How to install jpprofiler? Jpprofiler10 cracked version installation activation tutorial diagram (with registration code + download address)


Jpprofiler is a powerful and easy-to-use Java performance analysis tool, which can effectively view Java running memory usage, and has practical functions such as JDBC, JPA and NoSQL database analysis, memory leak analysis, etc. it can quickly help users in the process of using, separate out your operation errors and the existing errors, so that developers can understand their own shortcomings. To improve the success rate of java development, the software can also mark the required display classes, including memory allocation and information view, etc. How to install jpprofiler in this site? And what is the registration code of jpprofiler? Let’s introduce the steps of jpprofiler 10 installation, cracking and activation in detail, and attach the effective registration code. Welcome interested friends to learn about it.

Software name:
Jpprofiler v11.0.1 32-bit free Special Edition (with registration code + installation tutorial)
Software size:

Software name:
Jpprofiler v11.0.1 64 bit free Special Edition (with registration code + installation tutorial)
Software size:

Installation and cracking tutorial

1. Download and decompress the jpprofiler program on this site, double-click the “jpprofiler ﹣ windows-x64 ﹣ 10 ﹣ 1 ﹣ 1.exe” program, and wait for a moment after the following interface appears.


2. There are two installation options: the first is the default installation; the second is to select the installation location; the software is installed on Disk C by default. If you want to change the drive letter, you can click Customize installation; if you don’t want to change the location, you can click “next” between the following figures. The second option is selected by the editor.


3. Select “I accept the license agreement” and click “next” to proceed to the next item.


4. Click the “Browse” button to select the installation location, and then click “next”. In the second step, select the first item without the following interface.


5. Installing, wait a moment


6. The first item here is to fill in the registration code to register. The second item is not to register but to install. Here we choose the first option.


  7、Choose to register with the registration code and fill in the information.Just fill in the name and company options.


  Registration code (optional)











8. To integrate the JProfiler with the IDE, select the target IDE, click integrate, and then click next to proceed to the next step.


9. Check the update. Click “next” by default.


10. Click Finish to finish the installation wizard.


11. Here jpprofiler10 is installed and cracked successfully.


1. Click jpprofiler.exe

2. Execute the menu session integration wizards new server integration



Choose whether to test locally or remotely:


Select the script file that Tomcat runs:


Select the type of virtual machine:


Select monitoring port:

Just use the default


Choose whether the web container runs with the JProfiler:

By default


Configuration tips:

Read it carefully when “remote control”.


Then select start now to start operation.


Click “OK”, we can see another small window:


The window of JProfiler is:


So we can monitor!

New feature change release for JProfiler 10.1:

First, with script probes, you can define payload probes directly in the jpprofiler UI. They replace the old custom probes and are easier to configure. For each method intercept, you can configure a script to return the intercepted payload as a string.

The context menu of the call tree contains an operation that makes it easy to select the intercepting method for the script probe.

Each script probe adds a new view in the “Jee & probes” section, which contains the payload hotspot, default telemetry and probe event views.

A cradle plug-in has been added. The gradle plug-in is loaded from the gradle plug-in portal, but does not include the jpprofiler distribution. To use any jpprofiler gradle task, use start build script

Plug in {ID 'com. Jpprofiler' version 'XYZ'} jpprofiler {installdir = file ('/ path / to / jpprofiler / home')}

Using analysis tasks and preconfigured sessions with triggers, you can automate analysis sessions during the build process:

Task running (type: com. Jpprofiler. Gradle. Javaprofile) {main ='com. Mycorp. Mymainclass' classpath sourcesets. Main. Runtimeclasspath offline = true sessionid = 80 config file = file ('config / config. XML ')}

There are also command-line export and command-line comparison tasks, as well as using heap dumps to pre analyze snapshots.

2. The merge reference view in the stack has been re implemented and is now more available and useful. The view now shows the reference holder and reference object on each node, and makes the reference relationship clearer.

In addition, references can be grouped by class rather than by field. This is the new default mode for merging reference views. Many non-standard collection types that are not directly supported by the compact reference types in jpprofiler are automatically collapsed in this way.

On each node in the merged incoming reference view, you can select the object in the current object set that is referenced in this way or the reference holder of a specific node.

3. A merged master reference view has been added to the heap walker. Unlike the incoming references of a merge, the merged control references show which references must be eliminated to make some or all of the objects in the current object set eligible for garbage collection.

In the case of multiple independent GC roots, some or all objects in the current object set may not be referenced by a dominant reference, so the view may be empty. The merged master reference uses the same data as the largest object view, so the reference can be passed without a direct reference between the parent and child nodes.

The merged master reference view can display references to GC roots for the current object group, and vice versa. Depending on whether the reference you want to eliminate closes the object in the current object set or near the GC root, one or another mode is more convenient.

In the stack, the class and class loader groups in the max object view have been added. If you have many of the largest objects in the same class, it’s useful to switch to class grouping for better photos.

If class loaders are an important aspect of your investigation, then class loader grouping will help you find out where the classes of the largest objects come from.

IV. the asynchronous drive in mongodb now supports. In mongodb probes, asynchronous execution of code is tied to the stack trace that triggers the database operation. Whether to use a synchronous or asynchronous driver is indicated by the first node below the hotspot or the first node in the stack trace in the event view.

V. a telemetry overview of the detector has been added, combining all telemetry data of the probe. Just like the standard VM telemetry overview, you can click on the telemetry name to display the full view.

6. The quick search in the node details dialog box has been implemented. The node details dialog is an important tool for detecting load strings that can be very long, such as SQL statements in JDBC views. As you move the mouse over the text area, quick searches and copying all text to the clipboard become visible.

7. Jpprofiler 9 already supports Java 9 analysis, but the jpprofiler UI and all command-line tools can now run on Java 9. This is especially important for the Linux desktop that the jpprofiler UI can now use with the new hidpi support in Java 9.

Jpprofiler uses a lot of scripts entered directly in jpprofiler. Now you can choose Java 9 + JRE to compile these scripts.

In addition, starting with this release, you can profile Java 10 using all the features supported by jpprofiler.