我們知道，當我們對es發起search請求或其他操作時，往往都是隨機選擇一個coordinator發起請求。而這請求，可能是該節點能處理，也可能是該節點不能處理的，也可能是需要多節點共同處理的，可以說是情況比較複雜。
所以，coordinator的重要工作是，做請求分發與結果收集。那麼，如何高效能和安全準確地實現這一功能則至關重要。而這，也許諸君各有思路，孰優孰劣不訪一起來探討探討！
1. 請求分發的簡單思路
我們這裡所說的請求分發，一般是針對多個網路節點而言的。那麼，如何將請求發往多節點，並在最終將結果合併起來呢？
害，無腦的先來一個。同步請求各節點，當第一個節點響應後，再向第二個節點發起請求，以此類推，直到所有節點請求完成，然後再將結果聚合起來。就完成了需求了，不費吹灰之力。簡單不？
無腦處理自有無腦處理的缺點。依次請求各節點，無法很好利用系統的分散式特點，變並行為序列了，好不厲害。另外，對於當前請求，當其未處理完成這所有節點的分發收集工作時，當前執行緒將會一直被佔用。從而，下游請求將無法再接入，從而將你了併發能力，使其與執行緒池大小同日而語了。這可不好。
我們依次想辦法優化下。
首先，我們可以將序列分發請求變成並行分發，即可以使用多執行緒，向多節點發起請求，當某執行緒處理完成時，就返回結果。使用類似於CountDownLatch的同步工具，保證所有節點都處理完成後，再由外單主執行緒進行結果合併操作。
以上優化，看起來不錯，避免了同步的效能問題。但是，當有某個節點響應非常慢時，它將阻塞後續節點的工作，從而使整個請求變慢，從而同樣變成執行緒池的大小即是併發能力的瓶頸。可以說，治標不治本。
再來，繼續優化。我們可以釋放掉主執行緒的持有，讓每個分發執行緒處理完成當前任務時，都去檢查任務佇列，是否已完成。如果未完成則忽略，如果已完成，則啟動合併任務。
看起來不錯，已經有完全併發樣子了。但還能不能再優化？各節點的分發，同樣是同步請求，雖然處理簡單，但在這server響應期間，該執行緒仍是無法被使用的，如果類似請求過多，則必然是不小的消耗。如果能將單節點的請求，能夠做到非同步處理，那樣豈不完美？但這恐怕不好做吧！不過，終歸是一個不錯的想法了。
2. es中search的多節點分發收集
我們以search的分發收集為出發點，觀看es如何辦成這件。原因是search在es中最為普遍與經典，雖說不得每個地方實現都一樣，但至少參考意義還是有的。故以search為切入點。search的框架工作流程，我們之前已經研究過，本節就直接以核心開始講解，它是在 TransportSearchAction.executeRequest() 中的。
// org.elasticsearch.action.search.TransportSearchAction#executeRequest private void executeRequest(Task task, SearchRequest searchRequest, SearchAsyncActionProvider searchAsyncActionProvider, ActionListener<SearchResponse> listener) { final long relativeStartNanos = System.nanoTime(); final SearchTimeProvider timeProvider = new SearchTimeProvider(searchRequest.getOrCreateAbsoluteStartMillis(), relativeStartNanos, System::nanoTime); ActionListener<SearchSourceBuilder> rewriteListener = ActionListener.wrap(source -> { if (source != searchRequest.source()) { // only set it if it changed - we don't allow null values to be set but it might be already null. this way we catch // situations when source is rewritten to null due to a bug searchRequest.source(source); } final ClusterState clusterState = clusterService.state(); final SearchContextId searchContext; final Map<String, OriginalIndices> remoteClusterIndices; if (searchRequest.pointInTimeBuilder() != null) { searchContext = SearchContextId.decode(namedWriteableRegistry, searchRequest.pointInTimeBuilder().getId()); remoteClusterIndices = getIndicesFromSearchContexts(searchContext, searchRequest.indicesOptions()); } else { searchContext = null; remoteClusterIndices = remoteClusterService.groupIndices(searchRequest.indicesOptions(), searchRequest.indices(), idx -> indexNameExpressionResolver.hasIndexAbstraction(idx, clusterState)); } OriginalIndices localIndices = remoteClusterIndices.remove(RemoteClusterAware.LOCAL_CLUSTER_GROUP_KEY); if (remoteClusterIndices.isEmpty()) { executeLocalSearch( task, timeProvider, searchRequest, localIndices, clusterState, listener, searchContext, searchAsyncActionProvider); } else { // 多節點資料請求 if (shouldMinimizeRoundtrips(searchRequest)) { // 通過 parentTaskId 關聯所有子任務 final TaskId parentTaskId = task.taskInfo(clusterService.localNode().getId(), false).getTaskId(); ccsRemoteReduce(parentTaskId, searchRequest, localIndices, remoteClusterIndices, timeProvider, searchService.aggReduceContextBuilder(searchRequest), remoteClusterService, threadPool, listener, (r, l) -> executeLocalSearch( task, timeProvider, r, localIndices, clusterState, l, searchContext, searchAsyncActionProvider)); } else { AtomicInteger skippedClusters = new AtomicInteger(0); // 直接分發多shard請求到各節點 collectSearchShards(searchRequest.indicesOptions(), searchRequest.preference(), searchRequest.routing(), skippedClusters, remoteClusterIndices, remoteClusterService, threadPool, ActionListener.wrap( searchShardsResponses -> { // 當所有節點都響應後，再做後續邏輯處理，即此處的後置監聽 final BiFunction<String, String, DiscoveryNode> clusterNodeLookup = getRemoteClusterNodeLookup(searchShardsResponses); final Map<String, AliasFilter> remoteAliasFilters; final List<SearchShardIterator> remoteShardIterators; if (searchContext != null) { remoteAliasFilters = searchContext.aliasFilter(); remoteShardIterators = getRemoteShardsIteratorFromPointInTime(searchShardsResponses, searchContext, searchRequest.pointInTimeBuilder().getKeepAlive(), remoteClusterIndices); } else { remoteAliasFilters = getRemoteAliasFilters(searchShardsResponses); remoteShardIterators = getRemoteShardsIterator(searchShardsResponses, remoteClusterIndices, remoteAliasFilters); } int localClusters = localIndices == null ? 0 : 1; int totalClusters = remoteClusterIndices.size() + localClusters; int successfulClusters = searchShardsResponses.size() + localClusters; // 至於後續搜尋實現如何，不在此間 executeSearch((SearchTask) task, timeProvider, searchRequest, localIndices, remoteShardIterators, clusterNodeLookup, clusterState, remoteAliasFilters, listener, new SearchResponse.Clusters(totalClusters, successfulClusters, skippedClusters.get()), searchContext, searchAsyncActionProvider); }, listener::onFailure)); } } }, listener::onFailure); if (searchRequest.source() == null) { rewriteListener.onResponse(searchRequest.source()); } else { Rewriteable.rewriteAndFetch(searchRequest.source(), searchService.getRewriteContext(timeProvider::getAbsoluteStartMillis), rewriteListener); } }
可以看到，es的search功能，會被劃分為幾種型別，有點會走叢集分發，而有的則不需要。我們自然是希望走叢集分發的，所以，只需看 collectSearchShards() 即可。這裡面其實就是對多個叢集節點的依次請求，當然還有結果收集。
// org.elasticsearch.action.search.TransportSearchAction#collectSearchShards static void collectSearchShards(IndicesOptions indicesOptions, String preference, String routing, AtomicInteger skippedClusters, Map<String, OriginalIndices> remoteIndicesByCluster, RemoteClusterService remoteClusterService, ThreadPool threadPool, ActionListener<Map<String, ClusterSearchShardsResponse>> listener) { // 使用該計數器進行結果控制 final CountDown responsesCountDown = new CountDown(remoteIndicesByCluster.size()); final Map<String, ClusterSearchShardsResponse> searchShardsResponses = new ConcurrentHashMap<>(); final AtomicReference<Exception> exceptions = new AtomicReference<>(); // 迭代各節點，依次傳送請求 for (Map.Entry<String, OriginalIndices> entry : remoteIndicesByCluster.entrySet()) { final String clusterAlias = entry.getKey(); boolean skipUnavailable = remoteClusterService.isSkipUnavailable(clusterAlias); Client clusterClient = remoteClusterService.getRemoteClusterClient(threadPool, clusterAlias); final String[] indices = entry.getValue().indices(); ClusterSearchShardsRequest searchShardsRequest = new ClusterSearchShardsRequest(indices) .indicesOptions(indicesOptions).local(true).preference(preference).routing(routing); // 向叢集中 clusterAlias 非同步發起請求處理 search clusterClient.admin().cluster().searchShards(searchShardsRequest, new CCSActionListener<ClusterSearchShardsResponse, Map<String, ClusterSearchShardsResponse>>( clusterAlias, skipUnavailable, responsesCountDown, skippedClusters, exceptions, listener) { @Override void innerOnResponse(ClusterSearchShardsResponse clusterSearchShardsResponse) { // 每次單節點響應時，將結果存放到 searchShardsResponses 中 searchShardsResponses.put(clusterAlias, clusterSearchShardsResponse); } @Override Map<String, ClusterSearchShardsResponse> createFinalResponse() { // 所有節點都返回時，將結果集返回 return searchShardsResponses; } } ); } } // org.elasticsearch.client.support.AbstractClient.ClusterAdmin#searchShards @Override public void searchShards(final ClusterSearchShardsRequest request, final ActionListener<ClusterSearchShardsResponse> listener) { // 發起請求 indices:admin/shards/search_shards, 其對應處理器為 TransportClusterSearchShardsAction execute(ClusterSearchShardsAction.INSTANCE, request, listener); }
以上是es向叢集中多節點發起請求的過程，其重點在於所有的請求都是非同步請求，即向各節點傳送完成請求後，當前執行緒即為斷開狀態。這就體現了無阻塞的能力了，以listner形式進行處理後續業務。這對於傳送自然沒有問題，但如何進行結果收集呢？實際上就是通過listner來處理的。在遠端節點響應後，listener.onResponse()將被呼叫。
2.1. 多節點響應結果處理
這是我們本文討論的重點。前面我們看到es已經非同步傳送請求出去了（且不論其如何傳送），所以如何收集結果也很關鍵。而es中的做法則很簡單，使用一個 ConcurrentHashMap 收集每個結果，一個CountDown標識是否已處理完成。
// org.elasticsearch.action.search.TransportSearchAction.CCSActionListener#CCSActionListener CCSActionListener(String clusterAlias, boolean skipUnavailable, CountDown countDown, AtomicInteger skippedClusters, AtomicReference<Exception> exceptions, ActionListener<FinalResponse> originalListener) { this.clusterAlias = clusterAlias; this.skipUnavailable = skipUnavailable; this.countDown = countDown; this.skippedClusters = skippedClusters; this.exceptions = exceptions; this.originalListener = originalListener; } // 成功時的響應 @Override public final void onResponse(Response response) { // inner響應為將結果放入 searchShardsResponses 中 innerOnResponse(response); // maybeFinish 則進行結果是否完成判定，如果完成，則呼叫回撥方法，構造結果 maybeFinish(); } private void maybeFinish() { // 使用一個 AtomicInteger 進行控制 if (countDown.countDown()) { Exception exception = exceptions.get(); if (exception == null) { FinalResponse response; try { // 建立響應結果，此處 search 即為 searchShardsResponses response = createFinalResponse(); } catch(Exception e) { originalListener.onFailure(e); return; } // 成功響應回撥，實現結果收集後的其他業務處理 originalListener.onResponse(response); } else { originalListener.onFailure(exceptions.get()); } } } // CountDown 實現比較簡單，只有最後一個返回true, 其他皆為false, 即實現了 At Most Once 語義 /** * Decrements the count-down and returns <code>true</code> iff this call * reached zero otherwise <code>false</code> */ public boolean countDown() { assert originalCount > 0; for (;;) { final int current = countDown.get(); assert current >= 0; if (current == 0) { return false; } if (countDown.compareAndSet(current, current - 1)) { return current == 1; } } }
可見，ES中的結果收集，是以一個 AtomicInteger 實現的CountDown來處理的，當所有節點都響應時，就處理最終結果，否則將每個節點的資料放入ConcurrentHashMap中暫存起來。
而通過一個Client通用的非同步呼叫框架，實現多節點的非同步提交。整個節點響應以 CCSActionListener 作為接收者。可以說是比較簡潔的了，好像也沒有我們前面討論的複雜性。因為：大道至簡。
2.2. 非同步提交請求實現
我們知道，如果本地想實現非同步提交請求，只需使用另一個執行緒或者執行緒池技術，即可實現。而對於遠端Client的非同步提交，則還需要藉助於外部工具了。此處藉助於Netty的channel.write()實現，節點響應時再回撥回來，從而恢復上下文。整個過程，沒有一點阻塞同步，從而達到了高效的處理能力，當然還有其他的一些異常處理，自不必說。
具體樣例大致如下：因最終的處理器是以 TransportClusterSearchShardsAction 進行處理的，所以直接轉到 TransportClusterSearchShardsAction。
// org.elasticsearch.action.admin.cluster.shards.TransportClusterSearchShardsAction public class TransportClusterSearchShardsAction extends TransportMasterNodeReadAction<ClusterSearchShardsRequest, ClusterSearchShardsResponse> { private final IndicesService indicesService; @Inject public TransportClusterSearchShardsAction(TransportService transportService, ClusterService clusterService, IndicesService indicesService, ThreadPool threadPool, ActionFilters actionFilters, IndexNameExpressionResolver indexNameExpressionResolver) { super(ClusterSearchShardsAction.NAME, transportService, clusterService, threadPool, actionFilters, ClusterSearchShardsRequest::new, indexNameExpressionResolver, ClusterSearchShardsResponse::new, ThreadPool.Names.SAME); this.indicesService = indicesService; } @Override protected ClusterBlockException checkBlock(ClusterSearchShardsRequest request, ClusterState state) { return state.blocks().indicesBlockedException(ClusterBlockLevel.METADATA_READ, indexNameExpressionResolver.concreteIndexNames(state, request)); } @Override protected void masterOperation(final ClusterSearchShardsRequest request, final ClusterState state, final ActionListener<ClusterSearchShardsResponse> listener) { ClusterState clusterState = clusterService.state(); String[] concreteIndices = indexNameExpressionResolver.concreteIndexNames(clusterState, request); Map<String, Set<String>> routingMap = indexNameExpressionResolver.resolveSearchRouting(state, request.routing(), request.indices()); Map<String, AliasFilter> indicesAndFilters = new HashMap<>(); Set<String> indicesAndAliases = indexNameExpressionResolver.resolveExpressions(clusterState, request.indices()); for (String index : concreteIndices) { final AliasFilter aliasFilter = indicesService.buildAliasFilter(clusterState, index, indicesAndAliases); final String[] aliases = indexNameExpressionResolver.indexAliases(clusterState, index, aliasMetadata -> true, true, indicesAndAliases); indicesAndFilters.put(index, new AliasFilter(aliasFilter.getQueryBuilder(), aliases)); } Set<String> nodeIds = new HashSet<>(); GroupShardsIterator<ShardIterator> groupShardsIterator = clusterService.operationRouting() .searchShards(clusterState, concreteIndices, routingMap, request.preference()); ShardRouting shard; ClusterSearchShardsGroup[] groupResponses = new ClusterSearchShardsGroup[groupShardsIterator.size()]; int currentGroup = 0; for (ShardIterator shardIt : groupShardsIterator) { ShardId shardId = shardIt.shardId(); ShardRouting[] shardRoutings = new ShardRouting[shardIt.size()]; int currentShard = 0; shardIt.reset(); while ((shard = shardIt.nextOrNull()) != null) { shardRoutings[currentShard++] = shard; nodeIds.add(shard.currentNodeId()); } groupResponses[currentGroup++] = new ClusterSearchShardsGroup(shardId, shardRoutings); } DiscoveryNode[] nodes = new DiscoveryNode[nodeIds.size()]; int currentNode = 0; for (String nodeId : nodeIds) { nodes[currentNode++] = clusterState.getNodes().get(nodeId); } listener.onResponse(new ClusterSearchShardsResponse(groupResponses, nodes, indicesAndFilters)); } } // doExecute 在父類中完成 // org.elasticsearch.action.support.master.TransportMasterNodeAction#doExecute @Override protected void doExecute(Task task, final Request request, ActionListener<Response> listener) { ClusterState state = clusterService.state(); logger.trace("starting processing request [{}] with cluster state version [{}]", request, state.version()); if (task != null) { request.setParentTask(clusterService.localNode().getId(), task.getId()); } new AsyncSingleAction(task, request, listener).doStart(state); } // org.elasticsearch.action.support.master.TransportMasterNodeAction.AsyncSingleAction#doStart AsyncSingleAction(Task task, Request request, ActionListener<Response> listener) { this.task = task; this.request = request; this.listener = listener; this.startTime = threadPool.relativeTimeInMillis(); } protected void doStart(ClusterState clusterState) { try { final DiscoveryNodes nodes = clusterState.nodes(); if (nodes.isLocalNodeElectedMaster() || localExecute(request)) { // check for block, if blocked, retry, else, execute locally final ClusterBlockException blockException = checkBlock(request, clusterState); if (blockException != null) { if (!blockException.retryable()) { listener.onFailure(blockException); } else { logger.debug("can't execute due to a cluster block, retrying", blockException); // 重試處理 retry(clusterState, blockException, newState -> { try { ClusterBlockException newException = checkBlock(request, newState); return (newException == null || !newException.retryable()); } catch (Exception e) { // accept state as block will be rechecked by doStart() and listener.onFailure() then called logger.trace("exception occurred during cluster block checking, accepting state", e); return true; } }); } } else { ActionListener<Response> delegate = ActionListener.delegateResponse(listener, (delegatedListener, t) -> { if (t instanceof FailedToCommitClusterStateException || t instanceof NotMasterException) { logger.debug(() -> new ParameterizedMessage("master could not publish cluster state or " + "stepped down before publishing action [{}], scheduling a retry", actionName), t); retryOnMasterChange(clusterState, t); } else { delegatedListener.onFailure(t); } }); // 本地節點執行結果，直接以非同步執行緒處理即可 threadPool.executor(executor) .execute(ActionRunnable.wrap(delegate, l -> masterOperation(task, request, clusterState, l))); } } else { if (nodes.getMasterNode() == null) { logger.debug("no known master node, scheduling a retry"); retryOnMasterChange(clusterState, null); } else { DiscoveryNode masterNode = nodes.getMasterNode(); final String actionName = getMasterActionName(masterNode); // 傳送到master節點，以netty作為通訊工具，完成後回撥 當前listner transportService.sendRequest(masterNode, actionName, request, new ActionListenerResponseHandler<Response>(listener, responseReader) { @Override public void handleException(final TransportException exp) { Throwable cause = exp.unwrapCause(); if (cause instanceof ConnectTransportException || (exp instanceof RemoteTransportException && cause instanceof NodeClosedException)) { // we want to retry here a bit to see if a new master is elected logger.debug("connection exception while trying to forward request with action name [{}] to " + "master node [{}], scheduling a retry. Error: [{}]", actionName, nodes.getMasterNode(), exp.getDetailedMessage()); retryOnMasterChange(clusterState, cause); } else { listener.onFailure(exp); } } }); } } } catch (Exception e) { listener.onFailure(e); } }
可見，es中確實有兩種非同步的提交方式，一種是當前節點就是執行節點，直接使用執行緒池提交；另一種是遠端節點則起網路呼叫，最終如何實現非同步且往下看。
// org.elasticsearch.transport.TransportService#sendRequest public final <T extends TransportResponse> void sendRequest(final DiscoveryNode node, final String action, final TransportRequest request, final TransportRequestOptions options, TransportResponseHandler<T> handler) { final Transport.Connection connection; try { // 假設不是本節點，則獲取遠端的一個 connection, channel connection = getConnection(node); } catch (final NodeNotConnectedException ex) { // the caller might not handle this so we invoke the handler handler.handleException(ex); return; } sendRequest(connection, action, request, options, handler); } // org.elasticsearch.transport.TransportService#getConnection /** * Returns either a real transport connection or a local node connection if we are using the local node optimization. * @throws NodeNotConnectedException if the given node is not connected */ public Transport.Connection getConnection(DiscoveryNode node) { if (isLocalNode(node)) { return localNodeConnection; } else { return connectionManager.getConnection(node); } } // org.elasticsearch.transport.TransportService#sendRequest /** * Sends a request on the specified connection. If there is a failure sending the request, the specified handler is invoked. * * @param connection the connection to send the request on * @param action the name of the action * @param request the request * @param options the options for this request * @param handler the response handler * @param <T> the type of the transport response */ public final <T extends TransportResponse> void sendRequest(final Transport.Connection connection, final String action, final TransportRequest request, final TransportRequestOptions options, final TransportResponseHandler<T> handler) { try { final TransportResponseHandler<T> delegate; if (request.getParentTask().isSet()) { // If the connection is a proxy connection, then we will create a cancellable proxy task on the proxy node and an actual // child task on the target node of the remote cluster. // ----> a parent task on the local cluster // | // ----> a proxy task on the proxy node on the remote cluster // | // ----> an actual child task on the target node on the remote cluster // To cancel the child task on the remote cluster, we must send a cancel request to the proxy node instead of the target // node as the parent task of the child task is the proxy task not the parent task on the local cluster. Hence, here we // unwrap the connection and keep track of the connection to the proxy node instead of the proxy connection. final Transport.Connection unwrappedConn = unwrapConnection(connection); final Releasable unregisterChildNode = taskManager.registerChildConnection(request.getParentTask().getId(), unwrappedConn); delegate = new TransportResponseHandler<T>() { @Override public void handleResponse(T response) { unregisterChildNode.close(); handler.handleResponse(response); } @Override public void handleException(TransportException exp) { unregisterChildNode.close(); handler.handleException(exp); } @Override public String executor() { return handler.executor(); } @Override public T read(StreamInput in) throws IOException { return handler.read(in); } @Override public String toString() { return getClass().getName() + "/[" + action + "]:" + handler.toString(); } }; } else { delegate = handler; } asyncSender.sendRequest(connection, action, request, options, delegate); } catch (final Exception ex) { // the caller might not handle this so we invoke the handler final TransportException te; if (ex instanceof TransportException) { te = (TransportException) ex; } else { te = new TransportException("failure to send", ex); } handler.handleException(te); } } // org.elasticsearch.transport.TransportService#sendRequestInternal private <T extends TransportResponse> void sendRequestInternal(final Transport.Connection connection, final String action, final TransportRequest request, final TransportRequestOptions options, TransportResponseHandler<T> handler) { if (connection == null) { throw new IllegalStateException("can't send request to a null connection"); } DiscoveryNode node = connection.getNode(); Supplier<ThreadContext.StoredContext> storedContextSupplier = threadPool.getThreadContext().newRestorableContext(true); ContextRestoreResponseHandler<T> responseHandler = new ContextRestoreResponseHandler<>(storedContextSupplier, handler); // TODO we can probably fold this entire request ID dance into connection.sendReqeust but it will be a bigger refactoring final long requestId = responseHandlers.add(new Transport.ResponseContext<>(responseHandler, connection, action)); final TimeoutHandler timeoutHandler; if (options.timeout() != null) { timeoutHandler = new TimeoutHandler(requestId, connection.getNode(), action); responseHandler.setTimeoutHandler(timeoutHandler); } else { timeoutHandler = null; } try { if (lifecycle.stoppedOrClosed()) { /* * If we are not started the exception handling will remove the request holder again and calls the handler to notify the * caller. It will only notify if toStop hasn't done the work yet. */ throw new NodeClosedException(localNode); } if (timeoutHandler != null) { assert options.timeout() != null; timeoutHandler.scheduleTimeout(options.timeout()); } connection.sendRequest(requestId, action, request, options); // local node optimization happens upstream } catch (final Exception e) { // usually happen either because we failed to connect to the node // or because we failed serializing the message final Transport.ResponseContext<? extends TransportResponse> contextToNotify = responseHandlers.remove(requestId); // If holderToNotify == null then handler has already been taken care of. if (contextToNotify != null) { if (timeoutHandler != null) { timeoutHandler.cancel(); } // callback that an exception happened, but on a different thread since we don't // want handlers to worry about stack overflows. In the special case of running into a closing node we run on the current // thread on a best effort basis though. final SendRequestTransportException sendRequestException = new SendRequestTransportException(node, action, e); final String executor = lifecycle.stoppedOrClosed() ? ThreadPool.Names.SAME : ThreadPool.Names.GENERIC; threadPool.executor(executor).execute(new AbstractRunnable() { @Override public void onRejection(Exception e) { // if we get rejected during node shutdown we don't wanna bubble it up logger.debug( () -> new ParameterizedMessage( "failed to notify response handler on rejection, action: {}", contextToNotify.action()), e); } @Override public void onFailure(Exception e) { logger.warn( () -> new ParameterizedMessage( "failed to notify response handler on exception, action: {}", contextToNotify.action()), e); } @Override protected void doRun() throws Exception { contextToNotify.handler().handleException(sendRequestException); } }); } else { logger.debug("Exception while sending request, handler likely already notified due to timeout", e); } } } // org.elasticsearch.transport.RemoteConnectionManager.ProxyConnection#sendRequest @Override public void sendRequest(long requestId, String action, TransportRequest request, TransportRequestOptions options) throws IOException, TransportException { connection.sendRequest(requestId, TransportActionProxy.getProxyAction(action), TransportActionProxy.wrapRequest(targetNode, request), options); } // org.elasticsearch.transport.TcpTransport.NodeChannels#sendRequest @Override public void sendRequest(long requestId, String action, TransportRequest request, TransportRequestOptions options) throws IOException, TransportException { if (isClosing.get()) { throw new NodeNotConnectedException(node, "connection already closed"); } TcpChannel channel = channel(options.type()); outboundHandler.sendRequest(node, channel, requestId, action, request, options, getVersion(), compress, false); } // org.elasticsearch.transport.OutboundHandler#sendRequest /** * Sends the request to the given channel. This method should be used to send {@link TransportRequest} * objects back to the caller. */ void sendRequest(final DiscoveryNode node, final TcpChannel channel, final long requestId, final String action, final TransportRequest request, final TransportRequestOptions options, final Version channelVersion, final boolean compressRequest, final boolean isHandshake) throws IOException, TransportException { Version version = Version.min(this.version, channelVersion); OutboundMessage.Request message = new OutboundMessage.Request(threadPool.getThreadContext(), features, request, version, action, requestId, isHandshake, compressRequest); ActionListener<Void> listener = ActionListener.wrap(() -> messageListener.onRequestSent(node, requestId, action, request, options)); sendMessage(channel, message, listener); } // org.elasticsearch.transport.OutboundHandler#sendMessage private void sendMessage(TcpChannel channel, OutboundMessage networkMessage, ActionListener<Void> listener) throws IOException { MessageSerializer serializer = new MessageSerializer(networkMessage, bigArrays); SendContext sendContext = new SendContext(channel, serializer, listener, serializer); internalSend(channel, sendContext); } private void internalSend(TcpChannel channel, SendContext sendContext) throws IOException { channel.getChannelStats().markAccessed(threadPool.relativeTimeInMillis()); BytesReference reference = sendContext.get(); // stash thread context so that channel event loop is not polluted by thread context try (ThreadContext.StoredContext existing = threadPool.getThreadContext().stashContext()) { channel.sendMessage(reference, sendContext); } catch (RuntimeException ex) { sendContext.onFailure(ex); CloseableChannel.closeChannel(channel); throw ex; } } // org.elasticsearch.transport.netty4.Netty4TcpChannel#sendMessage @Override public void sendMessage(BytesReference reference, ActionListener<Void> listener) { // netty 傳送資料，非同步回撥，完成非同步請求 channel.writeAndFlush(Netty4Utils.toByteBuf(reference), addPromise(listener, channel)); if (channel.eventLoop().isShutdown()) { listener.onFailure(new TransportException("Cannot send message, event loop is shutting down.")); } }
簡單說，就是依託於netty的pipeline機制以及eventLoop實現遠端非同步請求，至於具體實現如何，請參考之前文章或各網文。
本文單討論如題話題，可大可小，通過思路羅列與es的實現參考，相信定能為大家帶來一些碰撞的火花。