A certain project needs to save the online data in a certain area and search the full text whether there is any sensitive information in these online records to prevent crimes in the area. In this…

Question

Options

• ACreate an index on Solr, save the data, and return all the data when searching the full text.
• BStore data on HBase, and satisfy fuzzy matching queries through HBase's filtering features.
• CWhen storing data, create an index on Solr and store the complete data in HBasx; when querying,

• A
  16% (3)
• B
  11% (2)
• C
  74% (14)

Explanation

Option C is correct because it leverages a hybrid architecture that uses each technology for its strength: Solr handles full-text indexing and search (using an inverted index to efficiently find sensitive keywords across millions of records), while HBase stores the complete raw data at scale. When a query runs, Solr quickly identifies which records match, and HBase retrieves the full content - this combination delivers both search performance and reliable data persistence.

Why A is wrong: Solr is a search engine, not a primary data store. Saving all data only in Solr and returning all records on search defeats the purpose - it ignores Solr's ranking/filtering and creates storage/retrieval inefficiencies.

Why B is wrong: HBase's native filtering (e.g., SingleColumnValueFilter) performs row-by-row scans and is not true full-text search. It lacks an inverted index, so fuzzy/keyword matching across large datasets would be extremely slow and impractical for crime-detection use cases.

Memory tip: Think of it as "Solr finds it, HBase holds it." Solr = the index in the back of a book (fast lookup), HBase = the book's full pages (complete content). For any exam question combining search + large-scale storage, the Solr+HBase pairing is almost always the right answer.

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