What's New in v0.3.1

2019-08-08

Features

  • Added a new type of index IVFSQ which could significantly improve the overall throughput of vector processing.
  • Added a new metric of vector distance calculation IP (Inner Product), in addition to L2 (Euclidean Distance).
  • Added multiple parameters which optimizes index building, search precision and search speed.

Improvements

  • When the data size is huge and cannot fit in the data file on one disk, you can add multiple secondary data storage directories on other disks.
  • You can choose if to enable parallel computing of vectors by multiple threads, by configuring parameter parallel_reduce.
  • You can designate a portion of the memory for buffer usage of data insertion, by configuring parameter insert_buffer_size.
  • In regard to cache management, by configuring cache_free_percent, you can now decide, when the cache reaches its capacity, how much data should be kept instead of being erased.
  • You can enable simultaneous inserting and searching of vectors by setting insert_cache_immediately to True.
  • Search results are evaluated based on the distances between search results and the target vectors, rather than the score.
Edit
© 2019 - 2020 Milvus. All rights reserved.