The Django docs on aggregation give the following example for annotations:
for store in Store.objects.all():
store.min_price # Error! min_price not defined!
for store in Store.objects.annotate(min_price=Min('books__price')):
store.min_price # Fine
However, we only annotated a single field. We only know what the price of the cheapest book is, but not exactly which is the cheapest book. What if I wanted the result of the annotation be precisely that book, not just its price? (I'll call this function or class AggregateRelation)
for store in Store.objects.annotate(
cheapest_book=AggregateRelation('books__price', Min)
):
store.cheapest_book.price
store.cheapest_book.title
Is there a way to do this?
I checked up FilteredRelation but that's only useful for filtering. It does not truly retrieve the instances.
If (and only if) you are using PostgreSQL, then I think there's an answer using .distinct(fields)
Book.objects.order_by('store_id', 'price').distinct('store_id')
should get you the cheapest book for each store if I've understood the documentation (linked above) right. Adding select_related() should mean that you don't hit the DB again when you refer to book.store.whatever
If you don't have PostgreSQL I think you can use a SubQuery. The following is my attempt to follow the documentation:
from django.db.models import OuterRef, Subquery
cheapest = Book.objects.filter(store=OuterRef('pk')).order_by('price')
stores = Store.objects.annotate(cheapest_book_pk=Subquery(cheapest.values('pk')[:1]))
Something like this will get you a list of Store objects, each annotated with the pk of the cheapest book that it is selling.
Please tell me whether I've got this right!
Related
I require some more advanced MDX knowledge than mine.
I need to get the RepoRate_MAX for repo products, at book and instrument level, but also looking at the Java code I'm replacing that code always uses the max MurexId.
How can I perform the below (I've placed MAX in here on the dimension but this is wrong) and I need the combo of the dimensions and also the MAX MurexId:
[Measures].[RepoRate_VAL] = (([Deal].[ProductType].&[REPO],[Deal].[Book],[Deal].[Instrument],MAX([Deal].[MurexId])),[Measures].[RepoRate_MAX])
I'm sure it's a simple one but my mind is part way between the Java OO and MDX worlds currently haha :D
Thanks
Leigh
So after some experimenting I found out about the TAIL and Item MDX functions.
I think at one point I did get it working, but didn't make a note of what did work. I was playing around with this and variants of it..but most versions ended up in unusable query times:
[Measures].[RepoRate_VAL] = (([Deal].[ProductType].&[REPO],[Deal].[Book],[Deal].[Instrument],TAIL(EXISTING([Deal].[MurexId].[MurexId])).Item(0)),[Measures].[RepoRate_MAX])
So I then decided to push the RepoRate calculation back to the SQL data preparation script. Cleaner/smoother data is always better and then to have simple calculated members.
I used SQL to determine the RepoRate from tradelevel with MAX(MurexId) and GROUP BY on Book, Instrument to then update my main fact table to ensure that the correct RepoRate was set at Book, Instrument level.
Thus the calculated member is then:
[Measures].[RepoRate_VAL] = (([Deal].[Book],[Deal].[Instrument]),[Measures].[RepoRate_MAX])
Fast data prep and a fast calculated member on the Excel/Pivot/UI layer.
Hej guys,
I'm working on some ranking related research. I would like to index a collection of documents with Lucene, take the tfidf representations (of each document) it generates, alter them, put them back into place and observe how the ranking over a fixed set of queries changes accordingly.
Is there any non-hacky way to do this?
Your question is too vague to have a clear answer, esp. on what you plan to do with :
take the tfidf representations (of each document) it generates, alter them
Lucene stores raw values for scoring :
CollectionStatistics
TermStatistics
Per term/doc pair stats : PostingsEnum
Per field/doc pair : norms
All this data is managed by lucene and will be used to compute a score for a given query term. A custom Similarity class can be used to change the formula that generates this score.
But you have to consider that a search query is made of multiple terms, and the way the scores of individual terms are combined can be changed as well. You could use existing Query classes (e.g. BooleanQuery, DisjunctionMax) but you could also write your own.
So it really depends on what you want to do with of all this but note that if you want to change the raw values stored by lucene this is going to be rather hard. You'll have to write a custom lucene codec and probably most the query stack to take benefit of your new data.
One nice thing you should consider is the possibility to store an arbitrary byte[] payloads. This way you could store a value that would have been computed outside of lucene and use it in a custom similarity or query.
Please see the following tutorials: Getting Started with Payloads and Custom Scoring with Lucene Payloads it may you give some ideas.
In foursquare Api documentation for "Search venues" https://developer.foursquare.com/docs/venues/search it states
"categoryId - A comma separated list of categories to limit results to. This is an experimental feature and subject to change or may be unavailable. If you specify categoryId you may also specify a radius. If specifying a top-level category, all sub-categories will also match the query."
Realise its supposed to be experimental, but when I provide Food category i.e. 4d4b7105d754a06374d81259, it only returns a few local results, the rest are miles away. However if I execute same search on website sing Food category, it returns correctly lots of results, assuming its the last bit "If specifying a top-level category, all sub-categories will also match the query" is not working , i.e. its not searching sub-categories ?
Any fix work around for this ?
Thanks,
Neil Pepper
You're making a /venues/search request with its default intent of intent=checkin. This returns a filter on nearby results, heavily biased by distance since it's trying to guess where the user might be checking in.
Foursquare Explore uses the /venues/explore endpoint and attempts to return recommended results for a query. If you want to get the sorts of results you get in that tool, call /venues/explore?section=food
I plan to build something like pricegrabber.com/google product search.
Assume I already have the data available in a huge table. I plan to submit this all to Solr. This solves the problem of search. However I am not sure how to do comparison. I can do a group by query(on UPC/SKU) for the products returned by Solr on the DB. However, I dont want to do that. I want to somehow get product comparison data returned to me along with search from Solr itself.
How do you think should my schema be? Do you think this use-case can be solved all by Solr/Sphinx?
You need 'result grouping' or 'field collapsing' support to properly handle it.
In Solr, the feature is not available in any release version and is still under development. If you are willing to use an unreleased version of Solr, then get the details here.
Sphinx supports result grouping and I had used it a long time ago in a similar project. You can get more details here.
An alternative strategy could be to preprocess your data so that only a single record per UPC/SKU gets inserted in the index. Each record can have a separate field containing the ids of all the items with the same UPC/SKU.
Doing a database GROUP BY on the products returned by Solr may not be enough. For example, if products A and B have the same UPC and a certain query matches A but not B, then you will not get both A and B in your result set.
What I want to do is implement submission scoring for a site with users voting on the content, much like in e.g. reddit (see the 'hot' function in http://code.reddit.com/browser/sql/functions.sql). Edit: Ultimately I want to be able to retrieve an arbitrarily filtered list of arbitrary length of submissions ranked according to their score.
My submission model currently keeps track of up and down vote totals. Currently, when a user votes I create and save a related Vote object and then use F() expressions to update the Submission object's voting totals. The problem is that I want to update the score for the submission at the same time, but F() expressions are limited to only simple operations (it's missing support for log(), date_part(), sign() etc.)
From my limited experience with Django I can see 5 options here:
extend F() somehow (haven't looked at the code yet) to support the missing SQL functions; this is my preferred option and seems to fit within the Django framework the best
define a scoring function (much like reddit's 'hot' function) in my database, and have Django use the value of that function for the value of the score field; as far as I can tell, #2 is not possible
wrap my two step voting process in a suitably isolated transaction so that I can calculate the voting totals in Python and then update the Submission's voting totals without fear that another vote against the submission could be added/changed in the meantime; I'm hesitant to take this route because it seems overly complex - what is a "suitably isolated transaction" in this case anyway?
use raw SQL; I would prefer to avoid this entirely -- what's the point of an ORM if I have to revert to SQL for such a common use case as this! (Note that this coming from somebody who loves sprocs, but is using Django for ease of development.)
(edit: added this after further discussion) compute the score using an extra select parameter containing a call to my function; this would work but impose unnecessary load on the DB (would be forced to calculate the score for every submission ever made every time the query ran; caching could help here, but it still seems like a bit of lame workaround)
Before I embark on this mission to extend F() (which I'm not sure is even possible), am I about to reinvent the wheel? Is there a more standard way to do this? It seems like such a common use case and yet in an hour of searching I have yet to find a common solution...
EDIT: There is another option: set the default value of the field in the database script to be an expression containing my function. This is not as flexible as #1, but probably the quickest and cleanest approach to solving the problem (although my initial investigation into extending F() looks promising).
Why can't you just denormalize the score and reconstruct it with the Vote objects every once and a while?
If you can't do that, it is very easy to make a 'property' function that acts as an object attribute for scoring.
#property
def score(self):
... calculate score from Vote objects ...
return score
I've never used F() on a property like this, but it's Python, so I bet it works.
If you are using django-voting (which I recommend), you can put #3 in the manager's record_vote function since that's how all vote transactions take place.