Handle Unprocessed Items

Handle Unprocessed Items sits at the heart of batch operations in DynamoDB. This guide walks through the concept step by step, with examples, a cheatsheet, and common mistakes to avoid.

Handle Unprocessed Items Overview

Handle Unprocessed Items is a building block you will reach for often in DynamoDB. It keeps related logic together and makes your intent obvious to reviewers and future maintainers.

When you learn handle unprocessed items properly, you avoid the guesswork that leads to bugs and rework. The example below shows the shape you will use in most real DynamoDB projects.

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

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

await docClient.send(new BatchWriteCommand({
  RequestItems: {
    Orders: [
      { PutRequest: { Item: { pk: 'ORDER#1', sk: 'META' } } },
      { PutRequest: { Item: { pk: 'ORDER#2', sk: 'META' } } },
    ],
  },
}));

BatchWriteCommand writes or deletes up to 25 items in a single request.

Handle Unprocessed Items 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 Handle Unprocessed Items example and grow it only as needed.
Keep configuration explicit so Handle Unprocessed Items behaves the same in every environment.
Name things clearly so teammates understand your Handle Unprocessed Items at a glance.
Add tests around Handle Unprocessed Items early to lock in expected behaviour.

Amazon DynamoDB Cheatsheet

Handy DynamoDB (AWS SDK v3) reference related to handle unprocessed items.

Operation	Command	Purpose
Create/replace	`PutCommand`	Write an item
Read one	`GetCommand`	Fetch by primary key
Update	`UpdateCommand`	Modify attributes
Delete	`DeleteCommand`	Remove an item
Query	`QueryCommand`	Efficient key-based read
Scan	`ScanCommand`	Full-table read (avoid)
Transaction	`TransactWriteCommand`	Atomic multi-item writes

How Handle Unprocessed Items Works in DynamoDB

Handle Unprocessed Items 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.

BatchWriteCommand writes or deletes up to 25 items in a single request.

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 Handle Unprocessed Items

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

Concern	Recommendation
Performance	Query by key; avoid table scans
Cost	Use on-demand or right-sized provisioned capacity
Modeling	Design for known access patterns
Reliability	Retry throttled requests with backoff

Common Mistakes

Skipping error handling and edge cases when wiring up handle unprocessed items.
Leaving handle unprocessed items untested, so regressions slip into production.
Over-engineering handle unprocessed items before you actually need the extra flexibility.
Ignoring documentation, which makes handle unprocessed items hard for the next developer to change.

Key Takeaways

Handle Unprocessed Items is a core part of working effectively with DynamoDB.
Start small and keep handle unprocessed items focused on a single responsibility.
Apply consistent patterns so handle unprocessed items scales across your project.
Test and document handle unprocessed items to keep it maintainable over time.

Pro Tip

Pair handle unprocessed items with automated tests from day one. It is far cheaper to catch DynamoDB regressions in CI than in production.