When interviewers ask about MySQL InnoDB vs MyISAM, go beyond transaction support and discuss six deeper differences—including count(*) performance, MVCC, storage layout, caching, crash recovery, and ideal use cases—to showcase comprehensive technical knowledge.
This article explains why correlated subqueries are a performance bottleneck, introduces the Apply (Correlated Join) operator and a systematic set of transformation rules that push Apply down and replace subqueries with efficient joins, covering scalar, existential, and quantified subqueries, aggregation handling, and set operations, all illustrated with TPC‑H examples.
This article presents essential MySQL interview topics, comparing MyISAM and InnoDB storage engines, explaining INT‑Char implicit conversion nuances, demonstrating efficient methods to fetch random rows, and outlining various index types with their appropriate use cases.
This article provides a comprehensive overview of ClickHouse, covering its typical application scenarios, inherent limitations, common SQL syntax, default values, data types, materialized and expression columns, and detailed explanations of its various storage engines such as TinyLog, Log, Memory, Merge, Distributed, Null, Buffer, Set, MergeTree, ReplacingMergeTree, SummingMergeTree, AggregatingMergeTree, and CollapsingMergeTree, accompanied by practical code examples.
The article critiques a popular MySQL tuning list, explains why many of its suggestions are misguided, and presents a more practical, performance‑focused checklist that covers benchmarking, schema design, indexing, query rewriting, and engine‑specific tricks.
