溫馨提示×
您好，登錄后才能下訂單哦！
點擊 登錄注冊 即表示同意《億速云用戶服務條款》
您好，登錄后才能下訂單哦！
這篇文章主要介紹“Java ES多節(jié)點任務的高效分發(fā)與收集實現(xiàn)”，在日常操作中，相信很多人在Java ES多節(jié)點任務的高效分發(fā)與收集實現(xiàn)問題上存在疑惑，小編查閱了各式資料，整理出簡單好用的操作方法，希望對大家解答”Java ES多節(jié)點任務的高效分發(fā)與收集實現(xiàn)”的疑惑有所幫助！接下來，請跟著小編一起來學習吧！
一、概述
二、請求分發(fā)的簡單思路
三、es中search的多節(jié)點分發(fā)收集
3.1、多節(jié)點響應結果處理
3.2、異步提交請求實現(xiàn)
我們知道，當我們對es發(fā)起search請求或其他操作時，往往都是隨機選擇一個coordinator發(fā)起請求。而這請求，可能是該節(jié)點能處理，也可能是該節(jié)點不能處理的，也可能是需要多節(jié)點共同處理的，可以說是情況比較復雜。
所以，coordinator的重要工作是，做請求分發(fā)與結果收集。那么，如何高性能和安全準確地實現(xiàn)這一功能則至關重要。
我們這里所說的請求分發(fā)，一般是針對多個網(wǎng)絡節(jié)點而言的。那么，如何將請求發(fā)往多節(jié)點，并在最終將結果合并起來呢？
同步請求各節(jié)點，當?shù)谝粋€節(jié)點響應后，再向第二個節(jié)點發(fā)起請求，以此類推，直到所有節(jié)點請求完成，然后再將結果聚合起來。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(jié)點，無法很好利用系統(tǒng)的分布式特點，變并行為串行了，好不厲害。另外，對于當前請求，當其未處理完成這所有節(jié)點的分發(fā)收集工作時，當前線程將會一直被占用。從而，下游請求將無法再接入，從而將你了并發(fā)能力，使其與線程池大小同日而語了。這可不好。
我們依次想辦法優(yōu)化下。
首先，我們可以將串行分發(fā)請求變成并行分發(fā)，即可以使用多線程，向多節(jié)點發(fā)起請求，當某線程處理完成時，就返回結果。使用類似于CountDownLatch的同步工具，保證所有節(jié)點都處理完成后，再由外單主線程進行結果合并操作。
以上優(yōu)化，看起來不錯，避免了同步的性能問題。但是，當有某個節(jié)點響應非常慢時，它將阻塞后續(xù)節(jié)點的工作，從而使整個請求變慢，從而同樣變成線程池的大小即是并發(fā)能力的瓶頸?？梢哉f，治標不治本。
再來，繼續(xù)優(yōu)化。我們可以釋放掉主線程的持有，讓每個分發(fā)線程處理完成當前任務時，都去檢查任務隊列，是否已完成。如果未完成則忽略，如果已完成，則啟動合并任務。
看起來不錯，已經(jīng)有完全并發(fā)樣子了。但還能不能再優(yōu)化？各節(jié)點的分發(fā)，同樣是同步請求，雖然處理簡單，但在這server響應期間，該線程仍是無法被使用的，如果類似請求過多，則必然是不小的消耗。如果能將單節(jié)點的請求，能夠做到異步處理，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。
我們以search的分發(fā)收集為出發(fā)點，觀看es如何辦成這件。原因是search在es中最為普遍與經(jīng)典，雖說不得每個地方實現(xiàn)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(jīng)研究過，本節(jié)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(jié)點數(shù)據(jù)請求
if (shouldMinimizeRoundtrips(searchRequest)) {
// 通過 parentTaskId 關聯(lián)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(fā)多shard請求到各節(jié)點
collectSearchShards(searchRequest.indicesOptions(), searchRequest.preference(), searchRequest.routing(),
skippedClusters, remoteClusterIndices, remoteClusterService, threadPool,
ActionListener.wrap(
searchShardsResponses -> {
// 當所有節(jié)點都響應后，再做后續(xù)邏輯處理，即此處的后置監(jiān)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;
// 至于后續(xù)搜索實現(xiàn)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，會被劃分為幾種類型，有點會走集群分發(fā)，而有的則不需要。我們自然是希望走集群分發(fā)的，所以，只需看 collectSearchShards() 即可。這里面其實就是對多個集群節(jié)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(shù)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(jié)點，依次發(fā)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);
// 向集群中 clusterAlias 異步發(fā)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(jié)點響應時，將結果存放到 searchShardsResponses 中
searchShardsResponses.put(clusterAlias, clusterSearchShardsResponse);
}
@Override
Map<String, ClusterSearchShardsResponse> createFinalResponse() {
// 所有節(jié)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(fā)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向集群中多節(jié)點發(fā)起請求的過程，其重點在于所有的請求都是異步請求，即向各節(jié)點發(fā)送完成請求后，當前線程即為斷開狀態(tài)。這就體現(xiàn)了無阻塞的能力了，以listner形式進行處理后續(xù)業(yè)務。這對于發(fā)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。在遠程節(jié)點響應后，listener.onResponse()將被調用。
這是我們本文討論的重點。前面我們看到es已經(jīng)異步發(fā)送請求出去了（且不論其如何發(fā)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，則調用回調方法，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 {
// 創(chuàng)建響應結果，此處 search 即為 searchShardsResponses
response = createFinalResponse();
} catch(Exception e) {
originalListener.onFailure(e);
return;
}
// 成功響應回調，實現(xiàn)結果收集后的其他業(yè)務處理
originalListener.onResponse(response);
} else {
originalListener.onFailure(exceptions.get());
}
}
}
// CountDown 實現(xiàn)比較簡單，只有最后一個返回true, 其他皆為false, 即實現(xiàn)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(xiàn)的CountDown來處理的，當所有節(jié)點都響應時，就處理最終結果，否則將每個節(jié)點的數(shù)據(jù)放入ConcurrentHashMap中暫存起來。
而通過一個Client通用的異步調用框架，實現(xiàn)多節(jié)點的異步提交。整個節(jié)點響應以 CCSActionListener 作為接收者?？梢哉f是比較簡潔的了，好像也沒有我們前面討論的復雜性。因為：大道至簡。
我們知道，如果本地想實現(xiàn)異步提交請求，只需使用另一個線程或者線程池技術，即可實現(xiàn)。而對于遠程Client的異步提交，則還需要借助于外部工具了。此處借助于Netty的channel.write()實現(xiàn)，節(jié)點響應時再回調回來，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(jié)點執(zhí)行結果，直接以異步線程處理即可
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);
// 發(fā)送到master節(jié)點，以netty作為通訊工具，完成后回調 當前l(fā)istner
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中確實有兩種異步的提交方式，一種是當前節(jié)點就是執(zhí)行節(jié)點，直接使用線程池提交；另一種是遠程節(jié)點則起網(wǎng)絡調用，最終如何實現(xiàn)異步且往下看。
// 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(jié)點，則獲取遠程的一個 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 發(fā)送數(shù)據(jù)，異步回調，完成異步請求
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，就是依托于netty的pipeline機制以及eventLoop實現(xiàn)遠程異步請求，至于具體實現(xiàn)如何，請參考之前文章或各網(wǎng)文。
到此，關于“Java ES多節(jié)點任務的高效分發(fā)與收集實現(xiàn)”的學習就結束了，希望能夠解決大家的疑惑。理論與實踐的搭配能更好的幫助大家學習，快去試試吧！若想繼續(xù)學習更多相關知識，請繼續(xù)關注億速云網(wǎng)站，小編會繼續(xù)努力為大家?guī)砀鄬嵱玫奈恼拢?/p>
免責聲明：本站發(fā)布的內容（圖片、視頻和文字）以原創(chuàng)、轉載和分享為主，文章觀點不代表本網(wǎng)站立場，如果涉及侵權請聯(lián)系站長郵箱：is@yisu.com進行舉報，并提供相關證據(jù)，一經(jīng)查實，將立刻刪除涉嫌侵權內容。
