Parallel Scan

Parallel Scan Overview

At its core, parallel scan is about doing one thing well inside your DynamoDB project. Once you understand the pattern, you can apply it consistently across features and teams.

Good parallel scan pays off across the whole codebase: fewer surprises, easier testing, and smoother onboarding. The snippet below is a solid starting point.

import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient, ScanCommand } from '@aws-sdk/lib-dynamodb';

const client = new DynamoDBClient({});
const docClient = DynamoDBDocumentClient.from(client);

const { Items } = await docClient.send(new ScanCommand({
  TableName: 'Orders',
  FilterExpression: '#s = :status',
  ExpressionAttributeNames: { '#s': 'status' },
  ExpressionAttributeValues: { ':status': 'NEW' },
}));

ScanCommand reads the whole table and filters afterwards — use it sparingly.

Parallel Scan Example

import { DynamoDBClient } from '@aws-sdk/client-dynamodb';
import { DynamoDBDocumentClient } from '@aws-sdk/lib-dynamodb';

const docClient = DynamoDBDocumentClient.from(new DynamoDBClient({}));
// docClient.send(new PutCommand(...)) etc.

• Start from a minimal Parallel Scan example and grow it only as needed.
• Keep configuration explicit so Parallel Scan behaves the same in every environment.
• Name things clearly so teammates understand your Parallel Scan at a glance.
• Add tests around Parallel Scan early to lock in expected behaviour.

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to parallel scan.

How Parallel Scan Works in DynamoDB

Parallel Scan builds on DynamoDB's key-value and document model, where every item lives in a partition chosen by its partition key and is optionally ordered by a sort key.

ScanCommand reads the whole table and filters afterwards — use it sparingly.

• Design access patterns first, then model keys around them.
• Prefer Query over Scan for predictable performance.
• Use expressions to read and write only what you need.
• Keep items small and avoid hot partitions.

Practical Guidance for Parallel Scan

In production, parallel scan should be cost-aware and resilient. Right-size capacity, handle throttling with retries, and lean on indexes to support your query patterns.

Common Mistakes

• Copying parallel scan snippets without understanding what each line does.
• Skipping error handling and edge cases when wiring up parallel scan.
• Leaving parallel scan untested, so regressions slip into production.
• Over-engineering parallel scan before you actually need the extra flexibility.

Key Takeaways

• Parallel Scan is a core part of working effectively with DynamoDB.
• Start small and keep parallel scan focused on a single responsibility.
• Apply consistent patterns so parallel scan scales across your project.
• Test and document parallel scan to keep it maintainable over time.