batch_etl benefits from time_series

batch etlBenefits Fromtime series rollup

Source: Workload·Target: Pattern

Summary

Batch ETL workloads that process historical time series data benefit from rollup pre-aggregation to reduce the data volume that must be scanned for each pipeline run.

Evidence

·batch_etl's access pattern is range_scan + aggregate with source-read impact as a primary constraint (workloads/batch_etl.yaml)
·time_series_rollup reduces row count for range queries so rolled-up scans are orders of magnitude faster; shares materialized_view as a related pattern (patterns/time_series_rollup.yaml)

Evidence grounding

Grounded, 2 supporting items

Pre-aggregation cuts the data volume ETL's scan/aggregate must process (when the source is time-series).