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Java Thread Synchronization and Concurrency Part 1

Introduction

Java thread synchronization and concurrency are the most discussed topics during various design phases of a complex application. There are many aspects of threads, synchronization techniques to achieve great concurrency in an application. The evolution of CPUs over the years (multi-core processors, registers, cache memory, and the main memory (RAM) has lead to some areas that usually developers tend to overlook — like thread context, context-switching, variable visibility, JVM memory model vs CPU memory model. 

In this series, we will discuss various aspects of the Java memory model, including how it impacts thread contexts, synchronization techniques in Java to achieve concurrency, race conditions, etc. In this article, we'll focus on the concepts of threads, synchronization techniques, and the memory models of both Java and our CPU.

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Java Thread Synchronization and Concurrency Part 2

Introduction

This is the second part of my two-part series on thread synchronization. If you missed the first article, check it out. In the previous article, we covered concepts of threads, synchronization techniques, and memory model of both Java and CPU. In this article, we'll focus on concepts of concurrency, how to execute tasks in concurrent mode, and the various classes and services in Java that offer concurrency (thread-pool).

Multi-Threading Costs

Before getting into concurrency, we have to understand the costs associated with multi-threading. The costs include application design, CPU, memory, and context switching. Below are some of the considerations for concurrency:

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How a URL Shortening Application Works

Introduction

Typically, a long URL is a system-generated URL, usually containing multiple query parameters that may be encrypted/encoded to mask those parameters. The need for shortened URLs arises when long URLs have to be shared for various purposes, like sharing links via SMSs, Emails, media types, like Twitter or WhatsApp, etc.

A URL shortening service might sound like a simple service at first, but it poses a very interesting and challenging engineering problem. Please pause here and think about how you could design a system to generate an infinite number of short URLs for possibly all long URLs in the world. The interesting part of the problem is generating unique, random identifiers for these long URLs. The identifiers should be short enough to fit in the URL with an acceptable character set.

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Scalable Data Grid Using Apache Ignite

In this article, I introduce the concept of a Data Grid, it's properties, services it offers, and finally how to design a scalable Data Grid for your needs.

What Is a Data Grid?

A Data Grid is a set of services that delivers a shared data management system, wherein heterogeneous data from various applications and services will be accessible by forming a grid-like structure. This is possible using strong middle-ware applications and services that support data ingress/query from various application requests.

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Cache in Java With LRU Eviction Policy

Introduction

LRU (or Least Recently Used) is a cache eviction strategy, wherein if the cache size has reached the maximum allocated capacity, the least recently accessed objects in the cache will be evicted. Also, the objects in the cache could be accessed by multiple threads in an application so is very important that the cache has good synchronization mechanism in-built. This article describes the implementation of a Java based cache with LRU eviction strategy; but fundamentally applies to any programming language.

Background

Many a times, developers embed caching frameworks in their application like Ehcache (which is a great library for general purpose, in-memory caching). But there are ocassions when there is no liberty to use such frameworks or libraries; like cases for lightweight Java applications or mobile applications which are targeted to run on minimal memory footprint (or sometimes due to delivery deadlines there is no extra time learn and configure 3rd party caching frameworks and deploy to production). In these times, such a simple, light-weight LRUCache class can be used and with sufficient unit test coverage the cache can be heaviliy relied upon.