I even less understand the number of bytes in delta indexes 6 - 10. Why 
does 1_delta contain 1128 bytes and 6_delta 24M? They're on the same 
records.

On Monday, June 29, 2015 at 9:03:04 AM UTC+3, [email protected] wrote:
>
> Rails version: 4.1.7
> TS version: 3.0.6
>
> On Monday, June 29, 2015 at 5:17:37 AM UTC+3, Pat Allan wrote:
>>
>> Hi Jonathan
>>
>> Can you share your index definitions so I can get a better idea of where 
>> the problem might be?
>>
>> Also: which versions of Rails and Thinking Sphinx are you using?
>>
>> — 
>> Pat
>>
>> On 28 Jun 2015, at 11:47 pm, [email protected] wrote:
>>
>> Hi Pat,
>>
>> I implemented according to this, and the indexing time went down (5 times 
>> faster on development). However, the delta indexing time went up (30 times 
>> slower on development). See below the indexing stats:
>>
>> Total docsBytesTime (sec)Total docsBytesTime (sec)incident_index_1_core
>> 7331653112239.436incident_index_6_core7331282395938.802
>> incident_index_1_delta611280.184incident_index_6_delta6247634255.234
>> incident_index_2_core7319675118945.477incident_index_7_core731928331726
>> 8.819incident_index_2_delta58430.233incident_index_7_delta5247632895.321
>> incident_index_3_core7390680381442.064incident_index_8_core739028310121
>> 7.913incident_index_3_delta821430.203incident_index_8_delta8247643665.282
>> incident_index_4_core7278637766437.665incident_index_9_core727828162260
>> 7.891incident_index_4_delta611080.436incident_index_9_delta6247633305.456
>> incident_index_5_core7396660135839.704incident_index_10_core739628152075
>> 9.562incident_index_5_delta69440.216incident_index_10_delta6247633085.303
>>
>> Any idea why this is happening?
>>
>> Thanks,
>> Jonathan
>>
>> On Friday, July 26, 2013 at 3:57:38 PM UTC+3, Pat Allan wrote:
>>>
>>> Heya Steve 
>>>
>>> Was just looking into how difficult this would be to implement properly, 
>>> and noticed I have added the ability to take a string as the source query - 
>>> instead of the column references. So, it's possible without hacking around 
>>> in the index definition itself: 
>>>
>>> https://gist.github.com/pat/6088629 
>>>
>>> It's worth noting that the document id (Sphinx's equivalent of a primary 
>>> key) involves the normal primary key with an offset and a multiplier. Make 
>>> sure those two integers match what's in your generated index in sql_query. 
>>> They may change when you add other indices to your app (depends on 
>>> alphabetical order of your index files). 
>>>
>>> Also: there's probably some metaprogramming you could add to simplify 
>>> things a bit more. 
>>>
>>> Would love to hear if this approach helps with your real app and not 
>>> just the test one :) 
>>>
>>> -- 
>>> Pat 
>>>
>>> On 26/07/2013, at 12:14 AM, Pat Allan wrote: 
>>>
>>> > Hi Steve 
>>> > 
>>> > I've got a way forward to greatly improve the speed of indexing… 
>>> unfortunately, it's not going to work within Thinking Sphinx easily right 
>>> now. 
>>> > 
>>> > Sphinx has the ability to gather attribute and field values from 
>>> separate queries - this existed for TS v1/v2 for attributes, and fields was 
>>> added in TS v3, but the catch is those separate queries don't work for 
>>> HABTM joins. I'd love to change that, it's just painful from an 
>>> ActiveRecord perspective because you're not dealing with a model's table as 
>>> the base, but the HABTM join table. 
>>> > 
>>> > Here's the configuration for the relevant source that I modified by 
>>> hand: 
>>> > https://gist.github.com/pat/6080031 
>>> > 
>>> > You'll see that the main query is nice and short - and then there's 
>>> each of the MVA and joined field definitions. If you put this in the 
>>> generated source definition in config/development.sphinx.conf, and then run 
>>> the indexer manually (NOT through the rake task, that'll overwrite this):
>>>  
>>> >  indexer --config config/development.sphinx.conf --all --rotate 
>>> > 
>>> > (Remove --rotate if Sphinx isn't running.) You'll see it's pretty damn 
>>> fast. 
>>> > 
>>> > Now, ways forward? Well, I'd love to write something for TS v3 that 
>>> can handle HABTM - it's just a shame that it might need to be pure ARel 
>>> rather than ActiveRecord-built (which can otherwise help with joins). 
>>> > 
>>> > But otherwise: switch from HABTM to has_many/has_many :through - make 
>>> each of the joins an actual model. Then, you can add :source => :query to 
>>> each of the appropriate field and attribute definitions, and it should 
>>> generate something pretty much the same. 
>>> > 
>>> > Hope this provides some clarity at the very least! And also: thanks 
>>> for the test app, really helped with debugging! 
>>> > 
>>> > -- 
>>> > Pat 
>>> > 
>>> > 
>>> > On 25/07/2013, at 2:54 PM, Steve Kenworthy wrote: 
>>> > 
>>> >> Hi there, 
>>> >> 
>>> >> Firstly, thinking-sphinx is awesome and I love it. Thanks Pat for an 
>>> excellent project. V3 is looking great and represents a lot of hard work 
>>> and effort. 
>>> >> 
>>> >> I've been using thinking-sphinx to index a document model and it's 
>>> really slowed down when I add lots of associations in the index. In fact, 
>>> it never finishes on my machine (8Gig RAM, 8 CPU's) when I add 4 indexes.
>>>  
>>> >> 
>>> >> Times: 
>>> >>         • 4 seconds - when 1 association (images) is indexed 
>>> >>         • 6 seconds - when 2 associations (images and subscribers) 
>>> are indexed 
>>> >>         • 23 seconds - when 2 associations (images and countries) are 
>>> indexed 
>>> >>         • 115 seconds - when 3 associations (images, subscribers and 
>>> tags) are indexed 
>>> >>         • 113 seconds - when 3 associations (images, subscribers and 
>>> videos) are indexed (just to prove it's not tags slowing it down) 
>>> >>         • ꝏ (not finishing) - when 4 associations or more are 
>>> selected. 
>>> >> 
>>> >> Here's my index file: 
>>> >> 
>>> >> ThinkingSphinx::Index.define :document, with: :active_record, delta: 
>>> true, sql_range_step: 999999999, group_concat_max_len: 16384 do 
>>> >> 
>>> >>  has countries(:id), as: :country_ids 
>>> >>  has images(:id), as: :image_ids, facet: true 
>>> >>  has subscribers(:id), as: :subscriber_ids, facet: true 
>>> >>  has tags(:id), as: :tag_ids, facet: true 
>>> >>  has videos(:id), as: :video_ids, facet: true 
>>> >> 
>>> >>  indexes countries.name, as: :countries 
>>> >>  indexes images.title, as: :images 
>>> >>  indexes subscribers.title, as: :subscribers 
>>> >>  indexes tags.name, as: :tags 
>>> >>  indexes videos.title, as: :videos 
>>> >> 
>>> >>  has updated_at 
>>> >> 
>>> >> end 
>>> >> 
>>> >> The generated sql is a massive group_by query and is not finishing. 
>>> See it here 
>>> https://github.com/crossroads/rails3-ts-example#what-sphinx-is-doing 
>>> >> 
>>> >> I'd really appreciate some advice on how to optimise this so indexing 
>>> becomes viable again. Do I just have too much going on here? I'm using 
>>> facets, indexes and attributes. Perhaps there is a better way to optimise? 
>>> A friend suggested pre-computing with some joins... how would this work?
>>>  
>>> >> 
>>> >> Vital stats: using mysql v14.14, sphinx 2.0.4, Ubuntu, rails 3.2.13, 
>>> thinking-sphinx 3.0.4 
>>> >> 
>>> >> For those who'd like to take a look, I've uploaded a sample project 
>>> here https://github.com/crossroads/rails3-ts-example which can be 
>>> cloned. If you follow the instructions, it will setup a db with test data 
>>> and reproduce the problem quickly. 
>>> >> 
>>> >> There's also the sphinx generated SQL and EXPLAIN: 
>>> https://github.com/crossroads/rails3-ts-example#what-sphinx-is-doing 
>>> >> 
>>> >> Thanks in advance for anyone taking the time to read. 
>>> >> 
>>> >> Regards, 
>>> >> Steve 
>>> >> 
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>>> > 
>>> > 
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