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Solr4.8.0源码分析(5)之查询流程分析总述

Solr4.8.0源码分析(5)之查询流程分析总述

前面已经写到,solr查询是通过http发送命令,solr servlet接受并进行处理。所以solr的查询流程从SolrDispatchsFilter的dofilter开始。dofilter包含了对http的各个请求的操作。Solr的查询方式有很多,比如q,fq等,本章只关注select和q。页面下发的查询请求如下:http://localhost:8080/solr/test/select?q=code%3A%E8%BE%BD*+AND+last_modified%3A%5B0+TO+1408454600265%5D+AND+id%3Acheng&wt=json&indent=true

1   @Override2   public void doFilter(ServletRequest request, ServletResponse response, FilterChain chain) throws IOException, ServletException {3     doFilter(request, response, chain, false);4   }

由于只关注select,实际的查询是从如下代码开始:this.execute()是查询的入口函数。这里需要注意下writeResponse()函数。execute只是获取了符合查询条件的doc id,最后在writeResponse()中会根据doc id获取stored属性的字段信息,并写入返回结果。

 1  // With a valid handler and a valid core... 2           if( handler != null ) { 3             // if not a /select, create the request 4             if( solrReq == null ) { 5               solrReq = parser.parse( core, path, req ); 6             } 7  8             if (usingAliases) { 9               processAliases(solrReq, aliases, collectionsList);10             }11             12             final Method reqMethod = Method.getMethod(req.getMethod());13             HttpCacheHeaderUtil.setCacheControlHeader(config, resp, reqMethod);14             // unless we have been explicitly told not to, do cache validation15             // if we fail cache validation, execute the query16             if (config.getHttpCachingConfig().isNever304() ||17                 !HttpCacheHeaderUtil.doCacheHeaderValidation(solrReq, req, reqMethod, resp)) {18                 SolrQueryResponse solrRsp = new SolrQueryResponse();19                 /* even for HEAD requests, we need to execute the handler to20                  * ensure we don‘t get an error (and to make sure the correct21                  * QueryResponseWriter is selected and we get the correct22                  * Content-Type)23                  */24                 SolrRequestInfo.setRequestInfo(new SolrRequestInfo(solrReq, solrRsp));25                 this.execute( req, handler, solrReq, solrRsp );26                 HttpCacheHeaderUtil.checkHttpCachingVeto(solrRsp, resp, reqMethod);27               // add info to http headers28               //TODO: See SOLR-232 and SOLR-267.  29                 /*try {30                   NamedList solrRspHeader = solrRsp.getResponseHeader();31                  for (int i=0; i<solrRspHeader.size(); i++) {32                    ((javax.servlet.http.HttpServletResponse) response).addHeader(("Solr-" + solrRspHeader.getName(i)), String.valueOf(solrRspHeader.getVal(i)));33                  }34                 } catch (ClassCastException cce) {35                   log.log(Level.WARNING, "exception adding response header log information", cce);36                 }*/37                QueryResponseWriter responseWriter = core.getQueryResponseWriter(solrReq);38                writeResponse(solrRsp, response, responseWriter, solrReq, reqMethod);39             }

进入excute后会进入SolrCore的excute(), preDecorateResponse 对结果的头信息比如进行预处理,postDecorateResponse对将时间、返回结果写入response中。handleRequest继续进行查询操作。

 1   public void execute(SolrRequestHandler handler, SolrQueryRequest req, SolrQueryResponse rsp) { 2     if (handler==null) { 3       String msg = "Null Request Handler ‘" + 4         req.getParams().get(CommonParams.QT) + "‘"; 5        6       if (log.isWarnEnabled()) log.warn(logid + msg + ":" + req); 7        8       throw new SolrException(SolrException.ErrorCode.BAD_REQUEST, msg); 9     }10 11     preDecorateResponse(req, rsp);12 13     // TODO: this doesn‘t seem to be working correctly and causes problems with the example server and distrib (for example /spell)14     // if (req.getParams().getBool(ShardParams.IS_SHARD,false) && !(handler instanceof SearchHandler))15     //   throw new SolrException(SolrException.ErrorCode.BAD_REQUEST,"isShard is only acceptable with search handlers");16 17 18     handler.handleRequest(req,rsp);19     postDecorateResponse(handler, req, rsp);20 21     if (log.isInfoEnabled() && rsp.getToLog().size() > 0) {22       log.info(rsp.getToLogAsString(logid));23     }24   }

RequestHandlerBase.handleRequest(SolrQueryRequest req, SolrQueryResponse rsp)再次调用了SearchHandle.handleRequestBody(SolrQueryRequest req, SolrQueryResponse rsp),这是时候才真正开始加载QueryComponents。

以下语句会加载查询有关的组件,包括QueryComponents,FacetComponents,MoreLikeThisComponent,HighlightComponent,StatsComponent,

DebugComponent,ExpandComponent。本文只关注查询,所以进入的QueryComponent.java.

for( SearchComponent c : components ) {    c.process(rb);}    

暂且不提QueryComponent.java中的关于Query的处理(查询的细节将在后面章节中说明,本章只作总述),QueryComponent.process

(ResponseBuilder rb) 会调用SolrindexSearch.search(QueryResult qr, QueryCommand cmd)进行查询,并在后续代码中对返回的结果进行处理,主要包括doFieldSortValues(rb, searcher);和doPrefetch(rb);

 1     // normal search result 2     searcher.search(result,cmd); 3     rb.setResult( result ); 4  5     ResultContext ctx = new ResultContext(); 6     ctx.docs = rb.getResults().docList; 7     ctx.query = rb.getQuery(); 8     rsp.add("response", ctx); 9     rsp.getToLog().add("hits", rb.getResults().docList.matches());10 11     if ( ! rb.req.getParams().getBool(ShardParams.IS_SHARD,false) ) {12       if (null != rb.getNextCursorMark()) {13         rb.rsp.add(CursorMarkParams.CURSOR_MARK_NEXT, 14                    rb.getNextCursorMark().getSerializedTotem());15       }16     }17     doFieldSortValues(rb, searcher);18     doPrefetch(rb);

SolrindexSearch.search函数比较简单,只是调用了SolrindexSearch.getDocListC.顾名思义,该函数返回了查询结果的doc id 的list。这时候才是真正的查询开始。查询之前,Solr会从queryResultCache缓存里面读取该条件的结果,queryResultCache里面存放了查询条件和查询结果的键值对。如果queryResultCache里面有这个查询条件,那Solr就会直接返回查询条件的值。如果没有该查询条件,则会进行正常查询,并把查询条件和查询命令写入queryResultCache的键值对里。queryResultCache具有容量大小,可以在solrconfig的缓存配置里进行配置。

 1     // we can try and look up the complete query in the cache. 2     // we can‘t do that if filter!=null though (we don‘t want to 3     // do hashCode() and equals() for a big DocSet). 4     if (queryResultCache != null && cmd.getFilter()==null 5         && (flags & (NO_CHECK_QCACHE|NO_SET_QCACHE)) != ((NO_CHECK_QCACHE|NO_SET_QCACHE))) 6     { 7         // all of the current flags can be reused during warming, 8         // so set all of them on the cache key. 9         key = new QueryResultKey(q, cmd.getFilterList(), cmd.getSort(), flags);10         if ((flags & NO_CHECK_QCACHE)==0) {11           superset = queryResultCache.get(key);12 13           if (superset != null) {14             // check that the cache entry has scores recorded if we need them15             if ((flags & GET_SCORES)==0 || superset.hasScores()) {16               // NOTE: subset() returns null if the DocList has fewer docs than17               // requested18               out.docList = superset.subset(cmd.getOffset(),cmd.getLen());19             }20           }21           if (out.docList != null) {22             // found the docList in the cache... now check if we need the docset too.23             // OPT: possible future optimization - if the doclist contains all the matches,24             // use it to make the docset instead of rerunning the query.25             if (out.docSet==null && ((flags & GET_DOCSET)!=0) ) {26               if (cmd.getFilterList()==null) {27                 out.docSet = getDocSet(cmd.getQuery());28               } else {29                 List<Query> newList = new ArrayList<>(cmd.getFilterList().size()+1);30                 newList.add(cmd.getQuery());31                 newList.addAll(cmd.getFilterList());32                 out.docSet = getDocSet(newList);33               }34             }35             return;36           }37         }38 39       // If we are going to generate the result, bump up to the40       // next resultWindowSize for better caching.41 42       if ((flags & NO_SET_QCACHE) == 0) {43         // handle 0 special case as well as avoid idiv in the common case.44         if (maxDocRequested < queryResultWindowSize) {45           supersetMaxDoc=queryResultWindowSize;46         } else {47           supersetMaxDoc = ((maxDocRequested -1)/queryResultWindowSize + 1)*queryResultWindowSize;48           if (supersetMaxDoc < 0) supersetMaxDoc=maxDocRequested;49         }50       } else {51         key = null;  // we won‘t be caching the result52       }53     }

如果没有复合的缓存,那么将进行正常的查询。这里查询会走排序和非排序的查询分支(两个分支的差别将在后续文章中写道)。最后查询会进入getDocListNC(qr,cmd)函数继续进行查询。superset.subset()会对查询结果进行截断,比如我查询的结果start=20,row=40,那么Solr查询实际的结果是start=0,row=60,也就是至少说会查(start+row)个结果,然后再获取第20到第60的结果集。

if (useFilterCache) {      // now actually use the filter cache.      // for large filters that match few documents, this may be      // slower than simply re-executing the query.      if (out.docSet == null) {        out.docSet = getDocSet(cmd.getQuery(),cmd.getFilter());        DocSet bigFilt = getDocSet(cmd.getFilterList());        if (bigFilt != null) out.docSet = out.docSet.intersection(bigFilt);      }      // todo: there could be a sortDocSet that could take a list of      // the filters instead of anding them first...      // perhaps there should be a multi-docset-iterator      sortDocSet(qr, cmd);    } else {      // do it the normal way...      if ((flags & GET_DOCSET)!=0) {        // this currently conflates returning the docset for the base query vs        // the base query and all filters.        DocSet qDocSet = getDocListAndSetNC(qr,cmd);        // cache the docSet matching the query w/o filtering        if (qDocSet!=null && filterCache!=null && !qr.isPartialResults()) filterCache.put(cmd.getQuery(),qDocSet);      } else {        getDocListNC(qr,cmd);      }      assert null != out.docList : "docList is null";    }    if (null == cmd.getCursorMark()) {      // Kludge...      // we can‘t use DocSlice.subset, even though it should be an identity op      // because it gets confused by situations where there are lots of matches, but      // less docs in the slice then were requested, (due to the cursor)      // so we have to short circuit the call.      // None of which is really a problem since we can‘t use caching with      // cursors anyway, but it still looks weird to have to special case this      // behavior based on this condition - hence the long explanation.      superset = out.docList;      out.docList = superset.subset(cmd.getOffset(),cmd.getLen());    } else {      // sanity check our cursor assumptions      assert null == superset : "cursor: superset isn‘t null";      assert 0 == cmd.getOffset() : "cursor: command offset mismatch";      assert 0 == out.docList.offset() : "cursor: docList offset mismatch";      assert cmd.getLen() >= supersetMaxDoc : "cursor: superset len mismatch: " +        cmd.getLen() + " vs " + supersetMaxDoc;    }

SolrIndexSearch.getDocListNC(qr,cmd)里面定义了许多Collector的内部类,不过暂时与本章节无关,所以直接查看以下这段代码。首先Solr会创建TopDocsCollector,它会存放所有复合查询条件的结果集。如果查询的时候设置了timeAllowed开关,那么查询就会走TimeLimitingCollector分支。TimeLimitingCollector是Collector的子类,当timeAllowed设定一个数字时,比如200ms,如果Solr查询一旦获取到结果就会在200ms内返回,不管查询的结果是否已经完整。可以看见最后查询过程最后调用了Lucene IndexSearch.Search(),这层开始进入Lucene.最后Solr会对TopDocsCollector的结果总数以及优先级队列进行处理。

 1 final TopDocsCollector topCollector = buildTopDocsCollector(len, cmd); 2       Collector collector = topCollector; 3       if (terminateEarly) { 4         collector = new EarlyTerminatingCollector(collector, cmd.len); 5       } 6       if( timeAllowed > 0 ) { 7         collector = new TimeLimitingCollector(collector, TimeLimitingCollector.getGlobalCounter(), timeAllowed); 8       } 9       if (pf.postFilter != null) {10         pf.postFilter.setLastDelegate(collector);11         collector = pf.postFilter;12       }13       try {14         super.search(query, luceneFilter, collector);15         if(collector instanceof DelegatingCollector) {16           ((DelegatingCollector)collector).finish();17         }18       }19       catch( TimeLimitingCollector.TimeExceededException x ) {20         log.warn( "Query: " + query + "; " + x.getMessage() );21         qr.setPartialResults(true);22       }23 24       totalHits = topCollector.getTotalHits();25       TopDocs topDocs = topCollector.topDocs(0, len);26       populateNextCursorMarkFromTopDocs(qr, cmd, topDocs);27 28       maxScore = totalHits>0 ? topDocs.getMaxScore() : 0.0f;29       nDocsReturned = topDocs.scoreDocs.length;30       ids = new int[nDocsReturned];31       scores = (cmd.getFlags()&GET_SCORES)!=0 ? new float[nDocsReturned] : null;32       for (int i=0; i<nDocsReturned; i++) {33         ScoreDoc scoreDoc = topDocs.scoreDocs[i];34         ids[i] = scoreDoc.doc;35         if 

进入Lucene的IndexSearch.Search()后,Solr开始对所有Segment进行遍历,AtomicReaderContext包含了Segment的所有信息,包括docbase,doc的个数。

遍历完后,会调用Weight.bulkScore()对多个条件进行重组,比如多个OR的条件组成一个条件,多个AND的查询条件再组成一个List。Weight.bulkScore()会对这个List按照查询条件的词频进行排序。对条件处理好以后,就是会从segment里面获取所有符合查询条件的doc id(具体的获取方法,在后续的文章里会详细介绍),这就是scorer.score(collector);的作用了。

 1  /** 2    * Lower-level search API. 3    *  4    * <p> 5    * {@link Collector#collect(int)} is called for every document. <br> 6    *  7    * <p> 8    * NOTE: this method executes the searches on all given leaves exclusively. 9    * To search across all the searchers leaves use {@link #leafContexts}.10    * 11    * @param leaves 12    *          the searchers leaves to execute the searches on13    * @param weight14    *          to match documents15    * @param collector16    *          to receive hits17    * @throws BooleanQuery.TooManyClauses If a query would exceed 18    *         {@link BooleanQuery#getMaxClauseCount()} clauses.19    */20   protected void search(List<AtomicReaderContext> leaves, Weight weight, Collector collector)21       throws IOException {22 23     // TODO: should we make this24     // threaded...?  the Collector could be sync‘d?25     // always use single thread:26     for (AtomicReaderContext ctx : leaves) { // search each subreader27       try {28         collector.setNextReader(ctx);29       } catch (CollectionTerminatedException e) {30         // there is no doc of interest in this reader context31         // continue with the following leaf32         continue;33       }34       BulkScorer scorer = weight.bulkScorer(ctx, !collector.acceptsDocsOutOfOrder(), ctx.reader().getLiveDocs());35       if (scorer != null) {36         try {37           scorer.score(collector);38         } catch (CollectionTerminatedException e) {39           // collection was terminated prematurely40           // continue with the following leaf41         }42       }43     }44   }

到这一步已经获取到符合查询条件的所有doc id了,但是我们的查询结果是需要显示多有的字段的,所以也就是说Solr后面还是会根据doc id再次取segment获取所有字段信息,至于这是在哪里实现的,在后续文章中会详细描述。

 

总结: Solr的查询过程还是比较绕的,且有很多可以优化的地方。本文主要简述了Solr查询的流程,对查询过程中的细节将在后续的文章里面具体阐述。