Using blevex packages

The blevex repository contains optional add-ons to bleve which cannot be a part of the main repository for the following reasons:

  • C dependency
  • Does not fully satisfy interface contracts
  • Experimental in nature

Using blevex packages

Bleve does not directly import any of the sub-packages with the blevex repository. If your application would like to use one of these packages, they can either import the package directly, or import the bleve config package, which then adds the ability to include blevex packages through common build-tags.

For example, if your application adds:

  1. import(
  2.   _ "github.com/blevesearch/bleve/config"
  3. )

Then when you build your application, it will automatically recognize a common set of build tags, which currently includes:

  • cellar
  • cld2
  • cznicb
  • forestdb
  • icu
  • kagome
  • leveldb
  • libstemmer
  • rocksdb

KV Stores

cellar

Cellar is an experimental KVStore implementation.

cznicb

Bleve supports using cznic/b as a KVStore implementation. Although this implementation is pure Go, it does not offer reader isolation, so it does not fully satisfy the bleve interface requirements. Under certain restrictions it can still be used safely.

forestdb

Bleve supports using ForestDB as a KVStore implementation. This requires a C/C++ dependency, please see Building.

leveldb

Bleve supports using LevelDB as a KVStore implementation. This requires a C/C++ dependency, please see Building.

rocksdb

Bleve supports using RocksDB as a KVStore implementation. This requires a C/C++ dependency, please see Building.

Tokenizers

ICU

Bleve supports using the ICU project to tokenize words. For most languages Bleve’s built-in unicode segmentation will work fine. However, languages which require dictionary-based segmentation may still require this library. This requires a C/C++ dependency, please see Building.

NOTE: It is recommended to get the most recent version of ICU possible. Older versions often included with distributions do not support language based tokenization.

Token Filters

detect_lang

Bleve supports using the cld2 library to determine the language of a sample of text. This is implemented as a token filter which will return the result as a ISO 639 language code. This requires a C/C++ dependency, please see Building.

stemmer_filter

Bleve supports using the libstemmer library to stem words for many languages. Many of the language specific analyzers depend on this library. This requires a C/C++ dependency, please see Building.