PostgreSQL · Pagila
actor
- Source rows
- 200
- Synthetic rows
- 200
- Broken foreign keys
- No foreign keys
- Rows equal to a source row
- 0%
Rows
Both databases, first rows by primary key, in one table: scrolling sideways moves them together. Rows at the same position are unrelated, unless the table holds kept reference data. Long values are cut at 60 characters.
| actor_id key | first_name | last_name | last_update |
|---|---|---|---|
| Source database · 12 of 200 rows | |||
| 1 | PENELOPE | GUINESS | 2022-02-15 09:34:33+00:00 |
| 2 | NICK | WAHLBERG | 2022-02-15 09:34:33+00:00 |
| 3 | ED | CHASE | 2022-02-15 09:34:33+00:00 |
| 4 | JENNIFER | DAVIS | 2022-02-15 09:34:33+00:00 |
| 5 | JOHNNY | LOLLOBRIGIDA | 2022-02-15 09:34:33+00:00 |
| 6 | BETTE | NICHOLSON | 2022-02-15 09:34:33+00:00 |
| 7 | GRACE | MOSTEL | 2022-02-15 09:34:33+00:00 |
| 8 | MATTHEW | JOHANSSON | 2022-02-15 09:34:33+00:00 |
| 9 | JOE | SWANK | 2022-02-15 09:34:33+00:00 |
| 10 | CHRISTIAN | GABLE | 2022-02-15 09:34:33+00:00 |
| 11 | ZERO | CAGE | 2022-02-15 09:34:33+00:00 |
| 12 | KARL | BERRY | 2022-02-15 09:34:33+00:00 |
| Synthetic database · 12 of 200 rows | |||
| 1 | NICHOLAS | ANDERSON | 2022-02-15 09:34:33+00:00 |
| 2 | WALTER | CASTILLO | 2022-02-15 09:34:33+00:00 |
| 3 | LARS LUKAS | ROSE | 2022-02-15 09:34:33+00:00 |
| 4 | JACKSON | FORD | 2022-02-15 09:34:33+00:00 |
| 5 | HEN | HAMILTON | 2022-02-15 09:34:33+00:00 |
| 6 | HARPER | RUSSELL | 2022-02-15 09:34:33+00:00 |
| 7 | LIAM LIAM | WILLIAMS | 2022-02-15 09:34:33+00:00 |
| 8 | LINDA LIAM | HALL | 2022-02-15 09:34:33+00:00 |
| 9 | RUSSELL | ANDERSON | 2022-02-15 09:34:33+00:00 |
| 10 | OLIVIA | ANDERSON | 2022-02-15 09:34:33+00:00 |
| 11 | DONNA LIAM | PORTER | 2022-02-15 09:34:33+00:00 |
| 12 | LIAM | THOMPSON | 2022-02-15 09:34:33+00:00 |
Column by column
Each figure is computed from all rows of both databases in the same way. S is the source, Y the synthetic copy. Difference runs from 0 (same distribution) to 1 (no overlap): Kolmogorov-Smirnov for numbers and times, total variation for columns with few values. Personal columns are meant to differ, so they show how many values also appear in the source instead. Lyrebird draws names from built-in lists, not from the source, so common names can match.
| Column | Model read it as | How it was generated | Empty | Distinct | Range or length | Most common | Difference |
|---|---|---|---|---|---|---|---|
| actor_idinteger | record key | New key values | S 0% Y 0% | S 200 Y 200 | S 1 → 200 Y 1 → 200 | S — Y — | — |
| first_nametext | first namepersonal | New text in the measured format | S 0% Y 0% | S 128 Y 93 | S 5.3 chars avg Y 6 chars avg | S — Y EMMA 5% · WALTER 3.5% · LIAM 3.5% · OLIVIA 2.5% · SOPHIA 2.5% · LOGAN LIAM 2.5% | 10% in source |
| last_nametext | last namepersonal | New text in the measured format | S 0% Y 0% | S 121 Y 83 | S 6.2 chars avg Y 6 chars avg | S — Y ANDERSON 7% · ALLEN 5% · TAYLOR 4.5% · WHITE 4.5% · THOMAS 4% · FISHER 3% | 9.5% in source |
| last_updatetimestamp with time zone | lifecycle timestamp | Times from the measured distribution | S 0% Y 0% | S 1 Y 1 | S 2022-02-15 09:34:33+00:00 → 2022-02-15 09:34:33+00:00 Y 2022-02-15 09:34:33+00:00 → 2022-02-15 09:34:33+00:00 | S 2022-02-15 09:34:33+00:00 100% Y 2022-02-15 09:34:33+00:00 100% | 0 KS |