The Overflow Blog. Podcast Making Agile work for data science. Stack Gives Back Featured on Meta. New post summary designs on greatest hits now, everywhere else eventually. Related Hot Network Questions. Question feed. It finds that the Namenode claims two Datanodes hold this Block. The client picks one at random and contacts it. Imagine that right before the client contacts that Datanode, the Datanode's network card dies. The client can't get through, so it contacts the second Datanode provided by the Namenode.
This time, the network connection works just fine. It should be clear that the system is most available and reliable when blocks are available on many different Datanodes. Clients have a better shot at finding an important block, and a Datanode disk failure do not mean the data disappears.
We could even do load-balancing by copying a popular block to many Datanodes. The Namenode spends a lot of its time making sure every block is copied across the system. It keeps track of how many Datanodes contain each block. When a Datanode becomes unavailable, the Namenode will instruct other Datanodes to make extra copies of the lost blocks.
A file cannot be added to the system until the file's blocks are replicated sufficiently. How much is sufficiently? That should be user-controlled, but right now it's hard-coded. The NDFS tries to make sure each Block exists on two Datanodes at any one time, though it will still operate if that's impossible.
The numbers are low because a lot of Nutch users use just a few machines, where higher replication rates are impossible. However, NDFS has been designed with large installations in mind. I'd strongly recommend using the system with a replication rate of 3 copies, 2 minimum.
Desired replication can be set in nutch config file using "ndfs. More details on NDFS operation are coming soon. The NameNode daemon cass is NameNode. A DataNode daemon cass is DataNode. It keeps track of where all the blocks are, which DataNodes are available, etc. It logs all changes to the critical NDFS state so the NameNode can go down at any time and the most recent change is always preserved.
Eventually, this is where we will insert the code to mirror changes to a second backup NameNode. Same with HeartbeatData. If not specified in command line arguments for tools using Nutch File System abstraction - filesystem implementation to be used is taken from config file property named "fs. Either the literal string "local" or a host:port for NDFS. For , server "Startup Parameters" are inside Advanced tab. Add '-m' in startup parameters as shown above and click on 'Add'.
For , server you have to add ':-m' in the last of the existing query. Save the settings and Restart the service. Sitecore - Moving items from web to master. August 14, However, sometimes few items are in web database and not in master. Reason can be anything, like you might have deleted it in master but did not publish the parent item or due to some other reason.
If you are thinking, you will create package from web and deploy it in master, that will not work. Right and easy way to do is Transfer the item. Yes, you read it right. There is a provision in Sitecore to transfer the items from one database to another.
Select the item which you want to transfer from one database to another. Right click on it and then select Copying. To enable this simply configure the following in nutch-site. In a parsing fetcher, outlinks are processed in the reduce phase at least when outlinks are followed. If a fetcher's reducer stalls you may run out of memory or disk space, usually after a very long reduce job. Behaviour typical to this is usually observed in this situation. In summary, if it is possible, users are advised not to use a parsing fetcher as it is heavy on IO and often leads to the above outcome.
Adding some regular expressions to the regex-urlfilter. Alternatively, you can set db. Doing this will let the crawl go through only these domains without leaving to start crawling external links. Unfortunately there is no way to record external links encountered for future processing, although a very small patch to the generator code can allow you to log these links to hadoop.
The Nutch de-facto is an excellent start point. The reason for that is that when a page is fetched, it is timestamped in the webdb. So basiclly if its time is not up it will not be included in a fetchlist. So for example if you generated a fetchlist and you deleted the segment dir created. So, two choices:.
See the HttpAuthenticationSchemes wiki page. A possible reason is that by default the 'partition. Secondly the default setting for 'generate. This means the more urls you collect, especially from the same host, the more urls of the same host will be in the same fetcher map job!
Because there is also a policy setting please do this at home!! Therefore the resulting reduce step will only be done when all fetcher maps are done, which is a bottleneck in the overall processing step. While fetching is in progress, the fetcher job will log such statement to indicate the progress of the job:. Fetcher threads try to get a fetch item url from a queue of all the fetch items this queue is actually a queue of queues.
For details see [0]. If a thread doesn't get a fetch-item, it spinwaits for ms before polling the queue again. The 'spinWaiting' count tells us how many threads are in their "spinwaiting" state at a given instance. The 'active' count tells us how many threads are currently performing the activities related to the fetch of a fetch-item.
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