release: bump version to 0.68.0

docs/technical/en/backend-collectors.md

@@ -75,6 +75,8 @@ async def run(self, db):
 
 Manual trigger, data clearing, and cache clearing now enter the PostgreSQL data job queue. `collection_tasks` remains the task ledger. Collectors only own `fetch -> transform -> save`; the `data_jobs.py` worker claims `collect` / `clear_data` / `clear_cache` / `earth_refresh` jobs and writes progress back. Earth layer refresh relationships live in `earth_layer_adapters.py`; do not hand-code cache invalidation or WebSocket broadcasts inside individual collectors or buttons.
 
+Data deletion runs in batches so AIS-scale tables are not locked by one huge statement. A `clear_data` job clears `collected_data`, then source-specific AIS derived tables, and broadcasts `records_processed` as it goes; the console queue renders only user-facing text such as `Deleting data` and `Delete complete`, while internal table names remain in logs and raw task details. After AIS cleanup, the backend runs `ANALYZE ais_raw_observations` so datasource-list estimates converge quickly. The datasource directory uses PostgreSQL statistics for AIS record counts by default to avoid a cold-start `count(*)`; opening a single datasource detail row requests the exact count for that source.
+
 ## III. Collector List
 
 | Collector | Data type | Content | Frequency |