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Optimizing Slow SQL and ETL
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Optimizing Slow SQL and ETL

MediumSQL · PostgreSQL

Problem

What is your approach to optimizing slow-running SQL queries or ETL jobs?

For this hands-on exercise, write PostgreSQL SQL that returns premium totals for active policies during 2025. Your solution should demonstrate an optimization-minded approach, including early filtering and appropriate handling of policies without qualifying payments.

Output

  1. One row per active policy issued before 2026-01-01.
  2. Columns: policy_id, customer_name, product_name, total_successful_premium, and latest_successful_payment.
  3. Include policies with no successful 2025 payments, showing zero and NULL respectively. Order by policy_id ascending.

Schema

customers
ColumnTypeDescription
customer_idPKINTUnique customer identifier
customer_nameVARCHAR(120)Customer full name
cityVARCHAR(80)Customer city
policies
ColumnTypeDescription
policy_idPKINTUnique policy identifier
customer_idINTCustomer who owns the policy
product_nameVARCHAR(100)Insurance product name
statusVARCHAR(20)Current policy status
issue_dateDATEDate the policy was issued
premium_payments
ColumnTypeDescription
payment_idPKINTUnique payment identifier
policy_idINTPolicy associated with the payment
payment_dateDATEDate the payment was recorded
amountDECIMAL(12,2)Payment amount
payment_statusVARCHAR(20)Payment processing status
Tablespoliciescustomerspremium_payments
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