Guys, are there any good recommendations?
How to make a good backlink
GETTING INPUT FROM THE KEYBOARD
Direction: create a program to computer for the final grade using scanner and JOptionpane.
Given:
Quiz- 20%
Activity-60%
Exam-20%
Output
Enter guiz grade:
Enter activity grade:
Enter exam grade:
The final grade of: (Student name) si: (total of quiz, activity,and exam grade
A List of Java Cache Providers
Last week, we described several criteria to look at to choose a cache. This week, it’s time to list Java cache providers based on these criteria.
- Java Caching System
- Guava
- Caffeine
- Ehcache
- Infinispan
- Coherence Community Edition
- Ignite
- Geode
- Hazelcast
Java Caching System
JCS is a distributed caching system written in Java. It is intended to speed up applications by providing a means to manage cached data of various dynamic natures. Like any caching system, JCS is most useful for high read, low put applications. Latency times drop sharply and bottlenecks move away from the database in an effectively cached system.
Creating Mappers Without Creating Underlying Objects in Java
As most Java developers know, putting values in a Java Map (like a HashMap) involves creating a large number of auxiliary objects under the covers. For example, a HashMap with int keys and long values might, for each entry, create a wrapped Integer, a wrapped Long object, and a Node that holds the former values together with a hash value and a link to other potential Node objects sharing the same hash bucket. Perhaps even more tantalizing is that a wrapped Integer might be created each time the Map is queried! For example, using the Map::get operation.
In this short tutorial, we will devise a way of creating an object-creation-free, light-weighted mapper with rudimentary lookup capability that is suitable for a limited number of associations. The mapper is first created and initialized, whereafter it can be queried. Interestingly, these mappers can also be serialized/deserialized and sent over the wire using Chronicle’s open-source libraries without incurring additional object creation.
How to Produce a Spring REST API Following the OpenAPI Specification
The OpenAPI specification defines how to write HTTP APIs that can be consumed by any programming language and provide insight into the APIs’ functionality without access to source code or documentation. In other words, following the specification makes it easier for consumers to understand what it does and how to use it. Tools, such as Swagger, can then be used to display documentation without developers maintaining documentation separate from an API’s code.
All these described points translate into happier users while mitigating some of the burdens you’ll face while supporting your APIs.
How to Render Jenkins Build Parameters Dynamically
While working with Jenkins jobs (whether they're declarative or freestyle), we often need to pass some parameters to the code being executed when triggering the job. Jenkins supports this use-case by means of parameters that you can declare and use as Groovy variables in your Jenkins job. However, often you are not aware of all the parameters in the beginning, or sometimes you want to render the parameters dynamically based on the value selected in any other parameter.
Given the declarative nature of Jenkins jobs, we cannot achieve the use-case with the native Jenkins parameters available. Here comes the Active Choices parameter plugin to the rescue, which can help us render parameter values dynamically.
Rewrite Rules in Nginx
Rewrite rules modify a part or whole of a URL. This is done for two reasons. First, to inform clients about the relocation of resources, and second, to control the flow to Nginx. The two general-purpose methods used widely for rewriting URLs are the return directive and the rewrite directive. Of these, the rewrite directive is more powerful. Let's discuss why it is so, as well as how to rewrite the URLs.
Having a better understanding of NGINX will make it easier to follow this blog.
Separation of Reactive and Non-Reactive Code
One of the most important distinctions to keep in mind when working with Project Reactor or any other reactive streams implementation is the difference between assembly-time vs. subscription-time in code execution.
Regardless of your level of experience with reactive programming, odds are you’ve already encountered the famous:
Encryption Key Lifecycle Management: Tools and Best Practices
A data protection strategy is only as good as the encryption key security used. A robust cybersecurity management plan helps keep sensitive data protected and prevents data breaches. Implementing good practices and centralized tools helps effectively manage encryption key lifecycles, providing better regulatory compliance and overall security.
Encryption Key Lifecycle Management: Best Practices
Ensuring the security of cryptographic keys, tokens, and secrets involves different lifecycle management strategies and cybersecurity knowledge. Listed below are ten tips to keep your encryption keys safe and efficient.
Concurrency-Safe Execution Using Ballerina Isolation
The Ballerina language establishes a concurrent friendly approach to programming through light-weighted threads called strands. This is achieved by providing support for both preemptive and cooperative multitasking. When executing a concurrent program in a multi-threaded environment, the safe usage of shared resources is pivotal. This is obtained through a language concept called isolation. In this article, we will take an in-depth look at the concurrent safety support of Ballerina and see how HTTP services can be implemented to provide timely and accurate responses using isolation.
Race Condition in Concurrent Programming
In order to maintain the dynamic nature of a service, the following two aspects are considered during its implementation.
Nebula Graph: How to Implement Variable-Length Pattern Matching
At the very heart of openCypher, the MATCH clause allows you to specify simple query patterns to retrieve the relationships from a graph database. A variable-length pattern is commonly used to describe paths and it is Nebula Graph’s first try to get nGQL compatible with openCypher in the MATCH clause.
As can be seen from the previous articles of this series, an execution plan is composed of physical operators. Each operator is responsible for executing unique computational logic. To implement the MATCH clause, the operators such as GetNeighbors, GetVertices, Join, Project, Filter, and Loop, which have been introduced in the previous articles, are needed. Unlike the tree structure in a relational database, the execution process expressed by an execution plan in Nebula Graph is a cyclic graph. How to transform a variable-length pattern into a physical plan in Nebula Graph is the focus of the Planner. In this article, we will introduce how variable-length pattern matching is implemented in Nebula Graph.
Four Metrics Every Mobile Developer Should Care About
Slow apps frustrate users, which leads to bad reviews or customers that swipe left to competition. Unfortunately, seeing and solving performance issues can be a time-consuming struggle.
Most developers use profilers within IDEs like Android Studio or Xcode to hunt for bottlenecks and automated performance tests to catch performance regressions in their code during development. However, testing an application before it ships is not enough.
Auto_Explain: How to Log Slow Postgres Query Plans Automatically
Do you want to know why a PostgreSQL query is slow? Then EXPLAIN ANALYZE is a great starting point. But query plans can depend on other server activity, can take a while to run, and can change over time, so if you want to see the actual execution plans of your slowest queries, auto_explain is the tool you need. In this post, we’ll look into what it does, how to configure it, and how to use those logs to speed up your queries.
What Is Auto_Explain?
Auto_explain is a PostgreSQL extension that allows you to log the query plans for queries slower than a (configurable) threshold. This is incredibly useful for debugging slow queries, especially those that are only sometimes problematic. It is one of the contribution modules, so it can be installed and configured easily on regular PostgreSQL.
How to Generate an Execution Plan With Planner
Planner is an execution plan generator. It generates an execution plan based on the semantically valid AST that was validated by Validator and then passes the plan to Optimizer to generate an optimized execution plan. Finally, Executor will execute the optimized plan. An execution plan is composed of a series of nodes (PlanNode).
Structure of Source Files
Here is the structure of source files for Planner.
Understanding Performance Capabilities of Data Warehouses
Don't you really hate latency? Yeah, I hate it too.
Today, I want to talk about building applications on top of data warehouses. I want to discuss how to achieve low latency if your app is consuming data from BigQuery, Snowflake, Redshift, or any other cloud-based data warehouse.
Cool Designer Coffee Mugs
There is no form of drinkware quite like the coffee mug. Anybody who knows what a good cup of coffee is supposed to taste like also knows that the right coffee mug will make any kind of coffee taste that much better. Although coffee mugs seem like they are simple enough in their design and...
The post Cool Designer Coffee Mugs appeared first on .
Quick and Easy Client-side JavaScript Search With Lunr.js
Search is a must-have for any website or application. A simple search widget can allow users to comb through your entire blog. Or allow customers to browse your inventory. Building a custom photo gallery? Add a search box. Website search functionality is available from a variety of third-party vendors. Or you can take the DIY approach and build the entire backend to answer search API calls.
Lunr.js works on the client-side via JavaScript. Instead of sending calls to a backend, Lunr looks up search terms in an index built on the client-side itself. This avoids expensive back-and-forth network calls between the browser and your server. There are plenty of tutorials online to showcase Lunr’s website search functionality. But you can actually use Lunr.js to search any array of JavaScript objects.
How To Integrate Security Into the DevOps Toolchain
Traditional Security Conundrum in DevOps
DevOps tactics and tools are significantly transforming the way businesses innovate. However, amidst this transformation, IT decision-makers are cognizing that traditional ‘siloed’ security approaches are hampering organizations from realizing the full potential of DevOps. In fact, the conventional security methods and controls are perceived as inhibitors to speed, agility, and scalability offered by DevOps.
Baking Security into DevOps
In response, forward-thinking and fortune 500 companies have started integrating security practices and controls into each phase of the DevOps software development lifecycle, a methodology popularly known as DevSecOps. It integrates security practices and procedures into DevOps tools and underlying policies, making security an integral part of software development. As DevSecOps gathers steam, IT firms are more likely to blend vulnerability assessment, risk modeling, and security automation into DevOps processes and toolchains. As a result, it improves security and compliance maturity levels of the DevOps pipeline and toolchain, while enhancing product quality and delivery. How? DevSecOps enables seamless flow of application changes through DevOps pipelines, bestowing on the developers the authority and autonomy, without axing security or increasing risk.