This screen cast shows how to use the call tree analyses to analyze both the cumulated outgoing calls of all top-level invocations of a selected method as well as to calculate the back traces of all its invocations. The results of the analyses are compared with the call graph that shows a combined view of incoming and outgoing calls.
This screen cast shows how to use the “Collapse recursions” call tree analysis to better understand recursive call trees. Recursive calls are stitched back to the topmost call of a method. Recursive call counts, merged stack counts as well as moved parts of the call tree are marked in the analysis view.
JProfiler has built-in SSH tunneling for direct and multi-hop SSH connections. This is useful for situations where you do not have a direct network connection to the machine where the profiled JVM is running. The screen cast shows how to configure the SSH tunnel and prepare the remote Java process for profiling.
This screen cast shows how to detect JDBC connection leaks and find out where they’re coming from. JDBC connection leak analysis is integrated into JProfiler’s JDBC probe and has its own view. If a connection leak is detected, the stack trace and other information will help you to pinpoint the origin of the leak.
This screen cast shows how to quickly add new telemetries to JProfiler. MBean telemetries draw their data from numeric attributes of MBeans that are published in the profiled JVM. Script telemetries are built with a script that can call static methods in the profiled code to return a value of type long. Telemetries can have multiple data lines and are persistent for the profiled session.
JProfiler has an MBean browser that shows you MBean attributes and operations. Many frameworks and libraries publish statistics and expose configuration interfaces via JMX. With JProfiler, no configuration of JMX connectors is required, the browser just works out of the box and is very easy to use.
This screen cast shows how to split selected methods in the call tree by their parameter values. Directly in the call tree, you can select methods and set up scripts whose return values are used for grouping. The splitting nodes in the call tree provide insight into the distribution of your parameter values and give you the possibility to analyze the recorded method calls separately for special cases.
This screen cast shows how JProfiler can split HTTP requests by the return values of scripts into multiple levels. This functionality allows you to both get a better overview as well as a more fine-grained analysis that can be adapted to your particular problem-related use cases. All the information in the HttpServletRequest object can be used for that purpose. In the screen cast, splitting by different user names is demonstrated.
This screen cast shows how to split your Java call tree for different JavaScript XHR calls. By installing the JProfiler Chrome plugin, a locally running JProfiler GUI will be notified of XHR calls in the browser and show an event description and a stack trace without further configuration. In this way, you can identify the sources of your CPU load beyond the granularity of your URLs and analyze the call tree in isolation for specific browser events.
This screen cast shows “Remote request tracking” in JProfiler. It makes it possible to profile business transactions that span multiple JVMs. Here, a web service call to another JVM is shown and profiled in isolation of other requests that are handled by the server. In addition, JProfiler supports remote request tracking for RMI and remote EJB calls.