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solr源码解读(转)
solr源码解读(转)原文地址:http://blog.csdn.net/duck_genuine/article/details/6962624
配置
solr 对一个搜索请求的的流程
在solrconfig.xml会配置一个handler。配置了前置处理组件preParams,还有后置处理组件filterResult,当然还有默认的组件
- <requestHandler name="standard" class="solr.SearchHandler" default="true">
- <arr name="first-components">
- <str>preParams</str>
- </arr>
- <lst name="defaults">
- <str name="echoParams">explicit</str>
- <int name="rows">10</int>
- <int name="start">0</int>
- <str name="q">*:*</str>
- </lst>
- <arr name="last-components">
- <str>filterResult</str>
- </arr>
- </requestHandler>
http请求控制器
当一个查询请求过来的时候,先到类SolrDispatchFilter,由这个分发器寻找对应的handler来处理。
- String qt = solrReq.getParams().get( CommonParams.QT );
- handler = core.getRequestHandler( qt );
---------------------------------------------------------------------------------------------------
- this.execute( req, handler, solrReq, solrRsp );
- HttpCacheHeaderUtil.checkHttpCachingVeto(solrRsp, resp, reqMethod);
-----------------------------------------------------------------------------------------------
从上面的代码里看出是由solrCore留下的接口来处理请求。从代码框架上,从此刻开始进入solr的核心代码。
- protected void execute( HttpServletRequest req, SolrRequestHandler handler, SolrQueryRequest sreq, SolrQueryResponse rsp) {
- sreq.getContext().put( "webapp", req.getContextPath() );
- sreq.getCore().execute( handler, sreq, rsp );
- }
看一下solrCore代码execute的方法 的主要代码
- public void execute(SolrRequestHandler handler, SolrQueryRequest req, SolrQueryResponse rsp) {
- 。。。。。
- handler.handleRequest(req,rsp);
- setResponseHeaderValues(handler,req,rsp);
- 。。。。。。。
- }
主要实现对请求的处理,并将请求结果的状态信息写到响应的头部
SolrRequestHandler 处理器
再看一下对请求的处理。。先看定义该请求处理器的接口,可以更好理解。只有两个方法,一个是初始化信息,主要是配置时的默认参数,另一个就是处理请求的接口。
- public interface SolrRequestHandler extends SolrInfoMBean {
- public void init(NamedList args);
- public void handleRequest(SolrQueryRequest req, SolrQueryResponse rsp);
- }
先看一下实现该接口的类RequestHandlerBase
- public void handleRequest(SolrQueryRequest req, SolrQueryResponse rsp) {
- numRequests++;
- try {
- SolrPluginUtils.setDefaults(req,defaults,appends,invariants);
- rsp.setHttpCaching(httpCaching);
- handleRequestBody( req, rsp );
- // count timeouts
- NamedList header = rsp.getResponseHeader();
- if(header != null) {
- Object partialResults = header.get("partialResults");
- boolean timedOut = partialResults == null ? false : (Boolean)partialResults;
- if( timedOut ) {
- numTimeouts++;
- rsp.setHttpCaching(false);
- }
- }
- } catch (Exception e) {
- SolrException.log(SolrCore.log,e);
- if (e instanceof ParseException) {
- e = new SolrException(SolrException.ErrorCode.BAD_REQUEST, e);
- }
- rsp.setException(e);
- numErrors++;
- }
- totalTime += rsp.getEndTime() - req.getStartTime();
- }
主要记录该请求处理的状态与处理时间记录。真正的实现方法交由各个子类 handleRequestBody( req, rsp );
现在看一下SearchHandler对于搜索处理的实现方法
首先是将solrconfig.xml上配置的各个处理组件按一定顺序组装起来,先是first-Component,默认的component,last-component.这些处理组件会按照它们的顺序来执行,以下是searchHandler的实现主体。方法handleRequestBody
- @Override
- public void handleRequestBody(SolrQueryRequest req, SolrQueryResponse rsp) throws Exception, ParseException, InstantiationException, IllegalAccessException
- {
- // int sleep = req.getParams().getInt("sleep",0);
- // if (sleep > 0) {log.error("SLEEPING for " + sleep); Thread.sleep(sleep);}
- ResponseBuilder rb = new ResponseBuilder();
- rb.req = req;
- rb.rsp = rsp;
- rb.components = components;
- rb.setDebug(req.getParams().getBool(CommonParams.DEBUG_QUERY, false));
- final RTimer timer = rb.isDebug() ? new RTimer() : null;
- if (timer == null) {
- // non-debugging prepare phase
- for( SearchComponent c : components ) {
- c.prepare(rb);
- }
- } else {
- // debugging prepare phase
- RTimer subt = timer.sub( "prepare" );
- for( SearchComponent c : components ) {
- rb.setTimer( subt.sub( c.getName() ) );
- c.prepare(rb);
- rb.getTimer().stop();
- }
- subt.stop()<span style="color:#FF0000;">;</span>
- }
- //单机版
- if (rb.shards == null) {
- // a normal non-distributed request
- // The semantics of debugging vs not debugging are different enough that
- // it makes sense to have two control loops
- if(!rb.isDebug()) {
- // Process
- for( SearchComponent c : components ) {
- c.process(rb);
- }
- }
- else {
- // Process
- RTimer subt = timer.sub( "process" );
- for( SearchComponent c : components ) {
- rb.setTimer( subt.sub( c.getName() ) );
- c.process(rb);
- rb.getTimer().stop();
- }
- subt.stop();
- timer.stop();
- // add the timing info
- if( rb.getDebugInfo() == null ) {
- rb.setDebugInfo( new SimpleOrderedMap<Object>() );
- }
- rb.getDebugInfo().add( "timing", timer.asNamedList() );
- }
- } else {//分布式请求
- // a distributed request
- HttpCommComponent comm = new HttpCommComponent();
- if (rb.outgoing == null) {
- rb.outgoing = new LinkedList<ShardRequest>();
- }
- rb.finished = new ArrayList<ShardRequest>();
- //起始状态为0,结束状态为整数的最大值
- int nextStage = 0;
- do {
- rb.stage = nextStage;
- nextStage = ResponseBuilder.STAGE_DONE;
- // call all components
- for( SearchComponent c : components ) {
- //得到所有组件运行后返回的下一个状态,并取最小值
- nextStage = Math.min(nextStage, c.distributedProcess(rb));
- }
- // 如果有需要向子机发送请求
- while (rb.outgoing.size() > 0) {
- // submit all current request tasks at once
- while (rb.outgoing.size() > 0) {
- ShardRequest sreq = rb.outgoing.remove(0);
- sreq.actualShards = sreq.shards;
- if (sreq.actualShards==ShardRequest.ALL_SHARDS) {
- sreq.actualShards = rb.shards;
- }
- sreq.responses = new ArrayList<ShardResponse>();
- // 向各个子机发送请求
- for (String shard : sreq.actualShards) {
- ModifiableSolrParams params = new ModifiableSolrParams(sreq.params);
- params.remove(ShardParams.SHARDS); // not a top-level request
- params.remove("indent");
- params.remove(CommonParams.HEADER_ECHO_PARAMS);
- params.set(ShardParams.IS_SHARD, true); // a sub (shard) request
- String shardHandler = req.getParams().get(ShardParams.SHARDS_QT);
- if (shardHandler == null) {
- params.remove(CommonParams.QT);
- } else {
- params.set(CommonParams.QT, shardHandler);
- }
- //提交子请求
- comm.submit(sreq, shard, params);
- }
- }
- // now wait for replies, but if anyone puts more requests on
- // the outgoing queue, send them out immediately (by exiting
- // this loop)
- while (rb.outgoing.size() == 0) {
- ShardResponse srsp = comm.takeCompletedOrError();
- if (srsp == null) break; // no more requests to wait for
- // Was there an exception? If so, abort everything and
- // rethrow
- if (srsp.getException() != null) {
- comm.cancelAll();
- if (srsp.getException() instanceof SolrException) {
- throw (SolrException)srsp.getException();
- } else {
- throw new SolrException(SolrException.ErrorCode.SERVER_ERROR, srsp.getException());
- }
- }
- rb.finished.add(srsp.getShardRequest());
- //每个组件都对于返回的数据处理
- for(SearchComponent c : components) {
- c.handleResponses(rb, srsp.getShardRequest());
- }
- }
- }//请求队列结束
- //再对该轮请求进行收尾工作
- for(SearchComponent c : components) {
- c.finishStage(rb);
- }
- //如果状态未到结束,则继续循环
- } while (nextStage != Integer.MAX_VALUE);
- }
- }
首先运行的是各个组件的方法prepare
- for( SearchComponent c : components ) {
- c.prepare(rb);
- }
再则如果不是分布式搜索,则比较简单的运行
- for( SearchComponent c : components ) {
- c.process(rb);
- }
就结束!
如果是分布式搜索,过程会比较复杂些,对于每个组件处理都会返回一个状态,对于以下几个方法循环执行,直到状态结束 。
在类ResponseBuilder定义了几个状态。
- public static int STAGE_START = 0;
- public static int STAGE_PARSE_QUERY = 1000;
- public static int STAGE_EXECUTE_QUERY = 2000;
- public static int STAGE_GET_FIELDS = 3000;
- public static int STAGE_DONE = Integer.MAX_VALUE;
从STAGE_START---->STAGE_PARSE_QUERY------>STAGE_EXECUTE_QUERY--------------->STAGE_GET_FIELDS------------>STAGE_DONE
从这些状态名称可以猜得出整个对应的过程。
每个组件先调用方法distributeProcess,并返回下一个状态
- for( SearchComponent c : components ) {
- // the next stage is the minimum of what all components report
- nextStage = Math.min(nextStage, c.distributedProcess(rb));
- }
而方法handleResponse主要处理返回来的数据
- for(SearchComponent c : components) {
- c.handleResponses(rb, srsp.getShardRequest());
- }
然后交由finishStage方法来对每一个状态的过程作结束动作。
------------------------------
- for(SearchComponent c : components) {
- c.finishStage(rb);
- }
-----------------------------
了解这个流程有助于扩展solr。比如有个业务是要我对搜索的自然结果排序进行干预,而这个干预只针对前几页结果,所以我不得不做个组件来对其中结果进行处理。
所以我想可以添加一个组件放在最后-------------》
1)如果是分布式搜索:
这个组件可以在重写finsihStage做处理。算是对最终结果的排序处理即可。
2)如果只是单机:
这个组件可以在重写process做处理
组件
现在看一下其中一个主要的组件QueryComponent
prepare
对于QueryComponent主要解析用户传送的语法解析参数defType,以及过滤查询fq,返回字段集fl.排序字段Sort
单机处理
process
分布式搜索过程中的某一步,这里应该是主机要合并文档,取出对应的文档的过程,
主机发出指定的solr主键ids来取文档集,首先取出对应的lucene的内部id集。如果某些文档已不在则弃掉。
- String ids = params.get(ShardParams.IDS);
- if (ids != null) {//将传过来的ids,放进结果集中,并在后面取出对应的结果文档
- SchemaField idField = req.getSchema().getUniqueKeyField();
- List<String> idArr = StrUtils.splitSmart(ids, ",", true);
- int[] luceneIds = new int[idArr.size()];
- int docs = 0;
- for (int i=0; i<idArr.size(); i++) {
- //solr主键id对应的文档lucene内部的id
- int id = req.getSearcher().getFirstMatch(
- new Term(idField.getName(), idField.getType().toInternal(idArr.get(i))));
- if (id >= 0)
- luceneIds[docs++] = id;
- }
- DocListAndSet res = new DocListAndSet();
- //这里并没有传入scores[]
- res.docList = new DocSlice(0, docs, luceneIds, null, docs, 0);
- //需要另一种doc集合处理。
- if (rb.isNeedDocSet()) {
- List<Query> queries = new ArrayList<Query>();
- queries.add(rb.getQuery());
- List<Query> filters = rb.getFilters();
- if (filters != null)
- queries.addAll(filters);
- res.docSet = searcher.getDocSet(queries);
- }
- rb.setResults(res);
- rsp.add("response",rb.getResults().docList);
- return;
- }
- <pre name="code" class="java"> //封装搜索值对象与封装结果值对象
- SolrIndexSearcher.QueryCommand cmd = rb.getQueryCommand();
- //设置超时最大值
- cmd.setTimeAllowed(timeAllowed);
- SolrIndexSearcher.QueryResult result = new SolrIndexSearcher.QueryResult();
- //搜索
- searcher.search(result,cmd);
- //设置搜索结果
- rb.setResult( result );
- rsp.add("response",rb.getResults().docList);
- rsp.getToLog().add("hits", rb.getResults().docList.matches());
- //对含有字段排序处理
- doFieldSortValues(rb, searcher);
- //非分布查询过程,且搜索结果数小于50,进行缓存
- doPrefetch(rb);
- <pre name="code" class="java"><p>目前看到真实获取文档内容的是在</p><p>QueryResponseWriter</p><p>例如xml的输出格式类XMLWriter</p></pre><p></p>
- <pre></pre>
- <pre></pre>
- <br>
- <p></p>
- <h2><a name="t10"></a>分布式处理<br>
- </h2>
- <h3><a name="t11"></a>1)distributedProcess</h3>
- <p></p><pre name="code" class="java"> @Override
- public int distributedProcess(ResponseBuilder rb) throws IOException {
- if (rb.stage < ResponseBuilder.STAGE_PARSE_QUERY)
- return ResponseBuilder.STAGE_PARSE_QUERY;
- if (rb.stage == ResponseBuilder.STAGE_PARSE_QUERY) {
- createDistributedIdf(rb);
- return ResponseBuilder.STAGE_EXECUTE_QUERY;
- }
- if (rb.stage < ResponseBuilder.STAGE_EXECUTE_QUERY) return ResponseBuilder.STAGE_EXECUTE_QUERY;
- if (rb.stage == ResponseBuilder.STAGE_EXECUTE_QUERY) {
- //分布式查询
- createMainQuery(rb);
- return ResponseBuilder.STAGE_GET_FIELDS;
- }
- if (rb.stage < ResponseBuilder.STAGE_GET_FIELDS) return ResponseBuilder.STAGE_GET_FIELDS;
- if (rb.stage == ResponseBuilder.STAGE_GET_FIELDS) {
- //这里就会去对应的主机拿取需要的字段,封装请求字段的参数,放进请求队列里,可以由外部的searchHandler提交该请求,最后结果放在ShardResponse类里。
- createRetrieveDocs(rb);
- return ResponseBuilder.STAGE_DONE;
- }
- return ResponseBuilder.STAGE_DONE;
- }</pre><br>
- <br>
- <p></p>
- <p> <br>
- </p>
- <p><br>
- </p>
- <h3><a name="t12"></a> 2) handleResponses<br>
- </h3>
- <pre name="code" class="java"> public void handleResponses(ResponseBuilder rb, ShardRequest sreq) {
- if ((sreq.purpose & ShardRequest.PURPOSE_GET_TOP_IDS) != 0) {
- //合并ids
- mergeIds(rb, sreq);
- //合并groupCount
- mergeGroupCounts(rb, sreq);
- }
- if ((sreq.purpose & ShardRequest.PURPOSE_GET_FIELDS) != 0) {
- //获取文档的字段,并将结题组装起来放到最终结果列表对应的位置里
- returnFields(rb, sreq);
- return;
- }
- }</pre><br>
- <br>
- <h3><a name="t13"></a> 3) finishStage</h3>
- <p><br>
- </p>
- <p> </p><pre name="code" class="java"> @Override
- public void finishStage(ResponseBuilder rb) {
- //这里说是==获取文档内容的值,在
- if (rb.stage == ResponseBuilder.STAGE_GET_FIELDS) {
- //有些文档可能已不存在了,则忽略掉
- for (Iterator<SolrDocument> iter = rb._responseDocs.iterator(); iter.hasNext();) {
- if (iter.next() == null) {
- iter.remove();
- rb._responseDocs.setNumFound(rb._responseDocs.getNumFound()-1);
- }
- }
- rb.rsp.add("response", rb._responseDocs);
- }
- }
- </pre><br>
- <p></p>
- <p><span style="color:#FF0000"><br>
- </span></p>
- <p><span style="color:#FF0000">同样最后的结果是保存在<br>
- <br>
- ResponseBuilder <br>
- <br>
- ResponseBuilder <br>
- NamedList values = new SimpleOrderedMap();<br>
- <br>
- 这个字段里,以键为"response",单机存储的是lucene 的内部id列表<br>
- 如果是分布式,则存储的是SolrDocumentList,不用再去索引拿出对应的存储字段,<br>
- 这个在QueryResponseWriter里有对应的处理</span><br>
- </p>
- <p></p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p><br>
- </p>
- <p></p>
- </pre>
solr源码解读(转)