A Chunker Service is a software component (or microservice) that takes a large payload — such as a file, stream, or dataset — and breaks it into smaller chunks so that:
- Each chunk can be processed or transmitted independently, and
- The system can handle large data efficiently and reliably.
After chunking, these smaller pieces are typically:
- Sent, stored, or processed in parallel, and then
- Reassembled by another service (often called a “Merger” or “Assembler” service).
Chunking is needed when:
- Data size exceeds limits (e.g., file upload limits or API size limits)
- Network reliability is an issue — smaller chunks are easier to retry if one fails
- Parallelism is desired — chunks can be processed concurrently
- Streaming is needed — chunks can be sent or processed as they arrive
| Use Case | How Chunker Helps |
|---|---|
| File Upload Service | Large file (e.g., 5GB video) is split into 5MB chunks. Each chunk is uploaded separately. If one fails, only that chunk retries. |
| Data Processing Pipelines | Large dataset is chunked into smaller batches, processed in parallel by multiple workers (e.g., Spark, Kafka consumers). |
| Streaming APIs / WebSockets | Chunker breaks a large message into smaller packets so it can be streamed in real time. |
| Backup / Storage Systems | Chunker divides big files into fixed-size blocks for deduplication, compression, and distributed storage (e.g., S3 multipart uploads). |
[Client]
↓
[Chunker Service] → splits data into small chunks
↓
[Storage / Message Queue / Network]
↓
[Assembler / Consumer Service] → reassembles or processes chunks
A user uploads a 2GB file via an API.
- The Chunker Service splits it into 200 chunks of 10MB each.
- Each chunk is uploaded separately to cloud storage (e.g., AWS S3).
- Once all chunks are uploaded, a merge request is sent to combine them.
- If upload fails halfway, only the missing chunks are retried.
A service needs to send a large JSON array to another microservice via HTTP. Since HTTP has payload limits (e.g., 10MB), the Chunker Service divides it into multiple smaller JSON chunks and sends them sequentially or through a message queue (like Kafka).
- Integrity check: Each chunk can have a checksum or hash to detect corruption.
- Encryption: Each chunk can be encrypted individually.
- Retries: Only failed chunks are resent (saves bandwidth).
- Tracking: A manifest file can maintain metadata (chunk order, size, etc.).
| Term | Meaning |
|---|---|
| Chunker Service | A service that splits large data into smaller pieces for easier transfer or processing |
| Purpose | Handle large payloads efficiently, improve fault tolerance, enable parallel processing |
| Common Use Cases | File uploads, distributed processing, data streaming, backups |
| Opposite Component | “Assembler” or “Merger” — reassembles chunks into the full original data |