Details
-
New Feature
-
Status: Stalled (View Workflow)
-
Critical
-
Resolution: Unresolved
Description
A common operation for multi-dimensional vectors is to find k nearest vectors to the given one.
This task is about implementing indexes that allow to do it fast.
- ideally they'll be engine independent
- indexes should be update-able
- in this task we'll only do Euclidean distance
- we'll benchmark it on real multi-million-rows data sets
- what algorithm, exactly, to use is still unclear
Attachments
Issue Links
- relates to
-
MDEV-32886 VEC_FromText() and VEC_AsText() functions
-
- In Testing
-
-
MDEV-33404 Engine-independent indexes: subtable method
-
- In Testing
-
-
MDEV-33405 Engine-independent indexes: low-level API method
-
- Open
-
-
MDEV-33406 basic optimizer support for k-NN searches
-
- In Testing
-
-
MDEV-33407 Parser support for vector indexes
-
- In Testing
-
-
MDEV-33408 HNSW for k-ANN vector searches
-
- In Testing
-
-
MDEV-33410 VECTOR data type
-
- Open
-
-
MDEV-33411 OPTIMIZE for graph indexes
-
- Open
-
-
MDEV-33413 cache k-ANN graph in memory
-
- In Testing
-
-
MDEV-33414 benchmark vector indexes
-
- In Testing
-
-
MDEV-33415 graph index search: heuristical edge choice
-
- Open
-
-
MDEV-33417 vector distance: add more metrics
-
- Open
-
-
MDEV-33419 graph index insert: consider more neighbors
-
- Open
-
-
MDEV-34356 a helper to configure vector search
-
- Open
-
-
MDEV-34436 DDL: per-index attributes
-
- Open
-
-
MDEV-32885 VEC_DISTANCE() function
-
- In Testing
-
-
MDEV-33409 Index Condition Pushdown for k-ANN graph searches
-
- Open
-
-
MDEV-33412 cost-based optimizer choice for k-NN indexes
-
- Open
-
-
MDEV-33416 graph index: use smaller floating point numbers
-
- In Testing
-
-
MDEV-33418 graph index insert: stronger selection of neighbors
-
- Stalled
-
- links to