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Window Functions for Analytics
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Window Functions for Analytics

HardSQL · PostgreSQL

Problem

Write a complex SQL query using window functions to calculate running totals and moving averages across multi-million-row partitioned tables.

Use the provided measurement, entity, and region tables. Restrict measurements to January 2025 and calculate daily totals before producing the analytical results.

Output

  1. One row per entity and measurement date, with entity_id, entity_name, region_name, measured_at, daily_total, running_total, and moving_avg_3_rows.
  2. Include only entities with measurements in the requested period. The moving average uses the current row and up to two preceding dates for the same entity.
  3. Order by region_name, entity_id, and measured_at ascending.

Schema

measurement_events
ColumnTypeDescription
measurement_idPKBIGINTUnique measurement identifier
entity_idINTMeasured entity identifier
measured_atDATEMeasurement date and partition key
amountNUMERIC(12,2)Measured numeric value
entities
ColumnTypeDescription
entity_idPKINTEntity identifier
entity_nameVARCHAR(100)Entity display name
region_idINTAssociated region identifier
regions
ColumnTypeDescription
region_idPKINTRegion identifier
region_nameVARCHAR(100)Region display name
Tablesmeasurement_eventsentitiesregions
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CodePostgreSQL
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