Nutch 1.3 学习笔记 7 CrawlDb - updatedb

分类： Nutch 2011-08-28 23:33  418人阅读  评论(3)  收藏  举报

Nutch 1.3 学习笔记 7 CrawlDb - updatedb
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这里主要看一下CrawlDb中的updatedb，它主要是用来更新CrawlDb数据库的

1. bin/nutch updatedb

我们用nutch的命令行时会看到一个方法叫updatedb，其实这个方法就是调用CrawlDb.java类中的update方法，它的参数帮助如下：

 Usage: CrawlDb <crawldb> (-dir <segments> | <seg1> <seg2> ...) [-force] [-normalize] [-filter] [-noAdditions]
     crawldb CrawlDb to update
     -dir segments   parent directory containing all segments to update from
     seg1 seg2 ...   list of segment names to update from
     -force  force update even if CrawlDb appears to be locked (CAUTION advised)
     -normalize  use URLNormalizer on urls in CrawlDb and segment (usually not needed)
     -filter use URLFilters on urls in CrawlDb and segment
     -noAdditions    only update already existing URLs, don't add any newly discovered URLs

2. 下面我们来分析一下其update方法到底做了些什么

2.1 update的任务提交参数，部分代码如下

 // 生成一个新的任务,这里面也做了一些相应的配置，
     // 加入了current目录，就是初始的CrawlDb目录，设置了输入格式为SequenceFileInputFormat
     // 配置了Map-Reducer为CrawlDbFilter-CrawlDbReducer
     // 配置了输出格式为MapFileOutputFormat
     // 还配置了输出的<key,value>类型<Text,CrawlDatum>
     JobConf job = CrawlDb.createJob(getConf(), crawlDb);
     // 配置一些参数
     job.setBoolean(CRAWLDB_ADDITIONS_ALLOWED, additionsAllowed);
     job.setBoolean(CrawlDbFilter.URL_FILTERING, filter);
     job.setBoolean(CrawlDbFilter.URL_NORMALIZING, normalize);
     // 加入输入目录，一个是crawl_fetch,另一个是crawl_parse
     for (int i = 0; i < segments.length; i++) {
       Path fetch = new Path(segments[i], CrawlDatum.FETCH_DIR_NAME);
       Path parse = new Path(segments[i], CrawlDatum.PARSE_DIR_NAME);
       if (fs.exists(fetch) && fs.exists(parse)) {
         FileInputFormat.addInputPath(job, fetch);
         FileInputFormat.addInputPath(job, parse);
       } else {
         LOG.info(" - skipping invalid segment " + segments[i]);
       }
     }

2.2 分析一下其任务的Map-Reducer做了些什么

CrawlDbFilter主要是对url进行过滤和正规化。
CrawlDbReducer主要是用来聚合相同url(老的与新产生的)的，这东东写得很复杂，下面来分析一下其源代码：

 public void reduce(Text key, Iterator<CrawlDatum> values,
                      OutputCollector<Text, CrawlDatum> output, Reporter reporter)
     throws IOException {


     CrawlDatum fetch = new CrawlDatum();
     CrawlDatum old = new CrawlDatum();


     boolean fetchSet = false;
     boolean oldSet = false;
     byte[] signature = null;
     boolean multiple = false; // avoid deep copy when only single value exists
     linked.clear();
     org.apache.hadoop.io.MapWritable metaFromParse = null;

     // 这个循环主要是遍历所有相同url的value(CrawlDatum)值，对old和fetch两个变量进行赋值。
     // 和收集其外链接，把它们放入一个按分数排序的优先队列中去
     while (values.hasNext()) {
       CrawlDatum datum = (CrawlDatum)values.next();
       // 判断是否要对CrawlDatum进行深度复制
       if (!multiple && values.hasNext()) multiple = true;
       // 判断CrawlDatum中是否有数据库相关的参数，如STATUS_DB_(UNFETCHED|FETCHED|GONE|REDIR_TEMP|REDIR_PERM|NOTMODIFIED)
       if (CrawlDatum.hasDbStatus(datum)) {
         if (!oldSet) {
           if (multiple) {
             old.set(datum);
           } else {
             // no need for a deep copy - this is the only value
             old = datum;
           }
           oldSet = true;
         } else {
           // always take the latest version
           // 总是得到最新的CrawlDatum版本
           if (old.getFetchTime() < datum.getFetchTime()) old.set(datum);
         }
         continue;
       }


         // 判断CrawlDatum是否有关抓取的状态，如STATUS_FETCH_(SUCCESS|RETRY|REDIR_TEMP|REDIR_PERM|GONE|NOTMODIFIED)
       if (CrawlDatum.hasFetchStatus(datum)) {
         if (!fetchSet) {
           if (multiple) {
             fetch.set(datum);
           } else {
             fetch = datum;
           }
           fetchSet = true;
         } else {
           // always take the latest version
           if (fetch.getFetchTime() < datum.getFetchTime()) fetch.set(datum);
         }
         continue;
       }


     // 根据CrawlDatum的状态来收集另一些信息
       switch (datum.getStatus()) {                // collect other info
           // 如果这个CrawlDatum是一个外链接，那放入一个优先队列中，按分数的降序来做
       case CrawlDatum.STATUS_LINKED:
         CrawlDatum link;
         if (multiple) {
           link = new CrawlDatum();
           link.set(datum);
         } else {
           link = datum;
         }
         linked.insert(link);
         break;
       case CrawlDatum.STATUS_SIGNATURE:
         // 得到其唯一ID号
         signature = datum.getSignature();
         break;
       case CrawlDatum.STATUS_PARSE_META:
         // 得到其元数据
         metaFromParse = datum.getMetaData();
         break;
       default:
         LOG.warn("Unknown status, key: " + key + ", datum: " + datum);
       }
     }

     // copy the content of the queue into a List
     // in reversed order
     int numLinks = linked.size();
     List<CrawlDatum> linkList = new ArrayList<CrawlDatum>(numLinks);
     for (int i = numLinks - 1; i >= 0; i--) {
       linkList.add(linked.pop());
     }

     // 如果这个CrawlDatum集合中没有数据库相关的状态(也就是说没有这个url的原始状态)或者配置了不添加外链接，直接返回
     // if it doesn't already exist, skip it
     if (!oldSet && !additionsAllowed) return;

     // if there is no fetched datum, perhaps there is a link
     // 如果这个CrawlDatum集合中没有和抓取相关的状态，并且外链接数量要大于0
     if (!fetchSet && linkList.size() > 0) {
       fetch = linkList.get(0); // 得到第一个外链接
       fetchSet = true;
     }

     // still no new data - record only unchanged old data, if exists, and return
     // 如果没有抓取相头的状态，也没有外链接，也就是说这个CrawlDatum是老的，
     if (!fetchSet) {
         // 判断是否有和数据库相关的状态，有的话就输出,没有的话就直接返回
       if (oldSet) {// at this point at least "old" should be present
         output.collect(key, old);
       } else {
         LOG.warn("Missing fetch and old value, signature=" + signature);
       }
       return;
     }

     // 下面是用来初始化最新的CrawlDatum版本
     if (signature == null) signature = fetch.getSignature();
     long prevModifiedTime = oldSet ? old.getModifiedTime() : 0L;
     long prevFetchTime = oldSet ? old.getFetchTime() : 0L;


     // initialize with the latest version, be it fetch or link
     result.set(fetch);
     if (oldSet) {
       // copy metadata from old, if exists
       if (old.getMetaData().size() > 0) {
         result.putAllMetaData(old);
         // overlay with new, if any
         if (fetch.getMetaData().size() > 0)
           result.putAllMetaData(fetch);
       }
       // set the most recent valid value of modifiedTime
       if (old.getModifiedTime() > 0 && fetch.getModifiedTime() == 0) {
         result.setModifiedTime(old.getModifiedTime());
       }
     }

     下面是用来确定其最新的状态
     switch (fetch.getStatus()) {                // determine new status


     case CrawlDatum.STATUS_LINKED:                // it was link
       if (oldSet) {                          // if old exists
         result.set(old);                          // use it
       } else {
         result = schedule.initializeSchedule((Text)key, result);
         result.setStatus(CrawlDatum.STATUS_DB_UNFETCHED);
         try {
           scfilters.initialScore((Text)key, result);
         } catch (ScoringFilterException e) {
           if (LOG.isWarnEnabled()) {
             LOG.warn("Cannot filter init score for url " + key +
                      ", using default: " + e.getMessage());
           }
           result.setScore(0.0f);
         }
       }
       break;

     case CrawlDatum.STATUS_FETCH_SUCCESS:         // succesful fetch
     case CrawlDatum.STATUS_FETCH_REDIR_TEMP:      // successful fetch, redirected
     case CrawlDatum.STATUS_FETCH_REDIR_PERM:
     case CrawlDatum.STATUS_FETCH_NOTMODIFIED:     // successful fetch, notmodified
       // determine the modification status
       int modified = FetchSchedule.STATUS_UNKNOWN;
       if (fetch.getStatus() == CrawlDatum.STATUS_FETCH_NOTMODIFIED) {
         modified = FetchSchedule.STATUS_NOTMODIFIED;
       } else {
         if (oldSet && old.getSignature() != null && signature != null) {
           if (SignatureComparator._compare(old.getSignature(), signature) != 0) {
             modified = FetchSchedule.STATUS_MODIFIED;
           } else {
             modified = FetchSchedule.STATUS_NOTMODIFIED;
           }
         }
       }
       // set the schedule
       result = schedule.setFetchSchedule((Text)key, result, prevFetchTime,
           prevModifiedTime, fetch.getFetchTime(), fetch.getModifiedTime(), modified);
       // set the result status and signature
       if (modified == FetchSchedule.STATUS_NOTMODIFIED) {
         result.setStatus(CrawlDatum.STATUS_DB_NOTMODIFIED);
         if (oldSet) result.setSignature(old.getSignature());
       } else {
         switch (fetch.getStatus()) {
         case CrawlDatum.STATUS_FETCH_SUCCESS:
           result.setStatus(CrawlDatum.STATUS_DB_FETCHED);
           break;
         case CrawlDatum.STATUS_FETCH_REDIR_PERM:
           result.setStatus(CrawlDatum.STATUS_DB_REDIR_PERM);
           break;
         case CrawlDatum.STATUS_FETCH_REDIR_TEMP:
           result.setStatus(CrawlDatum.STATUS_DB_REDIR_TEMP);
           break;
         default:
           LOG.warn("Unexpected status: " + fetch.getStatus() + " resetting to old status.");
           if (oldSet) result.setStatus(old.getStatus());
           else result.setStatus(CrawlDatum.STATUS_DB_UNFETCHED);
         }
         result.setSignature(signature);
         if (metaFromParse != null) {
             for (Entry<Writable, Writable> e : metaFromParse.entrySet()) {
               result.getMetaData().put(e.getKey(), e.getValue());
             }
           }
       }
       // if fetchInterval is larger than the system-wide maximum, trigger
       // an unconditional recrawl. This prevents the page to be stuck at
       // NOTMODIFIED state, when the old fetched copy was already removed with
       // old segments.
       if (maxInterval < result.getFetchInterval())
         result = schedule.forceRefetch((Text)key, result, false);
       break;
     case CrawlDatum.STATUS_SIGNATURE:
       if (LOG.isWarnEnabled()) {
         LOG.warn("Lone CrawlDatum.STATUS_SIGNATURE: " + key);
       }
       return;
     case CrawlDatum.STATUS_FETCH_RETRY:           // temporary failure
       if (oldSet) {
         result.setSignature(old.getSignature());  // use old signature
       }
       result = schedule.setPageRetrySchedule((Text)key, result, prevFetchTime,
           prevModifiedTime, fetch.getFetchTime());
       if (result.getRetriesSinceFetch() < retryMax) {
         result.setStatus(CrawlDatum.STATUS_DB_UNFETCHED);
       } else {
         result.setStatus(CrawlDatum.STATUS_DB_GONE);
       }
       break;


     case CrawlDatum.STATUS_FETCH_GONE:            // permanent failure
       if (oldSet)
         result.setSignature(old.getSignature());  // use old signature
       result.setStatus(CrawlDatum.STATUS_DB_GONE);
       result = schedule.setPageGoneSchedule((Text)key, result, prevFetchTime,
           prevModifiedTime, fetch.getFetchTime());
       break;


     default:
       throw new RuntimeException("Unknown status: " + fetch.getStatus() + " " + key);
     }


     // 这里用来更新result的分数
     try {
       scfilters.updateDbScore((Text)key, oldSet ? old : null, result, linkList);
     } catch (Exception e) {
       if (LOG.isWarnEnabled()) {
         LOG.warn("Couldn't update score, key=" + key + ": " + e);
       }
     }
     // remove generation time, if any
     result.getMetaData().remove(Nutch.WRITABLE_GENERATE_TIME_KEY);
     output.collect(key, result);   // 写出数据
   }

 }

3. 总结

• 这里大概分析了一下CrawlDb的更新流程，有一些地方还是没有看得太明白，可能要通过测试来更深入的理解。
• 其中流程就是对三个目录进行合并，对相同的url的value(CrawlDatum)进行聚合，产生新的CarwlDatum，再写回原来的数据库中。
• 其复杂的地方在于如果对聚合后的结果进行处理，这个有空还要再看一下。