[Elasticsearch] Integrate Elasticsearch for Fast Search Access to Startups and Projects

[mehalyna]

Task: Integrate Elasticsearch for Fast Search Access to Startups and Projects

Objective

To enhance the search performance and capabilities in the project, we aim to integrate Elasticsearch. This will enable quick, complex search queries on Startup and Project models, supporting features like keyword searches, filtering, and sorting.

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Sub-Tasks

1. Setup and Installation

   • Install Elasticsearch:
     • Run Elasticsearch locally or use a Docker container for development. For production, you may choose a managed Elasticsearch service.
   • Install Required Libraries:
     • Install django-elasticsearch-dsl and django-elasticsearch-dsl-drf libraries in your Django project.

     pip install django-elasticsearch-dsl django-elasticsearch-dsl-drf

2. Define Elasticsearch Settings

   • Update Django Settings:
     • Configure Elasticsearch settings in settings.py.

     ELASTICSEARCH_DSL = {
         'default': {
             'hosts': 'localhost:9200'
         },
     }

3. Create Elasticsearch Documents

   • Define Documents for Models:

     • Create Elasticsearch document definitions for Startup and Project models. These documents will map model fields to Elasticsearch fields.
     • Create a documents.py file in each relevant app (e.g., startups and projects).

     # startups/documents.py
     from django_elasticsearch_dsl import Document, Index
     from .models import Startup
     
     startup_index = Index('startups')
     
     @startup_index.doc_type
     class StartupDocument(Document):
         class Django:
             model = Startup
             fields = [
                 'company_name',
                 'description',
                 'funding_stage',
                 'location',
                 'industries',
             ]

   • Repeat for Projects:

     # projects/documents.py
     from django_elasticsearch_dsl import Document, Index
     from .models import Project
     
     project_index = Index('projects')
     
     @project_index.doc_type
     class ProjectDocument(Document):
         class Django:
             model = Project
             fields = [
                 'title',
                 'description',
                 'status',
                 'required_amount',
                 'startup',
             ]

4. Synchronize Data with Elasticsearch

   • Index Existing Data:

     • Run a management command to index existing data in Elasticsearch.

     python manage.py search_index --rebuild

   • Set Up Django Signals for Syncing:

     • Use Django signals to keep Elasticsearch indexes updated when data in the database changes.
     • Add signals in signals.py in each app to listen for post_save and post_delete events on Startup and Project.

5. Create DRF Views for Search Functionality

   • Build Search Views:

     • Implement views in views.py that leverage Elasticsearch to perform searches on Startup and Project.
     • Use django-elasticsearch-dsl-drf to create DRF views for search endpoints.

     # startups/views.py
     from django_elasticsearch_dsl_drf.viewsets import DocumentViewSet
     from .documents import StartupDocument
     from .serializers import StartupDocumentSerializer
     
     class StartupSearchViewSet(DocumentViewSet):
         document = StartupDocument
         serializer_class = StartupDocumentSerializer
         filter_backends = [
             FilteringFilterBackend,
             OrderingFilterBackend,
         ]
         search_fields = ('company_name', 'description')
         filter_fields = {
             'funding_stage': 'exact',
             'location': 'exact',
         }

   • Repeat for Projects.

6. Create Serializers for Elasticsearch Documents

   • Define Elasticsearch Document Serializers:
     • Create serializers for StartupDocument and ProjectDocument.

     # startups/serializers.py
     from rest_framework import serializers
     from .documents import StartupDocument
     
     class StartupDocumentSerializer(serializers.ModelSerializer):
         class Meta:
             model = StartupDocument
             fields = '__all__'

7. Update URLs

   • Add URLs for Search Endpoints:
     • Create URL routes for StartupSearchViewSet and ProjectSearchViewSet.

     # startups/urls.py
     from django.urls import path
     from .views import StartupSearchViewSet
     
     urlpatterns = [
         path('search/', StartupSearchViewSet.as_view({'get': 'list'}), name='startup-search'),
     ]

8. Testing

   • Write Unit Tests:
     • Test the search functionality with sample data to ensure the indexes are working as expected.
   • Perform Manual Testing:
     • Run searches with various filters and keywords to confirm Elasticsearch is providing fast and accurate results.

9. Documentation

   • Document API Endpoints:
     • Add endpoint descriptions, parameters, and example queries to the API documentation.

10. Deployment and Optimization

    • Configure Elasticsearch for Production:
      • Set up production configurations, including security settings, optimized indices, and backups.
    • Monitor and Tune:
      • Use monitoring tools to check Elasticsearch performance and make adjustments as necessary.

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Deliverables

• Working search functionality on the /startups/search/ and /projects/search/ endpoints.
• Documentation for API search endpoints.
• Tests covering indexing, querying, and filtering with Elasticsearch.

Notes

https://testdriven.io/blog/django-drf-elasticsearch/

https://codewithmuh.medium.com/how-to-integrate-elasticsearch-with-drf-a24ede1739d2

https://django-elasticsearch-dsl-drf.readthedocs.io/en/latest/