Natural Profiler MashApp

MashZone is a browser-based application from Software AG which is used to visualize data on a graphical, interactive dashboard, a so-called MashApp. The Natural Profiler MashApps evaluate the Profiler event data and depict it in MashZone.

This Dokument covers the following topics:

Preparing to Use the MashApps

This section provides instructions for implementing the MashApps:

Downloading the MashApps

The Natural Profiler MashApps and related data are supplied as a Natural component in a zip file.

Beginn der AnweisungslisteTo download the MashApps zip file

  1. Log in to Software AG's Empower web site at https://empower.softwareag.com/ (password required).

  2. Go to Products & Documentation > Download Components.

    The Download Components section is displayed.

  3. From the Download Components section, select Natural Profiler MashApp.

  4. Download the NaturalProfiler_MashApp.zip file.

    In addition to the zip file, Empower also provides the Readme file Readme_ NaturalProfiler_MashApp.txt which contains the latest update information.

Unpacking the Zip File

You have to unpack the MashApp zip file in the appropriate MashZone directory which depends on the MashZone version installed at your site.

Beginn der AnweisungslisteTo unpack the MashApp zip file

  • Unpack the NaturalProfiler_MashApp.zip file in the appropriate user data directory of MashZone:

    • For MashZone Version 9.0 and above:

      installation-directory\server\bin\work\work_mashzone_server-type\mashzone_data

      where server-type indicates the type of the MashZone server: s, m or i. For example, work_mashzone_m for a medium type.

    • For MashZone versions below Version 9.0:

      installation-directory

      where installation-directory is the MashZone installation directory.

    After unpacking the zip file, the following subdirectories are available in the user data directory of MashZone:

    Directory Content
    importexport\Profiler_date MashApps for the Natural Profiler.

    date is the MashApp generation date.

    resources\Profiler Parent directory of Profiler resources.

    Contains the user-modified Overview.csv resource file.

    See also Editing the Overview.csv Resource File.

    resources\Profiler\Definition Resources used by the MashApp.

    Initially, this directory contains the resources which do not have to be edited.

    resources\Profiler\Data Profiler data directory (including subdirectories) in which the Profiler data files are stored by default.
    resources\Profiler_src Source directory for resources which have to be edited and copied into the resources\Profiler directory.

    See also Editing the Overview.csv Resource File.

    assets\colorschemes Color schemes.

    The color schemes for the Natural Profiler are named Profiler_*.xml.

Editing the Overview.csv Resource File

You can edit the Overview.csv resource file in the resources\Profiler_src directory to adapt the Natural Profiler MashApps to your requirements. The resource file is a CSV-formatted file with semicolon (;) separators which can be edited with any text editor.

The supplied Overview.csv file contains one line for the sample Profiler data in the Profiler_Sample.csv file in the resources\Profiler\Data directory. Add more lines for each Profiler CSV file you want to evaluate. For information on creating Profiler CSV files, see Preparing the Profiler Data. You can also add or delete lines in the Overview.csv file later, after you have copied it to the resources\Profiler directory (see Activating the MashApp).

In the columns of the Overview.csv, you can specify the following:

Column Description
csv File Specify the name of the Profiler consolidated data file.

If the data file resides in a subdirectory of resources\Profiler, specify the relative path and the file name. For example:

Specify Data\ProfilerTrace.csv if the ProfilerTrace.csv data file is contained in ...\resources\Profiler\Data.

Description Specify a descriptive name for the Profiler consolidated data file. The descriptions are used in the Input selection box of the Natural Profiler MashApps.

If you do not enter a value, the value of the csv File column is used in the Input selection box.

Enable If you enter Y in this column, the name or description of the Profiler consolidated data file is shown in the Input selection box. Otherwise, it is not shown.

Activating the MashApps

Prerequisites for activating the Natural Profiler MashApps are a Professional, Enterprise or Event license file and administrator rights.

Beginn der AnweisungslisteTo activate the MashApps

  1. Copy the resource file from resources\Profiler_src to resources\Profiler.

  2. Invoke MashZone.

  3. Go to the Administration page (see the corresponding tab at the top of the page) and then to the Import/Export/Delete page.

  4. Import the MashZone archive files (*.mzp) from the importexport\Profiler_date directory by using the Import function.

    The MashApps in the importexport\Profiler_date directory are named as follows:

    M_MashAppName version_revision_date-time.mzp

    where MashAppName is the name of the MashApp in MashZone which can be either of the following:

    MashAppName Purpose
    Natural Profiler Evaluate the Natural Profiler data and the Profiler properties and statistics of a monitored application.
    Natural Profiler Compare Compare two Natural Profiler data files.

Preparing the Profiler Data

graphics/profiler_mash_zone_mf.png

The graphic above illustrates the steps you have to perform before you can evaluate the Natural Profiler data in MashZone:

  • Profile the Natural mainframe batch application with the Natural Profiler data collection functions as described in the section Using the Profiler Utility in Batch Mode. The Profiler writes the event data to an .nprf Natural Profiler resource file.

  • Consolidate the event data using the Profiler utility CONSOLIDATE function. The consolidated data is written to an .nprc Natural Profiler resource consolidated file.

  • Alternatively, you can specify CONSOLIDATE=ON with the Profiler utility INIT function when you profile the Natural mainframe batch application. In this case, the Profiler writes the event data directly to an .nprc Natural Profiler resource file.

  • Write the consolidated event data with the Profiler utility MASHZONE function in CSV (comma-separated values) format to Work File 7.

  • Export the data from Work File 7 with any tool (such as FTP) to the Profiler data directory (see Unpacking the Zip File). Use .csv as the file extension.

  • Enter a reference to the new file in the Overview.csv file in the resources\Profiler directory.

If you start MashZone, you will find the description of the new file in the Input selection box. If you select the line with the description, the Natural Profiler MashApps read the event data from the corresponding CSV file.

If you already started the Natural Profiler MashApp earlier, MashZone may not immediately detect the new entry in the Overview.csv file. In this case, start any other MashApp, and then restart the Natural Profiler MashApp to clear the internal MashZone buffer.

Opening the MashApps

After you have specified all required information as described in the previous sections, you can proceed as follows:

  1. Invoke MashZone.

  2. Open the Natural Profiler MashApp or the Natural Profiler Compare MashApp.

    The Natural Profiler MashApp offers two tabbed pages for analyzing the Profiler event data and viewing the Profiler properties and statistics:

    graphics/profiler_mash_app_tabs.png

    The Evaluation page provides the Profiler event data evaluation.

    The Properties page lists the Profiler properties and the statistics of the monitored application.

    The Natural Profiler Compare MashApp offers two tabbed pages for comparing the Profiler event data and the Profiler properties and statistics:

    graphics/profiler_mash_app_compare.png

    The Compare page compares the Profiler event data of two monitored applications.

    The Properties page lists the Profiler properties and the statistics of the two monitored applications.

The pages are described in the following section.

Evaluation Page

The Evaluation page (Natural Profiler MashApp) looks similar to the example below:

graphics/profiler_mash_app_description.png

The Evaluation page is organized in the following sections:

  • The header at the top of the page with Input and KPI selection fields, filters and totals;

  • The selection boxes for the distribution criteria and corresponding distribution pie charts;

  • The event data table at the bottom of the page with the consolidated event data.

This section covers the following topics:

Evaluation Header

The header contains the following elements (from left to right and top to bottom):

  • The name of the MashApp.

  • The path and name of the Profiler data file currently selected.

  • The Input selection box which is used to select the Profiler data file. The file names listed for selection are taken from the Description column in the Overview.csv file. See Editing the Overview.csv Resource File. The selected file is used for both pages of the Natural Profiler MashApp.

  • The Evaluate selection box which is used to select the KPI you want to evaluate in the pie charts. The following KPIs are available:

    CPU Time
    Elapsed Time
    Adabas Command Time
    Hit Count

    The CPU time is evaluated by default. All time values are expressed in milliseconds.

  • The Event selection box is used to filter the event type you want to evaluate. The event types available for selection depend on the event types collected with the Natural Profiler. The pie charts, the event data table and the totals reflect only the data returned for the selected event types. By default, all event types are evaluated.

    Filtering specific event types is especially useful, for example, to evaluate the hit count of events that seldom occur such as error events.

  • The Monitor Pause Events selection box is used to filter Monitor Pause events. The filter is valid for the pie charts, the event data table and the totals. By default, the evaluations do not reflect Monitor Pause events. If you include Monitor Pause events, you can see how often monitoring paused, and how long and why it paused.

  • The Program Level “0” selection box is used to filter events which are executed at Program Level 0. These events usually relate to the Natural administration rather than the application execution. The filter is valid for the pie charts, the event data table and the totals. By default, the evaluations do not reflect the events at the program level 0.

  • The I/O and Client Times selection box is used to filter the I/O time (IB event) and the Natural RPC client time (RW event). These times mainly measure the user reaction (how long it took to press ENTER), especially when the elapsed time for an interactive application is evaluated. They are less relevant for the application performance. The filter is valid for the pie charts, the event data table and the totals. By default, the evaluations reflect the I/O and client times.

  • Summarized totals for the CPU time, the elapsed time, the Adabas time and the hit count according to the values that are currently selected in the header and in the pie charts.

Distribution Pie Charts

The Evaluation page contains four pie charts. Each pie chart shows the distribution of the KPI (selected in the Evaluate selection box) for the criterion selected in the box directly above the pie chart (see the example in Evaluating Distribution Pie Charts).

This section covers the following topics:

Criteria for All Event Types

The following criteria are available for all event types:

Consumer

The consumer combines one or more event types into a new criterion. The new criterion depends on the process that consumed the CPU or elapsed time given with the event data. For example, the time returned for a Before Database Call (DB) event is consumed by the database (and therefore belongs to the Database consumer), whereas the time returned for an After Database Call (DA) event is consumed by the Natural application (and therefore belongs to the Natural consumer).

A consumer evaluation is not relevant for an Adabas time or hit count analysis.

The following consumers are provided:

Consumer Event Type Description
Administration PL, PT The time Natural used to load and release Natural objects.

On the mainframe, the loading of Natural objects from the Natural system file is charged to the Database consumer (DB event against FNAT or FUSER system file).

On UNIX and Windows, the entire operation is charged to the Administration consumer.

Database DB The time consumed for database calls.

For the CPU time, it is the time spent in the Natural region.

External CB The time spent for external (non-Natural) program calls.
I/O IB The time spent for I/Os.

When you analyze the elapsed time of an interactive application, this section shows the user response time.

This section is only displayed if I/O and Client Times is included in the selection box in the page header.

Pause MP The time for which the monitor paused.

This section is only displayed if Monitor Pause Events is included in the selection box in the page header.

RPC Client RW The time spent on the Natural RPC client side.

When you analyze the elapsed time of an interactive RPC application, this section shows the user’s response time.

This section is only displayed if I/O and Client Times is included in the selection box in the page header.

RPC Server RI, RO The time consumed by the Natural RPC server layer.
Session SI, ST The time required to initialize the Natural session.
Natural CA, DA, E, IA, NS, PR, PS, RS, U The time Natural spent executing the program code.
Event

The type of the event to be evaluated. All event types are listed in Events and Data Collected in the section Using the Profiler Utility in Batch Mode.

For technical reasons, a Program Resume (PR) event uses the same timestamp as the Program Termination (PT) event that immediately precedes the PR event. Therefore, the PT event generally shows a CPU time and elapsed time of zero (0).

Group

The group ID for Natural RPC applications running under Natural Security.

Level

The level at which the profiled program executes.

Library

The Natural library that contains the profiled program.

Line

The source line in which the Natural statement executed by the profiled program is coded.

Line100

Source lines with similar line numbers (rounded down to the next multiple of 100).

Program

The name of the profiled program.

Statement

The Natural statement (for example, EXAMINE) executed in the profiled program.

User

The user ID for Natural RPC applications running under Natural Security.

Criteria for Specific Event Types Only

The following criteria are only available for specific event types. If you select an event-specific criterion, the pie chart will only reflect the data of the related events.

Client User

The Natural RPC client user ID type for RI, RO and RW events.

Command

The Adabas command for DB and DA events.

File

The database ID and file number of the Natural system file for PS and PT events.
The database ID and file number of the Adabas file accessed for DB and DA events.

Return Code

The termination return code for ST events.
The database response and subcode for DA events.
The subprogram response code for CA events.
The error number for E events.
The Natural RPC return code for RI, RO and RW events.

Target Program

The session backend program name for ST events.
The target program name for PL events.
The name of the called subprogram for CB and CA events.
The error handling program name for E events.
The Natural RPC subprogram name for RS events.

Type

The program type for PS and PT events.
The monitor pause reason for MP events.
The user event subtype for U events.
The return code indicator (system or user) for ST events.

Evaluating Distribution Pie Charts

This section describes how you can evaluate distribution pie charts.

  • A distribution pie chart shows the distribution for the criterion currently selected in the selection box directly above the pie chart. In the following example, Statement has been selected as the criterion for evaluating the CPU time:

    graphics/profiler_pie_chart.png

    The pie chart shows the distribution of the CPU time for the used Natural statements. It indicates that the Examine statement consumed the most CPU time (23.1 ms / 44.9 percent).

  • If you click on a segment in the pie chart, all following pie charts, the event data table and the totals use the selected value as the filter criterion. In the example below, the Examine statement in the left pie chart has been selected:

    graphics/profiler_mash_evaluation_examine.png

    The right pie chart above displays only those two lines in which an Examine statement is executed. The event data table at the bottom of the page and the totals in the page header also reflect the data for the Examine statement only.

  • To remove a selection, click on the background of a pie chart.

  • If you move the cursor to the upper right corner of a pie chart, a drop down list provides the option to save the pie chart as a picture or to display and save the related data. For the display, a window opens with a table containing the data monitored for the Natural statements:

    graphics/profiler_statement_statistics.png

    In the example above, the table lists the values of the left pie chart in the previous graphic. The KPI column lists the CPU time and the KPI3 column the corresponding Natural statement.

    You can save the table data as a CSV (comma-separated values) formatted file.

Event Data Table

The event data table at the bottom of the Evaluation page lists the consolidated Profiler event data according to the values currently selected in the page header and the pie charts. If you click on the table header of a column, the data is sorted by that column.

In the following example, the event data table is sorted by the CPU time (descending):

graphics/profiler_event_data_table.png

Compare Page

The Compare page (Natural Profiler Compare MashApp) compares the Profiler event data of two monitored applications as shown in the following example:

graphics/profiler_mash_app_compare_page.png

The Compare page is organized in the following sections:

  • The header at the top of the page with Input and KPI selection fields, filters and totals.

  • The column chart comparing the values of the two monitored applications:

    Values for the first application are shown in the left (green) column, values for the second application are shown in the right (yellow) column.

This section covers the following topics:

Compare Header

The Compare header contains the following elements (from left to right and top to bottom):

  • The name of the MashApp.

  • The paths and names of the two Profiler data files to be compared.

  • The Input 1 and Input 2 selection boxes with the Profiler data files selected for comparison. The file names listed for selection are taken from the Description column in the Overview.csv file (see Editing the Overview.csv Resource File). The selected files are used for both pages of the Natural Profiler Compare MashApp.

  • Summarized totals for the CPU time, the elapsed time, the Adabas time and the hit count according to the values for both applications listed in the header and column chart.

  • The Evaluate selection box with the KPI to evaluate in the column chart (see Evaluation Header).

  • The Event selection box with the event type to evaluate for (see Evaluation Header).

  • The Criterion selection box with the filter criterion to use for the KPI distribution. The criteria available for selection correspond to the criteria for the distribution pie charts on the Evaluation page (see Evaluating Distribution Pie Charts.

  • The Monitor Pause Events selection box with the filter criterion to use for Monitor Pause events (see Evaluation Header).

  • The Program Level "0" selection box with the filter criterion to use for events at the program level 0 (see Evaluation Header).

  • The I/O and Client Times selection box with the filter criterion to use for I/O time (IB event) and Natural RPC client time (RW event) events; see Evaluation Header.

  • The Pre-Selection values with restrictions for the column chart values to a specific criterion instance, for example to a specific library.

Compare Column Chart

The Compare column chart compares the values of the KPI (selected in the Evaluate selection box) for the criterion specified in the Criterion selection box for both profiled applications.

In the example of a Compare page shown earlier, the CPU time (Evaluate selection box) of each program (Criterion selection box) executed by Numeric Operations MF (Input 1) is compared with the corresponding time of Numeric Operations LUW (Input 2). Additionally, a pre-selection has been specified so that only values from the library PRFDEMO are considered. The green columns show the CPU times of Numeric Operations MF, the yellow columns the CPU times of Numeric Operations LUW.

Properties Page

The Properties page lists the Profiler properties and the statistics of the monitored application as shown in the following example:

graphics/profiler_mash_app_properties.png

The Properties page of the Natural Profiler Compare MashApp lists the properties and statistics of both Profiler data files selected for comparison.

The Properties page is organized in the following sections:

  • The properties header at the top of the page with Input and Category selection fields and the property description;

  • The properties table with the properties and statistics.

This section covers the following topics:

Properties Header

The header contains the following elements (from left to right and top to bottom):

  • The name of the MashApp.

  • The path and name of the Profiler data file currently selected.

  • The Input selection box is used to select the Profiler data file. The names listed for selection are taken from the Description column in the Overview.csv file. See Editing the Overview.csv Resource File. The selected file is used for both pages of the Natural Profiler MashApp.

  • The Category selection box is used to select a category (listed alphabetically). The selection box only offers the categories for which at least one associated property is found in the Profiler data file.

    If you select a category, the table shows the properties of the selected category only. By default, all categories are displayed. The following categories are available:

    Category Description
    Data Consolidation Statistics of the data consolidation such as the consolidation factor
    Data Processing Statistics of the data processing, data compression and data transfer such as the number of events and the compression rate
    Event Type Statistics Statistics of the event types such as the number of Program Load events
    General Info Information related to the environment and the Natural Profiler such as the internal Profiler version
    Monitor Pause Statistics Statistics of Monitor Pause events such as the number of Profiler data pool full situations
    Monitor Session Statistics of the Profiler monitor session such as the monitor elapsed time
    Profiler Resource File Information related to the Profiler resource file such as the resource name and library
    Trace Session Statistics of the Profiler trace session including the application execution such as the CPU time of the total session

  • The Property description. If you click on a line in the properties table, the name of the corresponding property and a detailed description of it are displayed in the page header.

Properties Table

The properties table lists all collected Profiler properties and application statistics. If you click on an entry in the table header of a column, the entire table is sorted by this column. Each color in the second column corresponds to one category.

All Profiler categories and properties are described in detail in the section Profiler Statistics.

Use Cases

This section describes the following use cases:

Application Performance Analysis

By default, the Natural Profiler MashApp is set up to create CPU time performance analyses of libraries, programs, statements and source lines.

Each pie chart in the example below shows the distribution of the CPU time for each criterion selected:

graphics/profiler_appl_perf_analysis1.png

You can immediately see which library, program, statement or line has consumed how much of the CPU time.

The example above uses the following selections:

Evaluate: CPU Time
Event: All events
Criteria: Library, Program, Statement, Line

A large application, such as the example above, references many program lines, thus making it difficult to analyze the corresponding pie chart.

If you click on a segment in a pie chart, the corresponding value of that segment is used as a filter and the amount of data which is displayed in the following pie charts is reduced accordingly. In the example above, a click on the segment with the SYSEDMD library in the leftmost pie chart would change the contents of the other three pie charts and only show the programs, statements and lines executed in the SYSEDMD library.

The following example refers to the previous one and assumes that in addition to the SYSEDMD library, the program DISADA2, the Callnat statement and the line 3564 are selected in the rightmost chart:

graphics/profiler_app_perf_analysis2.png

The event data table and the total in the page header now only refer to Line 3564 where the program executes the CALLNAT statement. The CALLNAT statement caused the event types (NS, PL and PR), each executing 45 times which results in a total Hit Count of 135 events.

Combined Line Numbers

The Line100 criterion is another approach to reduce the number of entries in the line number chart. It replaces the lines by the previous multiples of 100, thus, combining lines with similar line numbers in one segment of the pie chart.

The example below assumes that you want to find out which part of the program OP3DISC consumed the most CPU time. Therefore, you select OP3DISC in the Program chart so that all other charts only display the data for this program:

graphics/profiler_line.png

The Line chart clearly indicates that the statement in the segment of line 4630 uses 19.9 percent of the program’s CPU time. However, all other segments are rather small and it is difficult to tell them apart.

The Line100 chart shows that more than half of the time was consumed by the statements in the lines ranging from 4600 through 4690. Additionally, considering the statements in the lines ranging from 4500 through 4590, this part of the program even consumes 70 percent of the entire execution time. Thus, this program is most busy with the statements in these lines.

The example above uses the following selections:

Evaluate: CPU Time
Event: All events
Criteria: Program, Line, Line100

Consumer

The Consumer analysis gives a quick overview of the processes that consumed the most CPU time such as external programs, database calls, I/Os, administration tasks or program instructions. For example:

graphics/profiler_consumer.png

In the example above (Natural for UNIX, without statement events), 45 % of the CPU time was consumed by administration tasks. A potential reason for this can be the usage of small subprograms which solely call other tiny subprograms. This keeps Natural busy with administration tasks (program load with buffer pool management and program termination), while the time used for executing the code itself is relatively short.

The example above uses the following selections:

Evaluate: CPU Time
Event: All events
Criteria: Consumer, Event

Natural RPC Server Evaluation

When analyzing the elapsed time of an interactive application, waiting for a user response usually takes the most time. For a Natural RPC application, this time is monitored with the RPC Wait for Client (RW) event or the RPC Client consumer.

In the example below, the Natural RPC client consumes nearly all of the elapsed time:

graphics/profiler_rpc_client_in.png

The example above uses the following selections:

Evaluate: Elapsed Time
Event: All events
I/O and Client Times: Include
Criteria: Consumer, Program, Line

The MashApp offers a selection field to exclude the client time. If you exclude I/O and Client Times, all individual processes performed in the server application are shown similar to the example below:

graphics/profiler_rpc_client_out.png

The example above uses the following selections:

Evaluate: Elapsed Time
Event: All events
I/O and Client Times: Exclude
Criteria: Consumer, Program, Line

Natural RPC Server Statistics

You can obtain statistics on remote procedure calls by evaluating the hit count.

Example of a Natural RPC Client User Evaluation

The following example shows which user issued Natural RPC requests and how often:

graphics/profiler_rpc_client_user.png

In the example above, the user PRF issued 12 Natural RPC requests.

The example uses the following selections:

Evaluate: Hit Count
Event: Inbound RPC
Criterion: Client User
Example of a Natural RPC Target Program Evaluation

The following example displays which target program was called on the server and how often:

graphics/profiler_rpc_target.png

In the example above, 13 Natural RPC requests were issued for the server program BENCH-C.

The example uses the following selections:

Evaluate: Hit Count
Event: Start of RPC Request Execution
Criterion: Target Program

In both examples shown above, single event types are used for the event selection so not to mix the data with other events. For example, if All events is selected, the target programs of external program calls (CA events) are also displayed in the chart.

Adabas Command Time Analysis

When the Natural application issues an Adabas command, the database returns the elapsed time the Adabas nucleus required to process the command.

The example below analyzes the distribution of the Adabas command time for the accessed files and for the used Adabas commands. The chart also shows the programs and Natural statements that consumed the Adabas command time.

graphics/profiler_adabas.png

The most Adabas command time was consumed by calls against the file 1114 of the database 76 and by the Adabas commands S1 (find record) and L3 (read logical sequential record).

If you could click on a segment in the pie chart below File, you would see the commands issued against the selected file and how much time they consumed. Since the segment of the program NOMSTCS is selected in the third pie chart, the fourth pie chart only shows the Adabas command time used by the statements in NOMSTCS.

The example uses the following selections:

Evaluate: Adabas Command Time
Event: All events
Criteria: File, Command, Program, Statement

Adabas Statistics

You can obtain statistics on Adabas requests by evaluating the hit count.

The following example shows which files have been accessed, which commands have been issued, which Adabas response codes have occurred and which Natural statements have issued Adabas requests and how often:

graphics/profiler_adabas_count.png

The most Adabas requests were issued against the file 2430 of database 10 and the most frequently Adabas command used was L3 (read logical sequential record). Most calls were successful (Adabas response 0) but 86 calls received an Adabas response 245 with subcode 2. The fourth pie chart shows that READ statements issued 367 Adabas calls.

The example uses the following selections:

Evaluate: Hit Count
Event: After Database Call
Criteria: File, Command, Return Code, Statement

Application Statistics

The following Profiler MashApp examples may answer common statistics questions about monitored Natural applications.

How often were Natural objects started?

Use the following selections to find out:

Evaluate: Hit Count
Event: Program Start
Criterion: Program

graphics/profiler_program_start.png

In the example above, the program NAT00009 started 4,994 times.

How many statements were executed in the monitored programs?

Use the following selections to find out:

Evaluate: Hit Count
Event: Natural Statement
Criterion: Program

graphics/profiler_statement.png

In the example above, the program NAT41004 executed 28,673 statement events.

Which objects were called by a selected program and how often?

Use the following selections to find out:

Evaluate: Hit Count
Event: Program Load
Criteria: Program, Target Program

graphics/profiler_program_load.png

In the example above, the right pie chart shows the Natural objects called by DISADA2. The Natural object NPR-NAME was called 89 times.

How often was a selected object called?

Use the following selections to find out:

Evaluate: Hit Count
Event: Program Load
Criteria: Target Program, Program

graphics/profiler_program_load_target.png

In the example above, the right pie chart shows the objects which called the program AOS-OP. AOS-OP was called 87 times by the program DISADA2 and 34 times by the program FILE-MF.

How many runtime errors occurred?

Use the following selections to find out:

Evaluate: Hit Count
Event: Runtime Error
Criteria: Return Code, Library, Line, Statement

graphics/profiler_errors.png

In the example above, the Hit Count in the page header indicates that three runtime errors occurred during application execution. The charts show which errors occurred, the library, program and line where they occurred, and the statements that caused the errors.