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Optimize Large-Scale SQL Aggregation
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Optimize Large-Scale SQL Aggregation

HardSQL · PostgreSQL

Problem

Optimize a slow-running SQL query that aggregates millions of customer interaction events across multiple sharded tables.

Write a PostgreSQL query that processes the January 2025 event data from both shards, associates events with known customers, and returns only customer and event-type combinations with at least two qualifying events.

Output

  1. One row per customer and event type
  2. Columns: customer_id, customer_name, event_type, event_count, and total_duration_seconds
  3. Include only January events for known customers with at least two events
  4. Order by event_count descending, then customer_id ascending and event_type ascending

Schema

interaction_events_shard_a
ColumnTypeDescription
event_idPKBIGINTUnique interaction event identifier
customer_idBIGINTCustomer associated with the event
event_typeVARCHAR(30)Interaction type
occurred_atTIMESTAMPEvent timestamp
duration_secondsINTEGERDuration of the interaction in seconds
interaction_events_shard_b
ColumnTypeDescription
event_idPKBIGINTUnique interaction event identifier
customer_idBIGINTCustomer associated with the event
event_typeVARCHAR(30)Interaction type
occurred_atTIMESTAMPEvent timestamp
duration_secondsINTEGERDuration of the interaction in seconds
customers
ColumnTypeDescription
customer_idPKBIGINTUnique customer identifier
customer_nameVARCHAR(100)Customer display name
Tablesinteraction_events_shard_ainteraction_events_shard_bcustomers
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