For each topic-partition, Kafka broker maintains two indices: one for message offset, one for message timestamp. By default, a new index entry is appended to each index for every 4KB messages. The lookup of the indices is a simple binary search. The indices are mmaped files, and cached by Linux page cache.
Both consumer fetch and follower fetch have to do an offset lookup, before accessing the actual message data. The simple binary search algorithm used for looking up the index is not cache friendly, and may cause page faults even on high QPS topic-partitions.
For example (diagram 1), when looking up an index entry in page 12, the binary search algorithm has to read page 0, 6, 9 and 11. After new messages are appended to the topic-partition, the index grows to 13 pages. Now, if the follower fetch request looking up the 1st index entry of page 13, the binary search algorithm will go to page 0, 7, 10 and 12. Among those pages, page 7 and 10 have not been used for a long time, and may already be swapped to hard disk.
Actually, in a normal Kafka broker, all the follower fetch requests and most consumer fetch requests should only look up the last few entries of the index. We can make the index lookup more cache friendly, by searching in the last one or two pages of the index first. (Diagram 2)