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Hadoop >> mail # user >> Creating a hive table for a custom log


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Re: Creating a hive table for a custom log
Hi,

On Thu, Sep 1, 2011 at 9:08 AM, Raimon Bosch <[EMAIL PROTECTED]> wrote:
>
> Hi,
>
> I'm trying to create a table similar to apache_log but I'm trying to avoid
> to write my own map-reduce task because I don't want to have my HDFS files
> twice.
>
> So if you're working with log lines like this:
>
> 186.92.134.151 [31/Aug/2011:00:10:41 +0000] "GET
> /client/action1/?transaction_id=8002&user_id=871793100001248&ts=1314749223525&item1=271&item2=6045&environment=2
> HTTP/1.1"
>
> 112.201.65.238 [31/Aug/2011:00:10:41 +0000] "GET
> /client/action1/?transaction_id=9002&ts=1314749223525&user_id=9048871793100&item2=6045&item1=271&environment=2
> HTTP/1.1"
>
> 90.45.198.251 [31/Aug/2011:00:10:41 +0000] "GET
> /client/action2/?transaction_id=9022&ts=1314749223525&user_id=9048871793100&item2=6045&item1=271&environment=2
> HTTP/1.1"
>
> And having in mind that the parameters could be in different orders. Which
> will be the best strategy to create this table? Write my own
> org.apache.hadoop.hive.contrib.serde2? Is there any resource already
> implemented that I could use to perform this task?

I would use the regex serde to parse them:

CREATE EXTERNAL
TABLE access_log
(ip STRING,
dt STRING,
request STRING)
ROW FORMAT SERDE 'org.apache.hadoop.hive.contrib.serde2.RegexSerDe'
WITH SERDEPROPERTIES ("input.regex" = "([\\d.]+)
\\[([\\w:/]+\\s[+\\-]\\d{4})\\] \"(.+?)\"")
LOCATION '/path/to/file';

That will parse the three fields out and could be modified to separate
out the action. Then I think you will need to parse the query string
in Hive itself.

>
> In the end the objective is convert all the parameters in fields and use as
> type the "action". With this big table I will be able to perform my queries,
> my joins or my views.
>
> Any ideas?
>
> Thanks in Advance,
> Raimon Bosch.
> --
> View this message in context: http://old.nabble.com/Creating-a-hive-table-for-a-custom-log-tp32379849p32379849.html
> Sent from the Hadoop core-user mailing list archive at Nabble.com.
>
>