How to Analyze Execution Plans in BigQuery

How do I analyze BigQuery execution plans with EXPLAIN?

EXPLAIN and EXPLAIN ANALYZE reveal BigQuery’s stage-by-stage execution plan, slot usage, and data movement so you can tune query cost and speed.

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Description

Example H2

Example H3

What does the BigQuery execution plan show?

The plan lists each stage, its input bytes, shuffle bytes, estimated rows, and slot-time consumed. Reading it helps locate skewed joins, expensive scans, and unnecessary shuffles.

How do I get a plan without running the query?

Prefix the statement with EXPLAIN. BigQuery performs a dry-run and returns JSON plus a tabular view in the console, so no slots are billed.

How do I see actual runtime statistics?

Use EXPLAIN ANALYZE.The query runs fully, then returns the same plan augmented with observed rows, bytes, and timing—ideal for verifying optimizations.

Which columns matter most?

input_rows and input_bytes flag large scans. shuffle_output_bytes shows network-heavy stages. slot_ms reveals stages monopolizing compute.

How can I spot skewed joins?

Look for a join stage where one input is tiny and the other huge, or where parallel_inputs differs greatly between sides.Consider reshuffling or clustering the large table.

Best practices for faster plans?

Partition and cluster large tables, filter early, avoid SELECT *, push aggregations below joins, and prefer EXISTS over DISTINCT when deduplicating.

Can I export the plan for tooling?

Yes. The first column returned by EXPLAIN contains JSON. You can save it to Cloud Storage or feed it into visualization tools.

Does EXPLAIN count toward quotas?

Dry-run EXPLAIN uses negligible resources and is free.EXPLAIN ANALYZE charges for the query because it executes fully.

When should I choose ANALYZE over INFORMATION_SCHEMA?

Use ANALYZE when you need stage-level slot and shuffle metrics. Use INFORMATION_SCHEMA.JOBS_BY_* for high-level job profiling across many queries.

Why How to Analyze Execution Plans in BigQuery is important

How to Analyze Execution Plans in BigQuery Example Usage


EXPLAIN
SELECT o.id,
       COUNT(*) AS item_cnt,
       SUM(oi.quantity * p.price) AS order_total
FROM   `ecommerce.Orders`      AS o
JOIN   `ecommerce.OrderItems`  AS oi ON oi.order_id   = o.id
JOIN   `ecommerce.Products`    AS p  ON p.id          = oi.product_id
WHERE  o.order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY)
GROUP  BY o.id
ORDER  BY order_total DESC;

How to Analyze Execution Plans in BigQuery Syntax


EXPLAIN [ANALYZE] [VERBOSE]
SELECT ... ;

-- e-commerce example
EXPLAIN ANALYZE
SELECT c.name,
       SUM(oi.quantity * p.price) AS lifetime_value
FROM   `ecommerce.Customers`   AS c
JOIN   `ecommerce.Orders`      AS o  ON o.customer_id = c.id
JOIN   `ecommerce.OrderItems`  AS oi ON oi.order_id   = o.id
JOIN   `ecommerce.Products`    AS p  ON p.id          = oi.product_id
GROUP  BY c.name
ORDER  BY lifetime_value DESC
LIMIT  10;

Common Mistakes

Running EXPLAIN instead of EXPLAIN ANALYZE when real slot and shuffle metrics are required. Fix: add ANALYZE to execute and collect runtime stats.
Ignoring high shuffle_output_bytes, assuming storage is the only cost driver. Fix: repartition or cluster tables to reduce data movement across slots.