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This series implements rescoring algorithm. Index options allowing to enable this functionality were introduced in earlier PR https://github.com/scylladb/scylladb/pull/28165. When Vector Index has enabled quantization, Vector Store uses reduced vector representation to save memory, but it may degrade correctness of ANN queries. For quantized index we can enable rescoring algorithm, which recalculates similarity score from full vector representation stored in Scylla and reorder returned result set. It works also with oversampling - we fetch more candidates from Vector Store, rescore them at Scylla and return only requested number of results. Example: Creating a Vector Index with Rescoring ```sql -- Create a table with a vector column CREATE TABLE ks.products ( id int PRIMARY KEY, embedding vector<float, 128> ); -- Create a vector index with rescoring enabled CREATE INDEX products_embedding_idx ON ks.products (embedding) USING 'vector_index' WITH OPTIONS = { 'similarity_function': 'cosine', 'quantization': 'i8', 'oversampling': '2.0', 'rescoring': 'true' }; ``` 1. **Quantization** (`i8`) compresses vectors in the index, reducing memory usage but introducing precision loss in distance calculations 2. **Oversampling** (`2.0`) retrieves 2× more candidates than requested from the vector store (e.g., `LIMIT 10` fetches 20 candidates) 3. **Rescoring** (`true`) recalculates similarity scores using full-precision (`f32`) vectors from the base table and re-ranks results Query example: ```sql -- Find 10 most similar products SELECT id, similarity_cosine(embedding, [0.1, 0.2, ...]) AS score FROM ks.products ORDER BY embedding ANN OF [0.1, 0.2, ...] LIMIT 10; ``` With rescoring enabled, the query: 1. Fetches 20 candidates from the quantized index (due to oversampling=2.0) 2. Reads full-precision embeddings from the base table 3. Recalculates similarity scores with full precision 4. Re-ranks and returns the top 10 results In this implementation we use CQL similarity function implementation to calculate new score values and use them in post query ordering. We add that column manually to selection, but it has to be removed from the final response. Follow-up https://github.com/scylladb/scylladb/pull/28165 Fixes https://scylladb.atlassian.net/browse/SCYLLADB-83 New feature - doesn't need backport. Closes scylladb/scylladb#27769 * github.com:scylladb/scylladb: vector_index: rescoring: Fetch oversampled rows vector_index: rescoring: Sort by similarity column select_statement: Modify `needs_post_query_ordering` condition vector_index: rescoring: Add hidden similarity score column vector_index: Refactor extracting ANN query information
Scylla
What is Scylla?
Scylla is the real-time big data database that is API-compatible with Apache Cassandra and Amazon DynamoDB. Scylla embraces a shared-nothing approach that increases throughput and storage capacity to realize order-of-magnitude performance improvements and reduce hardware costs.
For more information, please see the ScyllaDB web site.
Build Prerequisites
Scylla is fairly fussy about its build environment, requiring very recent versions of the C++23 compiler and of many libraries to build. The document HACKING.md includes detailed information on building and developing Scylla, but to get Scylla building quickly on (almost) any build machine, Scylla offers a frozen toolchain. This is a pre-configured Docker image which includes recent versions of all the required compilers, libraries and build tools. Using the frozen toolchain allows you to avoid changing anything in your build machine to meet Scylla's requirements - you just need to meet the frozen toolchain's prerequisites (mostly, Docker or Podman being available).
Building Scylla
Building Scylla with the frozen toolchain dbuild is as easy as:
$ git submodule update --init --force --recursive
$ ./tools/toolchain/dbuild ./configure.py
$ ./tools/toolchain/dbuild ninja build/release/scylla
For further information, please see:
- Developer documentation for more information on building Scylla.
- Build documentation on how to build Scylla binaries, tests, and packages.
- Docker image build documentation for information on how to build Docker images.
Running Scylla
To start Scylla server, run:
$ ./tools/toolchain/dbuild ./build/release/scylla --workdir tmp --smp 1 --developer-mode 1
This will start a Scylla node with one CPU core allocated to it and data files stored in the tmp directory.
The --developer-mode is needed to disable the various checks Scylla performs at startup to ensure the machine is configured for maximum performance (not relevant on development workstations).
Please note that you need to run Scylla with dbuild if you built it with the frozen toolchain.
For more run options, run:
$ ./tools/toolchain/dbuild ./build/release/scylla --help
Testing
See test.py manual.
Scylla APIs and compatibility
By default, Scylla is compatible with Apache Cassandra and its API - CQL. There is also support for the API of Amazon DynamoDB™, which needs to be enabled and configured in order to be used. For more information on how to enable the DynamoDB™ API in Scylla, and the current compatibility of this feature as well as Scylla-specific extensions, see Alternator and Getting started with Alternator.
Documentation
Documentation can be found here. Seastar documentation can be found here. User documentation can be found here.
Training
Training material and online courses can be found at Scylla University. The courses are free, self-paced and include hands-on examples. They cover a variety of topics including Scylla data modeling, administration, architecture, basic NoSQL concepts, using drivers for application development, Scylla setup, failover, compactions, multi-datacenters and how Scylla integrates with third-party applications.
Contributing to Scylla
If you want to report a bug or submit a pull request or a patch, please read the contribution guidelines.
If you are a developer working on Scylla, please read the developer guidelines.
Contact
- The community forum and Slack channel are for users to discuss configuration, management, and operations of ScyllaDB.
- The developers mailing list is for developers and people interested in following the development of ScyllaDB to discuss technical topics.