Which index type cannot efficiently support range queries?

Which index type cannot efficiently support range queries?

• A. Hash Index
• B. Inverted Index
• C. B-tree
• D. Geohash

Answer: (A)

Range queries depend on scanning a sequence of keys in a known order. A hash index uses a hash function to assign each key to a bucket, and that mapping hides any overall ordering. Because there’s no natural order to follow, you can’t efficiently walk from a lower bound to an upper bound; answering a range query would force examining many buckets and then filtering, which destroys the performance benefits of an index. In contrast, a B-tree keeps keys sorted, so you can locate the start of the range and scan through consecutive keys with good I/O efficiency. Geohash enables some spatial range searches via prefix matching, and inverted indexes are optimized for exact-term lookups rather than ordered ranges. So the hash index is the one that cannot efficiently support range queries.

Range queries depend on scanning a sequence of keys in a known order. A hash index uses a hash function to assign each key to a bucket, and that mapping hides any overall ordering. Because there’s no natural order to follow, you can’t efficiently walk from a lower bound to an upper bound; answering a range query would force examining many buckets and then filtering, which destroys the performance benefits of an index. In contrast, a B-tree keeps keys sorted, so you can locate the start of the range and scan through consecutive keys with good I/O efficiency. Geohash enables some spatial range searches via prefix matching, and inverted indexes are optimized for exact-term lookups rather than ordered ranges. So the hash index is the one that cannot efficiently support range queries.