I would like to give higher score for products not purchased yet by the user. We do not sell more than one piece of each product per user so there is no point to promote sold products to a user.
In some cases I filter out product based on id. But I would like to give a negative boost if id is in given list.
Any ideas how to implement this?
Well the best way to implement this would be as follows -
Maintain another index where each document has a field purchased which is an array holding docID's of purchased products.
Use function score query and use the function score function to depromote the purchased documents.
Use terms filter in the function score function. In terms filter , its possible to look up to a different document/field for the terms filter parameters. Utlize that to point to the purchased information
Provide boost as a negative value
Related
I have a site that has a search using elasticsearch.
There is a rule that I need to implement:
the site is a search engine for women's products
but we have some stores that will pay to have their products appear on the site
we need to give priority to products from paying stores
We think the formula would be this:
store that is a customer (higher weight)
number of product views
Is there a way to use function_score to solve this?
and display the products randomly? (without blocking the list with only products from paying stores)
I'm working on a e-commerce search page and need to free text search products and have multiple facet options and sorting capabilities. The issue I'm facing has to do with product prices:
One product has multiple prices - there are special discounts, B2B customer specific prices, and specific B2C prices. There could be a few hundred prices per product.
I need to be able to do to a full text search on products, but still be able to sort on one of the selected price groups.
My initial though would be to put all of the prices into the product item, but that means I'll need to update the product objects in the index every time a price changes - which is often. This will also make the objects quite big.
I see that elasticsearch now has the capability of HasParent/HasChildren queries, but I am not sure if that is the right way to go, or if it even is possible.
Is it possible to keep prices as a separate type outside the product type and use the HasParent/HasChilden queries to sort the procuts on the price?
My initial though would be to put all of the prices into the product item, but that means I'll need to update the product objects in the index every time a price changes - which is often. This will also make the objects quite big.
I would personally be inclined not to store complex pricing data within Elasticsearch, at least not prices calculated by business logic such as discounts and specific B2C prices.
A base price could be stored for querying and sorting, and apply pricing logic to this with scripting, using script queries and script sorting, respectively.
I see that elasticsearch now has the capability of HasParent/HasChildren queries, but I am not sure if that is the right way to go, or if it even is possible. Is it possible to keep prices as a separate type outside the product type and use the HasParent/HasChilden queries to sort the procuts on the price?
Parent/Child relationships operate on documents within a single index, with a join datatype field on a document to indicate the relationship between a parent and a child, and child documents indexed on the same shard as the parent. If children are not evenly distributed across parents/shards e.g. one parent document has a million children and the others have only a few each, it's possible to end up with hot spots within shards that can affect performance. Product and pricing data doesn't feel like a good fit for Parent/Child; pricing sounds like it's too dynamic to be stored within documents.
We car planning to store prices data to Memcache. prices are subject to car variant and location(city). This is how it is stored in the database.
variant, city, price
21, 48, 40000
Now the confusion is that how do we store this data into Memcache.
Possibility 1 : We store each price in separate cache object and do a multiget if the price of all variant belongs to a model need to be displayed on a single page.
Possibility 2 : We store prices at the model, city level. Prices of all variants of a model will be stored in a single object. This object will be slightly heavy but multiget wouldn't be required.
Need your help in taking the right decision.
TLDR: It all depends on how you want to expose the feature to your end users, and what the query pattern looks like.
For example:
If your flow is that a user can see all the variant prices on a detail page for a city, then you could use <city_id>_<car_model_id> as the key, and store all data for variants against that key (Possibility 2).
If the flow is that a user can see prices of all variants across cities on a single page, then you would need the key as <car_model_id> and store all data as Json against this key
If the flow is that a user can see prices of one variant at a time only for every city, then you would use the key <city_id>_<car_variant_id> and store prices.
One thing to definitely keep in mind is the frequency with which you may have to refresh the cache/ perform upserts, which in the case of cars should be infrequent (who changes the prices of a car every day/second). So, I would have gone with option 1 above (Possibility 2 as described by you).
I have an application with around 700 000 active products with actual stock quantity.
Each product can have multiple attributes and categories.
Product name, description and attributes can be delivered to the user in a few languages.
What I need to achive is fast search. By fast I mean that for example for product group which contains 250k of products I would like to return a first page of sorted results in 100ms.
My first thought was to deformalize data and push it into document db like elastic search. But there is one issue - product price: it depends on the user that is actually logged in.
Currently there will be 30k users. Each user can have different discount for each product category or even for each particular product. When discount or price is changed there is a business requirement to synchronize prices in a few minutes. Potentially system could compute prices for search results on fly, but there is an issue with sorting and pagination. When group consist of 250k products it will be hard to get results, compute price, sort and return given page.
Is there any way to return user dependent field in elastic search? Or I should rather start looking into some other solutions like graph databases?
I am using Magento 1.6.2.
I need to find an easy way of checking which category is the "default" category for any given product, where multiple categories have been assigned to that product.
The reason for this is as follows:
I have different discount amounts available on different categories in my store.
Where a product falls into two categories with different discounts applied, the highest discount should be applied to that product, but if that product has been added to the system (created) with a default category that has a lower discount, and then afterwards added into the higher discount category as well, the higher discount level is not being applied when that product is purchased.
If, however, I add the product to the higher discount category first, and then to the lower discount category afterwards (so the product appears on my website in all the right places), the correct (higher) discount level applies to that product.
I can only assume, therefore, that the default (or primary, or first, however you want to label it) category is the one that determines the outcome of the discount level to be applied to it. If this is wrong, then I need a lesson in understanding the mechanics behind this to see where I have gone wrong in the overall setup of this system...
If my assumption is correct, then I need a way to determine which category any given product (using the SKU) has been assigned to first, to ensure that the correct discount can be applied to that product.
I hope I have explained that clearly enough!
Does anyone have any suggestions. I have been unable to find information on this regardless of guessing specific search terms. The only things I can find are related to general category retrieval, and not this very specific task I need.
Cheers!
Im afraid your assumption is incorrect. Magento has no concept of a 'primary' category for a product. It only knows the product is in category id(s);
1, 12, 234
etc. The id's are stored numercially with no idea of which category might be more important than another.
What you could do instead is create a custom attribute and enter the id of the category you want to treat as 'primary' and retreive this attribute value when working out whether to give more discount or not.