updates

src/content/docs/guides/minimizing-costs.md

@@ -7,7 +7,12 @@ The HTTP Archive dataset is large and complex, and it's easy to write queries th
 
 ## Use clustered tables
 
-For example, the `httparchive.all.pages` table is [partitioned](https://cloud.google.com/bigquery/docs/partitioned-tables) and [clustered](https://cloud.google.com/bigquery/docs/clustered-tables) on the `client`, `is_root_page`, and `rank` columns, which means that queries that filter on these columns will be much faster and cheaper than queries that don't.
+Table | Partitioned on | Clustered on
+--- | --- | ---
+`httparchive.all.pages` | `date` | `client`, `is_root_page`, `rank`
+`httparchive.all.requests` | `date` | `client`, `is_root_page`, `is_main_document`, `type`
+
+For example, the `httparchive.all.pages` table is [partitioned](https://cloud.google.com/bigquery/docs/partitioned-tables) by `date` and [clustered](https://cloud.google.com/bigquery/docs/clustered-tables) on the `client`, `is_root_page`, and `rank` columns, which means that queries that filter on these columns will be much faster and cheaper than queries that don't.
 
 Legacy tables like `httparchive.pages.2023_05_01_desktop`, however, do not take advantage of these optimizations and always incur the full cost of scanning the entire table.