Azure Search Emulator

A local emulator for Azure (Cognitive) Search Service.

This project is currently a prototype, with work underway to validate it in various real-world scenarios to ensure that it accurately emulates Azure Search as best as possible.

Quick Start

1. Clone the repo.
2. Open AzureSearchEmulator.sln in Visual Studio 2022 and run it, or cd to the AzureSearchEmulator folder and run dotnet run from the command-line.

Features

This project aims to be a nearly complete, API-compatible emulator of Azure Search for your local development environment, offline use, or any dev/test scenario where using a cloud instance of Azure Search is impossible, impractical, or infeasible. This application is not intended for use in production or to replace Azure Search production workloads.

There is another azure-search-emulator project that may or may not be a better fit for your needs, depending on what you're trying to do. Compared to that project, this project:

• Has no external service/runtime dependencies beyond .NET 6
• Can be run and debugged simply with F5 in Visual Studio, or dotnet run on the command line
• Does not require Docker or any kind of containers/virtualization, but can be run with Docker if you prefer (see below)
• Does not require Solr (or Java), Docker Compose, or any kind of orchestration
• Supports index management APIs (creation and deletion at this time)

However, this project may lag behind the other project in some features due to implementing all functionality from scratch.

Currently, there is support (to varying degrees) for the following Azure Search REST APIs:

• Get indexes (multiple index support)
• Create an index
• Delete an index
• Bulk document indexing and deletion (merge, upload, mergeOrUpload, delete)
• Retrieve an individual document
• Get $count of all documents in an index
• Search with support for the following parameters:
  • $count - include a count of document matches
  • $skip - paging; skip X records, defaults to 0
  • $top - paging; take next X records, defaults to 50
  • $filter - OData filter expression to limit results, i.e. (Type eq 'Comment') or (Type eq 'File')
  • $orderby - OData sort expression to sort results, i.e. Type asc,Title desc
  • highlight - Comma-delimited list of fields to highlight, supports optional max highlight count i.e. Body-10,Title-5
  • highlightPreTag - Start tag to wrap highlighted result text, defaults to <em>
  • highlightPostTag - End tag to wrap highlighted result text, defaults to </em>
  • queryType - The type of query parser to use, either simple (default) or full
  • search - The actual search query text to pass to the query parser
  • searchFields - Comma-delimited list of fields to search
  • searchMode - The default boolean operator, either any (default) or all

Metadata about indexes are stored as JSON files in the indexes folder. Once documents have been added, a subfolder with the index name is created where the Lucene.net index data is stored. This uses the SimpleFSDirectory Lucene.net directory class to manage its data.

Authentication

Authentication is not yet implemented. If you're using the Azure Search SDK, you can provide any value for the AzureKeyCredential constructor parameter.

Building and Running with Docker

It is not required to use Docker to run this project, see the Quick Start section above.

The easiest way to run with Docker is to use Docker Compose. Run the following from the repo root:

docker compose up -d

This will build the image, create the volume, and run the container in the background at https://localhost:5081 and http://localhost:5080. See the docker-compose.yml file for how this works.

If you prefer to do this without Docker Compose (HTTP only):

# create a volume to persist your indexes across runs
docker volume create az-search-emu

# from repo root
docker build . -t azure-search-emulator

# run the container on port 5080 (feel free to change) and mount the volume
docker run -dp 5080:80 -v az-search-emu:/app/indexes azure-search-emulator

License

To help ensure the non-production-use of this code, this project uses an AGPL license. This requires releasing the source code of your application under a compatible license if this is used in production as a service. There is no requirement to release your source code if this application is used as intended, as a local emulator for development purposes.