This article explains MySQL InnoDB's MVCC mechanism, detailing how snapshot reads and current reads work, the hidden fields that drive versioning, the Read View rules for RC and RR isolation levels, and provides hands‑on SQL demos plus common pitfalls to avoid.
When a query suddenly slows down tenfold, adding an index often fails to help; the real solution is to read and understand MySQL's execution plan, which reveals how the optimizer works, which indexes are used, and where performance bottlenecks lie, enabling systematic query tuning.
The article chronicles the twelve‑year evolution of China’s Database Technology Conference (DTCC), showing how it transformed isolated DBA communities into a collaborative ecosystem, introduced new topics such as cloud and NoSQL, and enabled figures like 那海蓝蓝 to shape the nation’s database engineering landscape.
The article explains why high‑traffic MySQL deployments hit performance limits, introduces the concepts of vertical and horizontal sharding, and provides a step‑by‑step guide—including necessity assessment, shard key selection, schema design, middleware integration, and data migration—using an e‑commerce order system as a concrete example.
MySQL master‑slave replication separates writes to the master and reads to one or more replicas, using binary logs to record changes; the article explains its core concepts, typical scenarios like read‑write splitting and high‑availability, and provides a step‑by‑step configuration guide covering server IDs, binlog settings, replication accounts, data initialization, GTID options, and status verification.
Understanding MySQL’s lock types—table, row, and gap locks—reveals how they act as resource tokens to ensure data consistency under concurrency, while the article details their characteristics, appropriate and prohibited use cases, common pitfalls like lock degradation and deadlocks, and provides hands‑on SQL examples to reproduce and avoid these issues.
This article presents a complete design for a 12‑state payment order state machine that handles high‑concurrency scenarios such as payment callbacks arriving after an order has been cancelled, using explicit state transitions, database CAS updates, Redis + DB idempotency, Outbox pattern and Kafka‑driven asynchronous processing to achieve reliable, auditable and compensatable order lifecycle management.
This article walks through a comprehensive case study of a provincial medical appointment platform, diagnosing slow‑query bottlenecks, proposing patient‑id + create_time composite indexes, designing read‑write separation with replication, selecting patient_id for horizontal sharding, and implementing cache‑aside strategies to ensure consistency while handling cache avalanche, penetration and thundering‑herd scenarios.
This guide walks through why MySQL master‑slave replication lag occurs, the key metrics to monitor, a step‑by‑step troubleshooting flow, ten typical root causes, concrete remediation actions, verification methods, rollback plans, and production‑grade best practices for keeping replication latency near zero.
This article explains why indexes speed up queries by reducing disk I/O, dives into MySQL's page structure and B+Tree evolution, compares clustered and secondary indexes, clarifies composite index rules, lists common index‑misuse scenarios, and provides seven practical guidelines for designing efficient MySQL indexes.
This article explains why MySQL deadlocks occur in production, distinguishes them from simple lock waits, and provides a step‑by‑step guide—including enabling deadlock logging, analyzing InnoDB lock types, and applying four practical solutions such as distributed locks, unique constraints, isolation‑level changes, and SQL reordering—to reliably troubleshoot and prevent deadlocks.
The article explains what a database transaction is, breaks down the ACID properties, details MySQL’s four isolation levels with their appropriate use‑cases and pitfalls, and provides step‑by‑step SQL and SpringBoot code to reproduce and resolve dirty reads, non‑repeatable reads, and phantom reads.
The article analyses lock contention caused by per‑request ID generation, derives a segment‑based solution that batches IDs using a configurable step, defines a left‑closed/right‑open interval schema in MySQL, and builds a double‑buffer Java issuer with asynchronous pre‑loading, thorough concurrency handling, testing, and configuration guidelines.
The article explains that whether adding an index locks a MySQL table depends on the version and DDL algorithm—MySQL 5.5 and earlier lock the whole table, 5.6‑5.7 use Online DDL with brief metadata locks, and 8.0+ can create secondary indexes instantly without locking, while primary, unique, and full‑text indexes always require locking.
This article analyzes why cache and database can become inconsistent, compares four basic cache‑update patterns, explains the delayed double‑delete technique, shows how to use MQ for retrying cache deletions, and evaluates Canal binlog subscription as a zero‑intrusion solution for strong eventual consistency.
This article investigates whether SELECT COUNT(*) forces a full table scan, explains MySQL's cost‑based index selection (IO and CPU components), demonstrates the optimizer's choices with real‑world examples, and shows how EXPLAIN and optimizer trace can reveal and improve query performance.
The article explains how to generate strictly sequential invoice numbers required by auditors by using a MySQL InnoDB watermark (water level) table combined with row locking and UPSERT within a single transaction, covering the workflow, concurrency handling, rollback versus void semantics, performance trade‑offs, and applicability limits.
Oracle’s 2026 layoffs hit the MySQL team, community contributions fell 44% since 2017, while PostgreSQL climbs, and SQLite—once dismissed as a toy—now powers billions of devices and edge‑computing platforms, boosted by projects like LibSQL, Turso, Cloudflare D1 and Litestream, offering latency advantages over traditional servers.
The article walks through a real‑world MySQL deadlock incident, shows how to extract the LATEST DETECTED DEADLOCK section from SHOW ENGINE INNODB STATUS, explains gap and next‑key locks, and presents a three‑step method plus practical fixes to eliminate the deadlock.
This article explains why MySQL discourages using NULL as a default column value, demonstrates how NULL affects indexing, comparisons, and aggregate functions, and shows through concrete examples that improper NULL handling can lead to unexpected query results and performance degradation.
The article explains what MySQL slow queries are, why they must be detected, when to enable slow‑query logging, step‑by‑step commands to configure the log, how to simulate and analyze problematic SQL with EXPLAIN, and practical optimization techniques—including index creation and Spring Boot integration—to eliminate performance bottlenecks.
This article demystifies databases by contrasting them with Excel, explains core concepts such as tables, rows, columns, primary and foreign keys, compares relational and NoSQL systems, introduces SQL CRUD operations, ACID properties, and provides a quick MySQL hands‑on guide, helping readers decide when to adopt a database.
Adding a column to a MySQL table with tens of millions of rows can lock the table for minutes or even hours, disrupting services, so this article evaluates six practical approaches—including native online DDL, offline maintenance, PT‑OSC, logical migration with dual‑write, gh‑ost, and partition sliding‑window—detailing their mechanisms, trade‑offs, and suitable scenarios.
The article explains that a shopping cart can tolerate loss of recent writes but not accumulated items, outlines the data model with seven fields and a unique key, compares client‑side storage options, details merge strategies for guest and logged‑in carts, and evaluates Redis, MySQL, and hybrid solutions with concrete trade‑offs.
This article explains MySQL indexes with a simple book‑catalog analogy, shows why missing or mis‑used indexes cause severe latency and CPU issues, outlines when to create or avoid indexes, and provides a step‑by‑step SpringBoot demo that measures query time dropping from 80‑200 ms to under 5 ms.
This guide walks MySQL operators through a complete slow‑query troubleshooting workflow—starting with enabling and analyzing the slow‑query log, using pt‑query‑digest and EXPLAIN to pinpoint index, SQL, schema, configuration or hardware bottlenecks, and then applying concrete optimizations such as proper indexing, cursor pagination, JOIN tuning, and server‑level parameter tweaks.
The article examines how to implement read/unread status for single and group chats at scale, comparing a simple last‑read‑ID approach for one‑on‑one conversations with database, Redis hash, and bitmap‑watermark solutions for groups, and discusses their performance and memory trade‑offs.
This article explains how MySQL deadlocks arise, details the four necessary conditions, compares lock types, shows how to enable detailed deadlock logging, query lock metadata, interpret logs, and provides practical code‑level and configuration strategies to prevent and resolve common deadlock scenarios in production environments.
A logistics company struggled with mismatched label fees, manual reconciliation errors, and monthly profit loss, so the team deployed an automated recharge, label import, one‑click deduction, and reconciliation system that eliminated leakage, cut reconciliation time, and provided real‑time balance visibility.
The article walks through a systematic MySQL 8.0 index‑optimization workflow—starting with diagnosing slow queries and lock waits, validating execution plans with EXPLAIN ANALYZE, safely adding or dropping indexes using online DDL, handling pagination patterns, and verifying improvements via comprehensive metrics before and after.
This article walks MySQL developers through the essential architectural, schema, data‑type, SQL‑dialect, transaction, vacuum, indexing, and extension differences when moving to PostgreSQL, providing concrete examples, code snippets, and best‑practice recommendations to avoid common pitfalls.
The article explains why placing column C immediately after the equality column A in a composite index (A, C, B) avoids filesort and keeps performance stable regardless of how many values appear in the B IN list, outperforming other index orders such as (A, B, C).
This guide walks through a systematic approach to uncovering and fixing MySQL slow queries, covering slow‑query‑log configuration, log analysis with mysqldumpslow and pt‑query‑digest, EXPLAIN‑based execution‑plan inspection, index design principles, SQL rewrites, configuration tuning, and ongoing monitoring to prevent performance regressions.
The article examines why the common update‑database, delete‑cache, add‑TTL workflow can still produce permanent stale data under high concurrency, explains the underlying race conditions, and compares several alternative strategies—including delete‑first, binlog‑driven invalidation, and lease‑based approaches—to help engineers choose the most reliable and low‑complexity solution for cache consistency.
To address MySQL master‑slave replication lag, the article explains enabling parallel replication (setting slave_parallel_workers), routing reads to the master for latency‑sensitive operations, and using a Redis short‑term marker to direct recent writes to the master, while outlining configuration steps and trade‑offs.
This article breaks down MySQL’s locking mechanisms—table, row, and gap locks—explaining their principles, performance trade‑offs, when they are triggered, how they relate to index usage, and provides practical deadlock avoidance techniques and a concise cheat‑sheet for common concurrency problems.
This article walks through a complete production‑grade view of MySQL 8.4 LTS, explaining how a chain of traffic spikes, connection‑pool exhaustion, long transactions and replication lag can cause an avalanche, and then detailing the five core modules, seven production mechanisms, architectural evolution steps, incident post‑mortems, and concrete configuration and code examples to build a resilient MySQL service.
This comprehensive guide walks MySQL administrators through the fundamentals of backup and recovery, covering RPO/RTO concepts, tool comparisons (mysqldump, mydumper, xtrabackup), step‑by‑step scripts for full, incremental, and binlog backups, encryption, compression, troubleshooting, and best‑practice monitoring to ensure data safety and rapid restoration.
When MySQL replication latency jumps from milliseconds to 10 seconds, blindly raising replica_parallel_workers won’t help; the article walks through diagnosing the delay, then applies three concrete parallel‑replication optimizations—enabling WRITESET on the source, configuring LOGICAL_CLOCK with appropriate applier workers, and optionally preserving commit order—while showing the required SQL commands, monitoring queries, and rollback steps.
This article explains why database transactions are a core backend skill, breaks down the four ACID properties, clarifies dirty read, non‑repeatable read and phantom read, compares the four isolation levels, and offers practical guidelines for choosing the right level in production.
MySQL servers can trigger alarming disk‑space warnings even when the data directory is small, because unchecked binary logs rapidly consume storage; this article explains the log’s purpose, why it grows, how to diagnose the issue, and provides step‑by‑step cleanup, configuration, replication, monitoring, and recovery best practices.
This guide walks you through a complete emergency response, root‑cause analysis, and long‑term mitigation for MySQL connection‑limit exhaustion, covering Linux diagnostics, SQL commands, quick‑kill scripts, monitoring with Prometheus/Grafana, and best‑practice configuration of connection pools and max_connections.
The article analyzes why MySQL and Redis cannot guarantee strong consistency with simple cache‑aside patterns, explains the pitfalls of delayed double delete, and presents a tiered Java design—including transaction‑after‑commit deletion, retryable invalidation, CDC/Outbox pipelines, TTL safeguards, and multi‑level cache considerations—to achieve reliable cache consistency.
This white‑paper dissects why a monolithic MySQL‑based order service collapses under peak traffic and presents a layered, asynchronous architecture—using Redis for stock pre‑allocation, RocketMQ for transactional messaging, sharding, idempotency, and comprehensive observability—to reliably handle tens of millions of queries per second.
The article analyzes the requirements of a massive‑scale like feature, compares small‑scale MySQL implementations with the graph‑plus‑KV architectures used by ByteDance, Kuaishou and Xiaohongshu, and presents a practical hybrid solution based on Redis, MySQL and batch processing to handle hot content and super‑node challenges.
The article explains the differences between database sharding, table sharding, and combined sharding, outlines interview expectations, details vertical and horizontal splitting strategies, discusses when to apply each technique, and reviews practical tools such as ShardingSphere and MyCat for Java projects.
The article explains why deep pagination with large offsets becomes increasingly slow, why adding indexes often does not help, examines common “optimizations” like delayed joins, introduces cursor (keyset) pagination as a high‑performance alternative, and provides practical guidelines for designing pagination APIs in Java back‑ends at scale.
To survive a million concurrent flash‑sale clicks, the article breaks down a production‑grade, five‑layer architecture—CDN, load balancer, API gateway, Redis/Lua stock control, message‑queue order processing, and a state‑machine fallback—that filters traffic early, uses atomic operations, and decouples writes to keep database load to just a few QPS.
Databasus is an open‑source backup management platform that unifies PostgreSQL, MySQL, MariaDB and MongoDB backups with a web UI, offering logical, physical and incremental backups, automated scheduling, AES‑256‑GCM encryption, multi‑cloud storage, RBAC collaboration, and optional agents for secure, out‑bound connections.
The article explains why MySQL may still report Using filesort despite a composite index that appears to satisfy both WHERE and ORDER BY clauses, covering index ordering rules, the impact of range conditions, mismatched ORDER BY field order, ASC/DESC mixing, and practical optimization techniques.
The article walks through a real‑world order system that spikes to 300,000 QPS, explaining why the original single‑node MySQL design fails, and detailing a step‑by‑step evolution—index tuning, transaction fixes, read‑write splitting, vertical and horizontal sharding, plus data‑pipeline integration—to achieve stable low latency at massive scale.
The article examines the drawbacks of using Snowflake for generating short numeric user IDs, details a MySQL auto‑increment based approach, reveals deadlock problems with REPLACE INTO, evaluates alternative schemes, and presents a final sharding‑friendly short‑ID design that meets performance and usability requirements.
Adding a column to a tens‑of‑millions‑row MySQL table may look trivial, but the real difficulty lies in the metadata‑lock timing and online traffic impact, requiring careful DDL type selection, pre‑flight checks, and often an online migration tool such as gh‑ost to avoid business‑level outages.
The article explains how MySQL determines whether a statement should be recorded in the binary log under ROW format, detailing the check_table_binlog_row_based function, the cached_row_logging_check flag, OPTION_BIN_LOG, and various scenarios—such as temporary tables, replication filters, no‑replicate tables, session settings, and internal operations—where binlog entries are omitted.
This article provides a comprehensive, hands‑on guide to MySQL master‑slave replication, covering the underlying architecture, binlog formats, GTID and semi‑synchronous modes, detailed configuration steps, thread workflows, common failure scenarios with step‑by‑step diagnostics, and practical monitoring and failover scripts.
The article identifies eight easy-to-overlook SQL habits—such as using SELECT *, applying functions on indexed columns, careless LIKE patterns, improper IN/OR logic, deep offset pagination, unconditional UPDATE/DELETE, excessive indexing, and ignoring execution plans—that can cause slow queries, lock tables, index failures, and even data loss, and provides concrete examples and safer alternatives.
An in‑depth MySQL benchmark compares auto‑increment, UUID, and Snowflake‑style random long keys, showing how index structure, insert latency, and page fragmentation differ, and explains why auto‑increment keys usually outperform the others while also highlighting the security and lock‑contention drawbacks of sequential IDs.
When migrating tens of billions of rows, the article explains how a simple progress‑tracking table and failure‑log table enable automatic checkpoint‑based resumption, stateless execution, and dynamic batch tuning without restarting or rewriting code.
The article walks through setting up a MySQL fake server, crafting a malicious JDBC URL with autoDeserialize and query interceptors, demonstrating how the MySQL JDBC driver automatically deserializes BLOB data via ObjectInputStream, and traces the call chain to show how arbitrary code can be executed during connection initialization.
The article analyzes how MySQL executes different COUNT() forms—count(*), count(1), count(primary‑key), and count(column)—showing that count(*) and count(1) have identical performance, count(column) is the slowest, and offers indexing and approximation tips for large tables.
The article analyzes why simple auto‑increment or timestamp‑based IDs fail at massive scales, compares common distributed ID schemes, and presents an improved Snowflake‑plus‑segment hybrid solution with clock‑rollback protection, automatic machine/room allocation, and production‑grade safeguards for trillion‑level order processing.
MySQL connection failures are among the most frequent issues for developers and operators; this article systematically walks through typical error messages, explains how to collect relevant information, runs layered command checks, analyzes evidence, identifies root causes such as socket problems, bind‑address limits, host whitelist mismatches, authentication failures, connection‑limit exhaustion, and packet timeouts, and provides concrete fix and verification procedures for on‑premise, Docker, and Kubernetes deployments.
The article explains why MySQL's InnoDB engine uses REPEATABLE READ by default, clarifies the differences between snapshot and current reads, compares RC and RR isolation levels, details MVCC mechanics, and provides a concise interview answer template with practical SQL examples.
The article explains why excessive MySQL binary logs filled a CentOS server’s disk, walks through cleaning unrelated logs, shows how to inspect and purge the binlog files, and provides the exact my.cnf changes needed to permanently disable binary logging.
Even without rewriting any SQL, database performance can improve up to a hundredfold by first diagnosing bottlenecks, reducing unnecessary traffic, layering read paths, optimizing indexes, tuning connection pools, and progressively evolving from a single‑node setup to read‑write separation, sharding, and distributed read models.
When MySQL runs out of disk space, the safest approach is to identify the full filesystem, examine data, binlog, temporary and log directories, and use SQL‑based cleanup commands like PURGE BINARY LOGS while never manually removing critical files such as ibdata1, ib_logfile* or active binlogs.
This article presents a production‑grade, high‑concurrency order system design that separates responsibilities among Redis for traffic control, MySQL as the single source of truth, Kafka for event propagation, and Elasticsearch for search, while detailing state‑machine modeling, outbox patterns, seckill flow, and comprehensive observability and deployment practices.
MySQL 26.7.0 Early Access introduces calendar versioning that jumps the version number to 26, adds post‑quantum TLS support, a new Change Stream Applier, InnoDB refactoring, and moves the thread‑pool plugin to the community edition, while Oracle expands governance with a steering committee, a public roadmap, and a detailed release schedule for 2026‑2027.
The article uses a simple money‑transfer scenario to introduce database transactions, explains the four ACID properties, illustrates common concurrency anomalies such as dirty reads, non‑repeatable reads and phantom reads, and outlines the four isolation levels with their trade‑offs and default settings in MySQL and Oracle.
The article explains how database indexes act like a book's table of contents, reducing full‑table scans and disk I/O by using B+Tree structures, and compares clustered, non‑clustered, and covering indexes while highlighting their benefits and trade‑offs.
This comprehensive guide explains why MySQL permission mistakes happen, walks through the authentication and authorization process, shows how to design multi‑layered user models, role hierarchies, declarative GitOps workflows, Kubernetes integration, and production‑ready automation for secure, auditable, and scalable database access.
This article walks through Redis fundamentals, explaining its definition, internal modules, the full processing path of a SET command, essential commands, and how Redis differs from Memcached and MySQL, while also covering common connection and performance pitfalls.
This article walks through switching a SpringBoot + MybatisPlus project from MySQL to PostgreSQL, covering driver addition, JDBC URL changes, schema differences, and a detailed list of SQL syntax mismatches and runtime errors with concrete code examples and remediation scripts.
The article explains why coupon expiration cannot be handled by a simple scheduled scan and presents a production‑grade architecture that uses a task‑table, four‑plane design, fine‑grained splitting, lease‑based worker coordination, idempotent updates, and observability to reliably expire billions of coupons under peak load.
The article analyzes the delayed double‑delete cache‑consistency pattern, exposing how its fixed sleep interval, thread blocking, unreliable second delete, and inability to handle concurrent writes make it unsuitable for high‑traffic systems, and it proposes safer cache‑aside alternatives.
This article walks through a systematic, step‑by‑step troubleshooting guide for MySQL "Too many connections" errors, showing how to verify the symptom, inspect server variables, analyze connection status, identify common root causes such as connection‑pool misconfiguration, leaked connections, and long‑running queries, and apply safe fixes and preventive measures.
In just 20 minutes, the author uses Cursor AI to generate a full‑stack WeChat mini‑program for personal health management, featuring an AI‑driven health consultant, a Spring Boot 4 backend with JWT security, MySQL storage, and a Vue 3 admin console, and explains the architecture, routing, and deployment details.
This article introduces four command‑line tools—MySQLTuner.pl, tuning‑primer.sh, pt‑variable‑advisor, and pt‑query‑digest—explaining how to download, run them, and interpret their reports to assess MySQL performance, configuration, and query efficiency.
This article explains MySQL index fundamentals—from the B+‑tree storage engine and InnoDB’s clustered and secondary indexes to query execution, common index‑failure scenarios, and practical design principles for building effective indexes in interview settings.
The article explains that the real challenge is not merely running MySQL but placing it in the right resource model, and it provides a four‑dimensional decision framework—performance ceiling, stability floor, automation level, and organizational maturity—to guide when to use host‑installed MySQL, single‑node containers, or full Kubernetes deployment, illustrated with concrete resource analyses, architecture diagrams, configuration examples, pitfalls, checklists, and an evolution roadmap.
This comprehensive guide explains why seemingly indexed MySQL queries can still cause severe latency spikes in high‑traffic systems, explores the underlying InnoDB structures and optimizer cost model, enumerates twelve common failure patterns with concrete SQL examples, and provides a production‑grade methodology for diagnosing, engineering, and automating index governance.
If you need a cost‑free replacement for Navicat, this article compares three MySQL client tools—DBeaver, MySQL Workbench, and HeidiSQL—detailing their installation steps, supported databases, key features such as monitoring and ER diagrams, and practical usage tips.
The article walks through estimating peak QPS for a 50‑million‑daily‑request system, applies safety margins, and proposes a concrete deployment stack—including LVS, Nginx, Docker‑managed business servers, Redis cluster, MySQL sharding, and Kafka/RocketMQ—to reliably sustain roughly 4,500 QPS.
This guide walks through a complete MySQL master‑slave lag diagnosis process, explaining why relying solely on Seconds_Behind_Master is insufficient and showing how to separate IO and SQL thread issues, examine relay logs, detect long transactions, DDL locks, and apply best‑practice configurations and monitoring.
Oracle announced a new open‑source governance plan for MySQL, but developers, cloud providers, and third‑party vendors remain skeptical, demanding legally binding guarantees, fearing short‑term fixes, potential forks, and a shift of talent toward PostgreSQL.
The article explains why MySQL master‑slave replication lag occurs, lists common causes, provides a five‑level troubleshooting framework, and offers three concrete recovery methods—from emergency error skipping to multi‑threaded replication and long‑term architecture improvements—plus commands, configurations, and monitoring tips.
This article lists ten common IntelliJ IDEA pitfalls—slow performance, Lombok errors, broken breakpoints, encoding issues, unwanted Git files, Maven download slowness, class‑not‑found errors, broken shortcuts, MySQL timezone problems, and automatic reformatting—plus step‑by‑step solutions to make the IDE run smoothly for Java developers.
This guide walks through MySQL performance troubleshooting—from enabling and analyzing slow‑query logs with pt‑query‑digest, interpreting EXPLAIN plans, designing covering and composite indexes, tuning InnoDB buffer pool and connection settings, to best‑practice recommendations and real‑world case validation.
This article walks through diagnosing slow MySQL queries with EXPLAIN, applying index and join optimizations, using FORCE INDEX, monitoring index usage, preventing unsafe MyBatis patterns, and scaling massive tables with sharding, presenting concrete SQL examples and step‑by‑step guidance.
This article examines eight common SQL pitfalls—including misuse of LIMIT offsets, implicit type conversion, sub‑query updates, mixed ordering, EXISTS clauses, condition push‑down, early limiting, and intermediate result set handling—showing how each can degrade performance and providing rewritten queries with execution‑plan evidence that dramatically improve speed.
An UPDATE in MySQL 8.0 acquires three distinct locks—a server‑level metadata lock, an InnoDB intention exclusive lock (IX), and a row‑level exclusive lock—so understanding the three‑layer lock architecture (metadata, intention, row) helps both interview preparation and troubleshooting.
The author argues that in most companies you only need to write simple, single‑table or limited‑join queries and focus on index tuning and basic MySQL concepts such as InnoDB, locks, and execution flow, while complex SQL work often signals a poorly organized team.
The article dissects the delayed double‑delete pattern for Redis‑MySQL consistency, exposing its hidden pitfalls—unreliable delay timing, thread‑blocking sleeps, fragile second‑delete retries, and concurrent‑write anomalies—then recommends cache‑aside and stronger alternatives for production systems.
The article introduces go-vue-admin, an open-source Go-based backend management system with a Vue3 front‑end, outlines its built‑in modules such as user, role, and monitoring, lists environment requirements and repository links, provides step‑by‑step setup commands, and offers a curated collection of free Go books and video tutorials.
The article breaks down MySQL index mechanics into four visual sections, explaining B+Tree structure, why it outperforms B‑tree, hash and binary trees, common index‑failure scenarios, and three practical optimization techniques, giving interviewees a clear framework to answer index‑related questions confidently.
The article details how a sluggish batch‑processing system handling millions of records was redesigned with XXL‑JOB sharding, Redis‑based dynamic task distribution, cursor pagination, and selective transaction scopes, achieving nearly ten‑fold throughput improvement while addressing resource contention, load‑balancing, and reliable result reconciliation.
The article explains how an UPDATE without an indexed WHERE clause triggers InnoDB’s next‑key locks, effectively locking the entire table, shows transaction examples that cause blocking, and recommends enabling sql_safe_updates or using FORCE INDEX to ensure the statement uses an index scan.
This guide walks through practical MySQL backup and point‑in‑time recovery strategies using logical dumps with mysqldump and physical copies with Percona XtraBackup, covering configuration, command‑line examples, binlog handling, GTID/LSN concepts, incremental backups, restoration scripts, verification steps and common pitfalls for DBAs and DevOps engineers.
The article analyzes the write bottleneck of processing 30,000 payment orders per second on an Oracle‑Java‑Spring stack, explains why sharding was used historically, why MQ‑based peak‑shaving is discouraged, and compares self‑built sharding with modern distributed databases such as PolarDB‑X, TiDB and OceanBase, while summarizing public practices from major Chinese tech firms.
This article explains the three fundamental challenges of distributed locks—availability, deadlock, and split‑brain—compares database and Redis implementations, walks through the five evolutionary steps of Redis locking, and provides a structured interview answer framework to demonstrate deep understanding.
