Data display from FA_BALANCES_REPORT_GT table
Hi 2 all
Anyhody know that how to fetch the data from FA_BALANCES_REPORT_GT table in
sql environment
Thanks
zulqarnain
Hi;
Please check:
Oracle FA FASRSVED.rdf report need to customized ...FABAL.pll
Regard
Helios
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While Creating New Insert Form Existing Data Display from the Table
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I am New To Sun Java Studio Creator and New to Java Also While Creating New Insert Form Existing Data Display from the Table while i am Run the Form. Can any one help me to Solve this oneDear Giri,
As per your Advise, Literally I have Search the Properties for the Components to set value Null, but I am Unable to find the Value in Properties palate. I have tried in various options like
In the Properties Palate
TextField1_onselect use Value null
TextField1_text I have selected use Value option and I have manually Keyed-in null;
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<ui:textField binding="#{BI.textField2}" id="textField2" style="position: absolute; left: 240px; top: 96px" text="#{BI.bDataProvider.value['ISSUENO'] = null}"/>
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Hi,
I have used smartforms for generating suppler payment statement for financial department. more time duration is taken by the program when it is generating.
I think this problem comes while data fetching from BSEG table. because, it has more records for one vendor ID.
I want reduce this time duration.
Please guide me.Have you tried this selection in se16? I'm quite sure that It will take
a long time.
The problem has been explained in this group before and I think you
should search for bseg in the answers given.
As a hint: It has to do with the selection universe. You are restricting
only bukrs from the primary key (all the other restrictions in your
where clause are filters that are applied on SAP's side (not on the
database side)). The problem is that bseg isn't stored as separated
fields in the RDBMS, but as a table with the primary key and a stream of
bits in a raw field.
You should review and change the logic you're using before reading bseg.
It's the only way you'll improve the performance of this select. (for
example, you could use one or more secondary index tables - bi or ba
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Data fetching from Standard tables or transaction to SAP PI
Dear Friends !
Good day ! How are you ?
I have one requirement , My client asks me to develop a solution in that I should get the data from standard SAP tables like EKKO, EKPO ( MM related ) etc.. and send it to PI system and then PI system sends it to third party system database system.
We have current scenario is working fine, I have abap proxy that I called in various standard transaction codes ( MIRO, MIGO, etc ) ' Baddis just beforethe commit stament and it passed the data to SAP PI system and it sends to SQL system.
but my client dont want me to use Baddis. Client wants like u should read from those EKKO,EKPO tables as soon as you get new entry there and send it to PI system. I have no clue How can I go further in that. Shall I use events ? but then question is same I need to trgger them somewere? Is any one have idea How I can send the data to PI system frm SAP standard tcodes and tables without using Baddis.
Please reply me. your any help will be appreciated.
Regards
NaeemThe current Approach of your development perfectly good approach,
it is not possbiel to read data directly from SAP Tables, you have to use IDoc/RFC/Proxy,if you want to avoid BADI's then better to contact ABAP Team, they will help you different approches .
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Raj -
Value Set whose Data come from customize table with distinct record
Dear All,
I am new in Oracle EBS, currently i am creating value set whose data come from customize table which have 40 duplicate record in which distinct column return 27 record .
Table XX_ROUND_SET
Columns (Transactions_id,set_record)
Total Record (40)
Distinct Record (Set_Record --> 27)
I just want to show only 27 record in it.
Thanks
RehanHi Rehan,
PL.IGNORE MY EARLIER UPDATE AND TREAT THIS UPDATE AS YOUR SOLUTION.
Method 1
Create the VIEW based on DISTINCT values; use the VIEW for creates the VALUESET.
Method 2
Paste the QUERY in TABLE field with alias name, and give the column name (with alias name).
(in your case )
TABLE NAME : ( select distinct transactions_id, set_record from XX_ROUND_SET ) Y
VALUE : Y.transactions_id
HTH
Sanjay -
Hi
Is there a way to filter a drop down list by using the result main data display from"GetUserProfileByName" when open the form?
The second source has a huge list of company names that can be narrrow by email work.
background:SP 2010 and Infopath 2010
CRISTINA& MICROSOFT ForumI'm not sure if I understood your question clearly but here is a good resource on how to get attributes from "GetUserProfileByName" web services:
http://blog.mangroveweb.com/pre-populating-an-infopath-from-with-mysql-data-using-a-net-web-service/using-sharepoints-getuserprofilebyname-web-service-to-retrieve-ad-account-information/
Regarding filtering dropdown list then this could be done by applying form on-load rules.
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Invoking binding operation from backing bean -- no data displayed in ADF table ?
Hello experts, I have data control derived from Web Service proxy client. In this data control, I have multi record list derived from web service call.In my ADF page, I have bunch of input components with many drop down lists and radio buttons, check boxes etc.
Finally I want to transfer user input to data control. In my ADF page, I have mapped the result set of data conrol to ADF table.
When I click submit button, the input data from ADF page is passed to data control operation. In the bean method, I am making use of operationBinding.execute() and operationBinding.getParamsMap().put(). I see it is fetching data by checking getResult().
I am invoking partial trigger also on the table. However, table is not getting populated with the data.
please help me. Jdeveloper verion is 11.1.1.6. I have set "Refresh" attribute to "never" for iterator in the bindings tab. But no luck. I see that control coming to data control and calling web service and getting the data and then it comes back to my bean method submit() and I see that getResult() is showing records fetched. But why the table on ADF page is not showing the data ?
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Data fetch from two table without refresh
hi Friends,
I have a problem i want to extract data from two table without refresh into text field when i'll enter any value in a text field then corressponding value should come in to corressponding textfield.
eg. there two table A and B.
Table A has Colunm
s_id Number;
c_id Varchar2(30);
sec varchar2(4);
Second Table B Colunm Name
s_id Number;
f_name varchar(30);
l_name varchar(20);
when i enter s_id 101 in a text field then the c_id ,sec,first_name and last_name should come in to corressponding text fields without refresh.
How Can I do this.
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ManojHi Manoj,
You have to make an Ajax call to display data without refreshing the page. Search this forum for Ajax and you can find lots of related posts. This link might help too. http://www.dba-oracle.com/t_html_db_apex_ajax_application_express.htm
Thanks,
Manish. -
Most recent date (UDATE) from CDHDR table based on CDPOS
Hi,
I am working on one object where i stuck with one issue. The requirement is I have to retrieve the most recent date from CDHDR table based on CHANGENR in CDPOS table. Where i am doing FOR ALL ENTRIES on CDPOS table to get the MAX( date )and i got the error, that aggregate functions are not allowed except COUNT( * ) with for all entries.
Any thread which can solve this issue would help aswel.
Please guide me how to achieve this. <removed>
Edited by: Thomas Zloch on Mar 13, 2010 9:10 PMHi Li,
Thats was really helpful information , infact my requirement is same as what you said. I even checked in the table entries there is only one changenumber.
You said we can take the first record, i even did the same. But for TABNAME I have to pass 3 table name 'LFA1', 'LFB1' and 'LFM1'. For FNAME 'LOEVM', 'SPERR'. I have written the code as below.
SELECT objectclas
objectid
changenr
FROM cdpos
INTO TABLE i_cdpos_a1
FOR ALL ENTRIES IN i_lfabm1
WHERE objectclas = c_kred "KRED
AND objectid EQ i_lfabm1-objectid "Lifnr
AND ( tabname EQ c_lfa1 OR tabname EQ c_lfb1 OR tabname EQ c_lfm1 ) "LFA1, LFB1 and LFM1
AND ( fname EQ c_loevm OR fname OR fname EQ c_sperr ) "LOEVM, SPERR
AND value_new EQ c_x.
IF sy-subrc EQ c_0.
IF i_cdpos_a1[] IS NOT INITIAL.
Select UDATE from CDHDR based on CHANGENR in CDPOS.
SELECT objectclas
objectid
changenr
udate
FROM cdhdr
INTO TABLE i_cdhdr_a1
FOR ALL ENTRIES IN i_cdpos_a1
WHERE objectclas = c_kred "KRED
AND objectid EQ i_lfabm1-objectid "Lifnr
AND changenr EQ i_cdpos_a1-changenr. "(this is coming from CDPOS above selection)
Here i got UDATE which have all the dates from 3 tables. I have to display in the output the field value (X) of LOEVM and UDATE for LFA1, SPERR value and UDATE for LFA1.Same way for other two tables, I have to display the UDATE and its field value (X). Where UDATE should be most recent date respectively.
How can I populate the Recent date (UDATE) from one interal table for indvidual field values and table names. -
Data display from search help.
Dear All,
I create a search help from T005 table with 2 parameter LAND1 and LANDX.
I have a zempinfo table which have a field LAND1.
when I want to insert data in zempinfo table I get data for LAND1 from search help. In the meantime I want to display LANDX 's data in a screen by a DISPLAY_ITEM.
DISPLAY_ITEM is not a zempinfo table field. IT is a screen element only.
Now help me please, to display data LANDX into DISPLAY_ITEM.
Thanks
RayhanPls try to understand.
Though land1 landx are same table fields. I want to use only one search help.
When I enter value in LAND1 from search help, DISPLAY_ITEM automaticaly get data crossponding value of land1 from landx.
e.g. when we create a SO by tcode VA01. in this screen we enter the MATNR value & crossponding other field display its related data.
IF any way do this pls help that.
Thanks for your attention.
Edited by: Abu Rayhan on Jul 30, 2009 5:50 AM -
Data loading from one table to another
Hi,
I want to load some data from a temp table to a master table. The master is having 40million records and the temp table is having 23 million records. Master table is having around 50 columns and we are adding 4new columns and the temp table is having 5columns. The data for these 4new columns are available in the temporary table also the employee column is there in common to these two table.
I used a stored procedure to load the data, whcih uses a cursor. But its taking more that 6hours to load.
Can any one suggest me a good technique to load data faster?
Thanks,
Santhosh.hi consider this case scenario which matches with yours.
first of all you have to update not insert in master table.
master table = emp with columns (emp_id, emp_name, emp_designation)
to this original master table you added two more columns emp_salary, emp_department
so now your master table looks like emp_id, emp_name, emp_designation, emp_salary, emp_department
but when you do select * from master table, the last two columns salary & department are blank.
Now you have another temp table with folllowing columns (emp_id, emp_salary, emp_department)
now emp_id is common to master & temp tables & you want to put values from temp table into master tables? I think this is what ur trying to do..
so for the above case the query i would write is
update master_table m set m.emp_salary=(select t.emp_salary from temp_table t where
t.emp_id=m.emp_id);
commit;
Regds. -
How to select the data efficiently from the table
hi every one,
i need some help in selecting data from FAGLFLEXA table.i have to select many amounts from different group of G/L accounts
(groups are predefined here which contains a set of g/L account no.).
if i select every time for each group then it will be a performance issue, in order to avoid it what should i do, can any one suggest me a method or a smaple query so that i can perform the task efficiently.Hi ,
1.select and keep the data in internal table
2.avoid select inside loop ..endloop.
3.try to use for all entries
check the below details
Hi Praveen,
Performance Notes
1.Keep the Result Set Small
You should aim to keep the result set small. This reduces both the amount of memory used in the database system and the network load when transferring data to the application server. To reduce the size of your result sets, use the WHERE and HAVING clauses.
Using the WHERE Clause
Whenever you access a database table, you should use a WHERE clause in the corresponding Open SQL statement. Even if a program containing a SELECT statement with no WHERE clause performs well in tests, it may slow down rapidly in your production system, where the data volume increases daily. You should only dispense with the WHERE clause in exceptional cases where you really need the entire contents of the database table every time the statement is executed.
When you use the WHERE clause, the database system optimizes the access and only transfers the required data. You should never transfer unwanted data to the application server and then filter it using ABAP statements.
Using the HAVING Clause
After selecting the required lines in the WHERE clause, the system then processes the GROUP BY clause, if one exists, and summarizes the database lines selected. The HAVING clause allows you to restrict the grouped lines, and in particular, the aggregate expressions, by applying further conditions.
Effect
If you use the WHERE and HAVING clauses correctly:
There are no more physical I/Os in the database than necessary
No unwanted data is stored in the database cache (it could otherwise displace data that is actually required)
The CPU usage of the database host is minimize
The network load is reduced, since only the data that is required by the application is transferred to the application server.
Minimize the Amount of Data Transferred
Data is transferred between the database system and the application server in blocks. Each block is up to 32 KB in size (the precise size depends on your network communication hardware). Administration information is transported in the blocks as well as the data.
To minimize the network load, you should transfer as few blocks as possible. Open SQL allows you to do this as follows:
Restrict the Number of Lines
If you only want to read a certain number of lines in a SELECT statement, use the UP TO <n> ROWS addition in the FROM clause. This tells the database system only to transfer <n> lines back to the application server. This is more efficient than transferring more lines than necessary back to the application server and then discarding them in your ABAP program.
If you expect your WHERE clause to return a large number of duplicate entries, you can use the DISTINCT addition in the SELECT clause.
Restrict the Number of Columns
You should only read the columns from a database table that you actually need in the program. To do this, list the columns in the SELECT clause. Note here that the INTO CORRESPONDING FIELDS addition in the INTO clause is only efficient with large volumes of data, otherwise the runtime required to compare the names is too great. For small amounts of data, use a list of variables in the INTO clause.
Do not use * to select all columns unless you really need them. However, if you list individual columns, you may have to adjust the program if the structure of the database table is changed in the ABAP Dictionary. If you specify the database table dynamically, you must always read all of its columns.
Use Aggregate Functions
If you only want to use data for calculations, it is often more efficient to use the aggregate functions of the SELECT clause than to read the individual entries from the database and perform the calculations in the ABAP program.
Aggregate functions allow you to find out the number of values and find the sum, average, minimum, and maximum values.
Following an aggregate expression, only its result is transferred from the database.
Data Transfer when Changing Table Lines
When you use the UPDATE statement to change lines in the table, you should use the WHERE clause to specify the relevant lines, and then SET statements to change only the required columns.
When you use a work area to overwrite table lines, too much data is often transferred. Furthermore, this method requires an extra SELECT statement to fill the work area. Minimize the Number of Data Transfers
In every Open SQL statement, data is transferred between the application server and the database system. Furthermore, the database system has to construct or reopen the appropriate administration data for each database access. You can therefore minimize the load on the network and the database system by minimizing the number of times you access the database.
Multiple Operations Instead of Single Operations
When you change data using INSERT, UPDATE, and DELETE, use internal tables instead of single entries. If you read data using SELECT, it is worth using multiple operations if you want to process the data more than once, other wise, a simple select loop is more efficient.
Avoid Repeated Access
As a rule you should read a given set of data once only in your program, and using a single access. Avoid accessing the same data more than once (for example, SELECT before an UPDATE).
Avoid Nested SELECT Loops
A simple SELECT loop is a single database access whose result is passed to the ABAP program line by line. Nested SELECT loops mean that the number of accesses in the inner loop is multiplied by the number of accesses in the outer loop. You should therefore only use nested SELECT loops if the selection in the outer loop contains very few lines.
However, using combinations of data from different database tables is more the rule than the exception in the relational data model. You can use the following techniques to avoid nested SELECT statements:
ABAP Dictionary Views
You can define joins between database tables statically and systemwide as views in the ABAP Dictionary. ABAP Dictionary views can be used by all ABAP programs. One of their advantages is that fields that are common to both tables (join fields) are only transferred once from the database to the application server.
Views in the ABAP Dictionary are implemented as inner joins. If the inner table contains no lines that correspond to lines in the outer table, no data is transferred. This is not always the desired result. For example, when you read data from a text table, you want to include lines in the selection even if the corresponding text does not exist in the required language. If you want to include all of the data from the outer table, you can program a left outer join in ABAP.
The links between the tables in the view are created and optimized by the database system. Like database tables, you can buffer views on the application server. The same buffering rules apply to views as to tables. In other words, it is most appropriate for views that you use mostly to read data. This reduces the network load and the amount of physical I/O in the database.
Joins in the FROM Clause
You can read data from more than one database table in a single SELECT statement by using inner or left outer joins in the FROM clause.
The disadvantage of using joins is that redundant data is read from the hierarchically-superior table if there is a 1:N relationship between the outer and inner tables. This can considerably increase the amount of data transferred from the database to the application server. Therefore, when you program a join, you should ensure that the SELECT clause contains a list of only the columns that you really need. Furthermore, joins bypass the table buffer and read directly from the database. For this reason, you should use an ABAP Dictionary view instead of a join if you only want to read the data.
The runtime of a join statement is heavily dependent on the database optimizer, especially when it contains more than two database tables. However, joins are nearly always quicker than using nested SELECT statements.
Subqueries in the WHERE and HAVING Clauses
Another way of accessing more than one database table in the same Open SQL statement is to use subqueries in the WHERE or HAVING clause. The data from a subquery is not transferred to the application server. Instead, it is used to evaluate conditions in the database system. This is a simple and effective way of programming complex database operations.
Using Internal Tables
It is also possible to avoid nested SELECT loops by placing the selection from the outer loop in an internal table and then running the inner selection once only using the FOR ALL ENTRIES addition. This technique stems from the time before joins were allowed in the FROM clause. On the other hand, it does prevent redundant data from being transferred from the database.
Using a Cursor to Read Data
A further method is to decouple the INTO clause from the SELECT statement by opening a cursor using OPEN CURSOR and reading data line by line using FETCH NEXT CURSOR. You must open a new cursor for each nested loop. In this case, you must ensure yourself that the correct lines are read from the database tables in the correct order. This usually requires a foreign key relationship between the database tables, and that they are sorted by the foreign key. Minimize the Search Overhead
You minimize the size of the result set by using the WHERE and HAVING clauses. To increase the efficiency of these clauses, you should formulate them to fit with the database table indexes.
Database Indexes
Indexes speed up data selection from the database. They consist of selected fields of a table, of which a copy is then made in sorted order. If you specify the index fields correctly in a condition in the WHERE or HAVING clause, the system only searches part of the index (index range scan).
The primary index is always created automatically in the R/3 System. It consists of the primary key fields of the database table. This means that for each combination of fields in the index, there is a maximum of one line in the table. This kind of index is also known as UNIQUE.
If you cannot use the primary index to determine the result set because, for example, none of the primary index fields occur in the WHERE or HAVING clause, the system searches through the entire table (full table scan). For this case, you can create secondary indexes, which can restrict the number of table entries searched to form the result set.
You specify the fields of secondary indexes using the ABAP Dictionary. You can also determine whether the index is unique or not. However, you should not create secondary indexes to cover all possible combinations of fields.
Only create one if you select data by fields that are not contained in another index, and the performance is very poor. Furthermore, you should only create secondary indexes for database tables from which you mainly read, since indexes have to be updated each time the database table is changed. As a rule, secondary indexes should not contain more than four fields, and you should not have more than five indexes for a single database table.
If a table has more than five indexes, you run the risk of the optimizer choosing the wrong one for a particular operation. For this reason, you should avoid indexes with overlapping contents.
Secondary indexes should contain columns that you use frequently in a selection, and that are as highly selective as possible. The fewer table entries that can be selected by a certain column, the higher that columns selectivity. Place the most selective fields at the beginning of the index. Your secondary index should be so selective that each index entry corresponds to at most five percent of the table entries. If this is not the case, it is not worth creating the index. You should also avoid creating indexes for fields that are not always filled, where their value is initial for most entries in the table.
If all of the columns in the SELECT clause are contained in the index, the system does not have to search the actual table data after reading from the index. If you have a SELECT clause with very few columns, you can improve performance dramatically by including these columns in a secondary index.
Formulating Conditions for Indexes
You should bear in mind the following when formulating conditions for the WHERE and HAVING clauses so that the system can use a database index and does not have to use a full table scan.
Check for Equality and Link Using AND
The database index search is particularly efficient if you check all index fields for equality (= or EQ) and link the expressions using AND.
Use Positive Conditions
The database system only supports queries that describe the result in positive terms, for example, EQ or LIKE. It does not support negative expressions like NE or NOT LIKE.
If possible, avoid using the NOT operator in the WHERE clause, because it is not supported by database indexes; invert the logical expression instead.
Using OR
The optimizer usually stops working when an OR expression occurs in the condition. This means that the columns checked using OR are not included in the index search. An exception to this are OR expressions at the outside of conditions. You should try to reformulate conditions that apply OR expressions to columns relevant to the index, for example, into an IN condition.
Using Part of the Index
If you construct an index from several columns, the system can still use it even if you only specify a few of the columns in a condition. However, in this case, the sequence of the columns in the index is important. A column can only be used in the index search if all of the columns before it in the index definition have also been specified in the condition.
Checking for Null Values
The IS NULL condition can cause problems with indexes. Some database systems do not store null values in the index structure. Consequently, this field cannot be used in the index.
Avoid Complex Conditions
Avoid complex conditions, since the statements have to be broken down into their individual components by the database system.
Reduce the Database Load
Unlike application servers and presentation servers, there is only one database server in your system. You should therefore aim to reduce the database load as much as possible. You can use the following methods:
Buffer Tables on the Application Server
You can considerably reduce the time required to access data by buffering it in the application server table buffer. Reading a single entry from table T001 can take between 8 and 600 milliseconds, while reading it from the table buffer takes 0.2 - 1 milliseconds.
Whether a table can be buffered or not depends its technical attributes in the ABAP Dictionary. There are three buffering types:
Resident buffering (100%) The first time the table is accessed, its entire contents are loaded in the table buffer.
Generic buffering In this case, you need to specify a generic key (some of the key fields) in the technical settings of the table in the ABAP Dictionary. The table contents are then divided into generic areas. When you access data with one of the generic keys, the whole generic area is loaded into the table buffer. Client-specific tables are often buffered generically by client.
Partial buffering (single entry) Only single entries are read from the database and stored in the table buffer.
When you read from buffered tables, the following happens:
1. An ABAP program requests data from a buffered table.
2. The ABAP processor interprets the Open SQL statement. If the table is defined as a buffered table in the ABAP Dictionary, the ABAP processor checks in the local buffer on the application server to see if the table (or part of it) has already been buffered.
3. If the table has not yet been buffered, the request is passed on to the database. If the data exists in the buffer, it is sent to the program.
4. The database server passes the data to the application server, which places it in the table buffer.
5. The data is passed to the program.
When you change a buffered table, the following happens:
1. The database table is changed and the buffer on the application server is updated. The database interface logs the update statement in the table DDLOG. If the system has more than one application server, the buffer on the other servers is not updated at once.
2. All application servers periodically read the contents of table DDLOG, and delete the corresponding contents from their buffers where necessary. The granularity depends on the buffering type. The table buffers in a distributed system are generally synchronized every 60 seconds (parameter: rsdisp/bufreftime).
3. Within this period, users on non-synchronized application servers will read old data. The data is not recognized as obsolete until the next buffer synchronization. The next time it is accessed, it is re-read from the database.
You should buffer the following types of tables:
Tables that are read very frequently
Tables that are changed very infrequently
Relatively small tables (few lines, few columns, or short columns)
Tables where delayed update is acceptable.
Once you have buffered a table, take care not to use any Open SQL statements that bypass the buffer.
The SELECT statement bypasses the buffer when you use any of the following:
The BYPASSING BUFFER addition in the FROM clause
The DISTINCT addition in the SELECT clause
Aggregate expressions in the SELECT clause
Joins in the FROM clause
The IS NULL condition in the WHERE clause
Subqueries in the WHERE clause
The ORDER BY clause
The GROUP BY clause
The FOR UPDATE addition
Furthermore, all Native SQL statements bypass the buffer.
Avoid Reading Data Repeatedly
If you avoid reading the same data repeatedly, you both reduce the number of database accesses and reduce the load on the database. Furthermore, a "dirty read" may occur with database tables other than Oracle. This means that the second time you read data from a database table, it may be different from the data read the first time. To ensure that the data in your program is consistent, you should read it once only and then store it in an internal table.
Sort Data in Your ABAP Programs
The ORDER BY clause in the SELECT statement is not necessarily optimized by the database system or executed with the correct index. This can result in increased runtime costs. You should only use ORDER BY if the database sort uses the same index with which the table is read. To find out which index the system uses, use SQL Trace in the ABAP Workbench Performance Trace. If the indexes are not the same, it is more efficient to read the data into an internal table or extract and sort it in the ABAP program using the SORT statement.
Use Logical Databases
SAP supplies logical databases for all applications. A logical database is an ABAP program that decouples Open SQL statements from application programs. They are optimized for the best possible database performance. However, it is important that you use the right logical database. The hierarchy of the data you want to read must reflect the structure of the logical database, otherwise, they can have a negative effect on performance. For example, if you want to read data from a table right at the bottom of the hierarchy of the logical database, it has to read at least the key fields of all tables above it in the hierarchy. In this case, it is more efficient to use a SELECT statement.
Work Processes
Work processes execute the individual dialog steps in R/3 applications. The next two sections describe firstly the structure of a work process, and secondly the different types of work process in the R/3 System.
Structure of a Work Process
Work processes execute the dialog steps of application programs. They are components of an application server. The following diagram shows the components of a work process:
Each work process contains two software processors and a database interface.
Screen Processor
In R/3 application programming, there is a difference between user interaction and processing logic. From a programming point of view, user interaction is controlled by screens. As well as the actual input mask, a screen also consists of flow logic. The screen flow logic controls a large part of the user interaction. The R/3 Basis system contains a special language for programming screen flow logic. The screen processor executes the screen flow logic. Via the dispatcher, it takes over the responsibility for communication between the work process and the SAPgui, calls modules in the flow logic, and ensures that the field contents are transferred from the screen to the flow logic.
ABAP Processor
The actual processing logic of an application program is written in ABAP - SAPs own programming language. The ABAP processor executes the processing logic of the application program, and communicates with the database interface. The screen processor tells the ABAP processor which module of the screen flow logic should be processed next. The following screen illustrates the interaction between the screen and the ABAP processors when an application program is running.
Database Interface
The database interface provides the following services:
Establishing and terminating connections between the work process and the database.
Access to database tables
Access to R/3 Repository objects (ABAP programs, screens and so on)
Access to catalog information (ABAP Dictionary)
Controlling transactions (commit and rollback handling)
Table buffer administration on the application server.
The following diagram shows the individual components of the database interface:
The diagram shows that there are two different ways of accessing databases: Open SQL and Native SQL.
Open SQL statements are a subset of Standard SQL that is fully integrated in ABAP. They allow you to access data irrespective of the database system that the R/3 installation is using. Open SQL consists of the Data Manipulation Language (DML) part of Standard SQL; in other words, it allows you to read (SELECT) and change (INSERT, UPDATE, DELETE) data. The tasks of the Data Definition Language (DDL) and Data Control Language (DCL) parts of Standard SQL are performed in the R/3 System by the ABAP Dictionary and the authorization system. These provide a unified range of functions, irrespective of database, and also contain functions beyond those offered by the various database systems.
Open SQL also goes beyond Standard SQL to provide statements that, in conjunction with other ABAP constructions, can simplify or speed up database access. It also allows you to buffer certain tables on the application server, saving excessive database access. In this case, the database interface is responsible for comparing the buffer with the database. Buffers are partly stored in the working memory of the current work process, and partly in the shared memory for all work processes on an application server. Where an R/3 System is distributed across more than one application server, the data in the various buffers is synchronized at set intervals by the buffer management. When buffering the database, you must remember that data in the buffer is not always up to date. For this reason, you should only use the buffer for data which does not often change.
Native SQL is only loosely integrated into ABAP, and allows access to all of the functions contained in the programming interface of the respective database system. Unlike Open SQL statements, Native SQL statements are not checked and converted, but instead are sent directly to the database system. Programs that use Native SQL are specific to the database system for which they were written. R/3 applications contain as little Native SQL as possible. In fact, it is only used in a few Basis components (for example, to create or change table definitions in the ABAP Dictionary).
The database-dependent layer in the diagram serves to hide the differences between database systems from the rest of the database interface. You choose the appropriate layer when you install the Basis system. Thanks to the standardization of SQL, the differences in the syntax of statements are very slight. However, the semantics and behavior of the statements have not been fully standardized, and the differences in these areas can be greater. When you use Native SQL, the function of the database-dependent layer is minimal.
Types of Work Process
Although all work processes contain the components described above, they can still be divided into different types. The type of a work process determines the kind of task for which it is responsible in the application server. It does not specify a particular set of technical attributes. The individual tasks are distributed to the work processes by the dispatcher.
Before you start your R/3 System, you determine how many work processes it will have, and what their types will be. The dispatcher starts the work processes and only assigns them tasks that correspond to their type. This means that you can distribute work process types to optimize the use of the resources on your application servers.
The following diagram shows again the structure of an application server, but this time, includes the various possible work process types:
The various work processes are described briefly below. Other parts of this documentation describe the individual components of the application server and the R/3 System in more detail.
Dialog Work Process
Dialog work processes deal with requests from an active user to execute dialog steps.
Update Work Process
Update work processes execute database update requests. Update requests are part of an SAP LUW that bundle the database operations resulting from the dialog in a database LUW for processing in the background.
Background Work Process
Background work processes process programs that can be executed without user interaction (background jobs).
Enqueue Work Process
The enqueue work process administers a lock table in the shared memory area. The lock table contains the logical database locks for the R/3 System and is an important part of the SAP LUW concept. In an R/3 System, you may only have one lock table. You may therefore also only have one application server with enqueue work processes.
Spool Work Process
The spool work process passes sequential datasets to a printer or to optical archiving. Each application server may contain several spool work process.
The services offered by an application server are determined by the types of its work processes. One application server may, of course, have more than one function. For example, it may be both a dialog server and the enqueue server, if it has several dialog work processes and an enqueue work process.
You can use the system administration functions to switch a work process between dialog and background modes while the system is still running. This allows you, for example, to switch an R/3 System between day and night operation, where you have more dialog than background work processes during the day, and the other way around during the night.
ABAP Application Server
R/3 programs run on application servers. They are an important component of the R/3 System. The following sections describe application servers in more detail.
Structure of an ABAP Application Server
The application layer of an R/3 System is made up of the application servers and the message server. Application programs in an R/3 System are run on application servers. The application servers communicate with the presentation components, the database, and also with each other, using the message server.
The following diagram shows the structure of an application server:
The individual components are:
Work Processes
An application server contains work processes, which are components that can run an application. Work processes are components that are able to execute an application (that is, one dialog step each). Each work process is linked to a memory area containing the context of the application being run. The context contains the current data for the application program. This needs to be available in each dialog step. Further information about the different types of work process is contained later on in this documentation.
Dispatcher
Each application server contains a dispatcher. The dispatcher is the link between the work processes and the users logged onto the application server. Its task is to receive requests for dialog steps from the SAP GUI and direct them to a free work process. In the same way, it directs screen output resulting from the dialog step back to the appropriate user.
Gateway
Each application server contains a gateway. This is the interface for the R/3 communication protocols (RFC, CPI/C). It can communicate with other application servers in the same R/3 System, with other R/3 Systems, with R/2 Systems, or with non-SAP systems.
The application server structure as described here aids the performance and scalability of the entire R/3 System. The fixed number of work processes and dispatching of dialog steps leads to optimal memory use, since it means that certain components and the memory areas of a work process are application-independent and reusable. The fact that the individual work processes work independently makes them suitable for a multi-processor architecture. The methods used in the dispatcher to distribute tasks to work processes are discussed more closely in the section Dispatching Dialog Steps.
Shared Memory
All of the work processes on an application server use a common main memory area called shared memory to save contexts or to buffer constant data locally.
The resources that all work processes use (such as programs and table contents) are contained in shared memory. Memory management in the R/3 System ensures that the work processes always address the correct context, that is the data relevant to the current state of the program that is running. A mapping process projects the required context for a dialog step from shared memory into the address of the relevant work process. This reduces the actual copying to a minimum.
Local buffering of data in the shared memory of the application server reduces the number of database reads required. This reduces access times for application programs considerably. For optimal use of the buffer, you can concentrate individual applications (financial accounting, logistics, human resources) into separate application server groups.
Database Connection
When you start up an R/3 System, each application server registers its work processes with the database layer, and receives a single dedicated channel for each. While the system is running, each work process is a user (client) of the database system (server). You cannot change the work process registration while the system is running. Neither can you reassign a database channel from one work process to another. For this reason, a work process can only make database changes within a single database logical unit of work (LUW). A database LUW is an inseparable sequence of database operations. This has important consequences for the programming model explained below.
Dispatching Dialog Steps
The number of users logged onto an application server is often many times greater than the number of available work processes. Furthermore, it is not restricted by the R/3 system architecture. Furthermore, each user can run several applications at once. The dispatcher has the important task of distributing all dialog steps among the work processes on the application server.
The following diagram is an example of how this might happen:
1. The dispatcher receives the request to execute a dialog step from user 1 and directs it to work process 1, which happens to be free. The work process addresses the context of the application program (in shared memory) and executes the dialog step. It then becomes free again.
2. The dispatcher receives the request to execute a dialog step from user 2 and directs it to work process 1, which is now free again. The work process executes the dialog step as in step 1.
3. While work process 1 is still working, the dispatcher receives a further request from user 1 and directs it to work process 2, which is free.
4. After work processes 1 and 2 have finished processing their dialog steps, the dispatcher receives another request from user 1 and directs it to work process 1, which is free again.
5. While work process 1 is still working, the dispatcher receives a further request from user 2 and directs it to work process 2, which is free.
From this example, we can see that:
A dialog step from a program is assigned to a single work process for execution.
The individual dialog steps of a program can be executed on different work processes, and the program context must be addressed for each new work process.
A work process can execute dialog steps of different programs from different users.
The example does not show that the dispatcher tries to distribute the requests to the work processes such that the same work process is used as often as possible for the successive dialog steps in an application. This is useful, since it saves the program context having to be addressed each time a dialog step is executed.
Dispatching and the Programming Model
The separation of application and presentation layer made it necessary to split up application programs into dialog steps. This, and the fact that dialog steps are dispatched to individual work processes, has had important consequences for the programming model.
As mentioned above, a work process can only make database changes within a single database logical unit of work (LUW). A database LUW is an inseparable sequence of database operations. The contents of the database must be consistent at its beginning and end. The beginning and end of a database LUW are defined by a commit command to the database system (database commit). During a database LUW, that is, between two database commits, the database system itself ensures consistency within the database. In other words, it takes over tasks such as locking database entries while they are being edited, or restoring the old data (rollback) if a step terminates in an error.
A typical SAP application program extends over several screens and the corresponding dialog steps. The user requests database changes on the individual screens that should lead to the database being consistent once the screens have all been processed. However, the individual dialog steps run on different work processes, and a single work process can process dialog steps from other applications. It is clear that two or more independent applications whose dialog steps happen to be processed on the same work process cannot be allowed to work with the same database LUW.
Consequently, a work process must open a separate database LUW for each dialog step. The work process sends a commit command (database commit) to the database at the end of each dialog step in which it makes database changes. These commit commands are called implicit database commits, since they are not explicitly written into the application program.
These implicit database commits mean that a database LUW can be kept open for a maximum of one dialog step. This leads to a considerable reduction in database load, serialization, and deadlocks, and enables a large number of users to use the same system.
However, the question now arises of how this method (1 dialog step = 1 database LUW) can be reconciled with the demand to make commits and rollbacks dependent on the logical flow of the application program instead of the technical distribution of dialog steps. Database update requests that depend on one another form logical units in the program that extend over more than one dialog step. The database changes associated with these logical units must be executed together and must also be able to be undone together.
The SAP programming model contains a series of bundling techniques that allow you to group database updates together in logical units. The section of an R/3 application program that bundles a set of logically-associated database operations is called an SAP LUW. Unlike a database LUW, a SAP LUW includes all of the dialog steps in a logical unit, including the database update.
Happy Reading...
shibu -
Error while data shifting from one table to another table
i have two tables.
in one table i dont have constraints.in anothe rtable i have constraints.
my requiremnt is i have to shift data from unconstrained table to constrained table
while shifting data any constaint violation is there system hasto raise error by specifying the error
in below example it should be ename,esal values not null.
i tried with save exception but it gives only error.i want error by mentiong that column names also ie ename,esal is not null
if ename value only null then it should be give ename is null
create table tablea (eno number(10), ename varchar2(20) not null, esal number(5) not null)
create table tabl (eno number(10), ename varchar2(20) , esal number(5) )
DECLARE
TYPE tabl_tab IS TABLE OF tabl%rowTYPE;
tab tabl_tab;
-- create an exception handler for ORA-24381
ERRORS NUMBER;
dml_errors EXCEPTION;
PRAGMA EXCEPTION_INIT (dml_errors, -24381);
BEGIN
SELECT *
BULK COLLECT INTO tab
FROM tabl
WHERE rownum<=2;
-- add '_SR' to the job_id of the most senior employees
FORALL i IN tab.FIRST .. tab.LAST SAVE EXCEPTIONS
insert into tablea values tab(i);
EXCEPTION
WHEN dml_errors
THEN
rollback ; --roll backs all the good records updation
-- Now we figure out what failed and why.
ERRORS := SQL%BULK_EXCEPTIONS.COUNT;
DBMS_OUTPUT.put_line ('Number of statements that failed: ' || ERRORS);
FOR i IN 1 .. ERRORS
LOOP
DBMS_OUTPUT.put_line ( 'Error #'
|| i
|| ' occurred during '
|| 'iteration #'
|| SQL%BULK_EXCEPTIONS (i).ERROR_INDEX
DBMS_OUTPUT.put_line ( 'Error message is '
|| SQLERRM
(-SQL%BULK_EXCEPTIONS (i).ERROR_CODE)
END LOOP;
END;
how to implement that.it should give error as ename column is not null
-
Data Loading from one table to another in the Same Database based on conditions .
Hi ALL ,
I have 2 tables Products and Product_info .
Product_info table Product_id is Primary key but not an identity column so auto increment of number needs to be performed from the Package only .
Requirement is :
IF the Product_ID is = 20 and Date lies in the previous month not the current month in the Products table then
insert into the Product_info table based on below mentioned information .
1.If the Name has tap then ignore it completely don't perform any insert for it.
2.If the Name has Zork in it then perform 2 inserts in the Product_info table having Product_info_id's 1 and 2 .
3.If the Name doesn't contains Zork or tap insert it in the Product_info table having Product_info_id 4.
Very new to SSIS package development it will be helpful if you can provide detailed information .
Source Table (Products table )
ID
NAME
Product_ID
Date
Area_ID
1
P_tap_rus
20
13-01-2014
3
2
Enc_sap_top
10
15-01-2014
4
3
Yorl
20
05-02-2014
5
4
zork
20
20-01-2014
6
5
fadbt
10
22-01-2014
6
6
xyzzz_oprt
20
28-01-2014
5
7
def_type_ru
20
06-02-2014
2
8
acd_inc_tup
10
07-02-2014
3
9
bnf_dlk_fbg
20
03-02-2014
4
10
rtyui_vnmghj_sfdl
10
12-01-2014
5
11
wlwf_10103_123
10
04-02-2014
9
Destination table (Product_info)
Porduct_ID
ID
Area_ID
Product_info_ID
Column1
1
3
5
4
As NameString doesn’t contain Zork or Tap
2
4
3
1
As Id is 4 so 2 inserts one for 1 and other for 2 in the Product_info_id column
3
4
3
2
4
6
5
4
5
10
5
4
6
11
9
4
Please let me know if any other information is required .
Thanks
PriyaHi Priya,
You mentioned this was coming from two tables right? I believe I would try to perform the transformations with T-SQL in my source (If this is a possibility for you). Below is an example of something you could do.
WITH CTE
AS
SELECT ID, Product_ID, [Date], Area_ID,
CASE
WHEN Name like '%Zork%' THEN 1
ELSE 4
END AS Product_Info_ID
FROM [YourTable]
WHERE Product_ID = 20 and MONTH([DATE]) = MONTH(DATEADD(MM, -1, GETDATE())) AND NAME NOT LIKE '%tap%'
SELECT *
FROM CTE
UNION
SELECT ID, Product_ID, [Date], Area_ID, '2' AS Product_Info_ID
FROM CTE WHERE Product_Info_ID = 1
I hope this helps, Regards. -
How to check which column data differs from master table and archive table
Hi All,
i have two tables, table a (a1 number,a2 varchar2,a3 varchar2) and table b (b1 number,b2 varchar2,b3 varchar2).
how to check the data in both the table are same( including all columns).
data in a.a1 is same as b.b1 and a.a2 is same as b.b2 like that.
if they not same , i need to know which field differs.
Kindly Share ur ideas.887268 wrote:
thanks Sven W. ,
above reply clearly shows what my question is.
one column must be primary key, based on that key i need to find out which are the fields having different data..
im strugling with this, i tried the following already, but not able to get.
select the columns from a MINUS select the columns from b.
-- from this i can find whether the difference occurred or not.
but i cant able to get which are the fields value changed.Good. Then you would match the rows using the PK column and need to compare the columns
Instead of a MINUS + UNION ALL + MINUS we can now use a FULL OUTER JOIN
It is a little task to write out all column names, but 40 columns can be handled.
This statement would show you both tables with matching rows on the same line.
select a.*, b.*
from a
FULL OUTER JOIN b on a.id = b.idNow filter/check for mismatches
select case when a.col1 != b.col1 then 'COL1 value changed'
when a.col2 != b.col2 then 'COL2 value changed'
when a.col3 != b.col3 then 'COL3 value changed'
end as compare_result
,a.*, b.*
from a
FULL OUTER JOIN b on a.id = b.id
/* return only non matching columns */
where (a.col1,a.col2,a.col3) != (b.col1,b.col2,b.col3) You might need to add nvls to take care of null values. Test this!
Another way could be to group upon the primary key
select *
from (
select id
,count(distinct col1)-1 cnt_col1
,count(distinct col2)-1 cnt_col2
,count(distinct col3)-1 cnt_col3
from
select 'A' source, a.*
from a
UNION ALL
select 'B' source, b.*
from b)
group by ID
/* only records with differences */
where 1 in (cnt_col1, cnt_col2, cnt_col3)
;The count columns will hold either 1 or 0. If it is 1 then this column has a difference.
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