Hey everyone, I’m new to SOLR and could use some guidance. I’m working on an e-commerce site with a SQL database. We want to use SOLR for our category pages to show product info like stock and price. We also need to hide out-of-stock items.
I’m trying to use Delta import queries to speed things up, but I’m worried about page performance and keeping data current. Our database queries are complex with lots of joins, so updating SOLR is slow. This makes it hard to keep stock info up-to-date.
I’m not sure if I should:
Put all data in SOLR and use it exclusively
Just use SOLR for product IDs and get details from SQL
What’s the best way to set this up? Any tips on balancing speed and accuracy?
From my experience, a hybrid approach tends to work best for e-commerce platforms with complex data structures. I’d recommend keeping most product data in SOLR for fast searches and category browsing, but maintain real-time stock levels in your SQL database. This setup allows you to leverage SOLR’s search capabilities while ensuring accurate inventory information.
For implementation, consider using SOLR for product IDs, names, descriptions, and category information. Then, create a lightweight API that queries your SQL database for current stock levels when displaying product details or processing orders. This method balances search performance with data accuracy.
To optimize SOLR updates, focus on incremental indexing for changed products only, rather than full reindexes. Also, look into batch processing for stock updates during off-peak hours to reduce system load. Remember, perfect real-time sync isn’t always necessary – slight delays are often acceptable in e-commerce scenarios.
Hey Mike_Energetic! Your SOLR integration question is super interesting. I’ve been tinkering with similar setups and know how tricky it can be to get that balance just right.
Have you considered a hybrid approach? Maybe use SOLR for the basic product info and fast searches, but keep the real-time stock data in your SQL database? That way, you could update SOLR less frequently for the stuff that doesn’t change much, and just do a quick SQL check for stock levels when someone views a product.
I’m curious - how often does your stock actually change? And how many products are we talking about here? Those factors could really influence the best strategy.
Also, have you looked into caching solutions? They might help with those complex database queries without putting too much strain on SOLR.
What’s been your biggest pain point so far in trying to set this up?
yo mike, SOLR can be a pain! i’ve dealt with similar stuff. maybe try indexing just essential product data in SOLR (id, name, price) and fetch real-time stock from SQL when needed. it keeps SOLR light and fast, but gives u accurate stock info. also, consider async updates to SOLR during off hours to reduce load. whats ur traffic like? that could affect the approach too