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License: MIT License
Lightweight Text Search Engine written in Python
License: MIT License
The current implementation of search
reads all doc ids for the given tokens and stores them into set().
Improve this so that calculate intersection while reading ids one by one.
Prepare scripts build_index.py
and do_query.py
for https://github.com/quickwit-oss/search-benchmark-game.
Save DOC_LIST
and INVERTED_INDEX
into files, and restore them.
Binary format is used for index from v0.4.0. It's necessary to provide some tools for outputing it in a human readable format. Otherwise it's hard to debug.
The current implementation of indexing is based on 4.3 SPIMI (single-pass in-memory indexing) in Introduction on Information Retrieval but does not check memory availability.
Output every fixed sized index fragments and merge them at the end of indexing.
Currently, inverted index keeps a dict from a token to the list of docIds in memory, but keeps a dict from a token to the position in an inverted index file and the list of docIds is read from the file as needed.
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