Java – Example Very Simple Player (JMF)

If you wonder what a JMF player is, you are in the right spot. We’ve noticed that many aspiring developers want to try it out but are unsure how it works. Hence, we decided to put together this guide to make things a tad easier for you.

package org.jmf.example;

import javax.swing.JDialog;
import javax.swing.JFrame;
import javax.swing.UIManager;
import javax.swing.UnsupportedLookAndFeelException;
import javax.swing.plaf.metal.MetalLookAndFeel;

public class ExampleJMF
public static void main(String[] args)

UIManager.setLookAndFeel(new MetalLookAndFeel());
catch(UnsupportedLookAndFeelException e)

new exampleFrame();

But before we dive into it, let’s answer this crucial question:

What is Java?

Java is a high-level language that programmers use to develop projects with few implementation dependencies.

Java has transformed the web in many ways. A vast majority of online tools that we use today were built on Java. That includes websites mobile apps and multimedia playback platforms. This programming language has come a long way. This year it will be 27 years since James Gosling developed it.

What is a Java Media Framework

JMF is an API that enables you to play, process, and capture media audio and video. Whether you want to transmit or receive live media broadcasts and conduct videoconferences, you can easily do it thanks to this API. All thanks to RTP “Real-time Transport Protocol of the JMF.

A JMF is a straightforward player that encapsulates your multimedia component and allows you to control your player. It also offers methods that enable you to acquire necessary resources and query the current state.

These are tools you will use to build page objects. For instance, if you want to scan the page and create a class.

Here is what Java Media Framework can do:

A multifunctional tool

A JMF comes in handy, especially if you’re looking for a tool that can scan a page and build a class. You can also use it to create prototype code and later build a robust application.


A lot of what you read about the topic of Observability mentions the benefits and potential of analyzing data, but little about how you collect it. This process is called “instrumentation” and broadly involves collecting events in infrastructure and code that include metrics, logs, and traces.

There are of course dozens of methods, frameworks, and tools to help you collect the events that are important to you, and this post begins a series looking at some of those. This post focuses on introductory concepts, setting up the dependencies needed, and generating some basic metrics. Later posts will take these concepts further.

An Introduction to Metrics Data

Different vendors and open source projects created their own ways to represent the event data they collect. While this remains true, there are increased efforts to create portable standards that everyone can use and add their features on top of but retain interoperability. The key project is OpenTelemetry from the Cloud Native Computing Foundation (CNCF). This blog series will use the OpenTelemetry specification and SDKs, but collect and export a variety of the formats it handles.

The Application Example

The example for this post is an ExpressJS application that serves API endpoints and exports Prometheus-compatible metrics. The tutorial starts by adding basic instrumentation and sending metrics to a Prometheus backend, then adds more, and adds the Chronosphere collector. You can find the full and final code on GitHub.

Install and Setup ExpressJS

ExpressJS provides a lot of boilerplate for creating a JavaScript application that serves HTTP endpoints, so it is a great starting point. Add it to a new project by following the install steps.

Capture media streams

Not only does the JMF allows you to play music, but you can use it to capture media content as well. And all this will happen while you process and capture it from a source to a destination.

You’ll then identify each media stream by its content format. From there, the JMF will present the content of that specific video stream. Each media stream will have at least one or more tracks that you can play.

Identify each media stream by location

You can either identify your media stream by using uniform resource locators (URLs) or media locators.

It doesn’t matter how you locate them. What matters most is that you wouldn’t struggle to identify each media stream.

Process Time Bases and Clocks

You can also play time-based media, or capture them at an accurate time. To achieve this, JMF requires time-bases and clocks. So, without a thorough understanding of time bases and clocks, you won’t be able to work with JMF.

While at it, use the below

1. Eliminate Unused Tables

Usually, when you remove or deactivate a plugin, all the database tables remain. This can be a good thing, as you retain all the user information, preferences, and other data. However, in most cases, you’re left with a cumbersome dataset that may bring your server’s performance down.

If you’re using WordPress, you can get rid of leftover tables by installing a plugin called Plugins Garbage Collector. It scans your database for any unused tables, and you can delete the ones that you know aren’t needed. A more hands-on approach is finding inactive tables using the UPDATE_TIME string.

2. Create an Execution Plan

The execution plan’s main goal is to display the various methods of retrieving data by containing the operation’s type and order when creating a query. If you’re not familiar with execution plans, here’s a video going through the basics.

The typical execution plan includes the following:

3. Use Proper Indexing

Indexing allows for faster access to the database and speeds up the queries. If you don’t use indexes at all, then processing the queries becomes painfully slow. Yet, over-indexing your database is also ineffective.

Unfortunately, there isn’t a golden rule for optimizing your database the right way. However, with some trial and error, your database benefits from an index system.

4. Avoid Coding Loops

A SQL query that runs more than once is inefficient and can cause unnecessary performance issues, which pile up quickly, especially with large datasets. In essence, moving a query outside a loop with the goal of it executing only once is the way to go.

There are a couple of nifty solutions to achieve this.

Use JOIN and GROUP BY to select data from multiple tables and have the database perform the counting with a single query. This is especially effective for multiple queries, including COUNT and MAX clauses.

5. Get Rid of Correlated Subqueries

Correlated subqueries are essentially coding loops. The subquery runs row-by-row until it satisfies the parent statement. This method of processing is useful when the outcome lies on multi-part answer validation.

You can avoid the correlated subqueries by using JOIN clauses, which makes the query run more efficient. Essentially, this method replaces WHERE and removes the necessity to execute the subquery for each row separa

6. Avoid * Queries

The ultimate goal of every query is to retrieve relevant data for maximum efficiency. However, it’s relatively common to use SELECT * clauses when creating a query resulting in unnecessary data. While it doesn’t play a massive role in the performance of small datasets, it can leave a significant dent in larger ones.

Selecting the data sparingly helps with optimizing the query speed and reduces resource usage.

A quick way to turn this issue around is using the LIMIT clause instead of SELECT *. This way, you limit the output of the query results unless you do need the entire dataset retrieved by the query.


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