Interview Transcript: MySQL, Redis, PHP, and Distributed Systems Questions

The interview begins with a brief introduction of the interview panel, including an HR manager, a product manager, and three technical directors (A, B, and C) conducted via video due to the pandemic.

Director A asks about MySQL isolation levels, to which the candidate lists Read Uncommitted, Read Committed, Repeatable Read (default), and Serializable, and mentions phenomena such as dirty reads, non‑repeatable reads, and phantom reads along with their solutions.

Further questions cover InnoDB index types (primary, unique, normal, composite) and their implementations (B‑tree, B+‑tree, hash), with the candidate explaining differences in leaf node storage and I/O costs.

The discussion moves to MySQL lock categories and their practical usage, followed by a query on distributed systems where the candidate mentions using Redis SETNX with expiration for distributed locks and admits limited knowledge of etcd.

Director C probes PHP optimization, specifically OPCache and opcode handling; the candidate acknowledges lack of experience with these features.

When asked to describe the URL request flow, the candidate outlines DNS resolution, request routing to Nginx, CGI interaction with PHP‑FPM, script execution, and response generation.

CGI is defined as a protocol enabling communication between web servers and languages like PHP.

Questions about PHP‑FPM architecture reveal a master‑worker model; the candidate mentions adjusting process numbers and dynamic scaling.

The interview also touches on RabbitMQ architecture, topic exchange usage, Redis sharding, ranking with sorted sets, and the missing Redis ZRANGE member function.

Further topics include AOP concepts, Hyperf framework characteristics (Swoole‑based, plugin‑oriented, DI container, annotations), coroutine pools, and state management, with the candidate partially answering.

Additional queries cover Linux basics, shell scripting differences from PHP, and a brief mention of map‑reduce using MongoDB, which the interviewers correct to Hadoop.

Finally, the candidate is asked about future plans, ending the transcript with a reflection on why the interview felt unsatisfactory due to the depth and pace of the questions.