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Shepherd Advanced Notes

Dedicated to sharing advanced Java technical insights, daily work snippets, and the power of persistent effort.

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Latest from Shepherd Advanced Notes

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Shepherd Advanced Notes

Apr 10, 2023 · Backend Development

Understanding Spring @Conditional and Its Derived Annotations

This article explains how Spring Boot’s @Conditional annotation works, shows how to implement custom Condition classes for language switching, and reviews the suite of derived annotations such as @ConditionalOnBean, @ConditionalOnMissingBean, @ConditionalOnClass, @ConditionalOnMissingClass, and @ConditionalOnProperty with concrete code examples.

@ConditionalConditionalOnBeanConditionalOnProperty

0 likes · 9 min read

Understanding Spring @Conditional and Its Derived Annotations

Shepherd Advanced Notes

Apr 3, 2023 · Backend Development

Deep Dive into Spring’s @ComponentScan: Usage and Underlying Mechanics

This article explains why Spring Boot is popular, how @ComponentScan discovers @Component, @Controller, @Service, and @Repository beans across packages, demonstrates usage with code examples, and details the internal processing flow involving ConfigurationClassPostProcessor and related parsers.

AnnotationConfigurationDependency Injection

0 likes · 15 min read

Deep Dive into Spring’s @ComponentScan: Usage and Underlying Mechanics

Shepherd Advanced Notes

Mar 30, 2023 · Backend Development

Deep Dive into Spring’s @Import: Usage, Three Scenarios, and Internal Mechanics

This article explains Spring's @Import annotation, compares it to @Bean, demonstrates three distinct usage patterns with concrete code examples, and walks through the underlying processing performed by ConfigurationClassPostProcessor and related internal methods.

ImportJavaSpring Boot

0 likes · 16 min read

Deep Dive into Spring’s @Import: Usage, Three Scenarios, and Internal Mechanics

Shepherd Advanced Notes

Mar 27, 2023 · Databases

Why MySQL Uses B+ Trees for Indexing

The article explains the fundamentals of tree data structures, compares B, B+, B*, and red‑black trees, and shows how B+ trees reduce disk I/O and improve range query performance, which is why MySQL adopts B+ trees for its indexes.

B+TreeData StructuresMySQL

0 likes · 15 min read

Shepherd Advanced Notes

Mar 22, 2023 · Databases

Mastering MySQL Indexes: Advanced Concepts and Practical Tips

This article provides a comprehensive deep‑dive into MySQL indexing, covering the definition, pros and cons, differences between clustered and non‑clustered indexes, InnoDB vs MyISAM implementations, B+Tree structure, capacity calculations, adaptive hash indexes, index pushdown optimization, and how to interpret EXPLAIN output to verify index usage.

Adaptive Hash IndexB+TreeClustered Index

0 likes · 18 min read

Mastering MySQL Indexes: Advanced Concepts and Practical Tips

Shepherd Advanced Notes

Mar 9, 2023 · Databases

Understanding MySQL’s SQL Execution Flow and Transaction Mechanics

This article explains MySQL’s internal architecture, walks through how a SELECT query and an UPDATE statement are processed—including the connector, parser, optimizer, executor, redo log, binlog, and two‑phase commit—and details transaction properties, isolation levels, MVCC, and related configuration parameters.

ACIDBinlogInnoDB

0 likes · 19 min read

Understanding MySQL’s SQL Execution Flow and Transaction Mechanics

Shepherd Advanced Notes

Mar 1, 2023 · Fundamentals

Understanding Linked Lists: Storage, Structures, and Two-Pointer Techniques

This article introduces linked lists as a fundamental data structure, compares them with arrays, explains single, doubly, and circular variants, demonstrates insertion, deletion, and boundary handling with dummy nodes, and details two‑pointer techniques for cycle detection and finding the list’s midpoint.

Data StructuresJavaalgorithm

0 likes · 15 min read

Understanding Linked Lists: Storage, Structures, and Two-Pointer Techniques

Shepherd Advanced Notes

Feb 22, 2023 · Backend Development

Why Caffeine Is the High‑Performance Local Cache Framework You Need

Caffeine is a high‑performance, low‑memory Java cache library that outperforms alternatives in benchmarks, uses the W‑TinyLFU eviction algorithm, offers extensive configuration (capacity, weight, expiration, listeners, stats), and integrates seamlessly with Spring and Guava concepts.

CacheCaffeineJava

0 likes · 13 min read

Why Caffeine Is the High‑Performance Local Cache Framework You Need

Shepherd Advanced Notes

Feb 13, 2023 · Backend Development

Elasticsearch Advanced Guide: Core Concepts and Implementation Principles

This article provides a comprehensive technical overview of Elasticsearch, covering core concepts such as indexes, types, documents, fields, mappings, shards and replicas, the cluster architecture, routing, write and read workflows, segment handling, translog, refresh and flush mechanisms, as well as practical optimization recommendations for hardware, shard strategy, routing, write performance and memory configuration.

Cluster ArchitectureElasticsearchIndexing

0 likes · 36 min read

Elasticsearch Advanced Guide: Core Concepts and Implementation Principles

Shepherd Advanced Notes

Feb 8, 2023 · Fundamentals

Understanding Java’s AbstractQueuedSynchronizer: The Core of JUC Concurrency

This article explains the design and implementation of Java’s AbstractQueuedSynchronizer (AQS), detailing its state management, CLH queue, Node structure, and how ReentrantLock (both fair and non‑fair) leverages AQS for lock acquisition and release, with concrete code examples and step‑by‑step analysis.

AQSCLH queueJava concurrency

0 likes · 18 min read

Understanding Java’s AbstractQueuedSynchronizer: The Core of JUC Concurrency