On 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

Video
Slides

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

http://stats.wikimedia.org

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 in puppet/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:
Ooh!

https://wikitech.wikimedia.org/wiki/Analytics/Data/Webrequests_sampled

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/Overview

On Thu, Jun 25, 2015 at 10:03 AM, James Douglas <jdouglas@wikimedia.org> wrote:
> 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.

Cool, I'll get on that. In the meantime, where can I learn about the infrastructure?

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