So because i do not have the ability to get the millisecond data, the first
option is not really possible
I did use sequential keys for entering the data, so that should work well
I'm using this to get them sorted
FOR doc IN `stats_log`
FILTER
doc.`t_id` IN ["266","267","221","220"]
SORT doc.`terminal_id`, doc.`date` ASC, doc.`time` ASC, doc.`_key` ASC
RETURN doc
I'm thinking that for processing them I would add an incrementing session
id, based on home event, that is whenever there is a home found, I would
generate a new session and use it until another 'home' is found.
I would also add a step and increment it while the session is the same
I could do this in an app, but is there a way to do this using a an AQL
query?
On Friday, August 19, 2016 at 2:47:48 AM UTC-6, Jan wrote:
>
> Hi,
>
> one possible solution would be to add more precision to the timing events,
> e.g. by adding the milliseonds for each timestamp. This would make it more
> unlikely that two events will have the exact same timestamp though it could
> still happen in rare cases.
> It sounds like you've already considered this option and don't want to go
> that way.
>
> Another option is to use the `_key` attribute of each document and compare
> them. By default, the `_key` values generated by ArangoDB are increasing
> numbers packaged into strings. If there is only one process that inserts
> documents sequentially into the collection, then documents inserted later
> will get "higher" values in `_key` (technically they are not higher because
> `_key` is a string, but the "higher" assumption holds when `_key` is
> converted into a number).
> For example,
>
> FOR doc IN collection
> FILTER doc.time == '10:33:45'
> SORT TO_NUMBER(doc._key) ASC
> RETURN doc
>
> would give you the documents for time `10:33:45` in insertion order.
>
> A third alternative is have the insertion process generate an increasing
> value per document it inserts. This will work fine if only one process
> inserts documents into the collection. Then the process could simple
> compare the data by time, and use an increasing number for each value with
> the same time value, e.g.
>
> {"id":"917", "date":"2016-08-01", "time":"10:33:37",
> "location":"home","seq":0},
> {"id":"917", "date":"2016-08-01", "time":"10:33:39",
> "location":"category/1","seq":0},
> {"id":"917", "date":"2016-08-01", "time":"10:33:45",
> "location":"category/4","seq":0},
> {"id":"917", "date":"2016-08-01", "time":"10:33:45",
> "location":"item/6","seq":1},
> {"id":"917", "date":"2016-08-01", "time":"10:33:50",
> "location":"home","seq":0}
>
> You could then query events by sorting by time first and then seq.
> I hope this helps.
>
> Best regards
> Jan
>
> Am Freitag, 19. August 2016 00:30:37 UTC+2 schrieb Daniel:
>>
>> How can I get the behaviour flow of user using collection of logs?
>>
>>
>> Background:
>>
>> I'm using ArangoDB to hold an app's log data that is similar to web
>> traffic (I hope that this is a good use case)
>>
>> I've got two things I'm doing from the nodejs app that processes it
>> 1) insert parsed data
>> 2) pre-aggregate data to get event counts quickly
>>
>> In some cases I may need to get more advanced information such as the
>> most common behaviour flow.
>>
>> assuming I've got data such as this:
>> [
>> {"id":"917", "date":"2016-08-01", "time":"10:33:37", "location":"home"},
>> {"id":"917", "date":"2016-08-01", "time":"10:33:39",
>> "location":"category/1"},
>> {"id":"917", "date":"2016-08-01", "time":"10:33:45",
>> "location":"category/4"},
>> {"id":"917", "date":"2016-08-01", "time":"10:33:45", "location":"item/6"},
>> {"id":"917", "date":"2016-08-01", "time":"10:33:50", "location":"home"},
>> etc...
>> ]
>>
>> the problem I've found already is that even though I'm inserting them
>> sequentially, once I add two lines with the same timestamp (no millisecond
>> info) I can't tell which one came first.
>>
>> Is this something I could use the graph component for?
>>
>
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