What exactly are you looking for or trying to do? There is, as you've seen, lotsa stuff to learn ;pOn 25 June 2015 at 14:54, James Douglas <jdouglas@wikimedia.org> wrote:I discovered a presentation from last year that has answered most of my initial questions. Here are my notes:
Notes from Hadoop and Beyond
June 25, 2015
webrequest logs
This is a log for every WMF HTTP request. It can max out beyond 200k requests per second, which is a lot.
udp2log
Doesn't scale, because every instance must process every message, every packet.
Because it uses UDP, it's not guaranteed not to drop data.
Wikimedia Statistics
Most data here is generated by udp2log-collected data.
It's sampled because there's too much traffic for our storage/processing capacity.
Analytics cluster
Uses Hadoop for batch processing of logs, and (mostly) uses Hive to expose the data to analysts.
This diagram is a useful (and frequent) reference:
Analytics cluster diagram
Note the loopy-back lines in the diagram -- these are batch jobs to do various things (geocoding, anonymizing, etc.).
Hadoop
Hadoop = a distributed file system + a framework for distributed computation
Hive
Hypothetical analyst question: How to get the top referrals for an article?
Hive maps a SQL-like language onto Hadoop MapReduce jobs.
Example Hive query to answer the above question:
SELECT SUBSTR(referer,30) AS SOURCE, COUNT(DISTINCT ip) AS hits FROM webrequest WHERE uri_path = "/wiki/London" AND uri_host = "en.wikipedia.org" AND referer LIKE "http://en.wikipedia.org/wiki/%" AND http_status = 200 AND webrequest_source = ‘text’ AND year = 2014 AND month= 07 AND day = 14 AND hour = 14 GROUP BY SUBSTR(referer,30) ORDER BY hits DESC LIMIT 50;
This is nice because it lets you run SQL on top of text data.
Kafka cluster
This serves as a replacement for udp2log.
Kafka is a reliable, horizontally scalable, distributed pub/sub buffer.
Processes up to 200k messages per second at 30 MB per second.
Data is consumed every ten minutes into Hadoop
Camus
A job that runs on Hadoop to consume from Kafka, and write the data into HDFS.
Launches a MapReduce job every hour(?).
Can inspect the data as it's coming in -- lets it handle data based on time/content.
Oozie
Oozie is a Hadoop job scheduler that allows the composition of complex workflows.
Jobs are launched based on the existence of new data sets, rather than simply based on time or periodic intervals. This lets us can trigger Oozie whenever a Camus job completes.
Hue
Web GUI for interacting with Hadoop, Hive, Oozie, etc.
Provides a Hive query interface, a Pig script interface, a way to launch jobs, browse the file system, and install add-ons.
A command-line interface is also available for all of the above.
MediaWiki Vagrant
To play with this in Vagrant:
- Edit your .settings.yaml file and add:
vagrant_ram: 2048
- Comment out
include role::mediawiki
inpuppet/manifests/site.pp
(unless you really need this on your VM)- Run:
vagrant enable-role analytics
- Run:
vagrant up
Hive and Hadoop should now be available in Vagrant!
On Thu, Jun 25, 2015 at 10:41 AM, James Douglas <jdouglas@wikimedia.org> wrote:On Thu, Jun 25, 2015 at 10:28 AM, James Douglas <jdouglas@wikimedia.org> wrote:This looks possibly relevant: https://wikitech.wikimedia.org/wiki/Analytics/Cluster/OverviewOn Thu, Jun 25, 2015 at 10:03 AM, James Douglas <jdouglas@wikimedia.org> wrote:Cool, I'll get on that. In the meantime, where can I learn about the infrastructure?> The varnish logs == request logs == also in HDFS.Ah ha, thanks!
> To get access you'll need a phabricator ticket asking for stat1002 and analytics cluster access, with Ottomata CCd to make the patch and Dan CCd to confirm you need it.On Thu, Jun 25, 2015 at 10:01 AM, Oliver Keyes <okeyes@wikimedia.org> wrote:The varnish logs == request logs == also in HDFS. To get access you'll
need a phabricator ticket asking for stat1002 and analytics cluster
access, with Ottomata CCd to make the patch and Dan CCd to confirm you
need it.
On 25 June 2015 at 12:53, James Douglas <jdouglas@wikimedia.org> wrote:
> From IRC, it sounds like this information ought to be available in the
> Varnish logs. What's the story there?
>
> On Thu, Jun 25, 2015 at 9:52 AM, James Douglas <jdouglas@wikimedia.org>
> wrote:
>>
>> I misspoke: we're looking for HTTP requests coming from users who are
>> leaving the Portal, not retrieving the portal.
>>
>> e.g. Clicking on enwiki, using one of the search forms, etc.
>>
>> On Thu, Jun 25, 2015 at 9:50 AM, Oliver Keyes <okeyes@wikimedia.org>
>> wrote:
>>>
>>> * Nope :(
>>> * It's in HDFS!
>>>
>>> On 25 June 2015 at 12:05, James Douglas <jdouglas@wikimedia.org> wrote:
>>> > Let's say, hypothetically, that I wanted to measure information about
>>> > HTTP
>>> > requests coming into the Wikipedia Portal (www.wikipedia.org).
>>> >
>>> > * Do we record this information?
>>> > * If so, is it accessible via analytical tools?
>>> > * If so, how do I get my mitts on it?
>>> > * If not, is it accessible from a database or similar?
>>> >
>>> > Context: https://phabricator.wikimedia.org/T100673
>>> >
>>> > _______________________________________________
>>> > Wikimedia-search mailing list
>>> > Wikimedia-search@lists.wikimedia.org
>>> > https://lists.wikimedia.org/mailman/listinfo/wikimedia-search
>>> >
>>>
>>>
>>>
>>> --
>>> Oliver Keyes
>>> Research Analyst
>>> Wikimedia Foundation
>>>
>>> _______________________________________________
>>> Wikimedia-search mailing list
>>> Wikimedia-search@lists.wikimedia.org
>>> https://lists.wikimedia.org/mailman/listinfo/wikimedia-search
>>
>>
>
>
> _______________________________________________
> Wikimedia-search mailing list
> Wikimedia-search@lists.wikimedia.org
> https://lists.wikimedia.org/mailman/listinfo/wikimedia-search
>
--
Oliver Keyes
Research Analyst
Wikimedia Foundation
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--Oliver Keyes
Research Analyst
Wikimedia Foundation
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