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Technical exploration and thoughts · 655 articles
Flink Window Complete Guide: Tumbling, Sliding, Session
Flink's Window mechanism is the core bridge between stream processing and unified batch processing architecture. Flink treats batch as a special case of stream processing, using time windows (Tumbl...
Flink Sliding Window Deep Dive: Principles, Use Cases & I...
Sliding Window is one of the core mechanisms in Apache Flink stream processing, more flexible than fixed windows, widely used in real-time monitoring, anomaly...
Flink JDBC Sink Deep Dive: MySQL Real-time Write, Batch O...
JDBC Sink is one of the most commonly used data output components, often used to write stream and batch processing results to relational databases like MySQL,...
Flink Batch Processing DataSet API: Use Cases, Code Examp...
Flink's DataSet API is the core programming interface for batch processing, designed for processing static, bounded datasets, supporting TB to PB scale big...
Redis Memory Management: Key Expiration and Eviction Poli...
Comprehensive analysis of Redis memory control mechanisms, including maxmemory configuration, three key expiration deletion strategies (lazy/active/scheduled), and 8 memory eviction policies with a...
Redis Communication Internals: RESP Protocol and Reactor ...
Deep dive into Redis communication internals: RESP serialization protocol five data types, Pipeline batch processing mode, and how the epoll-based Reactor single-threaded event-driven architecture ...
Flink DataStream Transformation: Map, FlatMap, Filter to ...
Flink provides rich operators for DataStream to support flexible data stream processing in different scenarios. Common operators include Map, FlatMap and...
Flink Sink Usage Guide: Types, Fault Tolerance Semantics ...
Flink's Sink is the final output endpoint for data stream processing, used to write processed results to external systems or storage media. It is the endpoint of streaming applications, determining...
Flink Source Operator Deep Dive: Non-Parallel Source Prin...
Non-Parallel Source is a source operation in Flink with fixed parallelism of 1. It can only run in a single instance regardless of cluster scale, ensuring tasks are processed sequentially.
Flink SourceFunction to RichSourceFunction: Enhanced Sour...
RichSourceFunction and RichParallelSourceFunction are enhanced source functions suitable for scenarios requiring complex logic and resource management.
Flink on YARN Deployment: Environment Variables, Configur...
Deploying Flink in YARN mode requires completing a series of environment configuration and cluster management operations. First, configure environment...
Flink DataStream API: DataSource, Transformation & Sink C...
DataSource, Transformation and Sink. DataSource provides diverse data input methods including file systems, message queues, databases and custom data sources.
Redis Persistence: RDB vs AOF Comparison and Production S...
Systematic comparison of Redis two persistence solutions: RDB snapshot and AOF log — configuration methods, trigger mechanisms, pros and cons, AOF rewrite mechanism, and recommended strategies for ...
Redis RDB Persistence: Snapshot Principles, Configuration...
In-depth analysis of Redis RDB persistence mechanism, covering trigger methods, BGSAVE execution flow, configuration parameters, file structure, and comparison with AOF, helping you make informed p...
Flink Architecture Deep Dive: JobManager, TaskManager & C...
Flink's runtime architecture adopts typical Master/Slave pattern with clear division of responsibilities among core components. JobManager as Master is...
Flink Installation & Deployment Guide: Local, Standalone ...
Flink provides multiple installation modes to suit different scenarios. Local mode is suitable for personal learning and small-scale debugging with simple...
Apache Flink Deep Dive: From Origin to Technical Features
Apache Flink is an open-source big data stream processing framework, supporting efficient computation of unbounded stream and bounded batch data. With 'unified...
Flink Stream-Batch Integration Introduction: Concept Anal...
Apache Flink supports both stream processing and batch processing. Stream processing is suitable for real-time data like sensors, logs or trading streams,...
Redis Lua Scripts: EVAL, redis.call and Atomic Operations...
Systematic explanation of Redis Lua script EVAL command syntax, differences between redis.call and redis.pcall, and four typical practical cases: atomic counter, CAS (Compare-And-Swap), batch opera...
Redis Slow Query Log and Performance Tuning in Production
Detailed explanation of Redis slow query log configuration parameters (slowlog-log-slower-than, slowlog-max-len), core commands, and production-grade performance tuning strategies including data st...