Topic
Memory Management
Learn Memory Management as a connected topic across chapters, concepts, simulations, and interview reasoning.
10 Concepts5 Articles2h 10m
Overview
Learn Memory Management as a connected topic across chapters, concepts, simulations, and interview reasoning.
How this topic helps
Jvm
Context Window
Java
#apache Spark
Learning Path in this Topic
Series that contain articles from Memory Management. Select a path to filter the article list.
Articles
5 matched articles
Article 1Spark Executor Sizing: Memory Model, Core Tuning, and GC StrategyTLDR: Spark executor OOMs are almost never caused by insufficient total cluster RAM — they are caused by misallocating memory across five distinct JVM regions while ignoring GC behavior and memoryOver37 min
Article 2How AI Coding Agents Work: Models, Context, Sessions, and MemoryTLDR: An AI coding agent is an LLM stapled to a tool registry, wrapped in an orchestration loop that painstakingly rebuilds state on every single API call — because the model itself is completely stat34 min
Article 3How JVM Garbage Collection Works: Types, Memory Impact, and TuningTLDR: JVM garbage collection automatically reclaims unused heap memory, but every algorithm makes a different trade-off between throughput, latency, and memory footprint. The default G1GC targets 200m25 minArticle 4Context Window Management: Strategies for Long Documents and Extended ConversationsTLDR: 🧠 Context windows are LLM memory limits. When conversations grow past 4K-128K tokens, you need strategies: sliding windows (cheap, lossy), summarization (balanced), RAG (selective), map-reduce 20 min
Article 5Java Memory Model Demystified: Stack vs. HeapTLDR: Java memory is split into two main areas: the Stack for method execution frames and primitives, and the Heap for all objects. Understanding their differences is essential for avoiding stack over14 min