Query complexity analysis in GraphQL - Step-by-Step Execution

Concept Flow - Query complexity analysis

Start: Receive GraphQL Query

↓

Parse Query Structure

↓

Traverse Query Fields

↓

Calculate Complexity per Field

↓

Sum Field Complexities

↓

Compare Total Complexity to Limit

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Reject Query

The system receives a GraphQL query, breaks it down, calculates complexity for each part, sums it, and decides if it is allowed based on a set limit.

Execution Sample

GraphQL

query {
  user(id: "1") {
    name
    posts {
      title
      comments {
        text
      }
    }
  }
}

This query requests a user's name, their posts' titles, and comments' text, which will be analyzed for complexity.

Execution Table

Step	Field	Complexity per Field	Running Total	Action
1	user	1	1	Add complexity for user field
2	name	1	2	Add complexity for name field
3	posts	10	12	Add complexity for posts field (10 posts assumed)
4	title	1	13	Add complexity for title field
5	comments	5	18	Add complexity for comments field (5 comments assumed)
6	text	1	19	Add complexity for text field
7	Total Complexity		19	Compare total 19 to limit 20
8	Decision			Allow query execution (19 < 20)

💡 Total complexity 19 is less than limit 20, so query is allowed.

Variable Tracker

Variable	Start	After Step 1	After Step 2	After Step 3	After Step 4	After Step 5	After Step 6	Final
total_complexity	0	1	2	12	13	18	19	19

Key Moments - 3 Insights

Why does the 'posts' field add 10 to complexity instead of 1?

Because 'posts' is a list field assumed to return 10 items, each adding complexity 1, so total 10 is added at step 3 in the execution_table.

Why is the total complexity compared to a limit?

To prevent very expensive queries from running, the total complexity (19) is compared to a set limit (20) at step 7 to decide if the query is allowed.

Why do nested fields like 'comments' add complexity separately?

Each nested field can add its own complexity based on expected items (5 comments here), so 'comments' adds 5 at step 5, showing how nested structures increase total complexity.

Visual Quiz - 3 Questions

Look at the execution_table, what is the total complexity after processing the 'posts' field?

A 13

B 10

C 12

D 2

💡 Hint

Check the 'Running Total' column at step 3 in the execution_table.

At which step does the complexity for the 'comments' field get added?

A Step 4

B Step 5

C Step 6

D Step 3

💡 Hint

Look for the row with 'comments' in the 'Field' column in the execution_table.

If the limit was 15 instead of 20, what would be the decision at step 8?

A Reject query

B Allow query execution

C Partial execution

D Retry query

💡 Hint

Compare the final total complexity 19 with the new limit 15 in the exit_note and step 7.

Concept Snapshot

Query complexity analysis in GraphQL:
- Parse query fields
- Calculate complexity per field (scalars = 1, lists = items * complexity)
- Sum all complexities
- Compare total to limit
- Reject if over limit, else allow execution

Full Transcript

Query complexity analysis in GraphQL involves breaking down a query into its fields, calculating how complex each field is based on expected data size, summing these complexities, and then comparing the total to a predefined limit. If the total complexity is below the limit, the query is allowed to run; otherwise, it is rejected to protect the server from expensive operations. For example, a query requesting a user, their posts, and comments will have complexity calculated step-by-step, adding complexity for each field and nested list. This process helps keep GraphQL APIs efficient and safe.