• Bloom Filter 101

    What data structure would you use to determine whether an entity is in a given dataset with speed? Many would answer “Hashtable” without hesitation. Hashtable performs well when accessing an entity among a group of entities: the average time complexity of its read operations is constant. Nevertheless, using Hashtables can be rather costly when dealing with large datasets.
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  • A Brief Introduction to Pagination

    For many software engineers, endpoints for retrieving a list of entities are probably their favorite to implement–all they need to do is build an SQL statement that grabs all the available items, along with some other minor tasks. It’s all fun and games until the number of entities in the database becomes a bottleneck, where each GET request returns tens of thousands of items.
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  • A More Elegant Alternative to Golang's Error-Handling

    Recently, I joined a new project at Colorkrew that uses Golang as its backend language. Almost everyone on the team, including myself, had no experience with Golang, so we had to start from zero. Learning Golang has been a rewarding experience so far. After all, it is one of the most in demand programming languages now.
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  • Separation of Concerns: Split Your React Components into Containers and Views

    Many frontend engineers probably have experienced the head-scratching moment when their React components become so gigantic that they keep losing their train of thought when navigating through their frontend code. To salvage readability, one of the most common practices is to split up the humongous React components into smaller pieces. Traditionally, they would do this by chopping up the JSX elements.
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  • RESTful API 101

    It is almost impossible for a backend engineer to be oblivious to RESTful API in the 21st century, as it is one of the most popular API types. We can mostly attribute its popularity to its scalability, flexibility, and simplicity, all of which are highly sought-after qualities in modern APIs. If you also find these qualities desirable, you should consider building APIs following the RESTful principles.
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  • Introduction to Functional Programming

    The first programming paradigm that most programmers in the 21st century learn is probably Object Oriented Programming (or OOP for short). Object Oriented Programming allows us to transform real-world entities into highly abstract models with descriptive properties and executable methods to simulate their behaviors in the real world. Despite its numerous advantages, such as readability, reusability, and maintainability, it also introduces immense complexity to state management.
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  • OAuth Demystified: A Straightforward OAuth Tutorial

    Incorporating OAuth (short for Open Authorization) into an application might seem somewhat intimidating and disheartening for many entry-level software engineers. After all, they need to spend hours—or even days—implementing a complicated authentication process with the correct configuration, only to realize they have merely completed a tiny feature. Despite all the hard work it entails, OAuth is a safe and efficient way for users to grant websites and applications access to their personal information.
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  • Async/Await: a Game Changer for Haters of Promise Chaining

    If you became a frontend engineer after 2015, chances are that you have used or at least heard about Promise. As I have covered in my previous blog, Promise can help us specify sequential relations between operations in asynchronous programming in a readable and maintainable manner. Promise object in JavaScript has methods, such as then and catch, that can help us organize the sequential execution of operations in a pattern called Promise Chaining.
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  • The Whys and Hows of Promise in JavaScript

    If you have done any web development after 2015, chances are that you have heard of the concept of Promise. It wouldn’t be an overstatement to claim that Promise is ubiquitous in modern-day front-end codebases. However, many web developers—especially those who do not have much experience in front-end development—have been using Promise without thoroughly understanding its inner working.
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  • All You Need to Know about Isolation Levels and Read Inconsistencies

    Just like real life, the world of computer science is replete with trade-offs. Relational databases are no exception. When interacting with relational databases, we face the dilemma between data consistency and transaction concurrency. The former guarantees the data is trustworthy, while the latter ensures relational databases can conduct transactions swiftly. Both are desirable qualities of relational databases, but we cannot simultaneously achieve them to the fullest extent.
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  • CAP Theorem But Better? Introduce the PACELC Theorem

    In the previous blog, I introduced the famous CAP Theorem (please give it a read if you haven’t already before you start reading this one). It involves a trilemma of needing to give up one of the following three qualities: consistency, availability, and partition tolerance. Since all three are desirable features of modern-day distributed systems, determining which one to relinquish has become one of the most important and delicate decisions for designers of complicated distributed systems.
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  • What You Need to Know about the CAP Theorem

    The world that we live in is far from perfect. We constantly find ourselves in dilemmas, sometimes even trilemmas, that require us to make trade-offs. When shopping, we can only choose two out of “cheap,” “fast,” and “good.” In economics, a government cannot enjoy “sovereign monetary policy,” “fixed exchange rate,” and “free capital flow” at the same time.
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  • A Brief Introduction to Kafka

    There’s no denying that we have already ushered in the era of big data. An enormous amount of information is generated every second. While decision-makers can gain invaluable insights from this ever-growing data, its sheer volume also poses considerable challenges to data engineers–greater demand for storage spaces, the need to handle increasingly complex data formats, and highly unpredictable network traffic.
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  • A Brief Introduction to the Inner Working of MapReduce

    As a data engineer, you probably have heard about Hadoop. It is one of the most popular frameworks for distributed processing of large data sets. It is less costly and more secure than other frameworks. At its center is a programming model called MapReduce. Today we will take a closer look at MapReduce to understand the inner working of Hadoop.
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