# Row generator

The long_sequence() function may be used as a row generator to create table data for testing. Basic usage of this function involves providing the number of iterations required. Deterministic pseudo-random behavior can be achieved by providing seed values when calling the function.

This function is commonly used in combination with random generator functions to produce mock data.

## long_sequence​

• long_sequence(iterations) - generates rows
• long_sequence(iterations, seed1, seed2) - generates rows deterministically

Arguments:

-iterations: is a long representing the number of rows to generate. -seed1 and seed2 are long64 representing both parts of a long128 seed.

### Row generation​

The long_sequence() function can be used to generate very large datasets for testing e.g. billions of rows.

long_sequence(iterations) is used to:

• Generate a number of rows defined by iterations.
• Generate a column x:long of monotonically increasing long integers starting from 1, which can be accessed for queries.

### Random number seed​

When long_sequence is used conjointly with random generators, these values are usually generated at random. The function supports a seed to be passed in order to produce deterministic results.

note

Deterministic procedural generation makes it easy to test on vasts amounts of data without actually moving large files around across machines. Using the same seed on any machine at any time will consistently produce the same results for all random functions.

Examples:

Generating multiple rows
SELECT x, rnd_double()FROM long_sequence(5);
xrnd_double
10.3279246687
20.8341038236
30.1023834675
40.9130602021
50.718276777
Accessing row_number using the x column
SELECT x, x*xFROM long_sequence(5);
xx*x
11
24
39
416
525
Using with a seed
SELECT rnd_double()FROM long_sequence(2,128349234,4327897);
note

The results below will be the same on any machine at any time as long as they use the same seed in long_sequence.

rnd_double
0.8251337821991485
0.2714941145110299