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action support分析
Action这一部分主要是数据(索引)的操作和部分集群信息操作。 所有的请求通过client转发到对应的action上然后再由对应的TransportAction来执行相关请求。如果请求能在本机上执行则在本机上执行,否则使用Transport进行转发到对应的节点。action support部分是对action的抽象,所有的具体action都继承了support action中的某个类。这里将对这些抽象类进行分析。
这一部分总共分为broadcast(广播),master,nodes,replication及single几个部分。broadcast主要针对一些无具体目标主机的操作,如查询index是否存在,所有继承这个类的action都具有这种类似的性质;nodes主要是对节点的操作,如热点线程查询(hotThread)查询节点上的繁忙线程;replication的子类主要是需要或可以在副本上进行的操作,如索引操作,数据不仅要发送到主shard还要发送到各个副本。single则主要是目标明确的单shard操作,如get操作,根据doc的id取doc,doc 的id能够确定它在哪个shard上,因此操作也在此shard上执行。
这些support action的实现可以分为两类,第一类就是实现一个内部类作为异步操作器,子类执行doExecute时,初始化该操作器并启动。另外一种就是直接实现一个方法,子类doExecute方法调用该方法进行。TransportBroadcastOperationAction就属于前者,它实现了内部操作器AsyncBroadcastAction。TransportCountAction继承于它,它doExecute方法如下所示:
@Override protected void doExecute(CountRequest request, ActionListener<CountResponse> listener) { request.nowInMillis = System.currentTimeMillis(); super.doExecute(request, listener); }
调用父类的doExecute方法,也就是TransportBroadcastOperationAction的方法,它的实现如下所示:
@Override protected void doExecute(Request request, ActionListener<Response> listener) { new AsyncBroadcastAction(request, listener).start(); }
可以看到它初始化了AsyncBroadcastAction并启动。AsyncBroadcastAction只是确定了操作的流程,及操作完成如何返回response,并未涉及到具体的操作逻辑。因为这些逻辑都在每个子action中实现,不同的action需要进行不同的操作。如count需要count每个shard并且返回最后的总数值,而IndexExistAction则需要对比所有索引查看查询的索引是否存在。start方法的代码如下所示:
public void start() {
//没有shards if (shardsIts.size() == 0) { // no shards try { listener.onResponse(newResponse(request, new AtomicReferenceArray(0), clusterState)); } catch (Throwable e) { listener.onFailure(e); } return; } request.beforeStart(); // count the local operations, and perform the non local ones int shardIndex = -1;
//遍历对每个shards进行操作 for (final ShardIterator shardIt : shardsIts) { shardIndex++; final ShardRouting shard = shardIt.nextOrNull(); if (shard != null) { performOperation(shardIt, shard, shardIndex); } else { // really, no shards active in this group onOperation(null, shardIt, shardIndex, new NoShardAvailableActionException(shardIt.shardId())); } } }
start方法就是遍历所有shards,如果shard存在则执行performOperation方法,在这个方法中会区分该请求能否在本机上进行,能执行则调用shardOperation方法得到结果。这个方法在这是抽象的,每个子类都有实现。否则发送到对应的主机上。,如果shard为null则进行onOperation操作,遍历该shard的其它副本看能否找到可以操作的shard。performOperation代码如下所示:
protected void performOperation(final ShardIterator shardIt, final ShardRouting shard, final int shardIndex) { if (shard == null) {//shard 为null抛出异常 // no more active shards... (we should not really get here, just safety) onOperation(null, shardIt, shardIndex, new NoShardAvailableActionException(shardIt.shardId())); } else { try { final ShardRequest shardRequest = newShardRequest(shardIt.size(), shard, request); if (shard.currentNodeId().equals(nodes.localNodeId())) {//shard在本地执行shardOperation方法,并通过onOperation方法封装结果 threadPool.executor(executor).execute(new Runnable() { @Override public void run() { try { onOperation(shard, shardIndex, shardOperation(shardRequest)); } catch (Throwable e) { onOperation(shard, shardIt, shardIndex, e); } } }); } else {//不是本地shard,发送到对应节点。 DiscoveryNode node = nodes.get(shard.currentNodeId()); if (node == null) { // no node connected, act as failure onOperation(shard, shardIt, shardIndex, new NoShardAvailableActionException(shardIt.shardId())); } else { transportService.sendRequest(node, transportShardAction, shardRequest, new BaseTransportResponseHandler<ShardResponse>() { @Override public ShardResponse newInstance() { return newShardResponse(); } @Override public String executor() { return ThreadPool.Names.SAME; } @Override public void handleResponse(ShardResponse response) { onOperation(shard, shardIndex, response); } @Override public void handleException(TransportException e) { onOperation(shard, shardIt, shardIndex, e); } }); } } } catch (Throwable e) { onOperation(shard, shardIt, shardIndex, e); } } }
方法shardOperation在countTransportAction的实现如下所示:
@Override protected ShardCountResponse shardOperation(ShardCountRequest request) throws ElasticsearchException { IndexService indexService = indicesService.indexServiceSafe(request.shardId().getIndex());// IndexShard indexShard = indexService.shardSafe(request.shardId().id()); //构造查询context SearchShardTarget shardTarget = new SearchShardTarget(clusterService.localNode().id(), request.shardId().getIndex(), request.shardId().id()); SearchContext context = new DefaultSearchContext(0, new ShardSearchLocalRequest(request.types(), request.nowInMillis(), request.filteringAliases()), shardTarget, indexShard.acquireSearcher("count"), indexService, indexShard, scriptService, cacheRecycler, pageCacheRecycler, bigArrays, threadPool.estimatedTimeInMillisCounter()); SearchContext.setCurrent(context); try { // TODO: min score should move to be "null" as a value that is not initialized... if (request.minScore() != -1) { context.minimumScore(request.minScore()); } BytesReference source = request.querySource(); if (source != null && source.length() > 0) { try { QueryParseContext.setTypes(request.types()); context.parsedQuery(indexService.queryParserService().parseQuery(source)); } finally { QueryParseContext.removeTypes(); } } final boolean hasTerminateAfterCount = request.terminateAfter() != DEFAULT_TERMINATE_AFTER; boolean terminatedEarly = false; context.preProcess(); try { long count; if (hasTerminateAfterCount) {//调用lucene的封装接口执行查询并返回结果 final Lucene.EarlyTerminatingCollector countCollector = Lucene.createCountBasedEarlyTerminatingCollector(request.terminateAfter()); terminatedEarly = Lucene.countWithEarlyTermination(context.searcher(), context.query(), countCollector); count = countCollector.count(); } else { count = Lucene.count(context.searcher(), context.query()); } return new ShardCountResponse(request.shardId(), count, terminatedEarly); } catch (Exception e) { throw new QueryPhaseExecutionException(context, "failed to execute count", e); } } finally { // this will also release the index searcher context.close(); SearchContext.removeCurrent(); } }
可以看到这里是每个action真正的逻辑实现。因为这里涉及到index部分的内容,这里就不详细分析。后面关于index的分析会有涉及。这就是support action中的第一种实现。
第二种就master的相关操作,因此没有实现对应的操作类,而只是实现了一个方法。该方法的作用跟操作器作用相同,唯一的不同是它没有操作器这么多的变量, 而且它不是异步的。master的操作需要实时进行,执行过程中需要阻塞某些操作,保证集群状态一致性。这里就不再说明,请参考TransportMasterNodeOperationAction原码。
总结:本篇概括说了support action,并以countTransportAction为例说明了support Action中的异步操作器实现,最后简单的分析了master的同步操作。因为这里涉及到很多action不可能一一分析,有兴趣可以参考对应的代码。而且这里有以下index部分的内容,所以没有更深入的分析。在后面分析完index的相关功能后,会挑出几个重要的action做详细分析。
action support分析