How to validate data with ParadeDB in PostgreSQL

How do I validate ParadeDB vector data in PostgreSQL?

validate_data checks that vector columns managed by ParadeDB contain valid, on-dimension, non-NULL embeddings and reports any broken rows.

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Description

Example H2

Example H3

What does the validate_data function do?

validate_data scans a chosen vector column, confirms every embedding has the expected dimension, detects NULL values, and returns a list of offending row IDs. This prevents silent search failures caused by malformed vectors.

When should you run validate_data?

Run it after bulk imports, before building a new index, or on a schedule in CI to keep your similarity search dependable and fast.

How do you call validate_data?

Call the function from the parade schema, passing the table name, vector column, and expected dimension. Optional parameters let you choose a sampling size or abort on the first error.

Example: check product embeddings

SELECT * FROM parade.validate_data( table_name => 'products', column_name => 'embedding', dimension => 384, abort_on_error => false);

The query returns a JSON array of row IDs whose vectors are NULL, the wrong length, or not finite.

What does the result look like?

You receive a SETOF RECORD with two columns: id (primary key) and reason (text). An empty set means your data is clean.

Best practices for validate_data

Store the output in a temporary table and fix issues with an UPDATE or DELETE. Automate the check with a nightly scheduled job.

Can validate_data run on a sample?

Yes—use sample_size to validate only N random rows for faster feedback in development. Omit the parameter to scan the full table in production.

Is validate_data transaction-safe?

It runs read-only and can be wrapped in a transaction so your fix-up statements follow atomically.

Why How to validate data with ParadeDB in PostgreSQL is important

How to validate data with ParadeDB in PostgreSQL Example Usage


-- Validate that every order row has a non-NULL total_amount
SELECT *
FROM parade.validate_data(
    table_name      => 'orders',
    column_name     => 'total_amount',
    dimension       => 1,
    sample_size     => NULL,
    abort_on_error  => false);
-- Returns rows where total_amount IS NULL or NaN.

How to validate data with ParadeDB in PostgreSQL Syntax


SELECT parade.validate_data(
    table_name      => 'table_name',            -- text, required
    column_name     => 'vector_column',         -- text, required
    dimension       => integer,                 -- required
    sample_size     => integer DEFAULT NULL,    -- optional, rows to sample
    abort_on_error  => boolean DEFAULT true     -- optional, stop on first error
);
-- Returns: SETOF RECORD (id bigint, reason text)

-- Ecommerce context
SELECT parade.validate_data(
    table_name      => 'products',
    column_name     => 'embedding',
    dimension       => 384,
    sample_size     => 1000,
    abort_on_error  => false);

Common Mistakes

Mistake: Omitting the dimension argument. Why it’s wrong: validate_data cannot infer the correct length and will accept any vector, missing errors. Fix: Always supply the expected dimension.
Mistake: Running validate_data inside a write transaction holding heavy locks. Why it’s wrong: the scan is read-only but the lock blocks writers, hurting throughput. Fix: execute in a separate snapshot or during low-traffic windows.