Sort out the field separator issue in your handling of squid logs first.
To summarize:
1) Kafka byte offset is separated from hostname by a tab.
2) Other fields are separated by a space.
3) The content-type field contains unescaped spaces.
4) Beeswax only supports splitting on a single character.
As a result:
1) Byte offset is not separable from the hostname
("316554683463cp1043.wikimedia.org")
2) Spaces in content-type causes the field to span a variable number of columns, making it
impossible to select the user agent string.
I'd like a solution to this that does not require that I provide a jar file for
customized string processing.
--
Ori Livneh
On Tuesday, January 22, 2013 at 2:05 AM, David Schoonover wrote:
Yes! We've talked a bit about this paper when
thinking about the structure of our data storage and processing. To me the path Twitter
followed seems very reasonable, so it's encouraging to hear that it looks that way to
someone who gets dirty with data on a daily basis.
As it stands now, we weren't planning on enforcing any schema requirements in Kraken,
but it'd be interesting to experiment with a standardized event-data format if
y'all were in favor of it. Our most recent pass at a schema[1] -- mostly for binary
serialization, to save bits -- has an otherwise-untyped (String-String) map for the KV
pairs of the data payload. We intended to use an additional, optional field to permit
specifying a sub-schema to apply strong typing to incoming event data. (We plan on storing
things with Avro, but it's easy enough to convert between it and JSONSchema.) Event
subclasses would be more flexible but require custom processing for each class. I'd
normally oppose a standard model (Google doesn't use one internally, for example) but
as Twitter made it work, I think it's worth exploring.
Thoughts?
[1]
https://www.mediawiki.org/wiki/Analytics/Kraken/Data_Formats#Event_Data_Sch…
--
David Schoonover
dsc(a)wikimedia.org (mailto:dsc@wikimedia.org)
On Thursday, 17 January 2013 at 2:00 p, Dario Taraborelli wrote:
http://arxiv.org/pdf/1208.4171.pdf
This is a pretty interesting and accessible description of best practices and design
decisions driven by practical problems they had to solve at Twitter in the area of
client-side event logging, funnel analysis, user modeling.
E3: check out section "3.2 Client Events" in particular, which is quite
relevant to EventLogging.
Dario
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