danmartensen.svbtle.comDan Martensen

Svbtle Menu is writing on the Svbtle network. rss feed about svbtle sign up Software Engineering Read this first Java Streams Streams brought a functional and declarative style to Java. They convey elements from a source, such as a collection, through a pipeline of computational operations, But different than collections, streams don’t provide storage, return results without modifying the source, can be unbounded, and are consumable, where elements are visited once in each stream. Here we’ll cover how to create streams, common methods, and how sequencing operations affects output. Example Stream.of("acoustic guitar", "bass", "cello", "drums") .filter(s -> { System.out.println("filter: " + s); return true; }) .forEach(s -> System.out.println("forEach: " + s)); Output filter: acoustic guitar forEach: acoustic guitar filter: bass forEach: bass filter: cello forEach: cello filter: drums forEach: drums Each element moves vertically down the pipeline. Stream pipelines A... Continue reading → Aug 26, 2018 RabbitMQ Message Broker Patterns RabbitMQ uses variety of asynchronous architectural patterns to decouple applications. Here we’ll cover round robin, next available worker, and publish/subscribe models, and features such as routing, pattern filtering, acknowledgement, and durability [1]. Message Broker Producer - User application that sends messages to an exchange. Exchange - Pushes messages into queues. Exchange types define what to do with the message when it’s received, whether. appended to a one queue, to many queues, or discarded. Example exchange types are direct, topic, headers and fanout . Queue - Each exchange contains a buffer, or queue, that stores messages. A queue is only bound by the host’s memory & disk limits, it’s essentially a large message buffer. Many producers can send messages that go to one queue, and many consumers can try to receive data from one queue. Consumer - User application that... Continue reading → Feb 29, 2016 SQL Performance of Join and Where Exists Sometimes we need to identify record sets with at-least-one relationships. Find customers who’ve placed an order, products categorized as books, or cities that have airports. In this post we’ll compare the performance and execution paths of inner join to where exists in PostgreSQL 9.5. Let’s settle with finding all products that have been ordered . Setup Create and populate two tables, products and orders, with 1,000,000 rows each of random data. CREATE TABLE p ( p_id serial PRIMARY KEY, p_name character varying UNIQUE ); INSERT INTO p (p_name) SELECT substr(gen_salt('md5'), 4) FROM generate_series(1, 1000000); Output | p_id | p_name | -------------------------- | 1 | 5aHN4w0f | | 2 | 29LKwrBw | | 3 | 9cIR4iXE | | 4 | 5P9aTUQN | | ... | ... | | 1000000 | 6cpGNL18 | Pretty random looking. Now for... Continue reading → Dec 17, 2015 Rediscovering MVC and How to Write without a Framework If you’ve paid much attention to front-end development in the last few years you’ve heard about Angular, Backbone, Ember, and other JavaScript MV* frameworks. They offer structure, bundled APIs and streamlined approaches to complex UIs, although not without concerns of performance, monolithic designs, and high churn rates [1][6] . All these frameworks share an adaptation of classic MVC, a pattern that transcends platforms, libraries, and languages, where models hold state and logic, views visualize state as output, and controllers handle input and interactions with the model and view [2] . Understanding classic MVC helps us evaluate strengths and shortcomings when selecting a front-end framework or micro-framework alternative. In this post we’ll cover MVC’s relevance, the roles of each component and how to write it with vanilla JavaScript. Purpose So why is MVC so prevalent? Some... Continue reading → Sep 1, 2015 Designing Normalized SQL Tables SQL databases are reliable for complex queries, partial updates, transactions, and decoupling data modeling from application specific contexts. In this post we’ll cover how to normalize tables in 1NF, 2NF, and 3NF. We have a table. Name Position Team Jersey No. Home Stadium Stadium City Salary & Contract Aaron Rodgers QB Packers 12 Lambeau Field Green Bay $22M, 5 years J.J. Watt DL Texans 99 NRG Stadium Houston $16.7M, 6 years. Earl Thomas DB Seahawks 29 Century Link Field Seattle $10M, 4 years Andrew Luck QB Colts 12 Lucas Oil Stadium Indianapolis $5.5M, 4 years Some issues off the cuff, right? What if I wanted to add a new team but had no player? What if a player plays multiple positions? Or two teams share the same home stadium? All these deal with data redundancy. And what’s the primary key, anyways? 1NF 1NF defines the shape of a table. Concepts ... Continue reading → Jun 1, 2015 Build Better Apps with ES6 Modules ES6 is packed with features like iterators, generators, maps, sets, symbols, template strings and more. One of the biggest game changers to app architecture is the new modules, and different than the syntactic sugar of class and extends they’re an entirely new construct [1] . In this post I’ll cover ES6’s new module syntax and how it provides better performance, encapsulation, and error handling. But first a little backstory. Engineers have long defined modules with workarounds on the global window object using object literals, the module pattern, and any combination of IIFEs one can imagine. Each of these comes with a set of challenges from lack of encapsulation to forced singletons. In 2010 RequireJS became a popular tool to define modules client-side, being used on sites like PayPal, Dropbox and The New York Times. CommonJS, it’s counterpart, was adopted server-side by the... Continue reading → Apr 20, 2015 Events, Concurrency and JavaScript Modern web apps are inherently event-driven yet much of the browser internals for triggering, executing, and handling events can seem as black box. Browsers model asynchronous I/O thru events and callbacks, enabling users to press keys and click mouses while XHR requests and timers trigger in code. Understanding how events work is critical for crafting high performance JavaScript. In this post we’ll focus on the browser’s built-in Web APIs, callback queues, event loops and JavaScript’s run-time. Code in action. A button and event handler. <button id="doStuff">Do Stuff</button> <script> document.getElementById('doStuff') .addEventListener('click', function() { console.log('Do Stuff'); } ); </script> Let’s trace a Do Stuff click event thru browser and describe the components along the way. From Philip Robert’s diagram Browser ... Continue reading → Mar 20, 2015 JavaScript’s Map, Reduce, and Filter As engineers we build and manipulate arrays holding numbers, strings, booleans and objects almost everyday. We use them to crunch numbers, collect objects, split strings, search, sort, and more. So what’s the preferred way to traverse arrays? For years it’s been the trusty for loop which ensures iterating over the elements in order by index. In 2011, JavaScript introduced map , reduce , and filter as powerful alternatives when translating elements, finding cumulative values, or building subsets based on conditions. These methods help the developer manage less complexity, work without side effects, and often make code more readable. In this post we’ll cover the usefulness of Array’s map , reduce , and filter methods. You’ll see use cases, code samples, behavior, and parameters of each method. reduce() can find a Fibonacci sequence in O(n) Drawbacks of Looping Say I’m working on a... Continue reading → Feb 25, 2015 Converting a Tree to a List in JavaScript With the meteoric rise of JavaScript MVC frameworks, data structures and algorithms long handled server-side are now managed on the client. JavaScript references objects thru memory addresses, making linked lists, trees, even graphs all possible to build and traverse. So dust off the old computer science textbook, grab a...