- #Eclipse memory analyzer for mac os x how to
- #Eclipse memory analyzer for mac os x download
Change the selection criteria in SM21(e.g. time) to make sure that no log entry is shown on the screen.
#Eclipse memory analyzer for mac os x how to
We will show how to use the profile data analyzer to understand SM21’s logic and the performance of these two traces, including their difference. This blog will use two SM21 traces as examples to show the usage of the profile data analyzer. The main difference between these two SM21 traces is the data volume. We could get this file from OS level on the the dialog instance data folder( /usr/sap///data) or by SE30 following KBA 2881237. Profile data analyzer needs the ABAP trace without aggregation or aggregated by call stack which has more information than aggregation by call position. The file name is “AT*”. Collect a performance trace following KBA 2881237.It can be run on Windows, Linux, and macOS environments by double-clicking or command java -jar ProfileDataAnalyzer.jar. The profile data analyzer is a standalone jar file which needs Java 8 or higher.
#Eclipse memory analyzer for mac os x download
Download the profile data analyzer from here following KBA 2879724. To start the analysis, we only need 2 prerequisites – Donald Knuth, “Computer Programming as an Art (1974) Getting Started “The real problem is that programmers have spent far too much time worrying about efficiency in the wrong places and at the wrong times premature optimization is the root of all evil (or at least most of it) in programming.” In the following parts of this blog post, we will demonstrate how to use the profile data analyzer to understand both the performance bottleneck and the program logic for optimization. Sometimes it is helpful to compare two traces, for example, to understand why there is a performance downgrade after a support package upgrade. Find out the bottleneck in large and complex traces, especially when the time is averagely spent on different methods. Get an overall picture of the traced program, including the program logic and how the time is spent. The profile data analyzer is inspired by Brendan Gregg’s FlameGraphs. It provides additional graphic and interactive views comparing to SAT/SE30/ST12 to make the performance analysis easy, for example, in the following scenarios. The profile data analyzer supports both ABAP performance trace and SAP JVM Profiler performance trace (*.prf format) as documented in KBA 2879724, but we will focus on the analysis of ABAP performance trace in this blog post. 
In this blog post, we would like to introduce the “profile data analyzer”, a new standalone tool to analyze performance trace, including the idea behind it and the analysis steps.
0 kommentar(er)
