Plushcap here, summarizing the text in a neutral and interesting paragraph: Creating sample time-series data is crucial for testing various workloads, database features, or just to create fun samples. Knowing how to quickly generate large sets of data with native PostgreSQL and SQL functions can be a valuable skill. The built-in `generate_series()` function can be used to create large datasets quickly by joining multiple series using a CROSS JOIN or creating custom PostgreSQL functions as part of the query to generate more realistic values for your dataset. By leveraging these features, developers can harness the row value, counters with reset, and influence the pattern with relational data to create awesome sample data for all their testing and exploration needs. The examples demonstrated how to use `generate_series()` to create sine or cosine wave data with varying periods, amplitudes, and shifts, as well as combine it with random increasing data to shape the final dataset. By applying this knowledge, developers can quickly generate tens of millions of rows of realistic-looking data to test various workloads and database features.