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fix: make iterate_properties query scale linearly - #203
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pesap merged 2 commits intoOct 21, 2026
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The property query scanned all of t_data for every membership, because t_data.membership_id had no index, and scanned a materialized scenario CTE for every output row. The CTE repeated each scenario tag once per membership of its Scenario object, so on large models it grew to millions of rows. Both scans made the query quadratic: on a 747 MB Eastern Interconnect XML it ran 13+ hours without finishing. Add an index on t_data.membership_id, and join scenario tags through the t_tag primary key instead of the CTE. The scenario category filter now reads scenario_category.name. On a NYISO subset (87k data rows) the query went from 50+ minutes to under a second, returning identical rows, including with scenario and scenario-category filters. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
mcllerena
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Oct 20, 2026
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The property query scanned all of t_data for every membership, because t_data.membership_id had no index, and scanned a materialized scenario CTE for every output row. The CTE repeated each scenario tag once per membership of its Scenario object, so on large models it grew to millions of rows. Both scans made the query quadratic: on a 747 MB Eastern Interconnect XML it ran 13+ hours without finishing.
Add an index on t_data.membership_id, and join scenario tags through the t_tag primary key instead of the CTE. The scenario category filter now reads scenario_category.name. On a NYISO subset (87k data rows) the query went from 50+ minutes to under a second, returning identical rows, including with scenario and scenario-category filters.