This article demonstrates how to design and implement a miniature yet fully functional industrial intelligent scheduling system in Go, leveraging a workflow engine, priority queue, saga‑based transactions with FSM state management, concurrent station execution, and write‑ahead logging for reliable, real‑time factory automation.
This comprehensive guide explains PostgreSQL's Write-Ahead Logging (WAL) fundamentals, its role in durability, crash recovery, PITR and streaming replication, details the checkpoint mechanism, essential monitoring queries, production‑grade configuration recommendations, backup and recovery procedures, and practical DBA checklists for reliable operations.
This article explains SQLite's PRAGMA commands, compares synchronous modes and WAL settings, distinguishes persistent from session‑level pragmas, and highlights key Linux‑Windows differences, providing practical examples and a step‑by‑step initialization checklist for reliable database operation.
This comprehensive guide walks you through troubleshooting PostgreSQL physical (stream) replication, covering environment prerequisites, anti‑pattern warnings, step‑by‑step diagnostics for replication lag, split‑brain scenarios, replication slot problems, monitoring setup with Prometheus, and best‑practice recommendations to keep your primary‑standby cluster healthy.
This article walks through building a database storage engine from a simple shell script to a full distributed key‑value system, covering in‑memory indexing, SSTable creation, LSM‑Tree architecture with compaction, replication strategies, and sharding techniques for scaling across multiple machines.
Explore 15 classic MySQL log interview questions covering redo log, WAL, binlog, undo log, two‑phase commit, write‑ahead logging, crash‑safe mechanisms, log flushing settings, and recovery procedures, with detailed explanations, execution flow diagrams, and configuration parameters to help you ace database engineering interviews.
This article presents 15 classic MySQL log interview questions and provides detailed explanations of redo log, WAL, binlog, undo log, two‑phase commit, log flushing mechanisms, and recovery strategies, helping readers deepen their database knowledge and ace technical interviews.
An in‑depth guide explains MySQL’s write‑ahead log mechanism, covering buffer pool, redo and undo logs, checkpoint types, and how the system recovers from power failures, with step‑by‑step examples and practical configuration tips for reliable data consistency.
This article explains MySQL InnoDB’s write‑ahead logging, detailing the roles of Buffer Pool, Redo and Undo logs, checkpoint mechanisms, and how they ensure data consistency and atomicity when a sudden power loss occurs.
This article explains MySQL's binary log (binlog), a binary format file that records SQL statements for database updates, its role in master-slave replication, crash recovery, and detailed implementation mechanisms including cache management and event writing processes.
This article explains MySQL's transaction implementation, covering write‑ahead logging, transaction IDs, multi‑version concurrency control, buffer pool management, and the roles of redo and undo logs in ensuring durability and atomicity.
This article explains SQLite's Rollback and WAL logging modes, compares their performance and concurrency characteristics, investigates a real‑world problem where duplicate IM message IDs appear after app upgrades, and presents a step‑by‑step solution using UNIQUE constraints and index checks to prevent repeated inserts.
This article examines the drawbacks of using UUIDs as primary keys in PostgreSQL—highlighting WAL and index bloat, performance penalties, benchmark comparisons with sequences, and suggests ordered UUID alternatives for better scalability and maintainability.
This article explores MySQL’s write‑ahead log, two‑phase commit, engine plugins, memory management, lock strategies, and state‑machine design, showing how these internal mechanisms can inspire more reliable, scalable, and maintainable business system architectures.
This article examines SQLite's journal modes, Android's thread and connection‑pool configurations, and demonstrates through source‑code analysis that converting a database from the default rollback‑journal mode to write‑ahead logging (WAL) is safe and improves concurrency performance.
This article explains how a deep understanding of database internals, illustrated by an Oracle recovery story, enables you to restore PostgreSQL instances when WAL files or pg_control are missing, providing detailed command parameters, preparation steps, and cautions for safe recovery.
This article explains why PostgreSQL data loss occurs, compares DDL and DML causes, and reviews several recovery tools—including pg_resetwal, pg_dirtyread, pg_recovery, pg_filedump, WalMiner, and pageinspect—providing usage examples, summaries, and practical recommendations for effective data restoration.
This guide walks through setting up PostgreSQL's Point‑In‑Time Recovery (PITR) by enabling WAL archiving, performing a base backup, simulating data loss, and restoring the database to a specific timestamp, complete with command‑line examples and verification steps.
This article explains common database logging mechanisms such as MySQL redo logs and binlogs, compares them with Redis AOF and etcd's Raft‑based WAL, and provides an in‑depth analysis of etcd's WAL source code, including key structures, creation process, record types, encoding, and file pipeline management.
This article explains how PolarDB ensures transaction atomicity by analyzing ACID principles, detailing the shortcomings of simple Direct‑IO and Buffer‑IO, introducing write‑ahead logging, full‑page backup, checkpointing, visibility mechanisms, and distinguishing durability and atomicity points to achieve reliable crash recovery and consistent data visibility.
This article explains how PolarDB implements transaction atomicity by combining write‑ahead logging, buffer management, full‑page backup, CLOG, and ProcArray mechanisms to ensure crash‑safe recovery, consistent visibility, and durable commits within the database system.
This article explains the essential role of logging and recovery mechanisms—especially the ARIES algorithm—in ensuring ACID properties, covering physical vs logical logging, optimization techniques like group commit and early lock release, and the three-phase recovery process.
This article explains why a low‑traffic PostgreSQL 11 database can accumulate massive WAL files, analyzes relevant configuration parameters and replication slots, demonstrates diagnostic SQL commands, and provides step‑by‑step actions—including adjusting archive_timeout, handling replication slots, and forcing a checkpoint—to reclaim disk space.
The article explains how Write Ahead Log (WAL) improves metadata persistence and disaster recovery in distributed storage systems such as HDFS by buffering changes, reducing synchronous database writes, and providing checkpoint and recovery mechanisms, while also discussing practical control options.
MySQL achieves crash‑safe durability by employing a write‑ahead log architecture that records changes in redo, undo, and binary logs, coordinates them through two‑phase and group commit to maintain order, and uses a structured recovery process to replay or roll back transactions after any failure.
This article explains InfluxDB's storage engine workflow—including WAL, Cache, TSM files, compression components, and file management—then provides hardware sizing guidance based on write/query load, series cardinality, and recommends SSD storage with sample configuration settings.
This article explains how to handle high‑concurrency instant‑messaging scenarios by designing message deduplication, optimizing SQLite write performance with batch inserts and WAL mode, improving query speed with indexes and caching, and reducing UI refresh overhead through delayed and scroll‑aware updates.
This article explains the design and implementation of JDTX, a distributed transaction middleware that combines MVCC, WAL, and a one‑phase commit model to provide strong ACID guarantees, high performance, and multi‑database support while outlining its challenges and future roadmap.
This article introduces JDTX, a high‑performance, ACID‑compliant distributed transaction middleware, explains its architecture based on WAL and MVCC, compares rigid two‑phase commit and flexible BASE‑based approaches, and discusses the technical difficulties and future roadmap for integrating JDTX with Apache ShardingSphere and cloud‑native platforms.
This article explains MySQL's binlog group commit mechanism, detailing the three stages—Flush, Sync, and Commit—how they interact with redo logs and crash‑safe parameters, and analyzes a known bug in the Sync stage that was fixed in later MySQL versions.
An in‑depth look at SQLite’s Write‑Ahead Logging (WAL) mode and the asynchronous checkpoint optimization used in WeChat’s WCDB, covering implementation details, performance gains, A/B test results, and practical code examples for enabling these features on Android.
This article examines the evolution of write-ahead logging in relational databases, compares MySQL and PostgreSQL implementations, highlights the scalability limits of centralized WAL designs, and explores how distributed logging with global timestamps, dependency tracking, and hole‑avoidance techniques could dramatically improve single‑node database throughput.
The article explains HBase’s write‑ahead‑log architecture, detailing how client put/delete requests travel through RPC to the RegionServer, are processed by MultiRowMutationService, written to the WAL via FSHLog.append and sync, and finally stored in MemStore, while describing durability options and the underlying source‑code call chain.
This talk details how Tencent's iOS engineers tackled SQLite performance bottlenecks by redesigning multithreaded concurrency, optimizing Busy Retry handling, leveraging WAL and mmap, and applying low‑level I/O and lock improvements, resulting in dramatic reductions in UI lag and CPU waste for heavy‑use users.
This article explains HBase’s internal architecture, covering the roles of HRegionServer, Client, Zookeeper, Master, RegionServer, the physical storage layout, StoreFile and HFile structures, and the Write-Ahead Log mechanism that ensures data durability and fault tolerance.
