v0.3.2
版本发布时间: 2022-02-02 10:20:40
gorse-io/gorse最新发布版本:v0.4.15(2024-01-10 12:44:45)
Feature
- Support modify configuration via environment variables (#359). There are 8 environment variables available:
Environment Variable | Configuration | |
---|---|---|
GORSE_CACHE_STORE | cache_store |
database for caching. |
GORSE_DATA_STORE | data_store |
database for persist data. |
GORSE_MASTER_PORT | port |
master port |
GORSE_MASTER_HOST | host |
master host |
GORSE_MASTER_HTTP_PORT | http_port |
HTTP API port |
GORSE_MASTER_HTTP_HOST | http_host |
HTTP API host |
GORSE_MASTER_JOBS | n_jobs |
number of working jobs |
GORSE_SERVER_API_KEY | api_key |
secret key for RESTful APIs |
- (Experimental) Support IVF-based neighborhood searching (#363).
- (Experimental) Support HNSW based recommended items searching (#368).
Fix
- Split large Redis writes to batches (#352).
- Allow empty JSON string in relational databases (#355).
- Fix offset overflow in recommend API (#365).
- Optimize dashboard overview page layout (#369).
Upgrade Guide
-
Configuration: IVF-based neighborhood searching and HNSW based recommended items searching are experimental features.
- Use
enable_xxx_index
to enable experimental features. -
xxx_index_recall
is the expected recall of approximate searching. -
xxx_index_fit_epoch
is the number of epochs to adapt indices.
- Use
These approximate vector searching indices trade tolerable accuracy (recall) with larger throughput. The index builder tries to reach xxx_index_recall
in xxx_index_fit_epoch
. The building process will stop when xxx_index_recall
or xxx_index_fit_epoch
reached. Index-based searching costs more memory than brute force searching and its building process costs additional time, but they are negligible compared to the benefits.
# Enable approximate item neighbor searching using vector index.
enable_item_neighbor_index = false
# Minimal recall for approximate item neighbor searching.
item_neighbor_index_recall = 0.8
# Maximal number of fit epochs for approximate item neighbor searching vector index.
item_neighbor_index_fit_epoch = 3
# Enable approximate user neighbor searching using vector index.
enable_user_neighbor_index = false
# Minimal recall for approximate user neighbor searching.
user_neighbor_index_recall = 0.8
# Maximal number of fit epochs for approximate user neighbor searching vector index.
user_neighbor_index_fit_epoch = 3
# Enable approximate collaborative filtering recommend using vector index.
enable_collaborative_index = false
# Minimal recall for approximate collaborative filtering recommend.
collaborative_index_recall = 0.9
# Maximal number of fit epochs for approximate collaborative filtering recommend vector index.
collaborative_index_fit_epoch = 3
- Redis: Remove incompatible stale cache.
redis-cli KEYS "item_neighbors*" | xargs redis-cli DEL
redis-cli KEYS "user_neighbors*" | xargs redis-cli DEL
1、 gorse_darwin_amd64.zip 46.37MB
2、 gorse_darwin_arm64.zip 43.95MB
3、 gorse_linux_amd64.zip 47.17MB
4、 gorse_linux_arm64.zip 42.87MB
5、 gorse_windows_amd64.zip 47.47MB