Wanted to hit the list to get some more advice to finalize my market data 
design.  

Currently I have about 10 million events per week.  I would like to keep 
weekly indexes because they provide a nice logical separation of data (ie 
markets closed on weekend)
as of now I am using the default number of 5 shards which I was thinking of 
bumping to 10, right now I am routing based on symbol which there are about 
20, and I am wandering if I should just set number of shards = to number of 
symbols?

Data is about 1.5 gig per week so with 10 shards that 150 m each but I see 
that github has 120 gigs per shard (all be it with much beefier machines)

I had thought about daily indexes which is appealing because the potential 
is that many queries will not typically span more than a day and I would 
assume it is best to design indexes around the most frequent queries? 
 Would I be able to combine the daily indexes into a weekly 
and optimize over the weekend, is this possible?  

Also, I am trying to build candle data which is represented by the open 
(head) high, low, and close (last) values of the time period for which date 
histogram aggs are ideal.  High and low are easy but as of now its a two 
step query.  Any clever ways to get the first and last element of the 
bucket with aggs?

Just trying to nail this down and I appreciate any and all advice and 
feedback.

On Thursday, February 6, 2014 4:18:54 PM UTC-6, Bobby Richards wrote:
>
> great thanks.  I am not sure I would have found this on my own anytime 
> soon.  Ill look into it.
>
> Bobby
>
>
> On Thu, Feb 6, 2014 at 4:33 AM, Alexander Reelsen <a...@spinscale.de>wrote:
>
>> Hey,
>>
>> the side field as defined in your mapping (I assume you use elasticsearch 
>> 0.90.X) uses the standard analyzer, which by default removes stopwords. As 
>> "a" is a stopword, it gets removed as part of the indexing process - and 
>> that makes it impossible to search for. In order to find out more about 
>> this, a good way is to play around with the analyze API. If you like a nice 
>> UI on top of that, go with the inquisitor plugin. 
>>
>> The analyze API basically tells you, how a string is tokenized and stored 
>> in the index, which parts are being removed or altered (due to stemming for 
>> example).
>>
>> See 
>> http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/indices-analyze.html
>>
>>
>> --Alex
>>
>>
>> On Thu, Feb 6, 2014 at 3:38 AM, Bobby Richards 
>> <bobby.richa...@gmail.com>wrote:
>>
>>> So I have decided on using the week of year as the index and quotes as 
>>> my type.  I want to clarfiy a couple of things that I am seeing.
>>>
>>> first I create my index *curl 'http://localhost:9200/2014_6/quotes 
>>> <http://localhost:9200/2014_6/quotes>'*
>>>
>>> then I set my mapping:
>>>  
>>> *curl -XPUT 'http://localhost:9200/2014_6/quotes/_mapping 
>>> <http://localhost:9200/2014_6/quotes/_mapping>' -d '*
>>>
>>> *{*
>>>
>>> *  "quotes" : {*
>>>
>>> *     "properties" : {*
>>>
>>> *        "time_stamp": {"type":"date"},*
>>>
>>> *        "symbol": {"type":"string"},*
>>>
>>> *        "side" : {"type":"string"},*
>>>
>>> *        "price" : {"type":"double"}*
>>>
>>> *     },*
>>>
>>> *    "_routing" : {*
>>>
>>> *       "required": true,*
>>>
>>> *      "path":"symbol"*
>>>
>>> *   },*
>>>
>>> *     "_timestamp" : {*
>>>
>>> *        "enabled" : true,*
>>>
>>> *        "path":  "time_stamp",*
>>>
>>> *        "format": "date_hour_minute_second_millis"*
>>>
>>> *     }*
>>>
>>> *  }*
>>>
>>> *}*
>>>
>>> *'*
>>> now because of this I understand when I am posting a new event to be 
>>> indexed I do not need to specify quote?routing=<symbol>.  However my first 
>>> question is that now I must include symbol in the json object I am posting, 
>>> is this costing me more as far as storage?  If I do not do this via the 
>>> mapping I have no problem adding the routing to the uri, especially if it 
>>> saves me space.
>>>
>>> second I am seeing a couple of weird things...
>>> by running this:
>>> *curl -XGET 'http://localhost:9200/2014_5/quotes/_search?routing=eurusd 
>>> <http://localhost:9200/2014_5/quotes/_search?routing=eurusd>'*
>>>
>>> i get the following, which is good, what I expect.
>>> {"took":1,"timed_out":false,"_shards":{"total":1,"successful":1,"failed":0},"hits":{"total":3,"max_score":1.0,"hits":[{"_index":"2014_5","_type":"quotes","_id":"ZW5u1nCHTGW-xToRy8Yy5g","_score":1.0,
>>>  
>>> "_source" : 
>>> { "time_stamp":1391653001000, "symbol":"eurusd", "side":"a", 
>>> "price":1.3456}},{"_index":"2014_5","_type":"quotes","_id":"ok4FLnrfR4u2CnJ3lVNKkg","_score":1.0,
>>>  
>>> "_source" : 
>>> { "time_stamp":1391653001000, "symbol":"eurusd", "side":"b", 
>>> "price":1.3457}},{"_index":"2014_5","_type":"quotes","_id":"1eG5m0riSoiDEquQ3I-QSA","_score":1.0,
>>>  
>>> "_source" : 
>>> { "time_stamp":1391653001100, "symbol":"eurusd", "side":"b", 
>>> "price":1.3458}}]}}
>>>
>>> however if you will notice the first entry is of side "a".  by running 
>>> the following I get nothing.
>>> *url -XGET 'http://localhost:9200/2014_5/quotes/_search?routing=eurusd 
>>> <http://localhost:9200/2014_5/quotes/_search?routing=eurusd>' -d '*
>>>
>>> *{"query":{"filtered":{"query":{"match_all":{}},"filter":{"term":{"side":"a"}}}}}'*
>>>
>>> however if I change side to "b" I get 2 as I would expect.  Is there 
>>> some reserved feature that would limit me searching the a or is there some 
>>> text search thing I am not thinking about.
>>>
>>> Finally, I have added a few usdjpy quotes which are routed to a separate 
>>> shard. In my query I accidentally type *usejpy *and I got the two 
>>> eurusd events, even though it honored the side filter.
>>> correcting the symbol I get what I would expect.  Is this another text 
>>> search 'thing'?  All I can think of is that by mistyping the e matches the 
>>> eur in the other indexed items.  
>>>
>>> I just want to understand fully what I have going on there, thanks.
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> On Saturday, February 1, 2014 2:27:55 PM UTC-6, Bobby Richards wrote:
>>>>
>>>> Wanting to get some advice on how to go about design.  I have some 
>>>> currency market data and I get roughly 10 million events a week currently 
>>>> storing in postgres, it actually ends up being about 10 gigs, though I 
>>>> would like to work on getting this down obviously.  The data is seldom 
>>>> queried but I have all of my other data in elastic search which I love.  I 
>>>> am trying to determine the best way to store this.
>>>>
>>>> I would like to query by symbol and time and indexing by month so I can 
>>>> drop months whenever.  i guess that would mean 'month/symbol/(unixtime for 
>>>> minute).
>>>>
>>>> I am far from a data guy, so I am looking for direction, thoughts, 
>>>> etc...is this even a good use case for elastic search?
>>>>
>>>> Thanks,
>>>> Bobby
>>>>
>>>>
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