refactor: Update StatVarAggregator to use procedural BigQuery SQL features

[SandeepTuniki]

This is a purely refactoring PR. No functionality changes, or bug fixes.

This PR refactors the statvar aggregation SQL query. Presently the query is constructed through several python helpers as small snippets, and then combined together. But it's hard to logically follow the query's order and flow due to python's loops and conditions. So I refactored it to take advantage of BQ's native procedural features (i.e; variables, conditions, loops, and temp functions). Now the query is linear and easy to follow.

[codacy-production]

Not up to standards ⛔

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🟢 Metrics -8 complexity

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[gemini-code-assist]

Code Review

This pull request refactors the StatVarAggregator to consolidate the TimeSeries and Observation queries into a single multi-statement SQL script using temporary tables and BigQuery query parameters, alongside adding corresponding unit tests. The feedback suggests keeping the entities and facet columns as JSON type throughout the temporary tables to avoid expensive serialization/deserialization overhead, and simplifying the UpdateFacet temporary function by using a single JSON_SET call with multiple path-value pairs.