There is a complex analytical query on SCADA tags for the last 30 days with grouping by hours and filters on several tags. The query runs slowly. What would you do?

To optimize a complex analytical query on SCADA tags with grouping and filters, I would take the following steps:

1. Index checking: Ensure that indexes are created on columns involved in filters and groupings (e.g., tags and time).

2. Data aggregation: Consider pre-aggregating data (e.g., daily or hourly summaries) to reduce the volume of data processed.

3. Query optimization: Rewrite the query using more efficient constructs, avoiding subqueries and functions in WHERE that hinder index usage.

4. Parallelization: If the DBMS supports it, use parallel query execution or break the query into parts.

5. Caching: Use caching of results for repeated queries.

6. Profiling: Run EXPLAIN PLAN or a similar tool to identify bottlenecks in the execution plan.

7. Archiving: If data for 30 days is too large, consider storing old data in an archive with a separate structure.

8. Use of specialized storage: Consider using time-series databases or OLAP solutions optimized for such queries.

Example: if the query groups by hours, you can pre-create a materialized view with data aggregated by hours and update it regularly to speed up retrieval.