Serch查询流程
查询请求Rest路由注册也是在actionModule中
//查询操作
registerHandler.accept(new RestSearchAction());
@Override
public List<Route> routes() {
return unmodifiableList(asList(
new Route(GET, "/_search"),
new Route(POST, "/_search"),
new Route(GET, "/{index}/_search"),
new Route(POST, "/{index}/_search"),
// Deprecated typed endpoints.
new Route(GET, "/{index}/{type}/_search"),
new Route(POST, "/{index}/{type}/_search")));
}
和Get查询一样，请求会经过转发dispatchRequest，查询路由对应的handler处理类，然后执行处理
@Override
public void dispatchRequest(RestRequest request, RestChannel channel, ThreadContext threadContext) {
//小图标请求处理
if (request.rawPath().equals("/favicon.ico")) {
handleFavicon(request.method(), request.uri(), channel);
return;
}
try {
//处理rest请求
tryAllHandlers(request, channel, threadContext);
} catch (Exception e) {
try {
channel.sendResponse(new BytesRestResponse(channel, e));
} catch (Exception inner) {
inner.addSuppressed(e);
logger.error(() ->
new ParameterizedMessage("failed to send failure response for uri [{}]", request.uri()), inner);
}
}
}
调用BaseRestHandler的handleRequest方法
@Override
public final void handleRequest(RestRequest request, RestChannel channel, NodeClient client) throws Exception {
// prepare the request for execution; has the side effect of touching the request parameters
//处理请求
final RestChannelConsumer action = prepareRequest(request, client);
// validate unconsumed params, but we must exclude params used to format the response
// use a sorted set so the unconsumed parameters appear in a reliable sorted order
final SortedSet<String> unconsumedParams =
request.unconsumedParams().stream().filter(p -> !responseParams().contains(p)).collect(Collectors.toCollection(TreeSet::new));
// validate the non-response params
if (!unconsumedParams.isEmpty()) {
final Set<String> candidateParams = new HashSet<>();
candidateParams.addAll(request.consumedParams());
candidateParams.addAll(responseParams());
throw new IllegalArgumentException(unrecognized(request, unconsumedParams, candidateParams, "parameter"));
}
if (request.hasContent() && request.isContentConsumed() == false) {
throw new IllegalArgumentException("request [" + request.method() + " " + request.path() + "] does not support having a body");
}
usageCount.increment();
// execute the action
action.accept(channel);
}
首先构造请求request对象，RestSearchAction对该方法进行了重写
@Override
public RestChannelConsumer prepareRequest(final RestRequest request, final NodeClient client) throws IOException {
//创建查询请求对象
SearchRequest searchRequest = new SearchRequest();
IntConsumer setSize = size -> searchRequest.source().size(size);
request.withContentOrSourceParamParserOrNull(parser ->
parseSearchRequest(searchRequest, request, parser, setSize));
return channel -> {
RestCancellableNodeClient cancelClient = new RestCancellableNodeClient(client, request.getHttpChannel());
cancelClient.execute(SearchAction.INSTANCE, searchRequest, new RestStatusToXContentListener<>(channel));
};
}
首先根据请求的request解析成查询请求
public static void parseSearchRequest(SearchRequest searchRequest, RestRequest request,
XContentParser requestContentParser,
IntConsumer setSize) throws IOException {
//查询源包含哪些字段，为空查询所有字段
if (searchRequest.source() == null) {
searchRequest.source(new SearchSourceBuilder());
}
//查询索引
searchRequest.indices(Strings.splitStringByCommaToArray(request.param("index")));
if (requestContentParser != null) {
searchRequest.source().parseXContent(requestContentParser, true);
}
//协调节点的保护，从每个shard获取的数据最大数据量
final int batchedReduceSize = request.paramAsInt("batched_reduce_size", searchRequest.getBatchedReduceSize());
searchRequest.setBatchedReduceSize(batchedReduceSize);
//预过滤分片数量
if (request.hasParam("pre_filter_shard_size")) {
searchRequest.setPreFilterShardSize(request.paramAsInt("pre_filter_shard_size", SearchRequest.DEFAULT_PRE_FILTER_SHARD_SIZE));
}
//分片并发查询数量
if (request.hasParam("max_concurrent_shard_requests")) {
// only set if we have the parameter since we auto adjust the max concurrency on the coordinator
// based on the number of nodes in the cluster
final int maxConcurrentShardRequests = request.paramAsInt("max_concurrent_shard_requests",
searchRequest.getMaxConcurrentShardRequests());
searchRequest.setMaxConcurrentShardRequests(maxConcurrentShardRequests);
}
//允许部分搜索结果
if (request.hasParam("allow_partial_search_results")) {
// only set if we have the parameter passed to override the cluster-level default
searchRequest.allowPartialSearchResults(request.paramAsBoolean("allow_partial_search_results", null));
}
// do not allow 'query_and_fetch' or 'dfs_query_and_fetch' search types
// from the REST layer. these modes are an internal optimization and should
// not be specified explicitly by the user.
//搜索类型，默认query_then_fetch
String searchType = request.param("search_type");
//下面两种查询已经被废弃
if ("query_and_fetch".equals(searchType) ||
"dfs_query_and_fetch".equals(searchType)) {
throw new IllegalArgumentException("Unsupported search type [" + searchType + "]");
} else {
searchRequest.searchType(searchType);
}
parseSearchSource(searchRequest.source(), request, setSize);
//查询缓存
searchRequest.requestCache(request.paramAsBoolean("request_cache", searchRequest.requestCache()));
//滚动查询
String scroll = request.param("scroll");
if (scroll != null) {
searchRequest.scroll(new Scroll(parseTimeValue(scroll, null, "scroll")));
}
//type字段已废弃
if (request.hasParam("type")) {
deprecationLogger.deprecatedAndMaybeLog("search_with_types", TYPES_DEPRECATION_MESSAGE);
searchRequest.types(Strings.splitStringByCommaToArray(request.param("type")));
}
searchRequest.routing(request.param("routing"));
searchRequest.preference(request.param("preference"));
searchRequest.indicesOptions(IndicesOptions.fromRequest(request, searchRequest.indicesOptions()));
searchRequest.setCcsMinimizeRoundtrips(request.paramAsBoolean("ccs_minimize_roundtrips", searchRequest.isCcsMinimizeRoundtrips()));
checkRestTotalHits(request, searchRequest);
}
private static void parseSearchSource(final SearchSourceBuilder searchSourceBuilder, RestRequest request, IntConsumer setSize) {
QueryBuilder queryBuilder = RestActions.urlParamsToQueryBuilder(request);
if (queryBuilder != null) {
searchSourceBuilder.query(queryBuilder);
}
//分页查询
int from = request.paramAsInt("from", -1);
if (from != -1) {
searchSourceBuilder.from(from);
}
int size = request.paramAsInt("size", -1);
if (size != -1) {
setSize.accept(size);
}
//特定文档如何与查询匹配的详细信息和解释
if (request.hasParam("explain")) {
searchSourceBuilder.explain(request.paramAsBoolean("explain", null));
}
//带版本号查询
if (request.hasParam("version")) {
searchSourceBuilder.version(request.paramAsBoolean("version", null));
}
//是否返回seqNo和primaryTerm
if (request.hasParam("seq_no_primary_term")) {
searchSourceBuilder.seqNoAndPrimaryTerm(request.paramAsBoolean("seq_no_primary_term", null));
}
//超时时间
if (request.hasParam("timeout")) {
searchSourceBuilder.timeout(request.paramAsTime("timeout", null));
}
//收集后终止搜索
if (request.hasParam("terminate_after")) {
int terminateAfter = request.paramAsInt("terminate_after",
SearchContext.DEFAULT_TERMINATE_AFTER);
if (terminateAfter < 0) {
throw new IllegalArgumentException("terminateAfter must be > 0");
} else if (terminateAfter > 0) {
searchSourceBuilder.terminateAfter(terminateAfter);
}
}
//指示应如何获取存储的字段
StoredFieldsContext storedFieldsContext =
StoredFieldsContext.fromRestRequest(SearchSourceBuilder.STORED_FIELDS_FIELD.getPreferredName(), request);
if (storedFieldsContext != null) {
searchSourceBuilder.storedFields(storedFieldsContext);
}
//从doc_value字段查询
String sDocValueFields = request.param("docvalue_fields");
if (sDocValueFields != null) {
if (Strings.hasText(sDocValueFields)) {
String[] sFields = Strings.splitStringByCommaToArray(sDocValueFields);
for (String field : sFields) {
searchSourceBuilder.docValueField(field, null);
}
}
}
//从_source获取结果
FetchSourceContext fetchSourceContext = FetchSourceContext.parseFromRestRequest(request);
if (fetchSourceContext != null) {
searchSourceBuilder.fetchSource(fetchSourceContext);
}
//在排序时应用，并控制是否也会跟踪分数
if (request.hasParam("track_scores")) {
searchSourceBuilder.trackScores(request.paramAsBoolean("track_scores", false));
}
//如果值未设置，则返回应跟踪的总命中数或 null
if (request.hasParam("track_total_hits")) {
if (Booleans.isBoolean(request.param("track_total_hits"))) {
searchSourceBuilder.trackTotalHits(
request.paramAsBoolean("track_total_hits", true)
);
} else {
searchSourceBuilder.trackTotalHitsUpTo(
request.paramAsInt("track_total_hits", SearchContext.DEFAULT_TRACK_TOTAL_HITS_UP_TO)
);
}
}
//排序字段
String sSorts = request.param("sort");
if (sSorts != null) {
String[] sorts = Strings.splitStringByCommaToArray(sSorts);
for (String sort : sorts) {
int delimiter = sort.lastIndexOf(":");
if (delimiter != -1) {
String sortField = sort.substring(0, delimiter);
String reverse = sort.substring(delimiter + 1);
if ("asc".equals(reverse)) {
searchSourceBuilder.sort(sortField, SortOrder.ASC);
} else if ("desc".equals(reverse)) {
searchSourceBuilder.sort(sortField, SortOrder.DESC);
}
} else {
searchSourceBuilder.sort(sort);
}
}
}
//此请求将汇总的统计信息组
String sStats = request.param("stats");
if (sStats != null) {
searchSourceBuilder.stats(Arrays.asList(Strings.splitStringByCommaToArray(sStats)));
}
//推荐词
String suggestField = request.param("suggest_field");
if (suggestField != null) {
String suggestText = request.param("suggest_text", request.param("q"));
int suggestSize = request.paramAsInt("suggest_size", 5);
String suggestMode = request.param("suggest_mode");
searchSourceBuilder.suggest(new SuggestBuilder().addSuggestion(suggestField,
termSuggestion(suggestField)
.text(suggestText).size(suggestSize)
.suggestMode(SuggestMode.resolve(suggestMode))));
}
}
创建rest client开始发送请求
return channel -> {
RestCancellableNodeClient cancelClient = new RestCancellableNodeClient(client, request.getHttpChannel());
cancelClient.execute(SearchAction.INSTANCE, searchRequest, new RestStatusToXContentListener<>(channel));
};
执行execute方法
public < Request extends ActionRequest,
Response extends ActionResponse
> Task executeLocally(ActionType<Response> action, Request request, ActionListener<Response> listener) {
//获取transportAction开始执行
return transportAction(action).execute(request, listener);
}
最终调用到TransportSearchAction的doExecute方法
search操作会发送请求到索引下的所有分片，相同分片只会发送到主分片或副本分片
protected void doExecute(Task task, SearchRequest searchRequest, ActionListener<SearchResponse> listener) {
//服务启动相对时间
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);
}
//对其他集群的索引和当前集群的索引分组,合并本集群shard列表和远程集群的shard
final ClusterState clusterState = clusterService.state();
final Map<String, OriginalIndices> remoteClusterIndices = remoteClusterService.groupIndices(searchRequest.indicesOptions(),
searchRequest.indices(), idx -> indexNameExpressionResolver.hasIndexOrAlias(idx, clusterState));
OriginalIndices localIndices = remoteClusterIndices.remove(RemoteClusterAware.LOCAL_CLUSTER_GROUP_KEY);
//执行本集群搜索
if (remoteClusterIndices.isEmpty()) {
executeLocalSearch(task, timeProvider, searchRequest, localIndices, clusterState, listener);
} else {
//最小化查询次数
if (shouldMinimizeRoundtrips(searchRequest)) {
ccsRemoteReduce(searchRequest, localIndices, remoteClusterIndices, timeProvider,
searchService.aggReduceContextBuilder(searchRequest),
remoteClusterService, threadPool, listener,
(r, l) -> executeLocalSearch(task, timeProvider, r, localIndices, clusterState, l));
} else {
AtomicInteger skippedClusters = new AtomicInteger(0);
//收集所有需要查询的分片
collectSearchShards(searchRequest.indicesOptions(), searchRequest.preference(), searchRequest.routing(),
skippedClusters, remoteClusterIndices, remoteClusterService, threadPool,
ActionListener.wrap(
//查询分片返回的结果
searchShardsResponses -> {
List<SearchShardIterator> remoteShardIterators = new ArrayList<>();
Map<String, AliasFilter> remoteAliasFilters = new HashMap<>();
BiFunction<String, String, DiscoveryNode> clusterNodeLookup = processRemoteShards(
searchShardsResponses, remoteClusterIndices, remoteShardIterators, remoteAliasFilters);
//查询集群数
int localClusters = localIndices == null ? 0 : 1;
int totalClusters = remoteClusterIndices.size() + localClusters;
int successfulClusters = searchShardsResponses.size() + localClusters;
//执行查询
executeSearch((SearchTask) task, timeProvider, searchRequest, localIndices,
remoteShardIterators, clusterNodeLookup, clusterState, remoteAliasFilters, listener,
new SearchResponse.Clusters(totalClusters, successfulClusters, skippedClusters.get()));
},
listener::onFailure));
}
}
}, listener::onFailure);
if (searchRequest.source() == null) {
rewriteListener.onResponse(searchRequest.source());
} else {
Rewriteable.rewriteAndFetch(searchRequest.source(), searchService.getRewriteContext(timeProvider::getAbsoluteStartMillis),
rewriteListener);
}
}
这里收集本集群和跨集群及其他集群需要查询的索引，这里我们主要是分析本集群搜索
ES中查询主要包括两个方式:
- QUERY_THEN_FETCH：默认搜索方式， 先向所有的 shard 发出请求， 各分片只返回文档 id和排
名相关的信息及文档的打分然后按照各分片返回的文档的分数进行重新排序和排名， 取前
size 个文档。然后根据文档 id 去相关的 shard 取 document。 数据量是准确的，数据排名不准确 - DFS_QUERY_THEN_FETCH：在上面的查询方式之前多个一个DFS的过程，也就是在进行查询之前， 先对所有分片发送请求， 把所有分片中的词频和文档频率等打分依据全部汇总到一块， 再执行后面的操作，数据排名准确，但是性能比上面性能要差
private void executeSearch(SearchTask task, SearchTimeProvider timeProvider, SearchRequest searchRequest,
OriginalIndices localIndices, List<SearchShardIterator> remoteShardIterators,
BiFunction<String, String, DiscoveryNode> remoteConnections, ClusterState clusterState,
Map<String, AliasFilter> remoteAliasMap, ActionListener<SearchResponse> listener,
SearchResponse.Clusters clusters) {
clusterState.blocks().globalBlockedRaiseException(ClusterBlockLevel.READ);
// TODO: I think startTime() should become part of ActionRequest and that should be used both for index name
// date math expressions and $now in scripts. This way all apis will deal with now in the same way instead
// of just for the _search api
final Index[] indices = resolveLocalIndices(localIndices, searchRequest.indicesOptions(), clusterState, timeProvider);
Map<String, AliasFilter> aliasFilter = buildPerIndexAliasFilter(searchRequest, clusterState, indices, remoteAliasMap);
Map<String, Set<String>> routingMap = indexNameExpressionResolver.resolveSearchRouting(clusterState, searchRequest.routing(),
searchRequest.indices());
routingMap = routingMap == null ? Collections.emptyMap() : Collections.unmodifiableMap(routingMap);
String[] concreteIndices = new String[indices.length];
for (int i = 0; i < indices.length; i++) {
concreteIndices[i] = indices[i].getName();
}
//每个节点查询次数
Map<String, Long> nodeSearchCounts = searchTransportService.getPendingSearchRequests();
GroupShardsIterator<ShardIterator> localShardsIterator = clusterService.operationRouting().searchShards(clusterState,
concreteIndices, routingMap, searchRequest.preference(), searchService.getResponseCollectorService(), nodeSearchCounts);
//合并需要查询的shard分片
GroupShardsIterator<SearchShardIterator> shardIterators = mergeShardsIterators(localShardsIterator, localIndices,
searchRequest.getLocalClusterAlias(), remoteShardIterators);
//检查需要查询分片数量是否超过阈值
failIfOverShardCountLimit(clusterService, shardIterators.size());
Map<String, Float> concreteIndexBoosts = resolveIndexBoosts(searchRequest, clusterState);
// optimize search type for cases where there is only one shard group to search on
//针对只有一个分片组要搜索的情况优化搜索类型
if (shardIterators.size() == 1) {
// if we only have one group, then we always want Q_T_F, no need for DFS, and no need to do THEN since we hit one shard
searchRequest.searchType(QUERY_THEN_FETCH);
}
if (searchRequest.allowPartialSearchResults() == null) {
// No user preference defined in search request - apply cluster service default
//允许部分搜索结果返回
searchRequest.allowPartialSearchResults(searchService.defaultAllowPartialSearchResults());
}
if (searchRequest.isSuggestOnly()) {
// disable request cache if we have only suggest
// 如果我们只有建议，则禁用请求缓存
searchRequest.requestCache(false);
switch (searchRequest.searchType()) {
case DFS_QUERY_THEN_FETCH:
// convert to Q_T_F if we have only suggest
searchRequest.searchType(QUERY_THEN_FETCH);
break;
}
}
final DiscoveryNodes nodes = clusterState.nodes();
BiFunction<String, String, Transport.Connection> connectionLookup = buildConnectionLookup(searchRequest.getLocalClusterAlias(),
nodes::get, remoteConnections, searchTransportService::getConnection);
//提前过滤分片
boolean preFilterSearchShards = shouldPreFilterSearchShards(clusterState, searchRequest, indices, shardIterators.size());
//异步查询
searchAsyncAction(task, searchRequest, shardIterators, timeProvider, connectionLookup, clusterState,
Collections.unmodifiableMap(aliasFilter), concreteIndexBoosts, routingMap, listener, preFilterSearchShards, clusters).start();
}
根据两个搜索方式创建不同的action
AbstractSearchAsyncAction<? extends SearchPhaseResult> searchAsyncAction;
switch (searchRequest.searchType()) {
case DFS_QUERY_THEN_FETCH:
searchAsyncAction = new SearchDfsQueryThenFetchAsyncAction(logger, searchTransportService, connectionLookup,
aliasFilter, concreteIndexBoosts, indexRoutings, searchPhaseController, executor, searchRequest, listener,
shardIterators, timeProvider, clusterState, task, clusters);
break;
case QUERY_THEN_FETCH:
searchAsyncAction = new SearchQueryThenFetchAsyncAction(logger, searchTransportService, connectionLookup,
aliasFilter, concreteIndexBoosts, indexRoutings, searchPhaseController, executor, searchRequest, /*查询后的回调*/listener,
shardIterators, timeProvider, clusterState, task, clusters);
break;
default:
throw new IllegalStateException("Unknown search type: [" + searchRequest.searchType() + "]");
}
return searchAsyncAction;
创建action后开始执行
public final void start() {
if (getNumShards() == 0) {
//no search shards to search on, bail with empty response
//(it happens with search across _all with no indices around and consistent with broadcast operations)
int trackTotalHitsUpTo = request.source() == null ? SearchContext.DEFAULT_TRACK_TOTAL_HITS_UP_TO :
request.source().trackTotalHitsUpTo() == null ? SearchContext.DEFAULT_TRACK_TOTAL_HITS_UP_TO :
request.source().trackTotalHitsUpTo();
// total hits is null in the response if the tracking of total hits is disabled
boolean withTotalHits = trackTotalHitsUpTo != SearchContext.TRACK_TOTAL_HITS_DISABLED;
listener.onResponse(new SearchResponse(InternalSearchResponse.empty(withTotalHits), null, 0, 0, 0, buildTookInMillis(),
ShardSearchFailure.EMPTY_ARRAY, clusters));
return;
}
//执行搜索
executePhase(this);
}
private void executePhase(SearchPhase phase) {
try {
phase.run();
} catch (Exception e) {
if (logger.isDebugEnabled()) {
logger.debug(new ParameterizedMessage("Failed to execute [{}] while moving to [{}] phase", request, phase.getName()), e);
}
onPhaseFailure(phase, "", e);
}
}
遍历所有分片发送请求，并设置回调函数接收分片返回结果
public final void run() {
for (final SearchShardIterator iterator : toSkipShardsIts) {
assert iterator.skip();
skipShard(iterator);
}
if (shardsIts.size() > 0) {
...
for (int index = 0; index < shardsIts.size(); index++) {
//分片路由信息
final SearchShardIterator shardRoutings = shardsIts.get(index);
assert shardRoutings.skip() == false;
//分片执行
performPhaseOnShard(index, shardRoutings, shardRoutings.nextOrNull());
}
}
}
private void performPhaseOnShard(final int shardIndex, final SearchShardIterator shardIt, final ShardRouting shard) {
if (shard == null) {
fork(() -> onShardFailure(shardIndex, null, null, shardIt, new NoShardAvailableActionException(shardIt.shardId())));
} else {
//节流并发请求
final PendingExecutions pendingExecutions = throttleConcurrentRequests ?
pendingExecutionsPerNode.computeIfAbsent(shard.currentNodeId(), n -> new PendingExecutions(maxConcurrentRequestsPerNode))
: null;
Runnable r = () -> {
final Thread thread = Thread.currentThread();
try {
//执行查询
executePhaseOnShard(shardIt, shard,
new SearchActionListener<Result>(shardIt.newSearchShardTarget(shard.currentNodeId()), shardIndex) {
@Override
public void innerOnResponse(Result result) {
try {
//分片返回结果
onShardResult(result, shardIt);
} finally {
executeNext(pendingExecutions, thread);
}
}
@Override
public void onFailure(Exception t) {
try {
onShardFailure(shardIndex, shard, shard.currentNodeId(), shardIt, t);
} finally {
executeNext(pendingExecutions, thread);
}
}
});
} catch (final Exception e) {
try {
fork(() -> onShardFailure(shardIndex, shard, shard.currentNodeId(), shardIt, e));
} finally {
executeNext(pendingExecutions, thread);
}
}
};
//是否限流
if (throttleConcurrentRequests) {
pendingExecutions.tryRun(r);
} else {
r.run();
}
}
}
默认为QUERY_THEN_FETCH方式，调用SearchQueryThenFetchAsyncAction的executePhaseOnShard方法
protected void executePhaseOnShard(final SearchShardIterator shardIt, final ShardRouting shard,
final SearchActionListener<SearchPhaseResult> listener) {
//封装请求
ShardSearchRequest request = rewriteShardSearchRequest(super.buildShardSearchRequest(shardIt));
getSearchTransport().sendExecuteQuery(getConnection(shardIt.getClusterAlias(), shard.currentNodeId()),
request, getTask(), listener);
}
获取连接然后发送action为indices:data/read/search[phase/query]的RPC请求
public void sendExecuteQuery(Transport.Connection connection, final ShardSearchRequest request, SearchTask task,
final SearchActionListener<SearchPhaseResult> listener) {
// we optimize this and expect a QueryFetchSearchResult if we only have a single shard in the search request
// this used to be the QUERY_AND_FETCH which doesn't exist anymore.
final boolean fetchDocuments = request.numberOfShards() == 1;
Writeable.Reader<SearchPhaseResult> reader = fetchDocuments ? QueryFetchSearchResult::new : QuerySearchResult::new;
final ActionListener handler = responseWrapper.apply(connection, listener);
//发送查询
transportService.sendChildRequest(connection, QUERY_ACTION_NAME, request, task,
new ConnectionCountingHandler<>(handler, reader, clientConnections, connection.getNode().getId()));
}
- 数据节点
数据节点对应的RPC注册的处理handler
//注册分片查询处理
transportService.registerRequestHandler(QUERY_ACTION_NAME, ThreadPool.Names.SAME, ShardSearchRequest::new,
(request, channel, task) -> {
//执行查询
searchService.executeQueryPhase(request, (SearchShardTask) task,
/*查询后回调*/
new ChannelActionListener<>(channel, QUERY_ACTION_NAME, request));
});
数据节点接收RPC请求执行query阶段
public void executeQueryPhase(ShardSearchRequest request, SearchShardTask task, ActionListener<SearchPhaseResult> listener) {
assert request.canReturnNullResponseIfMatchNoDocs() == false || request.numberOfShards() > 1
: "empty responses require more than one shard";
//索引服务
IndexService indexService = indicesService.indexServiceSafe(request.shardId().getIndex());
//索引分片
IndexShard shard = indexService.getShard(request.shardId().id());
rewriteAndFetchShardRequest(shard, request, new ActionListener<ShardSearchRequest>() {
@Override
public void onResponse(ShardSearchRequest orig) {
//如果没有查询到doc可以返回null
if (orig.canReturnNullResponseIfMatchNoDocs()) {
ShardSearchRequest canMatchRequest = new ShardSearchRequest(orig);
try (Engine.Searcher searcher = shard.acquireCanMatchSearcher()) {
QueryShardContext context = indexService.newQueryShardContext(canMatchRequest.shardId().id(), searcher,
canMatchRequest::nowInMillis, canMatchRequest.getClusterAlias());
Rewriteable.rewrite(canMatchRequest.getRewriteable(), context, true);
} catch (Exception exc) {
listener.onFailure(exc);
return;
}
if (canRewriteToMatchNone(canMatchRequest.source())
&& canMatchRequest.source().query() instanceof MatchNoneQueryBuilder) {
assert canMatchRequest.scroll() == null : "must always create search context for scroll requests";
listener.onResponse(QuerySearchResult.nullInstance());
return;
}
}
// fork the execution in the search thread pool
//在搜索线程池中执行
runAsync(shard, () -> executeQueryPhase(orig, task), listener);
}
@Override
public void onFailure(Exception exc) {
listener.onFailure(exc);
}
});
}
执行search操作
private SearchPhaseResult executeQueryPhase(ShardSearchRequest request, SearchShardTask task) throws Exception {
final SearchContext context = createAndPutContext(request, task);
context.incRef();
try {
final long afterQueryTime;
try (SearchOperationListenerExecutor executor = new SearchOperationListenerExecutor(context)) {
contextProcessing(context);
//执行查询阶段
loadOrExecuteQueryPhase(request, context);
if (context.queryResult().hasSearchContext() == false && context.scrollContext() == null) {
freeContext(context.id());
} else {
contextProcessedSuccessfully(context);
}
afterQueryTime = executor.success();
}
//如果只有一个分片，执行fetch阶段
if (request.numberOfShards() == 1) {
return executeFetchPhase(context, afterQueryTime);
}
return context.queryResult();
} catch (Exception e) {
// execution exception can happen while loading the cache, strip it
if (e instanceof ExecutionException) {
e = (e.getCause() == null || e.getCause() instanceof Exception) ?
(Exception) e.getCause() : new ElasticsearchException(e.getCause());
}
logger.trace("Query phase failed", e);
processFailure(context, e);
throw e;
} finally {
cleanContext(context);
}
}
创建查询上下文对象SearchContext跟踪整个search流程，并且查询后的结果也会填充到SearchContext中
private void loadOrExecuteQueryPhase(final ShardSearchRequest request, final SearchContext context) throws Exception {
final boolean canCache = indicesService.canCache(request, context);
context.getQueryShardContext().freezeContext();
if (canCache) {
indicesService.loadIntoContext(request, context, queryPhase);
} else {
//执行查询
queryPhase.execute(context);
}
}
public void execute(SearchContext searchContext) throws QueryPhaseExecutionException {
if (searchContext.hasOnlySuggest()) {
suggestPhase.execute(searchContext);
searchContext.queryResult().topDocs(new TopDocsAndMaxScore(
new TopDocs(new TotalHits(0, TotalHits.Relation.EQUAL_TO), Lucene.EMPTY_SCORE_DOCS), Float.NaN),
new DocValueFormat[0]);
return;
}
if (LOGGER.isTraceEnabled()) {
LOGGER.trace("{}", new SearchContextSourcePrinter(searchContext));
}
//尽可能晚地预处理聚合。在 DFS_Q_T_F 的情况下
// 请求，preProcess 在 DFS 阶段调用，这就是我们预处理它们的原因
//这里是为了确保它发生在QUERY阶段
aggregationPhase.preProcess(searchContext);
//lucene搜索
boolean rescore = executeInternal(searchContext);
if (rescore) { // only if we do a regular search
//重新计算打分
rescorePhase.execute(searchContext);
}
//纠错
suggestPhase.execute(searchContext);
//聚合
aggregationPhase.execute(searchContext);
if (searchContext.getProfilers() != null) {
ProfileShardResult shardResults = SearchProfileShardResults
.buildShardResults(searchContext.getProfilers());
searchContext.queryResult().profileResults(shardResults);
}
}
这里可以看到首先会执行lucene的查询，然后对查询结果进行打分、执行聚合逻辑，然后生成SearchPhaseResult返回
数据节点查询数据后返回协调节点，我们继续回到executePhaseOnShard方法执行回调
//执行查询
executePhaseOnShard(shardIt, shard,
new SearchActionListener<Result>(shardIt.newSearchShardTarget(shard.currentNodeId()), shardIndex) {
@Override
public void innerOnResponse(Result result) {
try {
//分片返回结果
onShardResult(result, shardIt);
} finally {
executeNext(pendingExecutions, thread);
}
}
@Override
public void onFailure(Exception t) {
try {
onShardFailure(shardIndex, shard, shard.currentNodeId(), shardIt, t);
} finally {
executeNext(pendingExecutions, thread);
}
}
});
保存分片查询返回的数据到results数组中并进行计数
protected void onShardResult(Result result, SearchShardIterator shardIt) {
assert result.getShardIndex() != -1 : "shard index is not set";
assert result.getSearchShardTarget() != null : "search shard target must not be null";
successfulOps.incrementAndGet();
results.consumeResult(result);
hasShardResponse.set(true);
if (logger.isTraceEnabled()) {
logger.trace("got first-phase result from {}", result != null ? result.getSearchShardTarget() : null);
}
AtomicArray<ShardSearchFailure> shardFailures = this.shardFailures.get();
if (shardFailures != null) {
shardFailures.set(result.getShardIndex(), null);
}
successfulShardExecution(shardIt);
}
判断所有分片查询是否都已经返回，如果都已经返回则执行下一阶段及fetch阶段
private void successfulShardExecution(SearchShardIterator shardsIt) {
final int remainingOpsOnIterator;
if (shardsIt.skip()) {
remainingOpsOnIterator = shardsIt.remaining();
} else {
remainingOpsOnIterator = shardsIt.remaining() + 1;
}
final int xTotalOps = totalOps.addAndGet(remainingOpsOnIterator);
//所有分片都已经返回
if (xTotalOps == expectedTotalOps) {
onPhaseDone();
} else if (xTotalOps > expectedTotalOps) {
throw new AssertionError("unexpected higher total ops [" + xTotalOps + "] compared to expected ["
+ expectedTotalOps + "]");
}
}
final void onPhaseDone() { // as a tribute to @kimchy aka. finishHim()
executeNextPhase(this, getNextPhase(results, this));
}
@Override
protected SearchPhase getNextPhase(final SearchPhaseResults<SearchPhaseResult> results, final SearchPhaseContext context) {
//获取数据阶段
return new FetchSearchPhase(results, searchPhaseController, context, clusterState());
}
FetchSearchPhase(SearchPhaseResults<SearchPhaseResult> resultConsumer,
SearchPhaseController searchPhaseController,
SearchPhaseContext context,
ClusterState clusterState) {
this(resultConsumer, searchPhaseController, context, clusterState,
//最后收尾阶段
(response, scrollId) -> new ExpandSearchPhase(context, response, scrollId));
}
- fetch阶段
@Override
public void run() {
context.execute(new AbstractRunnable() {
@Override
protected void doRun() throws Exception {
// we do the heavy lifting in this inner run method where we reduce aggs etc. that's why we fork this phase
// off immediately instead of forking when we send back the response to the user since there we only need
// to merge together the fetched results which is a linear operation.
innerRun();
}
@Override
public void onFailure(Exception e) {
context.onPhaseFailure(FetchSearchPhase.this, "", e);
}
});
}
private void innerRun() throws IOException {
//查询分片数量
final int numShards = context.getNumShards();
//是否是滚动查询
final boolean isScrollSearch = context.getRequest().scroll() != null;
//search阶段返回结果
final List<SearchPhaseResult> phaseResults = queryResults.asList();
final String scrollId;
//如果是滚动查询则生成scrollId
if (isScrollSearch) {
final boolean includeContextUUID = clusterState.nodes().getMinNodeVersion().onOrAfter(Version.V_7_7_0);
scrollId = TransportSearchHelper.buildScrollId(queryResults, includeContextUUID);
} else {
scrollId = null;
}
final SearchPhaseController.ReducedQueryPhase reducedQueryPhase = resultConsumer.reduce();
final boolean queryAndFetchOptimization = queryResults.length() == 1;
//fetch结束后执行任务
final Runnable finishPhase = ()
-> moveToNextPhase(searchPhaseController, scrollId, reducedQueryPhase, queryAndFetchOptimization ?
queryResults : fetchResults);
if (queryAndFetchOptimization) {
assert phaseResults.isEmpty() || phaseResults.get(0).fetchResult() != null : "phaseResults empty [" + phaseResults.isEmpty()
+ "], single result: " + phaseResults.get(0).fetchResult();
// query AND fetch optimization
finishPhase.run();
} else {
ScoreDoc[] scoreDocs = reducedQueryPhase.sortedTopDocs.scoreDocs;
final IntArrayList[] docIdsToLoad = searchPhaseController.fillDocIdsToLoad(numShards, scoreDocs);
// no docs to fetch -- sidestep everything and return
//无文档执行fetch
if (scoreDocs.length == 0) {
// we have to release contexts here to free up resources
phaseResults.stream()
.map(SearchPhaseResult::queryResult)
.forEach(this::releaseIrrelevantSearchContext);
finishPhase.run();
} else {
final ScoreDoc[] lastEmittedDocPerShard = isScrollSearch ?
searchPhaseController.getLastEmittedDocPerShard(reducedQueryPhase, numShards)
: null;
final CountedCollector<FetchSearchResult> counter = new CountedCollector<>(r -> fetchResults.set(r.getShardIndex(), r),
docIdsToLoad.length, // we count down every shard in the result no matter if we got any results or not
finishPhase, context);
for (int i = 0; i < docIdsToLoad.length; i++) {
IntArrayList entry = docIdsToLoad[i];
SearchPhaseResult queryResult = queryResults.get(i);
if (entry == null) { // no results for this shard ID
if (queryResult != null) {
// if we got some hits from this shard we have to release the context there
// we do this as we go since it will free up resources and passing on the request on the
// transport layer is cheap.
releaseIrrelevantSearchContext(queryResult.queryResult());
progressListener.notifyFetchResult(i);
}
// in any case we count down this result since we don't talk to this shard anymore
counter.countDown();
} else {
SearchShardTarget searchShardTarget = queryResult.getSearchShardTarget();
Transport.Connection connection = context.getConnection(searchShardTarget.getClusterAlias(),
searchShardTarget.getNodeId());
//创建fetch请求
ShardFetchSearchRequest fetchSearchRequest = createFetchRequest(queryResult.queryResult().getContextId(), i, entry,
lastEmittedDocPerShard, searchShardTarget.getOriginalIndices());
//执行fetch
executeFetch(i, searchShardTarget, counter, fetchSearchRequest, queryResult.queryResult(),
connection);
}
}
}
}
}
创建fetch请求，执行fetch
private void executeFetch(final int shardIndex, final SearchShardTarget shardTarget,
final CountedCollector<FetchSearchResult> counter,
final ShardFetchSearchRequest fetchSearchRequest, final QuerySearchResult querySearchResult,
final Transport.Connection connection) {
//发送fetch请求
context.getSearchTransport().sendExecuteFetch(connection, fetchSearchRequest, context.getTask(),
new SearchActionListener<FetchSearchResult>(shardTarget, shardIndex) {
@Override
public void innerOnResponse(FetchSearchResult result) {
try {
progressListener.notifyFetchResult(shardIndex);
counter.onResult(result);
} catch (Exception e) {
context.onPhaseFailure(FetchSearchPhase.this, "", e);
}
}
@Override
public void onFailure(Exception e) {
try {
logger.debug(
() -> new ParameterizedMessage("[{}] Failed to execute fetch phase", fetchSearchRequest.contextId()), e);
progressListener.notifyFetchFailure(shardIndex, shardTarget, e);
counter.onFailure(shardIndex, shardTarget, e);
} finally {
releaseIrrelevantSearchContext(querySearchResult);
}
}
});
}
发送RPC为indices:data/read/search[phase/fetch/id]的fetch请求
public void sendExecuteFetch(Transport.Connection connection, final ShardFetchSearchRequest request, SearchTask task,
final SearchActionListener<FetchSearchResult> listener) {
sendExecuteFetch(connection, FETCH_ID_ACTION_NAME, request, task, listener);
}
数据节点注册的handler
//fetch请求
transportService.registerRequestHandler(FETCH_ID_ACTION_NAME, ThreadPool.Names.SAME, true, true, ShardFetchSearchRequest::new,
(request, channel, task) -> {
//执行请求
searchService.executeFetchPhase(request, (SearchShardTask) task,
new ChannelActionListener<>(channel, FETCH_ID_ACTION_NAME, request));
});
- 数据节点执行fetch阶段
public void executeFetchPhase(ShardFetchRequest request, SearchShardTask task, ActionListener<FetchSearchResult> listener) {
runAsync(request.contextId(), () -> {
final SearchContext context = findContext(request.contextId(), request);
context.incRef();
try {
context.setTask(task);
contextProcessing(context);
if (request.lastEmittedDoc() != null) {
context.scrollContext().lastEmittedDoc = request.lastEmittedDoc();
}
context.docIdsToLoad(request.docIds(), 0, request.docIdsSize());
try (SearchOperationListenerExecutor executor = new SearchOperationListenerExecutor(context, true, System.nanoTime())) {
//fetch查询
fetchPhase.execute(context);
if (fetchPhaseShouldFreeContext(context)) {
freeContext(request.contextId());
} else {
contextProcessedSuccessfully(context);
}
executor.success();
}
//返回结果
return context.fetchResult();
} catch (Exception e) {
logger.trace("Fetch phase failed", e);
processFailure(context, e);
throw e;
} finally {
cleanContext(context);
}
}, listener);
}
遍历文档id集合，查询详细信息
@Override
public void execute(SearchContext context) {
if (LOGGER.isTraceEnabled()) {
LOGGER.trace("{}", new SearchContextSourcePrinter(context));
}
final FieldsVisitor fieldsVisitor;
Map<String, Set<String>> storedToRequestedFields = new HashMap<>();
StoredFieldsContext storedFieldsContext = context.storedFieldsContext();
if (storedFieldsContext == null) {
// no fields specified, default to return source if no explicit indication
if (!context.hasScriptFields() && !context.hasFetchSourceContext()) {
context.fetchSourceContext(new FetchSourceContext(true));
}
fieldsVisitor = new FieldsVisitor(context.sourceRequested());
} else if (storedFieldsContext.fetchFields() == false) {
// disable stored fields entirely
fieldsVisitor = null;
} else {
for (String fieldNameOrPattern : context.storedFieldsContext().fieldNames()) {
if (fieldNameOrPattern.equals(SourceFieldMapper.NAME)) {
FetchSourceContext fetchSourceContext = context.hasFetchSourceContext() ? context.fetchSourceContext()
: FetchSourceContext.FETCH_SOURCE;
context.fetchSourceContext(new FetchSourceContext(true, fetchSourceContext.includes(), fetchSourceContext.excludes()));
continue;
}
Collection<String> fieldNames = context.mapperService().simpleMatchToFullName(fieldNameOrPattern);
for (String fieldName : fieldNames) {
MappedFieldType fieldType = context.smartNameFieldType(fieldName);
if (fieldType == null) {
// Only fail if we know it is a object field, missing paths / fields shouldn't fail.
if (context.getObjectMapper(fieldName) != null) {
throw new IllegalArgumentException("field [" + fieldName + "] isn't a leaf field");
}
} else {
String storedField = fieldType.name();
Set<String> requestedFields = storedToRequestedFields.computeIfAbsent(
storedField, key -> new HashSet<>());
requestedFields.add(fieldName);
}
}
}
boolean loadSource = context.sourceRequested();
if (storedToRequestedFields.isEmpty()) {
// empty list specified, default to disable _source if no explicit indication
fieldsVisitor = new FieldsVisitor(loadSource);
} else {
fieldsVisitor = new CustomFieldsVisitor(storedToRequestedFields.keySet(), loadSource);
}
}
try {
SearchHit[] hits = new SearchHit[context.docIdsToLoadSize()];
FetchSubPhase.HitContext hitContext = new FetchSubPhase.HitContext();
for (int index = 0; index < context.docIdsToLoadSize(); index++) {
if (context.isCancelled()) {
throw new TaskCancelledException("cancelled");
}
//文档id
int docId = context.docIdsToLoad()[context.docIdsToLoadFrom() + index];
int readerIndex = ReaderUtil.subIndex(docId, context.searcher().getIndexReader().leaves());
LeafReaderContext subReaderContext = context.searcher().getIndexReader().leaves().get(readerIndex);
int subDocId = docId - subReaderContext.docBase;
final SearchHit searchHit;
int rootDocId = findRootDocumentIfNested(context, subReaderContext, subDocId);
if (rootDocId != -1) {
searchHit = createNestedSearchHit(context, docId, subDocId, rootDocId,
storedToRequestedFields, subReaderContext);
} else {
searchHit = createSearchHit(context, fieldsVisitor, docId, subDocId,
storedToRequestedFields, subReaderContext);
}
hits[index] = searchHit;
hitContext.reset(searchHit, subReaderContext, subDocId, context.searcher());
//执行各种元数据获取
for (FetchSubPhase fetchSubPhase : fetchSubPhases) {
fetchSubPhase.hitExecute(context, hitContext);
}
}
if (context.isCancelled()) {
throw new TaskCancelledException("cancelled");
}
//执行各种元数据获取
for (FetchSubPhase fetchSubPhase : fetchSubPhases) {
fetchSubPhase.hitsExecute(context, hits);
if (context.isCancelled()) {
throw new TaskCancelledException("cancelled");
}
}
TotalHits totalHits = context.queryResult().getTotalHits();
context.fetchResult().hits(new SearchHits(hits, totalHits, context.queryResult().getMaxScore()));
} catch (IOException e) {
throw ExceptionsHelper.convertToElastic(e);
}
}
private SearchHit createSearchHit(SearchContext context,
FieldsVisitor fieldsVisitor,
int docId,
int subDocId,
Map<String, Set<String>> storedToRequestedFields,
LeafReaderContext subReaderContext) {
DocumentMapper documentMapper = context.mapperService().documentMapper();
Text typeText = documentMapper.typeText();
if (fieldsVisitor == null) {
return new SearchHit(docId, null, typeText, null, null);
}
//查询lucene保存的字段
Map<String, DocumentField> searchFields = getSearchFields(context, fieldsVisitor, subDocId,
storedToRequestedFields, subReaderContext);
Map<String, DocumentField> metaFields = new HashMap<>();
Map<String, DocumentField> documentFields = new HashMap<>();
SearchHit.splitFieldsByMetadata(searchFields, documentFields, metaFields);
SearchHit searchHit = new SearchHit(docId, fieldsVisitor.uid().id(), typeText, documentFields, metaFields);
// Set _source if requested.
SourceLookup sourceLookup = context.lookup().source();
sourceLookup.setSegmentAndDocument(subReaderContext, subDocId);
if (fieldsVisitor.source() != null) {
sourceLookup.setSource(fieldsVisitor.source());
}
return searchHit;
}
数据节点fetch数据后返回，协调节点。继续回到executeFetch方法的回调函数
@Override
public void innerOnResponse(FetchSearchResult result) {
try {
progressListener.notifyFetchResult(shardIndex);
counter.onResult(result);
} catch (Exception e) {
context.onPhaseFailure(FetchSearchPhase.this, "", e);
}
}
将返回的数据填充到fetchResults中，最后执行finish阶段
final Runnable finishPhase = ()
-> moveToNextPhase(searchPhaseController, scrollId, reducedQueryPhase, queryAndFetchOptimization ?
queryResults : fetchResults);
private void moveToNextPhase(SearchPhaseController searchPhaseController,
String scrollId, SearchPhaseController.ReducedQueryPhase reducedQueryPhase,
AtomicArray<? extends SearchPhaseResult> fetchResultsArr) {
final InternalSearchResponse internalResponse = searchPhaseController.merge(context.getRequest().scroll() != null,
reducedQueryPhase, fetchResultsArr.asList(), fetchResultsArr::get);
context.executeNextPhase(this, nextPhaseFactory.apply(internalResponse, scrollId));
}
执行ExpandSearchPhase的run方法
@Override
public void run() {
if (isCollapseRequest() && searchResponse.hits().getHits().length > 0) {
SearchRequest searchRequest = context.getRequest();
CollapseBuilder collapseBuilder = searchRequest.source().collapse();
final List<InnerHitBuilder> innerHitBuilders = collapseBuilder.getInnerHits();
MultiSearchRequest multiRequest = new MultiSearchRequest();
if (collapseBuilder.getMaxConcurrentGroupRequests() > 0) {
multiRequest.maxConcurrentSearchRequests(collapseBuilder.getMaxConcurrentGroupRequests());
}
for (SearchHit hit : searchResponse.hits().getHits()) {
BoolQueryBuilder groupQuery = new BoolQueryBuilder();
Object collapseValue = hit.field(collapseBuilder.getField()).getValue();
if (collapseValue != null) {
groupQuery.filter(QueryBuilders.matchQuery(collapseBuilder.getField(), collapseValue));
} else {
groupQuery.mustNot(QueryBuilders.existsQuery(collapseBuilder.getField()));
}
QueryBuilder origQuery = searchRequest.source().query();
if (origQuery != null) {
groupQuery.must(origQuery);
}
for (InnerHitBuilder innerHitBuilder : innerHitBuilders) {
CollapseBuilder innerCollapseBuilder = innerHitBuilder.getInnerCollapseBuilder();
SearchSourceBuilder sourceBuilder = buildExpandSearchSourceBuilder(innerHitBuilder, innerCollapseBuilder)
.query(groupQuery)
.postFilter(searchRequest.source().postFilter());
SearchRequest groupRequest = new SearchRequest(searchRequest);
groupRequest.source(sourceBuilder);
multiRequest.add(groupRequest);
}
}
context.getSearchTransport().sendExecuteMultiSearch(multiRequest, context.getTask(),
ActionListener.wrap(response -> {
Iterator<MultiSearchResponse.Item> it = response.iterator();
for (SearchHit hit : searchResponse.hits.getHits()) {
for (InnerHitBuilder innerHitBuilder : innerHitBuilders) {
MultiSearchResponse.Item item = it.next();
if (item.isFailure()) {
context.onPhaseFailure(this, "failed to expand hits", item.getFailure());
return;
}
SearchHits innerHits = item.getResponse().getHits();
if (hit.getInnerHits() == null) {
hit.setInnerHits(new HashMap<>(innerHitBuilders.size()));
}
hit.getInnerHits().put(innerHitBuilder.getName(), innerHits);
}
}
context.sendSearchResponse(searchResponse, scrollId);
}, context::onFailure)
);
} else {
//返回查询结果
context.sendSearchResponse(searchResponse, scrollId);
}
}
返回查询结果
@Override
public void sendSearchResponse(InternalSearchResponse internalSearchResponse, String scrollId) {
ShardSearchFailure[] failures = buildShardFailures();
Boolean allowPartialResults = request.allowPartialSearchResults();
assert allowPartialResults != null : "SearchRequest missing setting for allowPartialSearchResults";
if (allowPartialResults == false && failures.length > 0){
raisePhaseFailure(new SearchPhaseExecutionException("", "Shard failures", null, failures));
} else {
listener.onResponse(buildSearchResponse(internalSearchResponse, scrollId, failures));
}
}
这里的listener就是new RestStatusToXContentListener<>(channel)
@Override
public RestResponse buildResponse(Response response, XContentBuilder builder) throws Exception {
assert response.isFragment() == false; //would be nice if we could make default methods final
response.toXContent(builder, channel.request());
RestResponse restResponse = new BytesRestResponse(response.status(), builder);
if (RestStatus.CREATED == restResponse.status()) {
final String location = extractLocation.apply(response);
if (location != null) {
restResponse.addHeader("Location", location);
}
}
return restResponse;
}
@Override
public final RestResponse buildResponse(Response response) throws Exception {
return buildResponse(response, channel.newBuilder());
}
protected final void processResponse(Response response) throws Exception {
channel.sendResponse(buildResponse(response));
}
最后通过channel将结果返回客户端
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