7 publicaciones etiquetados con "Table"

You already have the entity. You already have the repository. Now someone wants a screen where they can see the records, click a header to sort, narrow the list down, and move through thousands of rows without the page falling over.

That screen is a Spring Data JPA grid, and in a Spring Boot app built with webforJ you write it in Java. The repository you have becomes the grid's data source. Sorting, filtering, and paging go to the database as queries, so the grid only shows what the query returns.

The webforJ Table is a Java data grid for the browser. You define columns with method references, hand it a repository, and it gives you sorting, selection, pinned columns, cell renderers, and virtual scrolling. All of it is configured in Java, with no JavaScript grid library to wire up.

This guide builds an orders grid from an in-memory list, then switches the same table to lazy loading from a database or REST API. If you need a Java table component for web apps that handles large data sets, the second half is the part to read.

A Java CRUD web app in webforJ is one Spring Data repository and one view class. A Table backed by SpringDataRepository lists and sorts the entities, a BindingContext with Jakarta validation drives the create and edit form, and a ConfirmDialog guards the delete. The whole screen is Java, so there is no REST layer to write, no JavaScript to wire up, and no template language to learn.

This tutorial builds that screen for a Customer entity. By the end you have a list with sorting, search, and paging, a form that validates before it saves, and a delete that asks first. It's the shape of a Spring Boot CRUD UI you can reuse for any entity.

Your users know what they want from a table. They just don't think in dropdowns and price fields. They think "laptops under 1000 that are in stock," and the filter form makes them translate that into five separate controls.

Natural language search for a Java table lets them type that sentence instead. The safe way to build it keeps the model away from your data: it only turns the sentence into a small typed filter, and plain Java applies that filter to the table. This post builds the flow with Spring AI and a webforJ Table.

Someone on the team needs a screen where support can look up an account, fix a record, and see an audit trail. The data is already in your Java services, and the request is small. It still turns into a project once you add a second language, a build pipeline and an API layer just to draw a table.

If you want to build internal tools in Java, pick a framework that lets the backend team write the UI in the same language, in the same project, against the same services. That's what webforJ does, as a full-stack Java framework. A view is a Java class, a table reads from your repository, a form binds to your bean, and route annotations decide who gets in.

You have a database that has been running for years. The tables are in good shape, a few Java services already read them, and now someone wants a screen where people can browse the rows, search them and fix a value without opening a SQL client.

A Java web front end for a database needs four things: an entity mapped to the table, a repository, a grid, and a form. With webforJ, the full-stack Java framework, you write all of it in Java. Spring Data JPA reads the table, the SpringDataRepository adapter hands it to a webforJ Table, data binding drives the edit form, and route annotations lock the screen down. No separate front-end project, no REST layer in between.

Data is the lifeblood of business applications, and displaying it properly can make or break someone's experience using your app. In order to visualize data, most developers quickly turn to tables for displaying that data. Here's the problem: just throwing information into rows and columns doesn't always tell the story clearly enough.

When users glance at a table, the idea is that they immediately understand what matters. Is that price change good or bad? Which items need attention? What's trending up versus down? If your users have to pause and think, squint at numbers, or do mental math to understand their data, your interface isn't working hard enough for them. Perhaps your first instinct is to say that tables aren't the answer, but that isn't the case.

This is where renderers come in. In webforJ, cell renderers let you transform raw data into visual, instantly understandable information. Earlier this year, I built a mock cryptocurrency dashboard, which is a perfect example of an app that needs quick, understandable information at a glance, since crypto data is fast-moving, emotionally charged, and needs to be digested within seconds. Green numbers for gains, red for losses, formatted prices, inline charts—all rendered dynamically to tell the story your data is trying to communicate.

The fun part was using renderers to contain all of this information inside a tidy table, and in this post, we'll explore when and how to use these renderers to build tables that don't just display data, but actually communicate with your users.