Document
A discrete representation of information, such as content or a structured record, optionally accompanied by metadata.
Elasticsearch in Action, Second Edition
An Elasticsearch document is a JSON record stored in an index with fields and associated metadata.
- How it is used
- Stores business records as JSON units that can be indexed, searched, retrieved, updated, or deleted.
- How deep it goes
- Explains JSON fields, nested objects, parsing, analysis, and mapping application; defers mapping detail and text analysis depth.
- Examples
- Uses book, news article, and student JSON records, plus ID-based retrieval requests.
- What you can do after
- Operate/configure it through REST APIs to index, fetch, update, delete, batch-import, and reindex JSON records.
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AI Agents and Applications
A document is a LangChain container holding content together with metadata such as source, page number, author, or timestamp.
- How it is used
- Packages source text and metadata as the shared input for ingestion, retrieval, question answering, and summarization.
- How deep it goes
- Defines the container and traces its creation, splitting, storage, and retrieval without detailing its fields or implementation.
- Examples
- Uses a Paestum Wikipedia loader, local TXT, DOCX, and PDF files, and a CSV ingestion scenario.
- What you can do after
- Apply it via LangChain loaders to prepare sourced text for splitting, retrieval, or summarization.
MongoDB 8.0 in Action, Third Edition
A document is a JSON-like data structure containing named fields and their values, potentially including arrays and nested documents.
- How it is used
- Stores application records as field–value structures within MongoDB collections.
- How deep it goes
- Defines BSON fields, arrays, nesting, identifiers, and the 16 MB limit, then demonstrates inspection with findOne().
- Examples
- Shows a grades record with embedded scores and a book record with arrays and nested details.
- What you can do after
- Apply it via mongosh to inspect a document with findOne() and plan fields around application queries.
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Build Python Web Apps with Streamlit
A Document is a LangChain data structure containing source text and associated metadata.
- How it is used
- Supports document loading, chunking, indexing, and retrieval in a LangChain RAG application.
- How deep it goes
- Explains the structure and pipeline role, then demonstrates loading, splitting, storing, and retrieving without detailing metadata fields.
- Examples
- Uses text files, support articles, chunked excerpts, and fountain-pen care instructions as ingestible source material.
- What you can do after
- Apply it via LangChain loaders and splitters to prepare source material for vector-store retrieval.
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Building Web APIs with ASP.NET Core
A database document is a self-contained record represented as structured fields, commonly including nested related information.
- How it is used
- Models NoSQL records as flexible documents containing fields and commonly related information.
- How deep it goes
- Defines document structure and relationship handling, but stops short of implementation syntax or database-specific operations.
- Examples
- Uses users, roles, board games, and comments to illustrate embedded and separately referenced information.
- What you can do after
- Evaluate whether related data should be embedded or referenced in a flexible NoSQL schema.
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Build AI-Enhanced Web Apps
A Document is a structured LangChain object representing retrieved content and associated document information.
- How it is used
- Represents parsed content and metadata as the handoff object for summarization, retrieval, embeddings, and vector storage.
- How deep it goes
- Defines content and metadata, then explains loader output and recursive chunking; it stops short of Document class internals.
- Examples
- Uses PDF and DOCX uploads, Aesop's fables, pageContent and metadata output, and overlapping chunks for summarization.
- What you can do after
- Build document-ingestion pipelines with PDFLoader, DocxLoader, and RecursiveCharacterTextSplitter.
Spring in Action, Sixth Edition
A document is a self-contained record in a document database that stores data as structured fields and values.
- How it is used
- Maps application domain types to MongoDB documents for persistence and retrieval.
- How deep it goes
- Explains core mapping annotations and collection naming, but does not descend into MongoDB storage internals.
- Examples
- Uses Ingredient, Taco, and TacoOrder classes, including embedded tacos and annotated identifiers.
- What you can do after
- Apply it via Spring Data MongoDB by annotating domain classes and choosing document identifiers, fields, and collection names.
Read how Spring in Action, Sixth Edition explains Document →
Fabulous Adventures in Data Structures and Algorithms
A document is an intermediate data structure that represents source-code layout rules and program text for pretty printing.
- How it is used
- Represents formatting decisions between parsing source code and rendering pretty-printed text.
- How deep it goes
- Defines the document’s role and encoded layout concepts, while deferring detailed node definitions and rendering implementation.
- Examples
- Uses an expression tree for Foo.Bar((x + y.z) * q, A.B.C) as a parse-tree-to-document example.
- What you can do after
- Build a pretty-printing pipeline by transforming parse trees into documents and rendering documents as text.
Read how Fabulous Adventures in Data Structures and Algorithms explains Document →
Related concepts
- match_all queryproduced by · A match_all query is an Elasticsearch query that matches every document eligible for the search.
- _sourcecontrasts with · The Elasticsearch _source field contains the original JSON document stored with a search or retrieval response.
- Elasticsearch indexpart of · An Elasticsearch index is a named, searchable collection of documents organized for querying and distributed across storage shards and replicas.
- nextproduced by · An iterator operation that advances an iterator and returns its next value or result, with behavior on exhaustion determined by the API.
- data structurekind of · A data structure is an organized representation of data and its relationships that supports defined operations for storing, accessing, or modifying it.
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