Django 带分面搜索的弹性搜索 DSL

Question

I am using ElasticSearch-DSL with my Django App to search for products. I am able to fetch the results and put them in my template (search.html) and it is working as expected.

I did some research but could not figure out how to add faceted search to my templates and how to implement faceted search.

My documents.py

from django_elasticsearch_dsl import Document
from django_elasticsearch_dsl.registries import registry
from products.models import Products
from elasticsearch_dsl import FacetedSearch, TermsFacet, DateHistogramFacet


@registry.register_document
class CarDocument(Document):
    class Index:
        # Name of the Elasticsearch index
        name = 'cars'
        # See Elasticsearch Indices API reference for available settings
        settings = {'number_of_shards': 1,
                    'number_of_replicas': 1}



    class Django:
        model = Products # The model associated with this Document

        # The fields of the model you want to be indexed in Elasticsearch
        fields = [
            'body_id',
            'product_make',
            'model_name',
            'product_id',
            'model_id', 
            'variant',
            'transmission',
            'bodystyle',
            'yom',
            'status',
            'ex_showroom',
            'registration_fees',
            'insurance',
            'handling_charges',
            'fastag',
            'on_road_price',
            'min_price',
            'max_price',
            'rating',

        ]

        # Ignore auto updating of Elasticsearch when a model is saved
        # or deleted:
        # ignore_signals = True

        # Don't perform an index refresh after every update (overrides global setting):
        # auto_refresh = False

        # Paginate the django queryset used to populate the index with the specified size
        # (by default it uses the database driver's default setting)
        # queryset_pagination = 5000

and my views.py code is mentioned below:

from django.shortcuts import render
from elasticsearch_dsl import Q
from elasticsearch_dsl.query import MultiMatch
# Create your views here.
from search.documents import CarDocument
from products.models import Products
from django.core.paginator import (
    Paginator, Page, EmptyPage, PageNotAnInteger
)
from django.utils.functional import LazyObject

def search(request):
   q = request.GET.get('q')
   if q:
       #cars = CarDocument.search().query("match", model_name=q)
      q = request.GET.get('q', None)
      query1 = MultiMatch(query=q,  fields=['product_make', 'bodystyle','model_name','variant','transmission','yom'],fuzziness='AUTO')

      s = CarDocument.search().query(query1)
      total = s.count()
      s= s[0:total]
      cars = s.execute()

      paginator = Paginator(cars, 100)
      page = request.GET.get('page')
      cars = paginator.get_page(page)
   else:
      cars = ''


   return render(request, 'search/search.html', {'cars': cars})

def product_detail(request,*args, **kwargs):

    return render(request, 'product_details.html', {})

My urls.py

urlpatterns = [
    url(r'^$', home_view, name='home'),
    url(r'^home/', home_view, name='home'),
    url(r'^search/', search, name='search'),
    url(r'^select/', select, name='select'),
    url('ajax/home_view/',home_view, name='ajax_load_models'),
    url(r'^carmodels/(?P<product_make>\w+)/(?P<model_name>\w+)/$', product_detail, name='product_detail'),
    ]+ static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

My question is what changes should I make and where to use faceted search on product_make, body_style, max-min price range, etc.

Answer 1

There is an example facet on this page :

 class BlogSearch(FacetedSearch): index = 'blogs' doc_types = [Blog, Post] fields = ['title', 'category', 'description', 'body'] facets = { 'type': TermsFacet(field='_type'), 'category': TermsFacet(field='category'), 'weekly_posts': DateHistogramFacet(field='published_from',interval='week') } def search(self): ' Override search to add your own filters ' s = super(BlogSearch, self).search() return s.filter('term', published=True) # when using: blog_search = BlogSearch("web framework", filters={"category": "python"}) # supports pagination blog_search[10:20] response = blog_search.execute() # easy access to aggregation results: for category, hit_count, is_selected in response.facets.category: print( "Category %s has %d hits%s." % ( category, hit_count, ' and is chosen' if is_selected else '' ) )

The above code is copyrighted by the contributors to the linked docs page and is licensed under a Apache License 2.0 .