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Generating a sequence of numbers in a query is fairly hard and time consuming in SQL, but super useful for things like generating data and avoiding loops. A common solution is to use a numbers table.

At Narrator we frequently use a sequence to generate test data, so we have a numbers table of our own:


We generated the data in Python as a dict – we have a backend system that can insert tables.

    N = 10000000
    number_data = dict(
        columns=[dict(name="number", type="integer")],
        rows=[dict(number=num) for num in range(N)],

But what if you wanted to do this in SQL? Here's how to do it for a few different warehouses we work with.


Snowflake has a generator function to do this automatically. The following code is basically straight from the docs. Here we're selecting the seq4() function which generates a 4-byte integer sequence.

select seq4() as number
from table(generator(rowcount => 10000000)) 
order by 1;


Postgres supports generate_series() so this is fairly straightforward.

SELECT * FROM generate_series(0,10000000);

I haven't tested the performance of this but if you're using numbers this large it's probably best to create a table or materialized view.


The best way I've found to generate 10M numbers is using a cross-join.

Note that this will take a fairly long time – at least several minutes. If you want to try with something smaller just remove a few digits (g, f) from the query.

Some people also use generate_series(), but that's officially unsupported and won't work on queries that insert data.

Azure SQL

The code is largely the same for Azure, with some slight changes for T-SQL's syntactic differences.

Inserts 10M numbers into a table. This script should also work with Azure Synapse Analytics

Big Query

StackOverflow has an answer suggesting the use of the generate_array function but I haven't had a chance to try out this approach. It looks like it's limited to about 1M rows per call – and I have no idea how it performs.

Generate 1M rows in BigQuery


If you have a pointer to a snippet for any other warehouses please feel free to contact me and I'll update the post.