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Customize Filters

This section details how to apply custom filters to your search query.

KDB.AI combines vector database functionality with traditional kdb database queries. In particular, you can combine a vector similarity search with traditional where clauses. The filter parameter is used for applying custom filtering to the query. This is specified using a list of triples where each triple has the form (operator; column name; values).

[("<=", "valFloat", 100), ("within", "qual", [0,2])]

[["<=", "valFloat", 100], ["within", "qual", [0,2]]]

The filters are applied in the order they are defined when selecting from the table.

Supported filter functions

Function Parameters Example
in Filters data that is not in the list of possible alternatives. ["in", "sym", ["AAPL", "MSFT"]] keeps symbols that are either AAPL or MSFT.
within Keeps numeric data that is within the bounds of a range using inclusive limits. ["within", "price", [100, 200]] keeps prices that are greater than or equal to 100 but less than or equal to 200.
< Keeps numeric data that is less than a threshold. ["<", "price", 100] keeps data that is less than 100.
> Keeps numeric data that is greater than a threshold. [">", "price", 100] keeps data that is greater than 100.
<= Keeps numeric data that is less than or equal to a threshold. ["<=", "price", 100] keeps data that is less than or equal to 100.
>= Keeps numeric data that is greater than or equal to a threshold. [">=", "price", 100] keeps data that is greater than or equal to 100.
= Keeps numeric data equals another value. ["=", "sym", "AAPL"] keeps only AAPL data.
<> Keeps data that is not equal to a value. ["<>", "sym", "AAPL"] keeps all data that is not AAPL.
like Filters string data that matches a simple expression ["like", "sym", "A*"] matches any symbols that start with an A.

Filtered search example

This example demonstrates a filtered query where the similarity search is run against vectors satisfying the filter condition. 

documents.search(vectors=[[1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0]], n=3, filter=[("within","createdDate",["2020.07.10D15:00:00.0000", "2021.07.10D15:00:00.0000"]),("<=", "length", 100)])

curl -s -H "Content-Type: application/json" localhost:8082/api/v1/kxi/search \
-d '{"table":"documents","n":3,"vectors":[[1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0,1.0,0.0,1.0]],"filter":[["within","createdDate",["2020.07.10D15:00:00.0000", "2021.07.10D15:00:00.0000"]],["<=", "length", 100]]}'

Next steps

Now that you're familiar with filters, you can do the following: