BigData / Apache Hudi Interview Questions
When should you use a bucket index instead of a Bloom index?
A bucket index assigns each record to a file group deterministically by hashing its record key into a fixed number of buckets, so no lookup against stored index data is needed at all — the target file is computed directly from the key.
This makes bucket indexing extremely fast for upserts, especially on very large tables, since it avoids the file-scanning or key-lookup cost every other index type pays in some form. The trade-off is rigidity: the bucket count is typically fixed at table creation, so resharding a table that has badly outgrown its original bucket count is a more involved operation than with a Bloom or Record-Level Index. It's a strong choice when key distribution is well understood upfront and extreme upsert throughput matters most.
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