I’m not sure why the sizes are so different, but I think the overall issue is 
related to the three attributes that have :source => :query.

I’d recommend making two changes to each of them:

* Add a condition to each query that filters by the appropriate incident ids 
(like you’re doing for the main query) so the results are sharded in the same 
way.
* Perhaps add a second SQL statement to each of those attributes (separated by 
a semi-colon), with :source set to :ranged_query, as covered in the Sphinx 
documentation:
http://sphinxsearch.com/docs/current.html#conf-sql-attr-multi 
<http://sphinxsearch.com/docs/current.html#conf-sql-attr-multi>

The first of those isn’t too complex, so I’d start with that. Certainly the 
second is far more fiddly, but may be worthwhile.

Hope this helps!

— 
Pat

> On 29 Jun 2015, at 8:52 pm, [email protected] wrote:
> 
> 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 docs   Bytes   Time (sec)                              Total docs      
>> Bytes   Time (sec)
>> incident_index_1_core        7331    6531122 39.436                  
>> incident_index_6_core   7331    28239593        8.802
>> incident_index_1_delta       6       1128    0.184                   
>> incident_index_6_delta  6       24763425        5.234
>> incident_index_2_core        7319    6751189 45.477                  
>> incident_index_7_core   7319    28331726        8.819
>> incident_index_2_delta       5       843     0.233                   
>> incident_index_7_delta  5       24763289        5.321
>> incident_index_3_core        7390    6803814 42.064                  
>> incident_index_8_core   7390    28310121        7.913
>> incident_index_3_delta       8       2143    0.203                   
>> incident_index_8_delta  8       24764366        5.282
>> incident_index_4_core        7278    6377664 37.665                  
>> incident_index_9_core   7278    28162260        7.891
>> incident_index_4_delta       6       1108    0.436                   
>> incident_index_9_delta  6       24763330        5.456
>> incident_index_5_core        7396    6601358 39.704                  
>> incident_index_10_core  7396    28152075        9.562
>> incident_index_5_delta       6       944     0.216                   
>> incident_index_10_delta 6       24763308        5.303
>> 
>> 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 <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 <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 <http://countries.name/>, as: :countries 
>> >>  indexes images.title, as: :images 
>> >>  indexes subscribers.title, as: :subscribers 
>> >>  indexes tags.name <http://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 
>> >> <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 
>> >> <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 
>> >> <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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