How data is written in table

Hi All,
I have a table which contains 2 main columns apart from other columns. These two columns are REC_ID and ENTRY_DATE_TIME.
In this table data is inserted through a data load process using SQL Loader. REC_ID is populated to table through a sequence and ENTRY_DATE_TIME is populated as a sysdate.
select rec_id, to_char(entry_date_time, 'dd-mon-yyyy hh24:mi:ss') entry_date_time from itpcs_grt_oa_tran_rdpk_stock order by 1;
REC_ID ENTRY_DATE_TIME
1     12-oct-2012 07:06:23
2     12-oct-2012 07:06:31
3     12-oct-2012 07:06:35
4     12-oct-2012 07:06:21
5     12-oct-2012 07:06:32
If we see the data, then time for REC_ID 4 is less than REC_ID 3.
Now the question is if REC_ID is populated through a sequence then sequence 3 must have been created before REC_ID 4 and if so then why the ENRTY_DATE_TIME of REC_ID 4 is less than REC_ID 3.
Further to the question, Can anyone please explain me how data is written in tables. What steps are performed by at database level when we any DML(insert) is performed.
My DB Version : Oracle Database 11g Enterprise Edition Release 11.2.0.2.0 - 64bit

583003 wrote:
Hi All,
I have a table which contains 2 main columns apart from other columns. These two columns are REC_ID and ENTRY_DATE_TIME.
In this table data is inserted through a data load process using SQL Loader. REC_ID is populated to table through a sequence and ENTRY_DATE_TIME is populated as a sysdate.
select rec_id, to_char(entry_date_time, 'dd-mon-yyyy hh24:mi:ss') entry_date_time from itpcs_grt_oa_tran_rdpk_stock order by 1;
REC_ID ENTRY_DATE_TIME
1     12-oct-2012 07:06:23
2     12-oct-2012 07:06:31
3     12-oct-2012 07:06:35
4     12-oct-2012 07:06:21
5     12-oct-2012 07:06:32
If we see the data, then time for REC_ID 4 is less than REC_ID 3.
Now the question is if REC_ID is populated through a sequence then sequence 3 must have been created before REC_ID 4 and if so then why the ENRTY_DATE_TIME of REC_ID 4 is less than REC_ID 3.
Further to the question, Can anyone please explain me how data is written in tables. What steps are performed by at database level when we any DML(insert) is performed.
My DB Version : Oracle Database 11g Enterprise Edition Release 11.2.0.2.0 - 64bitdoes DB reside in/on RAC?
Note that REC_ID 4 has a timestamp before all REC_ID 1 - 3.

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Thank you.

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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.).
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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

How to get common datas from two int.tables

hi,
please tell me , how to i will get the common datas between two int. tables
& place them in third int. table.
give me syntax.
regards
subhasis.

Hi Subhasis,
<b>SORT :</b></u>
SORT itab.
Extras:
1. ... BY f1 f2 ... fn
2. ... ASCENDING
3. ... DESCENDING
4. ... AS TEXT
5. ... STABLE
The syntax check performed in an ABAP Objects context is stricter than in other ABAP areas. See Field symbols not allowed as sort criterion.
Effect
The entries in the internal table are sorted in ascending order using the key from the table definition (DATA, TYPES).
Addition 1
... BY f1 f2 ... fn
Effect
Uses the sort key defined by the sub-fields f1, f2, ..., fn of the table itab instead of the table key. The fields can be of any type; even number fields and tables are allowed.
You can also specify the sort fields dynamically in the form (name). If name is blank at runtime, the sort field is ignored. If itab is a table with a header line, you can also use a field symbol pointing to the header line of itab as a dynamic sort criterion. A field symbol that is not assigned is ignored. If a field symbol is assigned, but does not point to the header line of the internal table, a runtime error occurs.
If the line type of the internal table contains object reference variables as components, or the entire line type is a reference variable, you can use the attributes of the object to which a reference is pointing in a line as sort criteria (see Attributes of Objects as the Key of an Internal Table.
You can address the entire line of an internal table as the key using the pseudocomponent TABLE_LINE. This is particularly relevant for tables with a non-structured line type when you want to address the whole line as the key of the table (see also Pseudocomponent TABLE_LINE With Internal Tables).
If you use one of the additions 2 to 5 before BY, it applies to all fields of the sort key by default. You can also specify these additions after each individual sort field f1, f2, ..., fn. For each key field, this defines an individual sort rule which overrides the default.
Addition 2
... ASCENDING
Effect
Sorts in ascending order. This is also the default if no sort order is specified directly after SORT. For this reason, it is not necessary to specify ASCENDING explicitly as the default sort order.
With the addition BY, you can also specify ASCENDING directly after a sort field to define ascending order explicitly as the sort sequence for this field.
Addition 3
... DESCENDING
Effect
Sorts in descending order. If the addition comes right after SORT, DESCENDING is taken as the default for all fields of the sort key.
With the addition BY, you can also specify DESCENDING directly after a sort field.
Addition 4
... AS TEXT
Effect
Text fields are sorted appropriate to the locale. This means that the relative order of characters is defined according to the text environment being used.
When an internal mode is opened (in other words, when a roll area is opened), the text environment is automatically set to the logon language specified in the user master record. If necessary, however, you can change the text environment explicitly in your program by using a SET-LOCALE statement.
If the addition comes directly after itab, locale-specific rules are used for all fields of the sort key where the type of these fields is C or W. After the sort, the sequence of entries usually does not match the sequence which results otherwise, without using the addition AS TEXT, i.e. with binary sorting.
With the addition BY, you can also specify AS TEXT directly after a sort field, provided it is of type C or W, or a structured type. Otherwise, a runtime error occurs. In sort fields with a structured type, AS TEXT only affects subcomponents with type C or W.
In case of an invalid character, a SYSLOG message is written, and the respective record is inserted at the end.
Note
Please keep the rules for site-specific sorting in mind.
Example
Sort a name table with different keys:
TYPES: BEGIN OF PERSON_TYPE,
         NAME(10)   TYPE C,
         AGE        TYPE I,
         COUNTRY(3) TYPE C,
       END OF PERSON_TYPE.
DATA: PERSON TYPE STANDARD TABLE OF PERSON_TYPE WITH
                  NON-UNIQUE DEFAULT KEY INITIAL SIZE 5,
      WA_PERSON TYPE PERSON_TYPE.
WA_PERSON-NAME    = 'Muller'. WA_PERSON-AGE = 22.
WA_PERSON-COUNTRY = 'USA'.
APPEND WA_PERSON TO PERSON.
WA_PERSON-NAME    = 'Moller'. WA_PERSON-AGE = 25.
WA_PERSON-COUNTRY = 'FRG'.
APPEND WA_PERSON TO PERSON.
WA_PERSON-NAME    = 'Möller'. WA_PERSON-AGE = 22.
WA_PERSON-COUNTRY = 'USA'.
APPEND WA_PERSON TO PERSON.
WA_PERSON-NAME    = 'Miller'. WA_PERSON-AGE = 23.
WA_PERSON-COUNTRY = 'USA'.
APPEND WA_PERSON TO PERSON.
SORT PERSON.
Now, the sequence of the table entries is as follows:
Miller 23 USA
Moller 25 FRG
Muller 22 USA
Möller 22 USA
If, for example, you apply German sort rules where the umlaut comes directly after the letter 'o' in the sort, the data record beginning with 'Möller' would not be in the right place in this sequence. It should come second.
Provided a German-language locale is set (e.g. sorting is according to German grammatical rules, see also SET LOCALE), you can sort the names according to German rules as follows:
SORT PERSON BY NAME AS TEXT.
Now, the sequence of table entries is as follows:
Miller 23 USA
Moller 25 FRG
Möller 22 USA
Muller 22 USA
Further examples:
SORT PERSON DESCENDING BY COUNTRY AGE NAME.
Now, the sequence of table entries is as follows:
Miller 23 USA
Möller 22 USA
Muller 22 USA
Moller 25 FRG
SORT PERSON DESCENDING BY AGE ASCENDING NAME AS TEXT.
Now, the sequence of table entries is as follows:
Muller 22 USA
Möller 22 USA
Miller 23 USA
Moller 25 FRG
Addition 5
... STABLE
Effect
Uses a stable sort, that is, the relative sequence of entries that have the same sort key remains unchanged.
Unlike additions 2 to 4, you cannot use this addition directly after a sort field.
Notes
General:
The number of sort fields is restricted to 250.
The sort process is only stable if you use the STABLE addition. Otherwise, a predefined sequence of fields used to sort a list is not usually retained.
It does not make sense to use the SORT command for a SORTED TABLE. If the table type is statically declared, the system returns a syntax error if you try to SORT the table. If the table type is not statically declared (for example, because the table was passed to a FORM routine as an INDEX TABLE in a parameter), and the system can interpret the SORT statement as an empty operation, it ignores the statement. This is the case when the key in the BY clause corresponds to the beginning of the table key. Otherwise, a runtime error occurs.
To delete all duplicate entries from a sorted internal table (e.g. just after SORT), you can use the DELETE ADJACENT DUPLICATES FROM itab statement.
When using the addition AS TEXT, the sequence of entries after the sort does not usually match the sequence resulting from a binary sort, i.e. if the addition AS TEXT is not specified. The consequence of this is that after the SORT, you are not allowed to access with the READ TABLE itab ... BINARY SEARCH statement.
If you still want to access data sorted apppropriate to the locale with a binary search, you can do this by including an additional component in the table where you can explictly store the data formatted using the CONVERT TEXT ... INTO SORTABLE CODE statement. This is also recommended for performance reasons if you have to re-sort the table several times according to locale-specific criteria.
If the internal table has more than 2^19 lines or is larger than 12 MB, the system sorts it physically using an external auxiliary file. You can specify the directory in which the file should be created using the SAP profile parameter DIR_SORTTMP. By default, the system uses the SAP data directory (SAP profile parameter DIR_DATA).
Notes
Performance:
The runtime required to sort an internal table increases with the number of entries and the length of the sort key.
Sorting an internal table with 100 entries with a 50 byte key requires about 1300 msn (standardized microseconds). Using a 30-byte key, the runtime is about 950 msn.
If one of the specified sort criteria is itself an internal table, SORT may sometimes take much longer.
The runtime increases if you use a stable sort.
Physical sorting reduces the runtime required for subsequent sequential processing.
Reward If Useful.
Regards,
Chitra

How to load text file data to Oracle Database table?

By using Oracle Forms, how to load text file data to Oracle Database table?

Metalink note 33247.1 explains how to use text_io as suggested by Robin to read the file into a Multi-Row block. However, that article was written for forms 4.5 and uses CREATE_RECORD in a loop. There was another article, 91513.1 describing the more elegant method of 'querying' the file into the block by transactional triggers. Unfortunately this more recent article has disappeared without trace and Oracle deny its existence. I know it existed as I have a printed copy in front of me, and very useful it is too.

How to get the data from a cluster table to BW

Dear All,
I want to extract the data from R/3 to BW by using 2 tables and one Cluster B2.
Actually my report contains some fields from PA2001, PA2002 and one cluster table B2 (Table ZES). Can I create View by using these 3 tables? If it is not possible how can I get the data from the cluster? Can I create generic datasource by using cluster tables directly?
In SE11 Transaction the Cluster (table ZES) is showing invalid table.
I referred some Forums, but no use.
Can any body tell me procedure to get the data from a cluster (table ZES) ?
Waiting for you results.
Thanks and regards
Rajesh

HI Siggi,
Thank you for your reply..
I am also planning to do FM to get the data. But it is saying that the Cluster table ZES does not exist (ZES is the the standard table, in SE11 also).
How can I use the Fields from the that table.?
What can I do now, can you please explain me about this point.
Waiting for your reply.
Thanks and Regards
Rajesh
Message was edited by:
rajesh

How to pass the data from a input table to RFC data service?

Hi,
I am doing a prototype with VC, I'm wondering how VC pass the data from a table view to a backend data service? For example, I have one RFC in the backend system with a tabel type importing parameter, now I want to pass all the data from an input table view to the RFC, I guess it's possible but I don't know how to do it.
I try to create some events between the input table and data service, but seems there is no a system event can export the whole table to the backend data service.
Thanks for your answer.

Thanks for your answer, I tried the solution 2, I create "Submit" button, and ser the mapping scope to be "All data rows", it only works when I select at least one row, otherwise the data would not be passed.
Another question is I have serveral imported table parameter, for each table I have one "submit" event, I want these tables to be submitted at the same time, but if I click the submit button in one table toolbar, I can only submit the table data which has a submit button clicked, for other tables, the data is not passed, how can I achieve it?
Thanks.

How to populate data in the same table based on different links/buttons

Hi
I'm using jdeveloper 11.1.4. I have a use case in which i need to populate data in the same table based on click of different links.
Can anyone please suggest how can this be achieved.
Thanks

I have a use case in which i need to populate data in the same table based on click of different linksDo you mean that you need to edit existing rows ?
What format do you have the date in - table / form ?

How can I join 3 tables while extracting data from SAP R/3?

I have 3 tables with the following columns
Emp table (emp)
emp_id
emp_name
emp_add
Dept table (dept)
dept_id
dept_name
dept_loc
Location table (loc)
loc_id
loc_name
Now. If I want to select data from loc_id = 10 and emp_id between 2000 and 3000
How to join these three tables while extracting data from R/3
join condition
loc.loc_id = dept.loc_id
and dept.dept_id = emp.dept_id
and loc.loc_id =10
and emp.emp_id between 2000 and 3000.
Could any one let me know the procedure to extract this data into BW system.

Hi,
shouldn't your join condition be:
loc.loc_id = dept.DEPT_LOC
and dept.dept_id = ??
If you can join the three tables then create a generic datasource (RSO) based on a view (create your view with your join in SE11).
Enable the loc_id and the emp_id as selectable in the datasource so you can then select the values from a BW IPack.
hope this helps...
Olivier.

How to insert data into the mysql table by giving as a text file

Hi,
Any one know's how to insert data into the mysql table by giving as a text file as the input in JSP.Please respond ASAP.
Thanks:)

At least you can try StringTokenizer to parse your text files. Or download a text JDBC driver to parse your files, for instance, HXTT Text(www.hxtt.net) or StelsCSV(www.csv-jdbc.com).

How can I modify data from a Transparent Table without ABAP code.

Hi,All
How can I modify data from a Transparent Table (like TCURR), and important thing is I want do all that with no ABAP code here. It is like that we always do that in a Oracle database use TOAD or PLSQL third party tools, with no script code here.
I had fond that there is a way can do that:
1, type 'se11',and Display Database table 'TCURR', click Contents, then click Execute to display all data
2, type '/h' and let debugging on
3, select one of this data then click 'Display',enter in debugging system.
4, then make a breakpoint in the code. But... display a dialog let I type a 'ABAP Cmnds', I want to know what can be type in for that?
and, My system is ECC6.
thank you all
Edited by: xuehui li on Aug 20, 2008 6:30 PM

Hello,
Your approach (with Vijay's suggestion) MAY work. However, depending on how tight security is at the company that you are working at you may or may not be able to acutaly change the value of the SHOW field to EDIT. This will be especially true if you are working in a Production environment. Vijay's other comment is true as well. This is not a recommended approach to change data (especially data with a financial impact like TCURR) in a production environment. The auditors will not be impressed.
Explore the option of a maintenace view or look at tcode TBDM to upload a file which includes daily rates from providers like Reuters or try tcode s_bce_68000174 which is a maintenance view on TCURR.
Regards
Greg Kern

How to insert row in table control and save the data in tables

Hi,
I have one table control i am displaying data into table control ,
my problem is : i want to display data into read mode in table control.
but when i click on insert button on the same screen i want one blank line should inserted into table control , then i want to insert some data into table control on that row , when i click the save button . the new data inserted into the table control is insert that data into ztable ,
please give me solution
main problen is how can know inserted line in table control and pass that data into ztable.

Hi,
Follow the below logic,
PROCESS BEFORE OUTPUT.
MODULE STATUS_0001.
MODULE POPULATE_TABLE_CONTROL. --> Get the data from table store in
                                                                      ITAB
LOOP AT GT_CTRL_LP_D516 INTO GS_WA_CTRL_LP_D516
       WITH CONTROL CTRL_LP_D516
       CURSOR CTRL_LP_D516-CURRENT_LINE.
The following module moves data to control
    MODULE MOVE_TO_CONTROL.--> Move data from ITAB to table control
ENDLOOP.
PROCESS AFTER INPUT.
LOOP AT GT_CTRL_LP_D516.
ENDLOOP.
MODULE EXIT AT EXIT-COMMAND.
MODULE USER_COMMAND_0001. --> Here you have to take out the values from table control and update database table
Reward points if helpful.
Thanks and regards,
Mallareddy Rayapureddy,
Munich, Germany.

How to check the data in a temporary table

Hi,
A procedure inserting data into a temporary table , data exists in the table now. so, how to see the data from the temporary table. Is it possible to see from the sqlplus by selecting, right now i'm not getting any data. .thanks Bcj.

If you are referring to Global Temporary Tables, then the only way to see the contents of the table are to select from the table while connected to the same session that inserted the data into the GTT.
Please note however that there is not a 1 to 1 correspondence between sessions and users (shcemas). A user may be connected to 1 or more sessions, but it is only the session that inserted the records that will be able to view the records.

How can we delete the data in e-fact table.

how can we delete the data in e-fact table.

hii,
You cannot delete the request individually but you can one of the following:
1. Do a selective deletion from the cube. RSA1 -> Cube -> Contents -> selective deletion.
2. Delete all the data in the cube and then reconstruct only the required request ids. This would work only if you have the PSA available for all the requests.
3. Reverse posting is another possibility.
hope it helps,
partha

How can I filter a table from Data Control without enter query

I have a table from a web service data control based on WSDL.
I want to filter the table without input query at filter text box. Without filter text box, each would filter the table with a hardcoded query internally.
For example, when user click A menu button then it filters the table where type = '1' and B menu button filters the table by type='2' and C menu button filters the table by type=' ' .
How can I filter the table without enter query?
Could anyone point me to a solution please.
Thanks.
jdev 11.1.5
Edited by: 893364 on Oct 26, 2011 12:15 PM
Edited by: 893364 on Oct 26, 2011 12:21 PM

Hi,
when you created the table, did you try selecting the "filter" option. Select the table and go to the Property Inspctor. In the tool bar of the Property Inspector there is an icon to change the configuration. Its adding filter filter fields for the user to search in.
Option 2: The data of the Web Service actually is held in the iterators. If you wanted to filter the WebService query, I would not use the WS DC but a JAX-WS proxy in a POJO to fetch the WS Data. Then have the Data Control created from the POJO. You could have a method exposed on the POJO that allows you to filter the internally held data
Frank

How data is written in table

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