Snapshots are an artifact of calls to
pgml.train() that specify the
y_column_name parameters. See Training Overview for ways to create new snapshots.
CREATE TABLE IF NOT EXISTS pgml.snapshots( id BIGSERIAL PRIMARY KEY, relation_name TEXT NOT NULL, y_column_name TEXT NOT NULL, test_size FLOAT4 NOT NULL, test_sampling pgml.sampling NOT NULL, status TEXT NOT NULL, columns JSONB, analysis JSONB, created_at TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT clock_timestamp(), updated_at TIMESTAMP WITHOUT TIME ZONE NOT NULL DEFAULT clock_timestamp() );
Every snapshot has an accompanying table in the
pgml schema. For example, the snapshot with the primary key
42 has all data saved in the
test_sampling was set to
random during training, the rows in the table are ordered using
ORDER BY RANDOM(), so that future samples can be consistently and efficiently randomized.