The next part will follow shortly, and will discuss the flexfield datamodel.

http://www.stijf.com/joomla/index.php/flexfield-articles/49-flexfields-and-flexfield-structures.html

It is the first part of a multi-part article. This part explains Key Flexfields in eBS. The next parts will discuss Descriptive Flexfields, the datamodel and special features. 

At the flexfields presentation at UKOUG, I promised an update on the PLSQL validation.

It turns out, that the only problem was a missing " at the end of the function. Here is the code for the function: 

FND PLSQL " declare

v_value varchar2(10) := :!value ;

v_num number;

begin

  v_num:=to_number(v_value);

  if mod(v_num,2)!=0 then

     fnd_message.raise_error;

  end if;

exception

   when others then

     fnd_message.set_name('FND','FND_GENERIC_MESSAGE');

     fnd_message.set_token('MESSAGE','This is not a valid number');

     fnd_message.raise_error;

end; "

So, use only the validate event:

And the parameter will validate correctly:

Good luck on your own experiments!

A long vacation, and testing different CMS's for the website account for the lost time. So I decided to give Joomla a try. I just finished installing the components that I want to use. And I wrote a short article, to see how it goes.

I'll be transferring the articles from this website to the new one in the days to come. 

For now, take a look at the new website: http://www.stijf.com/joomla

The article that I wrote is about adding a column to OA-Framework without using jDeveloper to change the VO. I describe how to use a descriptive flexfield to add a checkbox to the framework page.

You can read the article here: here.

Even though the article is not yet finished, I thought the part about ‘SPECIAL’ and ‘PAIR’ validation types might be interesting enough. Many people seem to think they can only use the seeded validation sets. However, you can also create your own validation sets. And their options are very powerful. So I wanted to publish this part of the article as a prelude to the full story.

Special Validation

Special validation is used to provide flexfield functionality for a single value. What that means is that you can have for example a concurrent program parameter that will be filled with a Key flexfield value, or a range of flexfield values.

Let’s go back to the Key Flexfield. We know that they are combinations of different segment values that are stored in a separate combination table.

When you want to submit a key-flexfield combination as a parameter to a concurrent program, you can code your own validation for the separate values. But you’ll be missing the nice functionality that gives you pop-ups, a validation over the resulting combination and if needed the ID-value for the flexfield combination.

That is possible with a ‘Special’ validation type.

The special validation uses a number of user exits to enter, validate and query keyflex segments. With special validation, you will be able to enter one or more segment values for a key flexfield. To enter these segment values, 3 user exits can be used. They are: ‘POPID’, ‘VALID’ and ‘LOADID’.

POPID is used to enable the user to enter the flexfield segment value. It is called when the users cursor enters the segment value field. With this user exit, you decide which segment values should be shown, and how they should be shown.

 VALID is called when the user exits the segment value, or confirms the chosen flexfield combination. It validates the entered value against the values existing in the key flexfield table.

LOADID is optional, and it can be used to choose which information will be returned as flexfield value. This can be the concatenated segments, or the id-value for the flexfield combination or segment values.

These 3 user exits can be assigned to 3 ‘events’. There are more events possible, but they are either not yet in use, or their use is not yet supported. So we will only use ‘Validate’, ‘Edit’ and ‘Load’.

Sounds complicated, so far? Don’t worry; this is not an easy validation. But we’ll build some examples to give you an idea. First we start with building a very easy special validation. This will be built on our Code Combination key flexfield. We’ll be using a concurrent program ‘Test Flex Validation’ program to see our different options.

This program is based on the following procedure:

CREATE OR REPLACE PROCEDURE XXX_TEST_FLEXFIELD_PARAMS

( errbuf   out varchar2

, retcode  out varchar2

, p_flex   in  varchar2

, p_flex2  in  varchar2 := ‘XXX’

, p_flex3  in  varchar2 := ‘XXX’

, p_flex4  in  varchar2 := ‘XXX’

, p_flex5  in  varchar2 := ‘XXX’

) IS

BEGIN

   FND_FILE.PUT_LINE(FND_FILE.OUTPUT,p_flex);

   FND_FILE.PUT_LINE(FND_FILE.OUTPUT,p_flex2);

   FND_FILE.PUT_LINE(FND_FILE.OUTPUT,p_flex3);

   FND_FILE.PUT_LINE(FND_FILE.OUTPUT,p_flex4);

   FND_FILE.PUT_LINE(FND_FILE.OUTPUT,p_flex5);

END;

This will only write the parameter value to the output of the request. To use flexfields as parameters for concurrent programs, we need to define a value set based on them.

We will start with the barest setup to enter a key-flexfield combination. For this article, we use the accounting flexfield, with code ‘GL#’  and id-num ‘101’.

In this case, we have the following definition:

So what does this mean?

The first box is for the edit event. This will be triggered when the user enters the cursor into the field with this value set.

FND POPID         This is the user exit to pop up a flexfield screen, and let the user enter the flexfield values.

CODE="GL#"     This is the flexfield code for the key flexfield that we will be using.

APPL_SHORT_NAME="SQLGL" The short name for the application the flexfield belongs too. Together with ‘Code’, this will identify the flexfield itself.

NUM="101"       The id-number for the flexfield structure. If you have only a single structure flexfield, it is optional. For flexfields enabled for multiple structures, you need to enter the id-number.

VALIDATE="PARTIAL"   Validate can be ‘None’, ‘Partial’ or ‘Full’. None means the combination is not validated. Partial means that the separate segments are validated, there is no validation if the combination exists. Full means that segments and combination will be checked, and if a new value is entered, this will be inserted into the key flexfield table.

SEG=":!VALUE"                This is the forms field that will be used to store the value of the segments.

The second box is for the ‘Validation’ event. This code will be called when the user navigates out of the field, or submits the entire combination.

Now when we set this value set as a parameter for our concurrent program, we can see how the validation works:

Now when we run the program, we get this pop-up:

We have all the functionality of the key flexfield. We can use the ‘Combinations’ button to search for existing combinations, and all separate segments will be validated, as will be the final combination.

When we submit a value to our program, it will show the concatenated segments as the value of our parameter:

Now let’s see some more features of this validation. For example, we’d like to have the value of the combination id. (CODE_COMBINATION_ID in our case, since we use the Accounting Flexfield).

To get that, we need to add the LOADID user exit:

The ‘Load’ event will get the combination-id from the flexfield table. This is only possible for the ‘VALIDATE=”FULL”, since it will validate the whole combination. Also we need to set the ID=”:!ID”. This will populate the :!ID column with the ID value of the combination.

Finally, I added the ‘DINSERT=”NO” ‘, because we don’t want to allow insertion of new code combinations from this value set. (And Validation=”FULL” by default inserts new combinations into the flexfield column).

Now when we run the concurrent request, we see that the parameter value is the code_combination_id instead of the concatenated segments:

With these user exits it is also possible to select just a number of segments, instead of the whole combination. For this we remove the ‘Load’ / ‘LOADID’ part again.

Then we add a ‘DISPLAY=”x” ‘ to the ‘Edit’ and ‘Validate’ user exits. The “display” parameter is defaulting to ‘ALL’. But you can also specify separate segments by their sequence number or names. In our case, we display the first 2 segments:

Now when we run the concurrent program, we get a pop-up for only the first 2 values:

A very nice feature (at least as far as I’m concerned) is the use of a where clause on the combination values. Consider the following ‘Enter’ code:

FND POPID

CODE="GL#"

NUM="101"

APPL_SHORT_NAME="SQLGL"

VALIDATE="FULL"

TITLE="Special Validation Key"

ID=":!ID"

SEG=":!VALUE"

DESC=":!MEANING"

WHERE="segment2 not like '1%' "

The “WHERE” clause prevents us from choosing combinations that have a segment2 starting with ‘1’. When we run our concurrent program with this, and choose the combinations:

There is no Dpt starting with 1.

When we add the “WHERE”-clause to the validation event too, it will prevent us from entering the values manually:

The last feature that we’ll look into is the use of a pl/sql validation through the special validation routines. By using the user-exit PLSQL, we can call an anonymous PL/SQL block in our ‘Validation’ event. I created a value set with the following function for the ‘Validation’ event:

FND PLSQL " declare

  v_value varchar2( 10 ) := :!value ;

  v_sum number;

  v_valid boolean;

begin

   v_sum:=0;

   for i in 1..length(v_value) loop

    v_sum :=v_sum+(length(v_value)+1-i)*substr(v_value,i,1);

  end loop;

  if mod(v_sum,11)=0 then

     v_valid := TRUE;

  else

     v_valid:=FALSE;

  end if;

  if not v_valid then

      fnd_message.set_name('FND','FND_GENERIC_MESSAGE' );

      fnd_message.set_token('MESSAGE','This is not a valid bank account');

      fnd_message.raise_error;

  end if;

END; "

This PL/SQL procedure validates a (Dutch) bank account number. If it does need pass the test, a message will be displayed. This gives you almost unlimited possibilities for validating entered data.

As you can see, it is only a ‘Validate’ event. Because we don’t need any special functionality for entering the data. We can limit the entry to numbers only on the ‘Validation Set’ main page.

Now when we use this value set for our concurrent program, we can only enter valid dutch bank accounts:

And

The list of parameters for the user exits is longer than this. So we won’t be going through all the possibilities. You can check the Developers Guide and the Flexfield guide for a complete listing of options. (Did you notice the flexfield title that I sneaked into the pop-up? Try and find the option for that!)

Please try the different options for yourself, and realize the possibilities of the special validation.

Pair Validation

Meanwhile, we’ll continue to the ‘Pair’ validation. The pair validation is very much like the ‘special’ validation. It uses the same kind of user exits, but this time, a range of segment values or combinations is selected.

Let’s first create a range of the account segment. Instead of using POPID and VALID, we use POPIDR and VALIDR. The R-version of the user-exits automatically create a range.

Of course we need 2 parameters to set the range. However, we need only one validation set.

I created the validation set ‘XXX_PAIR_VAL’. I entered only the edit and validate events:

The next step is to set the parameters for both the low and high value. Both parameters have the validation set ‘XXX_PAIR_VAL’.

Now when we run the program, we can enter a range. This includes validation that the high value is indeed higher or equal to the low value.

Of course the concurrent program will receive the values for 2 parameters.

When we use the full validation we can enter a range of the whole account combination. Note that we cannot use the FULL validation for pair-validation. Because that would mean the use of the combination-id from the flexfield table and based on the combination-id’s you cannot build a range.

So we can only use PARTIAL and NONE for the validation. For that same reason, I have not yet had a reason to use a LOAD event for PAIR validation. It is however allowed to use one.

I created a PAIR validation for the whole accounting range as follows:

When used in the concurrent program, it will indeed allow us to enter a range of all segments:

That completes the chapter on PAIR validation too.

In this article we will describe the infrastructure of Oracle eBusiness Suite (eBS). In its simplest form, eBS is a 3-tier application with a client tier, Application-tier and DB-tier.

Database-Tier

Let’s start with the DB-Tier. Surprisingly, the database tier has only very little eBS specific features.

Of course we need a database (instance) and therefore an ORACLE_HOME. But the database can either be a single-instance or a RAC-installation and all Oracle RDBMS features are transparently available for eBS.

The management of the RDBMS Installation is also independent of eBS.

DB-Tier filesystem

Let’s start with the filesystem on the DB-Tier. Of course there is an Oracle_home installation needed, for the RDBMS-Instance. This will be installed during installation of eBS. But also a fresh installed ORACLE_HOME can be used, with an eBS database.

In the ORACLE_HOME, an extra directory is added. The Appsutil directory. This directory contains the software and data needed for running Autoconfig and Rapidclone.

All other directories are at the discretion of the eBS DBA.

Oracle Instance

When we look at the instance to run eBS, we find a number of mandatory parameters for eBS. These are found in Metalink notes 216205.1 and 396009.1 (At the time of writing. Please verify these notes for yourself).

These parameters are recommended or mandatory based on testing by Oracle Corp. They will automatically be set by the eBS installer. But you should take note of them when you use a fresh installed ORACLE_HOME.

Then we finally come to the contents of the database.

The eBS Database

Let’s start with the schemas in the database. Oracle eBS creates a separate schema for every module. The schema is named as the short_name of the module, for example AP (Oracle Payables / Accounts Payable), AR (Oracle Receivables / Oracle Receivables).

There is a separate schema for the Application owner APPS.

The Application schemas contain the tables, indexes and sequences for the different applications. All objects in these schemas (except indexes, of course) have a synonym in the APPS Schema. In the APPS Schema we also find all PL/SQL objects, views and Materialized Views.

A major part of eBS is written in PL/SQL. All PL/SQL objects are also installed in the APPS Schema.

User sessions within eBS will usually run in the APPS Schema as well.

That brings us to an extra schema in the database: APPLSYSPUB. This schema has access to some of the eBS tables and packages, that allow it to validate eBS logins and start an APPS-session based on that login information. We will see the details of this later on.

Before release 11.5.2 every schema had its own tablespace. However, the number of modules for eBS (and with that the number of schemas) is ever increasing. So managing the database became more and more complex. In 11.5.2 Oracle introduced the Oracle Applications Tablespace Model (OATM). Within this model, the tablespaces in eBS are based on functionality, rather than schemas.

In this model, we see the following tablespaces:

APPS_TS_TX_DATA – Containing all transaction tables, Materialized Views and IOT’s

APPS_TS_TX_IDX – Containing all indexes for transaction tables

APPS_TS_SEED – Containing the tables and indexes with seeded data (as opposed to transaction data).

APPS_TS_INTERFACE – For Open Interface tables

APPS_TS_SUMMARY – Contains summary tables for several modules (AR, PA, BIM, etc)

APPS_TS_NOLOGGING – For tables and objects that are created with the NOLOGGING option

APPS_TS_ARCHIVE – Containing archive and history tables (and indexes)

APPS_TS_QUEUES – Containing the AQ (Advanced Queuing) objects

APPS_TS_MEDIA – Containing tables with LOB’s. For media objects or documents.

The Undo and Temp tablespaces are not part of the tablespace model.

Application Tier

Now it’s time to look at the Application Tier. In fact the Application Tier consists of 3 different services: Web service, Forms service and Concurrent Processing. In 11i installations, there is also an Administration service.

The Application Tier significantly changed from R11i to R12. We’ll discuss the 11i Apps Tier shortly, and then discuss the R12 tier in more detail.

The 11i infrastructure

Both the R11 and R12 infrastructure consist of a Web-service, a Forms Service and a Concurrent Processing part.

We will be discussing the different services here. The following picture shows all components and their communications. You might want to keep it for reference during this article.

R11i Web Service

For 11i, the web tier is built on Oracle iAS 9i. The iAS installation provides webservices (Apache HTTP/HTTPS), a Java Runtime Engine (JSERV) and a PL/SQL engine (modplsql).

The web service also acts a gateway for the Concurrent Request log and output files. And it is the first point of access when starting a forms session. (When using a socket forms connection, when using a forms servlet the web tier will host the forms process).

A detail from the picture above shows the iAS structure.

The core of iAS is the web server. This is the front-end for the client. Requests can also be forwarded to and from the forms server and the concurrent processing. We’ll see that in the next paragraphs.

Within the iAS Jserv and modplsql are plugins. They are the only components that communicate with the database. When they are called, they execute java (Jserv) or PL/SQL (modplsql) and return an html page. This page is then sent to the client through the HTTP service.

The Jserv delivers a Java Runtime Environment. In the Jserv, java servlets can be run. Also the JSP-files are executed in the Jserv. A JSP-file (Java Server Page) is a page with java code that returns an html-page (similar to the way scripting languages like PhP work). The java part is executed in Jserv, which returns the html to the webserver. The webserver redirects the html to the client.

Let’s take a closer look at the components and their executions:

Webserver

The webserver is based on the regular Apache 2 webserver. The configuration file is also equal to the Apache config file. The configuration is set in httpd.conf (or httpds.conf for SSL).

Instead of starting the webserver through $APACHE_HOME/bin/httpdctl, we start through $APACHE_HOME/apachectl. The default port number used for eBS 11i is 8000. This is part of port-pool 0. For different port-pools, the port number is increased. So for port-pool 1 the webserver runs on port 8001.

The root directory for the webserver is set to $OA_HTML, which is by default $COMMON_TOP/html. This directory contains all *.html files for eBS.

A number of virtual directories are set up within eBS.

JServ

As mentioned before, java code is executed by Jserv. Jserv is a java servlet engine. That means that it can run both servlets and jsp-files.

These servlets are mostly located in the $JAVA_TOP. The *.jsp files are located in the $OA_HTML directory.

One of the options of Jserv is to create a database connection to the rdbms database. This is done by a JDBC Thin Client connection.

Before we look at the configuration for Jserv, examine the following picture.

Within Jserv, we can define different java environments, called zones. These zones are configured with different servlets or java archives (jar-files). Each zone is configured with its own configuration file. Within the zone the startup parameters (initargs) for the servlet are defined.

On the other side of the picture, you see a group. All java processes within Jserv are grouped together. You must define at least one group. The default group is ‘OACoreGroup’. Within each group, we create one or more processes that will be mapped to our zones.

This mapping is done by mounting the zones and the groups to different logical directories. In the picture, a mountpoint is created: /oa_servlets/. It refers to the group ‘OACoreGroup’, which holds 3 java processes. And it is mapped to zone ‘root’, which includes the servlet ‘dummy’ with a set of startup parameters.

When iAS receives a call to the virtual directory /oa_servlets/ it will be recognized as a Jserv mount point and the request will be forwarded to Jserv. In this example Jserv has 3 java processes in the group for this mount point. And they will be able to run all the servlets in the zone.

Sounds complicated? Take a look at the following configurations:

Jserv.conf:

ApJServGroup OACoreGroup 3 1 /etc/oracle/iAS/Jserv/etc/jserv.properties

ApJServGroupMount /oa_servlets balance://OACoreGroup/root

Jserv.properties:

wrapper.bin=/opt/oracle/iAS/Apache/Apache/bin/java.sh

zones=root<host>

root<host>.properties = /etc/oracle/iAS/Jserv/etc/zone.properties

Zone.properties

servlet.Dummy.initArgs=message=I'm a dummy servlet

Within jserv.conf we define a group called OACoreGroup. This group is running 3 Java processes. And the definition of the group is in the jserv.properties file. The 1 indicates the weight for load-balancing with multiple groups.

Then we mount the zone ‘root’ to the group ‘OACoreGroup’. This mount point is linked to the virtual directory /oa_servlets/.

The virtual directory is used for redirection to the JServ. When a request is made to the virtual directory Jserv will be called. The part of the URL after the virtual directory is the path to the servlet. This path will be searched for in the $CLASSPATH.

When the java servlets need to connect to the database, they can build a connection using JDBC. The access information is stored in a *.dbc file in $FND_TOP/secure. The dbc-file is referred to in the parameters for the zone.

Modplsql

Let’s take a look at the modplsql module. This module is designed to run pl/sql procedures within the database. The connection is based on the wdbsvr.app file. This file contains the DAD (Database Access Descriptor), including the access data to the eBS database.

The module is also called through a virtual directory. For example http://<host>:<port>/pls/TESTDB/ dummy. /pls/ is the virtual directory that refers to modplsql. TESTDB is the name of the DAD and dummy is the name of a pl/sql procedure accessible for the db-user from the DAD.

That concludes the 9i iAS module for now.

Formsserver

Let’s take a look at the forms server.

Oracle forms can be set up in two ways, socket connection and servlet. The default is socket connection. With a socket connection, a separate forms server and dedicated forms processes are used. For the servlet connection, a java servlet is called within the iAS.

The formsserver itself is installed in the 8.0.9 ORACLE_HOME. Forms has a forms server, and one or more client processes. The forms server is started with f60svr. It will spawn a f60webmx process for every client session connecting.

On the server side, forms are run in the forms client processes. On the client side, they are run in a java applet. When the client clicks a forms based function in the Personal Home Page, it calls an URL that refers to the forms client executable in the 8.0.6 ORACLE_HOME.

This URL is taken from the profile option ‘ICX: Forms Launcher’, and the default value is like ‘http://<server>:<port>/dev60cgi/f60cgi’. The parameters referring to the function being clicked are added to this URL as parameters. (i.e. the name of the form to be started)

When this URL is called, the webserver will execute the executable f60cgi. This executable returns a HTML page to the client. This page is called the ‘Base HTML’ for this forms server. (by default this is $OA_HTML/US/appsbase.htm)

This HTML page calls the J-initiator plugin (or the native JVM when configured). It also includes the parameters to connect to the forms server and the name of the form to start.

The J-initiator will start an applet on the client, which connects to the forms listener process. The forms listener process then assigns a dedicated forms client process.

At this point the whole chain looks like this:

The configuration for the forms server is in the appsweb.cfg file in ($OA_HTML/bin). This file contains the basic coloring scheme for the forms server, the forms settings and the referral information to the J-Initiator plugin. The plugin on the client side is called through its class-id, which is also set in the appsweb.cfg.

Concurrent Managers

The last part of the application tier is the concurrent processing part. The concurrent managers are used to execute background and batch processes.

Different executables including host-command files, pl/sql procedures, Oracle Reports, SQL*Loader control files and Binary executables can be defined to be run as concurrent programs. Parameters are also optionally defined with the concurrent programs.

The executable files are defined separate from the concurrent programs. So an executable can be run as different programs with different parameters.

The programs are executed through ‘Requests’. A request is started as a concurrent program and the values of its parameters. It can be scheduled to start at a specific time, or in a specific schedule. The output of the program can be sent to a printer. It is also available through the application.

This picture shows the relation between programs, requests and managers.

The managers

We’ll take a closer look at the concurrent programs later. Let’s first look at the concurrent managers. There are concurrent managers and transaction managers. Also a number of control managers are defined.

We’ll start with the ‘Internal Manager’. This is the first manager to be started. Its purpose is to control the stopping and (re-)starting of the other managers. When Generic Service Management is enabled (default as of 11.5.7), it delegates to the ‘Service Managers’. On every node where concurrent processing is enabled, a ‘Service Manager’ is started. However, only one Internal Manager is running at any time.

The other concurrent managers are defined with a work shift that controls how many processes a concurrent manager should have at certain times. The work shifts consist of a time-range and a number of processes. The Service Managers (or Internal Manager) will start and stop processes according to these work shifts.

Another part of the setup of concurrent managers is their specialization rules. The specialization rules indicate which programs are valid for a concurrent manager, or are excluded for that manager. They work on an include/exclude principle. When programs are included for that manager, the manager can only run those programs. When programs are excluded, the manager can run any program except the excluded ones.

When a request (to run a program) is submitted from eBS, it will be placed in FND_CONCURRENT_REQUESTS with a status_code ‘I’ (The eBS forms have fewer statuses than the codes in the table). The manager processes will query this table for requests that they are eligible to run.

Once a manager process finds a request with status_code ‘I’, which it is eligible to run then it will put the request on its own queue. It will then run the executable with the defined parameters. The logfile and outputfile are written to the filesystem in $APPLCSF/$APPLLOG resp. $APPLCSF/$APPLOUT.

There are some special cases that need to be discussed. The first is the incompatibility. Concurrent Programs can be made incompatible with each other. That means that they cannot run at the same time. Once a program is started that is defined as incompatible with another, it will be automatically put on the queue for the ‘Conflict Resolution Manager’. This special manager will check if any incompatible program is running or ‘Pending’ with code ‘I’. If so, it will hold the request on its own queue. If no incompatible program is running or ‘Pending’, then it will set the status of the request to ‘Pending’.

Another special case are the ‘Transaction Managers’. They are started and stopped the same way as the other concurrent managers. But they do not use the request queue. Transaction managers are called online from the eBS forms. And they execute a limited number of programs. These programs defined within their executables. They are called through the ‘FND_TRANSACTION.SYNCHRONOUS’ procedure, which uses the ‘DBMS_PIPE’ package.

The programs

It’s time to look at the concurrent programs. As mentioned before, a concurrent program is an instantiation of an executable. The executable is defined with a short name, an application (module), a filename and a method.

The short name will uniquely identify the executable. The other data is needed to determine what should be run for this executable. If the executable is an OS-based program, the application will be used to derive the directory on the file system where the executable is found.

When the executable is defined as PL/SQL, the filename will contain the procedure that needs to be run.

The concurrent program is defined as the executable with an (optional) set of parameters. It also has some properties for the printing of the output (print-style, pre-defined printer, size of the output).

Depending on the type of executable that needs to be run, the parameters will be sent to the executable ordered or named. For PL/SQL and host files, the parameters are ordered. And the order in which they are defined in the form defines how they will be sent to the executable. For reports the parameters are named, which means they are sent as <parameter>=<value>, ….

After the request has finished, the request table ‘FND_CONCURRENT_REQUESTS’ will be updated with the status information and a reference to the log- and output file. During the execution of the request, a status_code and phase_code are updated. The exact values of these fields are described in one of the next articles. That will go deeper into concurrent processing.

The output

The log- and output file from the requests are written to the directories $APPLCSF/$APPLLOG and $APPLCSF/$APPLOUT. But they of course also need to be made available to the user. This is done through the ‘Applications Report Review Agent’.

There is quite a lot of setup that can be done for the whole process. But within the scope of this article, we’ll only look at the basic architecture.

From the eBS form the log and output file are available from 2 buttons. These buttons call the web server for ‘FNDWRR.exe’ (.exe on both Windows and Unix).

FNDWRR.exe is a cgi-executable that will call the ‘FNDFS listener’.

This is an 8.0.6 TNS-listener in the eBS ORACLE_HOME on the eBS application tier. One of the less known features of the TNS-listeners is that they can do more than create database connections.

In the listener.ora, you can define a program to be called when a connection is made on a certain tns-entry. That feature is used for the FNDFS listener. When it is called, it will redirect traffic to the ‘FNDFS’ (FND File System) executable. This executable will read the requested file from the file-system and send it to FNDWRR.exe.

Again, we have a schema to show the whole flow:

This complex retrieval is of course needed because the concurrent processing tier can be separate from the forms and web-tiers.

On this webpage, I’ll make a FAQ on common eBS problems and troubleshooting. Probably the format will change over time. But I’ll just start. I use basic flow diagrams, to give an overview of the process. Under the diagrams is an explanation of all the steps.

Ø My concurrent manager does not start

1)      Check if the Internal Manager is running. On Unix, you can run: ps –ef | grep ‘FNDLIBR FND CPMGR’. If this returns a process, check the start time for the process to make sure it is the correct process.

2)      If a process is returned, and it started at the time you started the managers, the ICM is running.

3)      The ICM is not running. First check the adcmctl.txt file. It is found in the process_log directory. (Check your autoconfig xml file or the adcmctl.sh script). It will show the logs for the start-up scripts of the ICM.

4)      The ICM is running, but can’t start the other managers. Most common cause is  the APPS Listener is down. Check for it running with: ps –ef  | grep ‘tnslsnr APPS_<SID>’

5)      If no process is returned, start the apps listener with adalnctl.sh. Wait a minute afterwards, for the ICM to retry starting the managers.

6)      The ICM is running, or was started successfully before it died. Check the logfile from the ICM in $APPLCSF/$APPLLOG. By default the file is named <SID>_<proc>.mgr, where proc is the process_id from adcmctl.txt.

Ø Notifications are not being sent by the notification mailer

1)      Look for the notification in ‘wf_notifications’. Check the status, mail_status, recipient_role and notification_id.

2)      If Mail_status = ‘SENT’, the message has been mailed already. If status<>’OPEN’ (Note the difference between status and mail_status), the notification is not eligible to be mailed anymore.

3)      The Notification Mailer has already sent this message. Maybe it was sent to the TEST_ADDRESS  from the Notification Mailer.

4)      Check the mail_preference for the recipient_role from wf_roles.

5)      If the preference is ‘QUERY’, ‘SUMHTML’, ‘SUMMARY’ or ‘DISABLED’ then the recipient will not receive notifications by mail.

6)      Change the preference in the Users preferences. Or test with a different user.

7)  The Notification Mailer reads notifications to send from the queue WF_NOTIFICATION_OUT. Select from the queue-view:

select notification_id,msg_state,msg_id,role,corrid,enq_time,deq_time

from  (select msg_id, o.enq_time, o.deq_time, msg_state

              ,(select str_value

                from   table (o.user_data.header.properties)

                where  name = 'NOTIFICATION_ID') notification_id

              , (select str_value

                 from   table (o.user_data.header.properties)

                 where  name = 'ROLE') role

              , (select str_value

                 from   table (o.user_data.header.properties)

                 where  name = 'Q_CORRELATION_ID') corrid

       from   applsys.aq$wf_notification_out o)         

where notification_id=<notification_id>

and rownum=1;

      If you received a result on the query, the notification is in the queue.

9)      The status of the notification in the queue should be ‘READY’. If it is ‘PROCESSED’, or ‘ERROR’, the notification is already dequeued or errored. Otherwise check the status of the queue with:

select name,enqueue_enabled,dequeue_enabled

from dba_queues

where name='WF_NOTIFICATION_OUT';

10)   The status of the message should be ‘READY’. The ‘ENQUEUE_ENABLED’ and ‘DEQUEUE_ENABLED’ columns should be ‘YES’.

11)   Reprocess the message with the conc. Request. Or stop/start the queue with dbms_aqadm.

12)   Check the Notification Mailer logfile. The notification is ready for the mailer, but it is unable to pick it up. Check if the mailer shut down due to too many errors.

13)   The message is not in ‘WF_NOTIFICATION_OUT’. It can still be queued on the ‘WF_DEFERRED’ queue. Check this queue with:

select v.msg_id,v.msg_state,v.enq_time,v.deq_time,v.corr_id

from   applsys.aq$wf_deferred v

,      table(v.user_data.parameter_list) t

where v.corr_id like 'APPS:oracle.apps.wf.notification.%'

and name ='NOTIFICATION_ID'

and value = <Notification_id>;

14)   If the query returned results and the msg_state is ‘READY’, the notification is still being processed. Skip to 16

15)   Unfortunately, your notification seems to have gone missing. Consult Oracle Support. Please inform us of the solution in this case, so we can extend the FAQ.

16)   The notification is still in the deferred queue, waiting to be picked up by the ‘Workflow Deferred Notification Agent Listener’. Check the status of this listener. And if needed, check its logfile.

17)   If the Deferred Notification Agent Listener is not running, or erroring

18)   (re)start it.

19)   Check if the Business Event ‘oracle.apps.wf.notification.denormalize’ is enabled and has a subscription to procedure ‘Wf_Notification_Util.Denormalize_RF’.

20)   If either the Business event is disabled, or the subscription non-existent or disabled, go to 21.

21)   Make sure that the Business event is enabled and the subscription is valid and enabled. You will still have to reprocess the notification with the concurrent program to resubmit notifications.

22)   Unfortunately, we can’t locate the issue yet. If you manage to solve the issue please inform us, so we can update this FAQ.

Maybe it will be interesting for other people too. So here is the summary of it.

MAIN RULES OF EFFICIENT SQL

The main rules of efficient SQL are:

·         Less is better

·         More is better

That seems easy, since everything is better. But let me explain.

Less is better: The less I/O generated the better your statement will perform. Even though somebody might be able to think of some exceptions. It is safe to keep this as a rule of thumb.

Avoid unnecessary work for your query. You can do that by selecting only the rows that you need. (That sounds obvious, but I’ll give an example soon). In complex queries, make sure that you select the smallest possible set in every part of your query. Rather than collecting a huge amount of data and then selecting what you need, select the smallest set possible before you join.

Also select only the columns that you need. One argument is that it might give Oracle a chance to skip the table access, and use an index-only access.

Think about the use of ‘select *’. Most often this is a complete waste of resources. In packaged software, it can easily lead to bugs when the table definition changes. In all situations, it will cost extra resources to collect the data, send them to the client and then filter out the data that is not needed.

More is better: This is of course not about I/O. It is about the information that you give Oracle about your data and your query. Add as many predicates as possible, since it can help the optimizer do a better job. When 2 tables are joined on an ID-column. But you know, from your knowledge of the data, that another column can also be used as a join-condition then use both join conditions.

It will help the optimizer work out the relationship between the tables, and select the optimal plan. If 2 columns have related data, and the predicate on one column means that the other column is restricted too, put a predicate on both columns.

Consider the following:

SQL> create table Xxx_inner

  2  as select * from dba_objects

  3  where object_type='TABLE';

Table created.

SQL> create index xxx_inner_n1 on xxx_inner(object_id,object_type);

Index created.

SQL> create index xxx_inner_n2 on xxx_inner(Object_type);

Index created.

SQL> create table xxx_outer

  2  as select * from dba_objects;

Table created.

SQL> insert into  xxx_outer

  2  select * from dba_objects;

71136 rows created.

SQL> create index xxx_outer_n1 on xxx_outer(Object_id,object_type);

Index created.

SQL> create index xxx_outer_n2 on xxx_outer(object_type);

Index created.

SQL> analyze table xxx_inner compute statistics;

Table analyzed.

SQL> analyze table xxx_outer compute statistics;

Table analyzed.

SQL> set autotrace traceonly;

SQL> select o.*

  2  from xxx_outer o

  3  where o.object_id in (select object_id from xxx_inner i)

  4  and o.object_type='PROCEDURE';

no rows selected

Statistics

———————————————————-

        113  consistent gets

       1064  bytes sent via SQL*Net to client

Consistent gets is the number of times data was read from the buffer cache into our session memory. It is therefore a good measure of the amount of work a session needed to do while executing a query.

SQL> select o.*

  2  from xxx_outer o

  3  where o.object_id in (select object_id

    from xxx_inner i

    where i.object_type=o.object_type)

  4  and o.object_type='PROCEDURE';

no rows selected

Statistics

———————————————————-

         15  consistent gets

       1064  bytes sent via SQL*Net to client

SQL> select o.object_id

  2  from xxx_outer o

  3  where o.object_id in (select object_id

    from xxx_inner i

    where i.object_type=o.object_type)

  4  and o.object_type='PROCEDURE';

no rows selected

Statistics

———————————————————-

         15  consistent gets

        254  bytes sent via SQL*Net to client

Here we see two tables created from ‘DBA_OBJECTS’. We join these tables on ‘OBJECT_ID’. In this case, we have some information that the Oracle Optimizer does not have. The object_id,object_type combination is the same in both tables. Unaware of this fact, Oracle has to search all object_id’s for ‘XXX_INNER’. When we tell Oracle that the object_type is the same, it can skip most of the records resulting in less I/O.

When we finally tell Oracle that we’re only interested in the object_id, we also reduce the network traffic by 75%.

The concepts

For every query, Oracle will have to collect some data. And in most cases, it will have to join one or more data-sets. Let’s see what options Oracle has for collecting data and joining the data together. In this presentation we only look at the basic options, not the more sophisticated features. So don’t expect this list to be complete. We will see how data can be retrieved from the database, and how tables / data-sets can be joined together. We will not yet go into the most efficient way to do it, because the most efficient way to retrieve data depends on many factors. Only when you have a basic understanding of the concepts, we can start thinking about the most efficient way to do things.

Collecting data

To gather data from a table, Oracle can use 3 different options, called ‘Access Paths’:

·         Full Table Scan

·         Index Scan / Table Access by Rowid

·         Index Scan

The Full Table Scan (FTS) is exactly as the name implies, a full scan of the table. All the records of the table are read into memory, and checked against the predicates in the query (where clause or Join condition). The blocks of the table don’t have to be read in any particular order. Oracle will just try to get the blocks of the table as quickly as possible.

When a sizable part of the table needs to be selected, this will be the most efficient access path. It will be the only one available, if there is no predicate available that matches (part of) an index.

The ‘Index Scan / Table Access by Rowid’, will use an index to decide which rows need to be read into memory. Then based on the rowid in the index, the correct row will be retrieved. The rowid refers directly to the position on disk where the row is located.

And the last option is the ‘Index Scan’. The difference with the previous option is that Oracle does not need to get the table data anymore. The data in the index is sufficient to answer the query.

So which one of these is the most efficient?

As usual, it depends. Many people think a FTS is less efficient than an Index Scan. But consider this:

SQL> create table xxx_access as select * from dba_objects;

Table created.

SQL> create index xxx_access_n1 on xxx_access (object_id);

Index created.

SQL> select object_id,object_name from xxx_access where object_id>0;

71139 rows selected.

Elapsed: 00:00:08.02

Execution Plan

———————————————————-

   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=287 Card=78799 Bytes=6225121)

   1    0   TABLE ACCESS (FULL) OF 'XXX_ACCESS' (TABLE) (Cost=287 Card=78799 Bytes=6225121)

Statistics

———————————————————-

       5803  consistent gets

    2727442  bytes sent via SQL*Net to client

      71139  rows processed

SQL> select /*+ INDEX (xxx_access) */ object_id, object_name from xxx_access where object_id>0;

71139 rows selected.

Elapsed: 00:00:10.05

Execution Plan

———————————————————-

0     SELECT STATEMENT Optimizer=ALL_ROWS (Cost=1290 Card=78799 Bytes=6225121)

1   0   TABLE ACCESS (BY INDEX ROWID) OF 'XXX_ACCESS' (TABLE) (Cost=1290 Card=78799 By=6225121)

2   1     INDEX (RANGE SCAN) OF 'XXX_ACCESS_N1' (INDEX) (Cost=161 Card=78799)

Statistics

———————————————————-

      10771  consistent gets

    2727442  bytes sent via SQL*Net to client

      71139  rows processed

The FTS needs 5803 I/O operations. While the Index Scan takes almost double at 10771 I/O’s and 2 seconds more. (out of 10 sec’s!)

Imagine what will happen, when you try this with a multi-million row table.

But for sure an Index Scan will be the most efficient when it can be done? Again, it depends. Consider this:

SQL> create table test1 (l number, txt varchar2(500));

Table created.

SQL> create index test1_idx on test1(l,txt);

Index created.

SQL> Begin

  2  For I In (Select  Level L, Rpad('ABC',500,To_char(Level)) Txt

  3            From Dual Connect By Level <= 50000) Loop

  4    Insert Into Test1 Values (I.L,I.Txt);

  5    If Mod(I.L,5)!=0 Then

  6       Delete From Test1 Where L=I.L;

  7    End If;

  8  End Loop;

  9  Commit;

 10  end;

 11  /

PL/SQL procedure successfully completed.

SQL> analyze table test1 compute statistics;

Table analyzed.

SQL> set autotrace traceonly;

SQL> select l from test1 t where l>0;

10000 rows selected.

Execution Plan

———————————————————-

   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=773 Card=10000 Bytes=40000)

   1    0   TABLE ACCESS (FULL) OF 'TEST1' (TABLE) (Cost=773 Card=10000 Bytes=40000)

Statistics

———————————————————-

       1393  consistent gets

     140549  bytes sent via SQL*Net to client

      10000  rows processed

SQL> select /*+ INDEX(t,test1_idx) */ l from test1 t where l>0;

10000 rows selected.

Execution Plan

———————————————————-

   0      SELECT STATEMENT Optimizer=ALL_ROWS (Cost=3338 Card=10000 Bytes=40000)

   1    0   INDEX (RANGE SCAN) OF 'TEST1_IDX' (INDEX) (Cost=3338 Card=10000 Bytes=40000)

Statistics

———————————————————-

       4003  consistent gets

     140549  bytes sent via SQL*Net to client

      10000  rows processed

How can the Full Table Scan be more efficient?

Good question. To answer it, we have to look at the amount of work that Oracle has to do to get the data. We start with the FTS:

As mentioned, a FTS needs to scan all the blocks in a table. In my system, the table XXX_ACCESS was created with 1152 blocks. So basically Oracle will read 1152 blocks. However Oracle has optimized this process. One of the most noticeable optimizations is the db_file_multiblock_readcount, which tells Oracle to read multiple blocks in one I/O operation. So instead of doing 1152 reads, Oracle reads 4 (on my system) blocks at a time in 288 reads. (Take a look at the explain plan above again, and notice the cost of the Full Table Scan!).

Now how much work does an Index Scan / Table Access rowid need to do?

To answer that question, you need to know the structure of an index. An index in Oracle is a B-Tree structure. It looks like an inverted tree, with the top being the ‘Root-block’. The lowest level contains the ‘Leaf blocks’, that hold the index keys and the matching rowid’s. The index keys in the leaf blocks are sorted. So the lowest value will be in the utter-left block, the highest in the far right block.

All upper level blocks show the ranges that the lower level blocks contain.

To find a range of data, Oracle starts at the root block, and follows the pointers to the first leaf block containing an index key within the range. From here Oracle can walk the leaf blocks from left to right (or right to left, if needed).

See the following picture:

That means that Oracle has to walk the ‘height’ of the index (Index level). Then read a number of leaf blocks. And for every entry in the leaf-block, it needs to retrieve the data from the table.

In the worst case scenario, the data is spread throughout the table. And for every index key, Oracle has to retrieve a different table block. In that case, the amount of work is: (index level – 1) + number of index leaf blocks + (Number of keys * Number of table blocks).

It will be obvious that is a lot more I/O than just reading the table once. The formula is not completely correct, because Oracle does not read the same table block twice, when the next rowid from the index is in the same block.

But the formula should make it clear that with more data being retrieved, the cost of the index access / Table Rowid, is increasing faster than the cost of the Full Table Scan.

What happened to Index Only Access?

The example showed that a Full Table Scan is still more efficient than using only an index. Even though Oracle would only have to walk through the index to retrieve all the data.

This is caused by a feature of the index structure and the way the data was entered into the table. This caused the index to grow bigger than the actual table:

SQL> select table_name,num_rows,blocks from dba_Tables where table_name='TEST1';

TABLE_NAME             NUM_ROWS     BLOCKS

——————– ———- ———-

TEST1                     10000        772

SQL> select index_name, distinct_keys, leaf_blocks from dba_indexes where index_name='TEST1_IDX';

INDEX_NAME           DISTINCT_KEYS LEAF_BLOCKS

——————– ————- ———–

TEST1_IDX                    10000        3334

This situation can occur when a lot of inserts and deletes are taking place in the same transaction. The space for the deleted table rows can be reused immediately. But the space for the deleted index keys only comes available after the commit. NOTE: The space in the index will be reusable after the commit!

Another situation where this can happen is with an index key based on a sequence. So new data is only inserted at the end of the range. When you delete a lot of values on the lower end of the range (but not all). Richard Foote has some excellent material on his website about Deleted Index Keys:

http://en.wordpress.com/tag/index-delete-operations/

Join Mechanisms

I hope you’re not yet in despair. Because so far we have only retrieved data from single tables. In most cases, we need to join tables together to get our data. Now we will look at 3 basic forms of joining data-sets together. Note that it is not necessarily only tables that we join. It can also be a result set from an earlier part of your query. For example we might collect some data from an Index Only Access and then join it to data from a Full Table Scan.

Oracle has 3 mechanisms to perform Joins: Nested Loops, Hash Join, Merge Join. Let’s take a look at them.

Nested Loops

The Nested Loop join loops over a smaller data set, and for every record in that set, it searches a matching record in the second data set. Visually, it looks like this:

You can see that the first set is fully scanned. This is the Outer or Driving Set. For every record in this set, we look up a matching record in the second set. Usually this will be done through an index, even though this is not mandatory.

The efficiency of this mechanism depends on the size of Set A, and the number of records we need to  retrieve from Set B.

We will see some situations where a Nested Loops join is more or less efficient.

The second join mechanism is the

Hash Join

For a Hash Join, Oracle builds a hash table from a (preferably) smaller data set (Build set), where the key is a hash value derived from the join columns. Then Oracle reads the second data set (Probe set), derives the hash value on the join columns and probes the hash table for a match.

Schematically, it looks like this:

For the Hash Join, it is not relevant if the data is retrieved through an index, or from a Table scan. Both data sets need to be read fully. One of the features of hashing is that collisions may occur. A collision means that 2 different values result in the same hash value. Therefore, the full data set is stored in the hash table. When a match is found on the hash values, Oracle double-checks the actual values of the join columns to see if they match.

There is a major drawback for this mechanism. When the hash table does not fit into the available memory (hash_area_size). Then Oracle will dump parts of the hash table to disk (Temp tablespace). A bitmap of all possible hash values is kept in memory with a bit indicating if a hash-value is used or not.

So while scanning the Probe set, Oracle can check if there is a possible match. If that part of the hash table is not in memory, Oracle will set aside the records from the probe table. When finished with the probe set, the next part of the hash table is loaded into memory, and the records that were set aside are tested again. This is called a ‘Multipass Hash Join’, instead of the ‘Onepass Hash Join’ where the entire hash table is held in memory.

You can imagine that the hash join can be very efficient even without index access. However it can deteriorate quickly when a ‘Multipass Hash Join’  is needed.

That brings us to the

Merge Join

A Merge Join is possible when 2 datasets are both ordered on their join columns. The datasets can then be read in an alternating way. You start reading the first dataset, then you read the second dataset until you find a matching value, or exceed the value. If it is a matching value, you can start building your result set. If you pass the join value, you continue reading the first dataset again.

Schematically, it looks like this:

 The main requirement is of course that both data sets are ordered, before the join takes place. If that is the case, this is probably the most efficient join mechanism. It can handle all kinds of join comparisons, including range comparisons.

Back to efficient SQL

Now it is time to go back to the main focus of this article. How to write efficient SQL.

We have seen how Oracle can access data and join it together. It is the job of the Oracle Optimizer to find out the most efficient way to do that, for a given query. It does this based on statistics on the tables and indexes. It is not in the scope of this article to discuss how to gather statistics. But we will see the use of several of the statistics. These statistics include (but are not limited to) the number of rows in the table, the number of blocks, the average row length, etc. For an index, they include (but are not limited to) the number of leaf blocks, the number of keys per leaf block, the number of datablocks in the table per key, etc.

In an ideal world, we would be able to trust the optimizer to do the right thing all the time.

However, we live in an imperfect world, and the Oracle Optimizer does not always have perfect information about the data or your query. Either the statistics might not be up to date, or they might not include some dependencies within the data. Also your query might not give the optimizer all the information that you have. (see the first example in this article, where we can give the optimizer extra information by adding a predicate).

Consider this query:

Select * From

Tiny  T, –7089 rec

Small S   – 71151 Rec

Where t.Object_id = s.Object_id;

Which explain plan is more efficient:

0 SELECT STATEMENT  

1  HASH JOIN        

2   TABLE ACCESS FULL  TINY

3   TABLE ACCESS FULL  SMALL

Or:

0 SELECT STATEMENT                      

1  TABLE ACCESS BY INDEX ROWID SMALL     

2   NESTED LOOPS                       

3    TABLE ACCESS FULL         TINY    

4    INDEX RANGE SCAN          SMALL_IDX

The first explain plan uses a Hash Join, with Tiny as the Build Table. The second uses a Nested Loops Join, with Tiny as the Inner Table.

I hope you have decided that you don’t know which one is the most efficient. Because you cannot know based on the information you have. If I selected 2 non-overlapping sets of data, the Nested Loop Join might be more efficient.  It would scan Tiny for 7089 records, then do 7089 index lookups on Small (without result), so it would need to read approximately 7089+7089=14178 blocks.

If the 2 sets would have a 1-n relationship, and every occurrence of object_id in Small is also in Tiny, both tables would need to be read fully and the Hash Join would be more efficient.

That means that to write efficient SQL, you’ll need to have an understanding of the data. And you must have considered the optimal execution plan for your query. When you write your query, keep in mind the mantra in first part of this article. Less is Better, More is Better. You want to give Oracle as much information as possible, and you want to get as small as possible result sets.

The last part that we will do in this part, is to look at the

Explain plan

To see what Oracle will do when executing a query, you can make an explain plan. Many tools have built-in options to show explain plans on queries. Alternatively, you can use the Oracle commands:

SQL> Explain plan for

  2  Select * From

  3  Tiny  T, –7089 rec

  4  Small S   – 71151 Rec

  5  Where t.Object_id = s.Object_id;

Explained.

SQL> select * from table( dbms_xplan.display() );

PLAN_TABLE_OUTPUT

——————————————————————————–

Plan hash value: 803478362

—————————————————————————-

| Id  | Operation          | Name  | Rows  | Bytes | Cost (%CPU)| Time     |

—————————————————————————-

|   0 | SELECT STATEMENT   |       |  7089 |  1287K|  1264   (1)| 00:00:16 |

|*  1 |  HASH JOIN         |       |  7089 |  1287K|  1264   (1)| 00:00:16 |

|   2 |   TABLE ACCESS FULL| TINY  |  7089 |   650K|   213   (0)| 00:00:03 |

|   3 |   TABLE ACCESS FULL| SMALL | 71151 |  6392K|  1049   (1)| 00:00:13 |

—————————————————————————-

PLAN_TABLE_OUTPUT

——————————————————————————–

Predicate Information (identified by operation id):

—————————————————

   1 – access("T"."OBJECT_ID"="S"."OBJECT_ID")

15 rows selected.

I took the previous query, and ran an explain plan on it. First I should tell you how I created tiny and small, so you can verify:

create table tiny as select * from dba_objects where mod(object_id,10)=0;

create table small as select * from dba_objects;

create index tiny_idx on tiny(object_id);

create index small_idx on small(object_id);

Analyze Table Tiny Compute Statistics;

analyze table small compute statistics;

You can see that both tables were created from dba_objects and tiny is a subset of small. Therefore a Hash Join makes most sense.

Let’s take a closer look at the explain plan now. Keep in mind that all the numbers are estimates from the optimizer. They are based on the statistics available, and the runtime numbers might be completely different.

The execution starts at the rows furthest right. And top down. In this case that means that we start with a Full Table Scan of Tiny. Then we do a Full Table Scan of Small, and finally we Hash join the 2 sets together.

The result of the Hash Join is returned, and becomes the result of the query (Select).

Let’s take a closer look at the Full Table Scans. After the name of the table, we see ‘Rows’,’Bytes’,’Cost’ and ‘Time’.

The ‘Time’ is an estimate of the amount of time it will take to complete this step. It is useful in query tuning  to see which step will take the most time.

The ‘Bytes’ are an estimate of the amount of data used to complete this step. I find it useful when a hash join is involved. Because when it exceeds my hash_area_size, Oracle will need a ‘Multi-Pass Hash Join’.

The ‘Cost’ is often used for query tuning, and people will try to ‘tune down’ the cost. This makes sense, because the cost is an estimate for the amount of I/O Oracle needs to do for this step. However, there is a logical trap in this.

Oracle has used the cost of different explain plans for the original query to decide the most efficient one. Now when we change the query, the cost can no longer be compared to the original query. After all, it is a different query. It will return a different result. Unless, of course there is some information about the data we are selecting, that we didn’t give the optimizer initially.

To me, it makes more sense to look at the ‘Rows’. This is the number of records Oracle expects from that step in the query. If this is very different from the number you are expecting, something is wrong. Either the statistics are outdated, or the Optimizer is missing some information that you have, or you are not selecting the data you are expecting.

In the query above, we see that Oracle has made the perfect assumptions. Tiny will return 7089 rows, Small will return 71151 rows and there is a 1-1 relationship  between them. So the join will return one record for each record in Tiny. No use looking for a more efficient plan here. Unless again, we did not query what we are looking for.

After a long silence, it’s time to write another blog entry. I received a request to write about Oracle Reports. And I think that will be a new series (Even though I didn’t finish the workflow series yet). 

But the last few days, I’ve been working on cleaning up workflow tables. 

Most of these tables are very straightforward and you can find queries and descriptions in the workflow series. However, there are some more complex cases. There are the advanced queuing (aq) tables. And also some data hidden in wf_item_attribute_values for items started by the Business Event System (BES) (reminder to self: Write that article about BES too).

In the aq-tables, the payload of the message (i.e. the data transferred by the message) is stored in a custom type. The same goes for  the event_data in wf_item_attribute_values. In this article we’ll see how we can get the data from those ‘strange’ columns. 

Let us start with wf_item_attribute_values. Processes that are started from a business event, store the data from the originating business event in the column ‘EVENT_VALUE’. This has a type ‘WF_EVENT_T’. When you query it in a sql*plus session, you will see a huge column filled with something like: 

EVENT_VALUE(PRIORITY, SEND_DATE, RECEIVE_DATE, CORRELATION_ID, PARAMETER_LIST(NAME, VALUE), EVENT_NA
----------------------------------------------------------------------------------------------------
WF_EVENT_T(0, '17-SEP-09', NULL, NULL, WF_PARAMETER_LIST_T(WF_PARAMETER_T('TASK_ID', '16719879'), WF('ABORT_WORKFLOW', 'N'), WF_PARAMETER_T('SUB_GUID', '73BAB9A51BAF5307E04400144F687CA0')), 'oracle.ap, NULL, NULL)

The problem that many ebs-dba’s are facing is how to select the data inside this column. In this case, it would be the task_id that we are interested in. Oracle delivers several API's for use in PL/SQL. But sometimes you want plain SQL. 

One way to do it is to use a clever substr/instr construction or a regular expression. But the efficient way to do it, is to tell Oracle which info you want. 

Let’s take a look at the custom type. As mentioned, it is WF_EVENT_T. We can find the description in the DBA_TYPES table.

select owner,type_name,typecode,attributes,methods
from dba_types
where type_name='WF_EVENT_T';

OWNER                          TYPE_NAME                      TYPECODE                       ATTRIBUTES    METHODS
------------------------------ ------------------------------ ------------------------------ ---------- ----------
APPS                           WF_EVENT_T                     OBJECT                                 13         31

This tells us that the WF_EVENT_T is an object type. 

We can find its attributes in DBA_TYPE_ATTRS: 

select owner,type_name,attr_name,attr_type_owner,attr_type_name,length
from dba_type_attrs
where type_name=’WF_EVENT_T’;

OWNER		TYPE_NAME	ATTR_NAME         	ATTR_TYPE_OWNER		ATTR_TYPE_NAME
---------	------------	-------------------	----------------	--------------
APPS   		WF_EVENT_T      CORRELATION_ID					VARCHAR2
APPS     	WF_EVENT_T      ERROR_MESSAGE       				VARCHAR2
APPS     	WF_EVENT_T      ERROR_STACK         				VARCHAR2
APPS     	WF_EVENT_T      ERROR_SUBSCRIPTION  				RAW
APPS     	WF_EVENT_T      EVENT_DATA          				CLOB
APPS     	WF_EVENT_T      EVENT_KEY					VARCHAR2
APPS     	WF_EVENT_T      EVENT_NAME          				VARCHAR2
APPS     	WF_EVENT_T      FROM_AGENT         	APPS			WF_AGENT_T
APPS     	WF_EVENT_T      PARAMETER_LIST    	APPS			WF_PARAMETER_LIST_T
APPS     	WF_EVENT_T      PRIORITY         				NUMBER
APPS     	WF_EVENT_T      RECEIVE_DATE     				DATE
APPS     	WF_EVENT_T     	SEND_DATE        				DATE
APPS     	WF_EVENT_T     	TO_AGENT         	APPS			WF_AGENT_T

You see that the attributes are defined including their datatype, which can be a seeded datatype (VARCHAR2) or a custom one (WF_PARAMETER_LIST_T). Now that we now the attributes of the type, we can select them directly. To select the ‘PRIORITY’, just use an extra qualifier: 

select v.event_value.priority
from   wf_item_attribute_values v
where  ROWNUM = 1;

EVENT_VALUE.PRIORITY
--------------------
                   0

But how about the ‘PARAMETER_LIST’? That is where the task_id was stored. Let’s check the WF_PARAMETER_LIST_T definition: 

select owner,type_name,typecode,attributes,methods
from   dba_types
where  type_name ='WF_PARAMETER_LIST_T';

OWNER	  TYPE_NAME         	TYPECODE  		ATTRIBUTES  METHODS
--------- -------------------	-------------------	----------- -------
APPS      WF_PARAMETER_LIST_T	COLLECTION       		  0       0

This time, the type is a collection. We can find more info about a collection with: 

select type_name,coll_type,elem_type_owner,elem_type_name
from 	 dba_coll_types
where  type_name='WF_PARAMETER_LIST_T';

TYPE_NAME                      COLL_TYPE                      ELEM_TYPE_OWNER                ELEM_TYPE_NAME
------------------------------ ------------------------------ ------------------------------ --------------
WF_PARAMETER_LIST_T            VARYING ARRAY                  APPS                           WF_PARAMETER_T

So the WF_PARAMETER_LIST_T is a Varray of WF_PARAMETER_T. Before we look at selecting from Varrays, we first check what WF_PARAMETER_T looks like:

select owner,type_name,typecode,attributes,methods
from   dba_types
where  type_name ='WF_PARAMETER_T';

OWNER	  TYPE_NAME           TYPECODE	ATTRIBUTES METHODS
--------- ------------------- ---------	---------- ----------
APPS  	  WF_PARAMETER_T      OBJECT             2          4

That is an object type again. So we select: 

select owner,type_name,attr_name,attr_type_owner,attr_type_name
from   dba_type_attrs
where  type_name='WF_PARAMETER_T';

OWNER	TYPE_NAME             ATTR_NAME	ATTR_TYPE_OWNER	    ATTR_TYPE_NAME
--------- ------------------- --------- ------------------- --------------
APPS	WF_PARAMETER_T        NAME			    VARCHAR2
APPS	WF_PARAMETER_T	      VALUE			    VARCHAR2

Ok. We now know the whole structure of the parameter list. Back to the Varray.  A Varray (Varying Array) is of course an array structure. Since this is similar to a table structure, you can cast the Varray into a table. Then you use the casted table to select your data. Let’s do that to get the names from the parameter list.

select t.name
from   wf_item_attribute_values v
,      table(v.event_value.parameter_list) t
Where  v.event_value IS NOT NULL
And    ROWNUM = 1;

NAME
------------------------------
TASK_ID

Now that’s a neat trick. We can join our table to its own column! 

In our case, we only have a task_id parameter. We could do the same again, to get the value of the parameter from the value column.

But to join wf_item_attribute_values to itself is a very expensive operation. Take a look at the explain plan: 

PLAN_TABLE_OUTPUT

-----------------------------------------------------------------------------------------------------------------
| Id  | Operation                           |  Name                     | Rows  | Bytes | Cost  | Pstart| Pstop |
-----------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                    |                           |     1 |    62 |   432M|       |       |
|*  1 |  COUNT STOPKEY                      |                           |       |       |       |       |       |
|   2 |   NESTED LOOPS                      |                           |   207G|    11T|   432M|       |       |
|   3 |    PARTITION RANGE ALL              |                           |       |       |       |     1 |    77 |
|   4 |     PARTITION HASH ALL              |                           |       |       |       |     1 |     8 |
|*  5 |      TABLE ACCESS FULL              | WF_ITEM_ATTRIBUTE_VALUES  |    25M|  1453M|   948K|     1 |   616 |
|   6 |    COLLECTION ITERATOR PICKLER FETCH|                           |       |       |       |       |       |
-----------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter(ROWNUM=1)
   5 - filter(SYS_OP_NOEXPAND("V"."EVENT_VALUE") IS NOT NULL)

Note: cpu costing is off

That can kind of hurt if it,were it not for the NL with a COUNT STOPKEY (Because of the rownum=1). The reason for the expensive plan, is because for every row from wf_item_attribute_values, Oracle needs to get the data from event_value. It basically does a carthesian join with itself.

So here is another way to get your data: 

select v.item_key
,      (select value
        from table(v.event_value.parameter_list) t
        where t.name='TASK_ID' ) task_id
from   wf_item_attribute_values v
where  v.event_value is not null
and    rownum=1;

ITEM_KEY						TASK_ID
-------------------------------------------------	--------
oracle.apps.jtf.cac.task.createTask-155563676		16719879

Now we use a scalar subquery, where Oracle will access only the event_value for the rows that will be returned to the user. You can see this in the explain plan by the collection iterator picklefetch (= the operation that collects the data from a collection type) being pushed up to just before the select. 

PLAN_TABLE_OUTPUT

---------------------------------------------------------------------------------------------------------------
| Id  | Operation                         |  Name                     | Rows  | Bytes | Cost  | Pstart| Pstop |
---------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                  |                           |     1 |    60 |   948K|       |       |
|*  1 |  COLLECTION ITERATOR PICKLER FETCH|                           |       |       |       |       |       |
|*  2 |  COUNT STOPKEY                    |                           |       |       |       |       |       |
|   3 |   PARTITION RANGE ALL             |                           |       |       |       |     1 |    77 |
|   4 |    PARTITION HASH ALL             |                           |       |       |       |     1 |     8 |
|*  5 |     TABLE ACCESS FULL             | WF_ITEM_ATTRIBUTE_VALUES  |    25M|  1453M|   948K|     1 |   616 |
---------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter(SYS_OP_ATG(VALUE(KOKBF$),1,2,2)='TASK_ID')
   2 - filter(ROWNUM=1)
   5 - filter(SYS_OP_NOEXPAND("SYS_ALIAS_1"."EVENT_VALUE") IS NOT NULL)

Note: cpu costing is off

Still expensive. But much better.

So that will let us peek into the  event_value column on wf_item_attribute values. Be aware that different processes will enter different parameters into the event_value column. But with the information above you should be able to understand how to select the data and use it in your own queries. 

Now let’s take a look at the AQ-tables? 

As I mentioned, they carry their payloads in custom types too. One that most ebs-dba’s will have seen is WF_NOTIFICATION_OUT. When the workflow engine generates a notification, it will be stored in ‘WF_NOTIFICATIONS’. However, a message will be posted on ‘WF_NOTIFICATION_OUT’ too. This message will be read by the workflow notification mailer, which will use it to get the relevant data from WF_NOTIFICATIONS.

If you haven’t run the notification mailer for a long time, you might want to clean up WF_NOTIFICATION_OUT a bit. There is a script available from Metalink to do the job. (There is also a quicker but unsupported way). But you might want to see the records in WF_NOTIFICATION_OUT related to WF_NOTIFICATIONS to decide if a cleanup is appropriate. 

Let’s look at WF_NOTIFICATION_OUT:

Name                    Null?    Type
----------------------- -------- ----------------
Q_NAME                           VARCHAR2(30)
MSGID                   NOT NULL RAW(16)
CORRID                           VARCHAR2(128)
PRIORITY                         NUMBER
STATE                            NUMBER
DELAY                            DATE
EXPIRATION                       NUMBER
TIME_MANAGER_INFO                DATE
LOCAL_ORDER_NO                   NUMBER
CHAIN_NO                         NUMBER
CSCN                             NUMBER
DSCN                             NUMBER
ENQ_TIME                         DATE
ENQ_UID                          NUMBER
ENQ_TID                          VARCHAR2(30)
DEQ_TIME                         DATE
DEQ_UID                          NUMBER
DEQ_TID                          VARCHAR2(30)
RETRY_COUNT                      NUMBER
EXCEPTION_QSCHEMA                VARCHAR2(30)
EXCEPTION_QUEUE                  VARCHAR2(30)
STEP_NO                          NUMBER
RECIPIENT_KEY                    NUMBER
DEQUEUE_MSGID                    RAW(16)
SENDER_NAME                      VARCHAR2(30)
SENDER_ADDRESS                   VARCHAR2(1024)
SENDER_PROTOCOL                  NUMBER
USER_DATA                        SYS.AQ$_JMS_TEXT _MESSAGE

The regular AQ-information is there. And our payload in USER_DATA. This time it’s an AQ-type. 

Let’s follow the same procedure: 

select type_name,typecode,attributes,methods
from   dba_types
where  type_name='AQ$_JMS_TEXT_MESSAGE';

TYPE_NAME                      TYPECODE                       ATTRIBUTES    METHODS
------------------------------ ------------------------------ ---------- ----------
AQ$_JMS_TEXT_MESSAGE           OBJECT                                  4         34

An object type. So let’s see its attributes: 

select type_name,attr_name,attr_type_owner,attr_type_name
from   dba_type_attrs
where  type_name='AQ$_JMS_TEXT_MESSAGE';

TYPE_NAME                      ATTR_NAME                      ATTR_TYPE_OWNER                ATTR_TYPE_NAME
------------------------------ ------------------------------ ------------------------------ --------------
AQ$_JMS_TEXT_MESSAGE           HEADER                         SYS                            AQ$_JMS_HEADER
AQ$_JMS_TEXT_MESSAGE           TEXT_LEN                                                      INTEGER
AQ$_JMS_TEXT_MESSAGE           TEXT_LOB                                                      CLOB
AQ$_JMS_TEXT_MESSAGE           TEXT_VC                                                       VARCHAR2

We can already read the text_len, text_lob and text_vc. The last 2 contain an XML with a reference to the notification. But the information that I want to show you is in the header. This is a type ‘AQ$_JMS_HEADER’. When we check this one, we see that it again is an object with these attributes:

select type_name,typecode,attributes,methods
from   dba_types
where  type_name='AQ$_JMS_HEADER';

TYPE_NAME                      TYPECODE                       ATTRIBUTES    METHODS
------------------------------ ------------------------------ ---------- ----------
AQ$_JMS_HEADER                 OBJECT                                  7         31

select type_name,attr_name,attr_type_owner,attr_type_name
from   dba_type_attrs
where  type_name='AQ$_JMS_HEADER';

TYPE_NAME                      ATTR_NAME                      ATTR_TYPE_OWNER                ATTR_TYPE_NAME
------------------------------ ------------------------------ ------------------------------ -------
AQ$_JMS_HEADER                 APPID                                                         VARCHAR2
AQ$_JMS_HEADER                 GROUPID                                                       VARCHAR2
AQ$_JMS_HEADER                 GROUPSEQ                                                      INTEGER
AQ$_JMS_HEADER                 PROPERTIES                     SYS                            AQ$_JMS_USERPROPARRAY
AQ$_JMS_HEADER                 REPLYTO                        SYS                            AQ$_AGENT
AQ$_JMS_HEADER                 TYPE                                                          VARCHAR2
AQ$_JMS_HEADER                 USERID                                                        VARCHAR2

As you can imagine, we need to drill down into ‘PROPERTIES’. The other attributes might or might not contain any data, depending on the notification. properties is a Varray of ‘AQ$_JMS_USERPROPERTY’:

select type_name,typecode,attributes,methods
from   dba_types
where  type_name='AQ$_JMS_USERPROPARRAY';

TYPE_NAME                      TYPECODE                       ATTRIBUTES    METHODS
------------------------------ ------------------------------ ---------- ----------
AQ$_JMS_USERPROPARRAY          COLLECTION                              0          0

select type_name,coll_type,elem_type_owner,elem_type_name
from 	 dba_coll_types
where  type_name='AQ$_JMS_USERPROPARRAY';

TYPE_NAME                      COLL_TYPE                      ELEM_TYPE_OWNER                ELEM_TYPE_NAME
------------------------------ ------------------------------ ------------------------------ --------------------
AQ$_JMS_USERPROPARRAY          VARYING ARRAY                  SYS                            AQ$_JMS_USERPROPERTY

One more level to check: 

select type_name,typecode,attributes,methods
from   dba_types
where  type_name='AQ$_JMS_USERPROPERTY';

TYPE_NAME                      TYPECODE                       ATTRIBUTES    METHODS
------------------------------ ------------------------------ ---------- ----------
AQ$_JMS_USERPROPERTY           OBJECT                                  5          0

select type_name,attr_name,attr_type_owner,attr_type_name
from   dba_type_attrs
where  type_name='AQ$_JMS_USERPROPERTY';

TYPE_NAME                      ATTR_NAME                      ATTR_TYPE_OWNER                ATTR_TYPE_NAME
------------------------------ ------------------------------ ------------------------------ -------
AQ$_JMS_USERPROPERTY           JAVA_TYPE                                                     INTEGER
AQ$_JMS_USERPROPERTY           NAME                                                          VARCHAR2
AQ$_JMS_USERPROPERTY           NUM_VALUE                                                     NUMBER
AQ$_JMS_USERPROPERTY           STR_VALUE                                                     VARCHAR2
AQ$_JMS_USERPROPERTY           TYPE                                                          INTEGER

So let’s see what properties we have. I just query the whole contents of properties for the first row in wf_notification_out (This particular system doesn’t have a WF-mailer running. If it is running, chances are that you won’t have any records in WF_NOTIFICATION_OUT).

select p.*
from   (select *
        from wf_notification_out
        where rownum=1) n
,      table(n.user_data.header.properties) p;

NAME	              	TYPE  STR_VALUE	                                   NUM_VALUE JAVA_TYPE
----------------------- ----- -------------------------------------------- --------- ---------
BES_EVENT_NAME	      	  100 oracle.apps.wf.notification.send                              27
BES_EVENT_KEY	      	  100                                               39388680        27
BES_PRIORITY	      	  200                                                     50        23
BES_SEND_DATE	       	  100 2009/03/06 01:12:23		                            27
BES_RECEIVE_DATE	  100 2009/03/06 01:12:34		                            27
BES_FROM_AGENT	      	  100 WF_NOTIFICATION_OUT@TESTDB.STIJF.COM                          27
BES_ERROR_SUBSCRIPTION    100 C10E7C2EF71253C1E0340800208D03E1		           	    27
NOTIFICATION_ID	      	  100 39388680		                                            27
ROLE		       	  100 FND_RESP535:21704		                                    27
GROUP_ID		  100 39388680		                                            27
Q_CORRELATION_ID	  100 XDPWFSTD		                                            27

There you go. Among others, the ‘NOTIFICATION_ID’ is there. It maps to the notification_id on ‘WF_NOTIFICATIONS’. And by now, we have seen enough to select it directly in our queries:

select n.msgid,(select str_value
                from   table(n.user_data.header.properties)
		where  name='NOTIFICATION_ID') notification_id
from   wf_notification_out n
where  rownum=1;

MSGID			    	 NOTIFICATION_ID
-------------------------------- ---------------
64672D4985E57075E04400144F687CA0	39388680

That concludes this article. Based on the above, you will be able to select the data you want.

Didn't have any time to format it in HTML format yet. So for the moment it is only available in PDF format from the link-page and from here. 

Enjoy!