Principle:Deepset ai Haystack Document Writing
| Knowledge Sources | |
|---|---|
| Domains | Data_Storage, ETL |
| Last Updated | 2026-02-11 00:00 GMT |
Overview
A pipeline component pattern that persists processed documents into a document store with configurable duplicate handling.
Description
Document writing is the terminal step in indexing pipelines that persists processed documents (with embeddings, cleaned content, or metadata) into a document store. It abstracts the store-specific write operations behind a uniform interface, handling duplicate detection through configurable policies (skip, overwrite, or fail on duplicates). This decouples the document processing pipeline from the storage backend.
Usage
Use document writing as the final component in any indexing or preprocessing pipeline. It connects after embedding, cleaning, or splitting steps to persist the processed documents. The duplicate policy parameter determines behavior when documents with matching IDs already exist.
Theoretical Basis
Document writing follows the sink pattern in dataflow architectures:
- Single responsibility: The writer only persists; it does not transform data
- Policy-based duplicate handling: NONE (store default), SKIP, OVERWRITE, or FAIL
- Store abstraction: Works with any DocumentStore implementation through the protocol interface
# Abstract pattern (NOT real implementation)
writer = create_writer(store=document_store, policy="skip_duplicates")
writer.write(documents=[doc1, doc2, doc3])
# Returns count of documents successfully written