Practice search indexing vocabulary: inverted indexes, tokenization pipelines, full-text indexing, index size, refresh intervals, and nightly index rebuilds.
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An 'inverted index' maps:
An inverted index maps each term to the list of documents containing it, with position and frequency data. This is the core data structure enabling fast full-text search.
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The 'tokenization pipeline' in search indexing consists of:
The tokenization pipeline transforms raw text: a tokenizer splits text into tokens, then token filters apply transformations (lowercase, remove stop words, stem) to produce index terms.
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'The index has 50M _____.' What is the basic unit of search indexing?
Documents are the basic units indexed — each document corresponds to an item (webpage, product, article) indexed for search. '50M documents' describes the scale of the search corpus.
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'Index _____ interval' determines how frequently new documents become searchable.
The index refresh interval (configurable in Elasticsearch/OpenSearch) controls how often the in-memory write buffer is flushed to the segment, making newly indexed documents searchable.
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'The index is rebuilt _____.' When is a full rebuild typically scheduled?
Nightly full index rebuilds are common for search systems where data changes incrementally — rebuilding ensures the index reflects all changes and removes deleted/stale documents.