BigQuery Optimization Guidebook

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🎯 Purpose

This guidebook focuses on optimizing BigQuery SQL for speed, cost-efficiency, and scalability. It includes best practices for partitioning, filtering, schema design, and usage control.

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💰 1. BigQuery Cost Model

• You are charged per query based on scanned bytes
• ✅ Minimize scanned columns → avoid SELECT *
• ✅ Use preview tools to check query size before running

SELECT column1, column2
FROM `project.dataset.table`
WHERE DATE(timestamp_col) = CURRENT_DATE()

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📦 2. Partitioning Best Practices

Type	Use Case
DATE partition	Time-series data (events, logs, sessions)
INGESTION_TIME	When no date field exists
INTEGER RANGE	Bucketing IDs, static ranges

• Use _PARTITIONTIME for filtering:

WHERE _PARTITIONTIME >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)

✔️ Always include partition filters to avoid scanning all partitions

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🧱 3. Clustering

• Improves performance after partitioning
• Works best on fields with moderate-to-high cardinality (e.g., user_id, device)

CREATE TABLE ...
PARTITION BY DATE(event_date)
CLUSTER BY user_id, event_type

✔️ Cluster on fields commonly used in filtering, joining, grouping

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🔍 4. Query Structure Tips

Strategy	Example
Avoid SELECT *	Select only needed fields
Use CTEs	Break down logic for readability + reuse
Push filters early	Apply WHERE before JOINs when possible
Avoid CROSS JOINs	Use JOIN ON keys instead
Limit data for debugging	Use LIMIT 1000 + WHERE slices

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🧪 5. Safe & Efficient Functions

-- Avoid crashes from bad casts
SELECT SAFE_CAST(amount AS FLOAT64)

-- Handle nulls gracefully
SELECT IFNULL(channel, 'unknown')

✔️ Use SAFE_CAST, IFNULL, COALESCE to avoid type errors

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📊 6. Materialized Views & Temp Tables

• Use materialized views for pre-aggregated logic (cost-efficient)
• Use temporary tables for intermediate analysis

CREATE TEMP TABLE user_counts AS
SELECT user_id, COUNT(*) AS events
FROM `project.dataset.events`
GROUP BY user_id;

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✅ Optimization Checklist

• [ ] Columns scoped precisely — no SELECT *
• [ ] Partition filters applied (_PARTITIONTIME, DATE(event_date))
• [ ] Clustering enabled for common filters or joins
• [ ] Temporary tables or CTEs used to structure logic
• [ ] Previewed query scan size before running (optional)
• [ ] SAFE functions used to prevent failures

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💡 Tip

“In BigQuery, clean queries aren’t just elegant — they’re affordable.”