StormTopology build() {
    DefaultDirectedGraph<Node, IndexedEdge> graph = (DefaultDirectedGraph) _graph.clone();
    completeDRPC(graph, _colocate, _gen);
    List<SpoutNode> spoutNodes = new ArrayList<>();
    // can be regular nodes (static state) or processor nodes
    Set<Node> boltNodes = new LinkedHashSet<>();
    for (Node n : graph.vertexSet()) {
        if (n instanceof SpoutNode) {
            spoutNodes.add((SpoutNode) n);
        } else if (!(n instanceof PartitionNode)) {
            boltNodes.add(n);
        }
    }
    Set<Group> initialGroups = new LinkedHashSet<>();
    for (List<Node> colocate : _colocate.values()) {
        Group g = new Group(graph, colocate);
        boltNodes.removeAll(colocate);
        initialGroups.add(g);
    }
    for (Node n : boltNodes) {
        initialGroups.add(new Group(graph, n));
    }
    GraphGrouper grouper = new GraphGrouper(graph, initialGroups);
    grouper.mergeFully();
    Collection<Group> mergedGroups = grouper.getAllGroups();
    // add identity partitions between groups
    for (IndexedEdge<Node> e : new HashSet<>(graph.edgeSet())) {
        if (!(e.source instanceof PartitionNode) && !(e.target instanceof PartitionNode)) {
            Group g1 = grouper.nodeGroup(e.source);
            Group g2 = grouper.nodeGroup(e.target);
            // g1 being null means the source is a spout node
            if (g1 == null && !(e.source instanceof SpoutNode))
                throw new RuntimeException("Planner exception: Null source group must indicate a spout node at this phase of planning");
            if (g1 == null || !g1.equals(g2)) {
                graph.removeEdge(e);
                PartitionNode pNode = makeIdentityPartition(e.source);
                graph.addVertex(pNode);
                graph.addEdge(e.source, pNode, new IndexedEdge(e.source, pNode, 0));
                graph.addEdge(pNode, e.target, new IndexedEdge(pNode, e.target, e.index));
            }
        }
    }
    // if one group subscribes to the same stream with same partitioning multiple times,
    // merge those together (otherwise can end up with many output streams created for that partitioning
    // if need to split into multiple output streams because of same input having different
    // partitioning to the group)
    // this is because can't currently merge splitting logic into a spout
    // not the most kosher algorithm here, since the grouper indexes are being trounced via the adding of nodes to random groups, but it 
    // works out
    List<Node> forNewGroups = new ArrayList<>();
    for (Group g : mergedGroups) {
        for (PartitionNode n : extraPartitionInputs(g)) {
            Node idNode = makeIdentityNode(n.allOutputFields);
            Node newPartitionNode = new PartitionNode(idNode.streamId, n.name, idNode.allOutputFields, n.thriftGrouping);
            Node parentNode = TridentUtils.getParent(graph, n);
            Set<IndexedEdge> outgoing = graph.outgoingEdgesOf(n);
            graph.removeVertex(n);
            graph.addVertex(idNode);
            graph.addVertex(newPartitionNode);
            addEdge(graph, parentNode, idNode, 0);
            addEdge(graph, idNode, newPartitionNode, 0);
            for (IndexedEdge e : outgoing) {
                addEdge(graph, newPartitionNode, e.target, e.index);
            }
            Group parentGroup = grouper.nodeGroup(parentNode);
            if (parentGroup == null) {
                forNewGroups.add(idNode);
            } else {
                parentGroup.nodes.add(idNode);
            }
        }
    }
    for (Node n : forNewGroups) {
        grouper.addGroup(new Group(graph, n));
    }
    // add in spouts as groups so we can get parallelisms
    for (Node n : spoutNodes) {
        grouper.addGroup(new Group(graph, n));
    }
    grouper.reindex();
    mergedGroups = grouper.getAllGroups();
    Map<Node, String> batchGroupMap = new HashMap<>();
    List<Set<Node>> connectedComponents = new ConnectivityInspector<>(graph).connectedSets();
    for (int i = 0; i < connectedComponents.size(); i++) {
        String groupId = "bg" + i;
        for (Node n : connectedComponents.get(i)) {
            batchGroupMap.put(n, groupId);
        }
    }
    //        System.out.println("GRAPH:");
    //        System.out.println(graph);
    Map<Group, Integer> parallelisms = getGroupParallelisms(graph, grouper, mergedGroups);
    TridentTopologyBuilder builder = new TridentTopologyBuilder();
    Map<Node, String> spoutIds = genSpoutIds(spoutNodes);
    Map<Group, String> boltIds = genBoltIds(mergedGroups);
    for (SpoutNode sn : spoutNodes) {
        Integer parallelism = parallelisms.get(grouper.nodeGroup(sn));
        Map<String, Number> spoutRes = new HashMap<>(_resourceDefaults);
        spoutRes.putAll(sn.getResources());
        Number onHeap = spoutRes.get(Config.TOPOLOGY_COMPONENT_RESOURCES_ONHEAP_MEMORY_MB);
        Number offHeap = spoutRes.get(Config.TOPOLOGY_COMPONENT_RESOURCES_OFFHEAP_MEMORY_MB);
        Number cpuLoad = spoutRes.get(Config.TOPOLOGY_COMPONENT_CPU_PCORE_PERCENT);
        SpoutDeclarer spoutDeclarer = null;
        if (sn.type == SpoutNode.SpoutType.DRPC) {
            spoutDeclarer = builder.setBatchPerTupleSpout(spoutIds.get(sn), sn.streamId, (IRichSpout) sn.spout, parallelism, batchGroupMap.get(sn));
        } else {
            ITridentSpout s;
            if (sn.spout instanceof IBatchSpout) {
                s = new BatchSpoutExecutor((IBatchSpout) sn.spout);
            } else if (sn.spout instanceof ITridentSpout) {
                s = (ITridentSpout) sn.spout;
            } else {
                throw new RuntimeException("Regular rich spouts not supported yet... try wrapping in a RichSpoutBatchExecutor");
            // TODO: handle regular rich spout without batches (need lots of updates to support this throughout)
            }
            spoutDeclarer = builder.setSpout(spoutIds.get(sn), sn.streamId, sn.txId, s, parallelism, batchGroupMap.get(sn));
        }
        if (onHeap != null) {
            if (offHeap != null) {
                spoutDeclarer.setMemoryLoad(onHeap, offHeap);
            } else {
                spoutDeclarer.setMemoryLoad(onHeap);
            }
        }
        if (cpuLoad != null) {
            spoutDeclarer.setCPULoad(cpuLoad);
        }
    }
    for (Group g : mergedGroups) {
        if (!isSpoutGroup(g)) {
            Integer p = parallelisms.get(g);
            Map<String, String> streamToGroup = getOutputStreamBatchGroups(g, batchGroupMap);
            Map<String, Number> groupRes = g.getResources(_resourceDefaults);
            Number onHeap = groupRes.get(Config.TOPOLOGY_COMPONENT_RESOURCES_ONHEAP_MEMORY_MB);
            Number offHeap = groupRes.get(Config.TOPOLOGY_COMPONENT_RESOURCES_OFFHEAP_MEMORY_MB);
            Number cpuLoad = groupRes.get(Config.TOPOLOGY_COMPONENT_CPU_PCORE_PERCENT);
            BoltDeclarer d = builder.setBolt(boltIds.get(g), new SubtopologyBolt(graph, g.nodes, batchGroupMap), p, committerBatches(g, batchGroupMap), streamToGroup);
            if (onHeap != null) {
                if (offHeap != null) {
                    d.setMemoryLoad(onHeap, offHeap);
                } else {
                    d.setMemoryLoad(onHeap);
                }
            }
            if (cpuLoad != null) {
                d.setCPULoad(cpuLoad);
            }
            Collection<PartitionNode> inputs = uniquedSubscriptions(externalGroupInputs(g));
            for (PartitionNode n : inputs) {
                Node parent = TridentUtils.getParent(graph, n);
                String componentId = parent instanceof SpoutNode ? spoutIds.get(parent) : boltIds.get(grouper.nodeGroup(parent));
                d.grouping(new GlobalStreamId(componentId, n.streamId), n.thriftGrouping);
            }
        }
    }
    HashMap<String, Number> combinedMasterCoordResources = new HashMap<String, Number>(_resourceDefaults);
    combinedMasterCoordResources.putAll(_masterCoordResources);
    return builder.buildTopology(combinedMasterCoordResources);
}

Example 4 with PartitionNode

use of org.apache.storm.trident.planner.PartitionNode in project storm by apache.

the class TridentTopology method getGroupParallelisms.

private static Map<Group, Integer> getGroupParallelisms(DirectedGraph<Node, IndexedEdge> graph, GraphGrouper grouper, Collection<Group> groups) {
    UndirectedGraph<Group, Object> equivs = new Pseudograph<>(Object.class);
    for (Group g : groups) {
        equivs.addVertex(g);
    }
    for (Group g : groups) {
        for (PartitionNode n : externalGroupInputs(g)) {
            if (isIdentityPartition(n)) {
                Node parent = TridentUtils.getParent(graph, n);
                Group parentGroup = grouper.nodeGroup(parent);
                if (parentGroup != null && !parentGroup.equals(g)) {
                    equivs.addEdge(parentGroup, g);
                }
            }
        }
    }
    Map<Group, Integer> ret = new HashMap<>();
    List<Set<Group>> equivGroups = new ConnectivityInspector<>(equivs).connectedSets();
    for (Set<Group> equivGroup : equivGroups) {
        Integer fixedP = getFixedParallelism(equivGroup);
        Integer maxP = getMaxParallelism(equivGroup);
        if (fixedP != null && maxP != null && maxP < fixedP) {
            throw new RuntimeException("Parallelism is fixed to " + fixedP + " but max parallelism is less than that: " + maxP);
        }
        Integer p = 1;
        for (Group g : equivGroup) {
            for (Node n : g.nodes) {
                if (n.parallelismHint != null) {
                    p = Math.max(p, n.parallelismHint);
                }
            }
        }
        if (maxP != null)
            p = Math.min(maxP, p);
        if (fixedP != null)
            p = fixedP;
        for (Group g : equivGroup) {
            ret.put(g, p);
        }
    }
    return ret;
}

Example 5 with PartitionNode

use of org.apache.storm.trident.planner.PartitionNode in project storm by apache.

the class TridentTopology method extraPartitionInputs.

private static List<PartitionNode> extraPartitionInputs(Group g) {
    List<PartitionNode> ret = new ArrayList<>();
    Set<PartitionNode> inputs = externalGroupInputs(g);
    Map<String, List<PartitionNode>> grouped = new HashMap<>();
    for (PartitionNode n : inputs) {
        if (!grouped.containsKey(n.streamId)) {
            grouped.put(n.streamId, new ArrayList());
        }
        grouped.get(n.streamId).add(n);
    }
    for (List<PartitionNode> group : grouped.values()) {
        PartitionNode anchor = group.get(0);
        for (int i = 1; i < group.size(); i++) {
            PartitionNode n = group.get(i);
            if (!n.thriftGrouping.equals(anchor.thriftGrouping)) {
                ret.add(n);
            }
        }
    }
    return ret;
}