Metadata large_catalog_schema_summary

Metadata benchmark · all Metadata queries

Representative SQL

Rendered in the benchmark’s native SQL with default parameters (no dialect translation available).

SELECT
  COUNT(DISTINCT t.table_name) AS table_count,
  COUNT(c.column_name) AS total_columns,
  AVG(col_counts.column_count) AS avg_columns
FROM information_schema.tables AS t
LEFT JOIN information_schema.columns AS c
  ON t.table_name = c.table_name AND t.table_schema = c.table_schema
LEFT JOIN (
  SELECT
    table_name,
    COUNT(*) AS column_count
  FROM information_schema.columns
  WHERE
    table_name LIKE 'benchbox_catalog_%'
  GROUP BY
    table_name
) AS col_counts
  ON t.table_name = col_counts.table_name
WHERE
  t.table_name LIKE 'benchbox_catalog_%'

Representative DataFrame

No DataFrame implementation is registered for this query.

Get the exact query for your run

The blocks above are representative. To get the precise statement a specific platform runs at a specific scale, substitute your own values:

from benchbox import MetadataPrimitives

bench = MetadataPrimitives(scale_factor=1.0)            # your scale factor
print(bench.get_queries()['large_catalog_schema_summary'])

Source

Query text: benchbox/core/metadata_primitives/queries.py