Question

我正在使用stormcrawler来抓取40k网站，max_depth = 2，我想尽可能快地进行抓取。我有5个风暴节点（具有不同的静态ips）和3个弹性节点。目前我最好的拓扑结构是：

spouts:
  - id: "spout"
    className: "com.digitalpebble.stormcrawler.elasticsearch.persistence.CollapsingSpout"
    parallelism: 10

bolts:
  - id: "partitioner"
    className: "com.digitalpebble.stormcrawler.bolt.URLPartitionerBolt"
    parallelism: 1
  - id: "fetcher"
    className: "com.digitalpebble.stormcrawler.bolt.FetcherBolt"
    parallelism: 5
  - id: "sitemap"
    className: "com.digitalpebble.stormcrawler.bolt.SiteMapParserBolt"
    parallelism: 5
  - id: "parse"
    className: "com.digitalpebble.stormcrawler.bolt.JSoupParserBolt"
    parallelism: 100
  - id: "index"
    className: "com.digitalpebble.stormcrawler.elasticsearch.bolt.IndexerBolt"
    parallelism: 25
  - id: "status"
    className: "com.digitalpebble.stormcrawler.elasticsearch.persistence.StatusUpdaterBolt"
    parallelism: 25
  - id: "status_metrics"
    className: "com.digitalpebble.stormcrawler.elasticsearch.metrics.StatusMetricsBolt"
    parallelism: 5

和抓取工具配置：

config: 
  topology.workers: 5
  topology.message.timeout.secs: 300
  topology.max.spout.pending: 250
  topology.debug: false
  fetcher.threads.number: 500
  worker.heap.memory.mb: 4096

问题： 1）我应该使用AggreationsSpout还是CollapsingSpout，有什么区别？我尝试了AggregationSpout，但性能等于默认配置的1台机器的性能。

2）这种并行性的配置是否正确？

3）当我从1节点跳到5节点配置时，我发现“FETCH ERROR”增加了大约20％并且很多站点没有正确获取。可能是什么原因？

更新

ES-conf.yaml：

# configuration for Elasticsearch resources

config:
  # ES indexer bolt
  # adresses can be specified as a full URL
  # if not we assume that the protocol is http and the port 9200
  es.indexer.addresses: "1.1.1.1"
  es.indexer.index.name: "index"
  es.indexer.doc.type: "doc"
  es.indexer.create: false
  es.indexer.settings:
    cluster.name: "webcrawler-cluster"

  # ES metricsConsumer
  es.metrics.addresses: "http://1.1.1.1:9200"
  es.metrics.index.name: "metrics"
  es.metrics.doc.type: "datapoint"
  es.metrics.settings:
    cluster.name: "webcrawler-cluster"

  # ES spout and persistence bolt
  es.status.addresses: "http://1.1.1.1:9200"
  es.status.index.name: "status"
  es.status.doc.type: "status"
  #es.status.user: "USERNAME"
  #es.status.password: "PASSWORD"
  # the routing is done on the value of 'partition.url.mode'
  es.status.routing: true
  # stores the value used for the routing as a separate field
  # needed by the spout implementations
  es.status.routing.fieldname: "metadata.hostname"
  es.status.bulkActions: 500
  es.status.flushInterval: "5s"
  es.status.concurrentRequests: 1
  es.status.settings:
    cluster.name: "webcrawler-cluster"

  ################
  # spout config #
  ################

  # positive or negative filter parsable by the Lucene Query Parser
  # es.status.filterQuery: "-(metadata.hostname:stormcrawler.net)"

  # time in secs for which the URLs will be considered for fetching after a ack of fail
  es.status.ttl.purgatory: 30

  # Min time (in msecs) to allow between 2 successive queries to ES
  es.status.min.delay.queries: 2000

  es.status.max.buckets: 50
  es.status.max.urls.per.bucket: 2
  # field to group the URLs into buckets
  es.status.bucket.field: "metadata.hostname"
  # field to sort the URLs within a bucket
  es.status.bucket.sort.field: "nextFetchDate"
  # field to sort the buckets
  es.status.global.sort.field: "nextFetchDate"

  # Delay since previous query date (in secs) after which the nextFetchDate value will be reset
  es.status.reset.fetchdate.after: -1

  # CollapsingSpout : limits the deep paging by resetting the start offset for the ES query 
  es.status.max.start.offset: 500

  # AggregationSpout : sampling improves the performance on large crawls
  es.status.sample: false

  # AggregationSpout (expert): adds this value in mins to the latest date returned in the results and
  # use it as nextFetchDate
  es.status.recentDate.increase: -1
  es.status.recentDate.min.gap: -1

  topology.metrics.consumer.register:
       - class: "com.digitalpebble.stormcrawler.elasticsearch.metrics.MetricsConsumer"
         parallelism.hint: 1
         #whitelist:
         #  - "fetcher_counter"
         #  - "fetcher_average.bytes_fetched"
         #blacklist:
         #  - "__receive.*"

Answer 1

1）我应该使用AggreationsSpout还是CollapsingSpout，它是什么区别？我尝试过AggregationSpout，但性能等于具有默认配置的1台机器的性能。

顾名思义，AggregationSpout使用聚合作为按主机（或域或IP或其他）对URL进行分组的机制，而CollapsingSpout使用collapsing。如果您将每个存储桶配置为多于1个URL（ es.status.max.urls.per.bucket ），则后者可能会更慢，因为它会为每个存储桶发出子查询。 AggregationSpout应该具有良好的性能，尤其是当 es.status.sample 设置为true时。在此阶段，CollapsingSpouts是实验性的。

2）这种并行配置是否正确？

这可能比需要的更多JSoupParserBolts。在实践中，与Fetcherbolts相比，1：4的比例即使有500个取出线也很好。 Storm UI可用于发现瓶颈以及哪些组件需要扩展。其他一切看起来还不错，但实际上，您应该查看Storm UI和指标，将拓扑调整为爬行的最佳设置。

3）我发现＆＃34; FETCH ERROR＆＃34;增加了约20％，许多网站没有当我从1个节点跳到5个节点配置时，正确获取。可能是什么原因？

这可能表明您正在使网络连接饱和，但在使用更多节点时则不应该这样。也许请查看Storm UI如何在节点之间分配FetcherBolts。是一个工作人员运行所有实例还是他们都得到相同的数字？查看日志以查看发生的情况，例如是否有超载异常？

StormCrawler：群集的最佳拓扑

1 个答案: