Nutch 1.3 学习笔记 7 CrawlDb - updatedb
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
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：
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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。