How to insert a row in Tree table which is dragged from the table?
Hi All,
I am having a Tree table and a Table in the same page, like below
Treetable Table
Item1 Subitem12
Subitem1 Subitem13
Subitem2 Subitem14
Subitem3 Subitem15
Subitem4 Subitem16
Item2 Subitem17
Subitem5 Subitem18
Subitem6 Subitem19
Subitem7 Subitem20
Subitem8 Subitem21
Item3
Subitem9
Subitem10
Subitem11
The requirement is i need to "drag" a row from the Table and place it under any parent node in the Tree table.
What i have done is I make the Tree table as ".ui-sortable" and table as a "draggable".
I am not able to find the position of the dragged item when i dropped it in the Treetable.
Please provide me a solution.
Regards,
Aravindh
Hello:
Do you mean setting the selectedRowKeys in the setter method of the treeTable in the Request Scoped Managed Bean?
If that is what you mean, I tried that and there was no change in behavior. (Still does not highlight the correct row in the tree table upon execution of the next method for the bindings) Does anyone have any sample code they can provide that works?
Thanks for the help.
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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 process each records in the derived table which i created using cte table using sql server
I want to process each row from the CTE table I created, how can I traverse from first row to second row and so on....
how to process each records in the derived table which i created using cte table using sql serverIdeally you would be doing a set based processing rather than traversing row by row as thats more efficient. To answer it specific to your scenario we may need more info. Can you explain with some sample data your exact requirement?
Please Mark This As Answer if it solved your issue
Please Mark This As Helpful if it helps to solve your issue
Visakh
My MSDN Page
My Personal Blog
My Facebook Page -
How to export some data from the tables of an owner with integrity?
Hi to all,
How to export some data from the tables of an owner with integrity?
I want to bring some data from all tables in a single owner of the production database for development environment.
My initial requirements are: seeking information on company code (emp), contract status (status) and / or effective date of contract settlement (dt_liq_efetiva) - a small amount of data to developers.
These three fields are present in the main system table (the table of contracts). Then I thought about ...
- create a temporary table from the query results table to contract;
- and then use this temporary table as a reference to fetch the data in other tables of the owner while maintaining integrity. But how? I have not found the answer, because: what to do when not there is the possibility of a join between the contract and any other table?
I am considering the possibility of consulting the names of tables, foreign keys and columns above, and create dynamic SQL. Conceptually, something like:
select r.constraint_name "FK name",
r.table_name "FK table",
r.column_name "FK column",
up.constraint_name "Referencing name",
up.table_name "Referencing table",
up.column_name "Referencing column"
from all_cons_columns up
join all_cons_columns r
using (owner, position), (select r.owner,
r.constraint_name fk,
r.table_name table_fk,
r.r_constraint_name r,
up.table_name table_r
from all_constraints up, all_constraints r
where r.r_owner = up.owner
and r.r_constraint_name = up.constraint_name
and up.constraint_type in ('P', 'U')
and r.constraint_type = 'R'
and r.owner = 'OWNERNAME') aux
where r.constraint_name = aux.fk
and r.table_name = aux.table_fk
and up.constraint_name = aux.r
and up.table_name = aux.table_r;
-- + Dynamic SQL
If anyone has any suggestions and / or reuse code to me thank you very much!
After resolving this standoff intend to mount the inserts in utl_file by a table and create another program to read and play in the development environment.
Thinking...
Let's Share!
My thanks in advance,
PhilipsThanks, Peter.
Well, I am working with release 9.2.0.8.0. But the planning is migrate to 10g this year. So my questions are:
With Data Pump can export data just from tables owned for me (SCHEMAS = MYOWNER) parameterizing the volume of data (SAMPLE) and filters to table (QUERY), right? But parameterizing a contract table QUERY = "WHERE status NOT IN (2,6) ORDER BY contract ":
1º- the Data Pump automatically searches for related data in other tables in the owner? ex. parcel table has X records related (fk) with Y contracts not in (2,6): X * SAMPLE records will be randomly exported?
2º- for the tables without relation (fk) and which are within the owner (MYOWNER) the data is exported only based on the parameter SAMPLE?
Once again, thank you,
Philips
Reading Oracle Docs... -
How to dispaly datas from the table, base on the selection screen
hi there gurus,
im currently developing a stock aging report,
i have completed one program but it do not allow me to excutes the program althought the syntax is correct.
i would to get some ideas from you, regarding how to extract the datas from the tables?
my selction screen will be, mat number, date, and gl account.
and the out put datas are, mbew-matnr, makt-maktx, mbew-lbkum, mara_meins, mbew-salk3,and the consumptions for the past 12months and the values for it.
can u plz guide me with this,
thank you,.
this is kind of very urgent program that i need to finish , plz help me.here is the total code the i do
REPORT ZSTK_AGING_REP2.
*TABLES
TABLES: mseg,
mara,
makt,
SKAT,
SKA1,
MARV,
T001,
T030,
T149D,
AM07M,
MCMSEG,
T001K,
T001W,
T134M,
vbak,
mbew,
mcon, rmcb0, marc, t024w, mvke, v134w, t438a, propf, maprf, t000, t024e
, tvko.
DATA: BEGIN OF ta_material OCCURS 2,
werks LIKE mard-werks,
lgort LIKE mard-lgort,
matnr LIKE mard-matnr,
labst LIKE mard-labst,
umlme LIKE mard-umlme,
insme LIKE mard-insme,
einme LIKE mard-einme,
speme LIKE mard-speme,
retme LIKE mard-retme,
verpr LIKE mbew-verpr,
maktx LIKE makt-maktx,
meins LIKE mara-meins,
bukrs LIKE t001-bukrs,
konto LIKE t030-konts,
butxt LIKE t001-butxt,
txt50 LIKE skat-txt50,
MABTR LIKE MCMSEG-DMBTR,
SKBTR LIKE MCMSEG-DMBTR,
WAERS LIKE T001-WAERS,
WAER2 LIKE T001-WAERS,
BWKEY LIKE MBEW-BWKEY,
LBKUM LIKE MBEW-LBKUM,
MEINS LIKE MARA-MEINS,
SALK3 LIKE MBEW-SALK3,
WAERS1 LIKE T001-WAERS,
BUKRS1 LIKE T001-BUKRS,
KONTO1 LIKE T030-KONTS,
lbkum LIKE mbew-lbkum,
erdat LIKE vbak-erdat,
END OF ta_material.
DATA: BEGIN OF ta_mseg OCCURS 2,
mblnr LIKE mseg-mblnr,
*->Begin of KL02+ -
mjahr like mseg-mjahr,
zeile like mseg-zeile,
*->End of KL02+ -
meins LIKE mseg-meins,
menge LIKE mseg-menge,
werks LIKE mseg-werks,
lgort LIKE mseg-lgort,
matnr LIKE mseg-matnr,
budat LIKE mkpf-budat,
saknr LIKE SKA1-SAKNR,
END OF ta_mseg.
single recs based on MATNR
DATA: BEGIN OF i_matnr OCCURS 0,
werks LIKE mard-werks,
lgort LIKE mard-lgort,
matnr LIKE mard-matnr,
maktx LIKE makt-maktx,
mblnr LIKE mseg-mblnr,
verpr LIKE mbew-verpr,
labst LIKE mard-labst, "Valuated stock with
*unrestricted use
umlme LIKE mard-umlme, "Stock in transfer
*(from one storage location to another)
insme LIKE mard-insme, "Stock in quality
*inspection
einme LIKE mard-einme, "Total Stock of All
*Restricted Batches
speme LIKE mard-speme, "Blocked stock
retme LIKE mard-retme, "Blocked Stock Returns
meins LIKE mara-meins, "base unit
bukrs LIKE t001-bukrs,
konto LIKE t030-konts,
butxt LIKE t001-butxt,
txt50 LIKE skat-txt50,
MABTR LIKE MCMSEG-DMBTR,
SKBTR LIKE MCMSEG-DMBTR,
WAERS LIKE T001-WAERS,
WAER2 LIKE T001-WAERS,
BWKEY LIKE MBEW-BWKEY,
LBKUM LIKE MBEW-LBKUM,
MEINS LIKE MARA-MEINS,
SALK3 LIKE MBEW-SALK3,
WAERS1 LIKE T001-WAERS,
BUKRS1 LIKE T001-BUKRS,
KONTO1 LIKE T030-KONTS,
lbkum LIKE mbew-lbkum,
END OF i_matnr.
recs based on MBLNR
DATA: BEGIN OF i_mblnr OCCURS 0,
mblnr LIKE mseg-mblnr,
werks LIKE mseg-werks,
lgort LIKE mseg-lgort,
matnr LIKE mseg-matnr,
menge LIKE mseg-menge,
meint LIKE mseg-meins,
budat LIKE mkpf-budat,
bukrs LIKE t001-bukrs,
konts LIKE t030-konts,
butxt LIKE t001-butxt,
txt50 LIKE skat-txt50,
MABTR LIKE MCMSEG-DMBTR,
SKBTR LIKE MCMSEG-DMBTR,
WAERS LIKE T001-WAERS,
WAER2 LIKE T001-WAERS,
BWKEY LIKE MBEW-BWKEY,
LBKUM LIKE MBEW-LBKUM,
MEINS LIKE MARA-MEINS,
SALK3 LIKE MBEW-SALK3,
WAERS1 LIKE T001-WAERS,
BUKRS1 LIKE T001-BUKRS,
KONTO1 LIKE T030-KONTS,
END OF i_mblnr.
TYPES: BEGIN OF t_mat,
lgort LIKE mseg-lgort,
werks LIKE mseg-werks,
matnr LIKE mseg-matnr,
mblnr LIKE mseg-mblnr,
maktx LIKE makt-maktx,
meins LIKE mara-meins,
meng0 LIKE mbew-lbkum,
value0 LIKE mbew-salk3,
meng0 LIKE mard-labst, "0 to 10 days
value0 LIKE mseg-dmbtr,
meng1 LIKE mard-labst, "11 to 30 days
value1 LIKE mseg-dmbtr,
meng2 LIKE mard-labst, "31 to 60 days
value2 LIKE mseg-dmbtr,
meng3 LIKE mard-labst, "61-90
value3 LIKE mseg-dmbtr,
meng4 LIKE mard-labst, "90 days onwards
value4 LIKE mseg-dmbtr,
END OF t_mat.
DATA: i_mat2 TYPE t_mat OCCURS 0 WITH HEADER LINE.
TYPES: BEGIN OF t_mat2,
lgort LIKE mard-lgort, " storage location
cnt0(5),
cnt1(5),
cnt2(5),
cnt3(5),
cnt4(5),
meng0 LIKE mbew-lbkum,
value0 LIKE mbew-salk3,
meng0 LIKE mard-labst, "0 to 10 days
value0 LIKE mseg-dmbtr,
meng1 LIKE mard-labst, "11 to 30 days
value1 LIKE mseg-dmbtr,
meng2 LIKE mard-labst, "31 to 60 days
value2 LIKE mseg-dmbtr,
meng3 LIKE mard-labst, "61-90
value3 LIKE mseg-dmbtr,
meng4 LIKE mard-labst, "90 days onwards
value4 LIKE mseg-dmbtr,
END OF t_mat2.
DATA: i_matsum TYPE t_mat2 OCCURS 0 WITH HEADER LINE.
DATA: w_mengb TYPE mbew-lbkum,
w_workqyt TYPE mbew-lbkum,
w_index TYPE sy-tabix,
*DATA: w_mengb TYPE mard-labst, "tmp Balance qty
w_workqty TYPE mard-labst, "Work qty
w_index TYPE sy-tabix,
w_days(5) TYPE n, "duration difference (days)
w_mths(5) TYPE n, "duration difference (mths)
w_dat1 TYPE sy-datum, "date
w_dat2 TYPE sy-datum, "today's date
w_detl(1) TYPE c,
w_summ(1) TYPE c,
w_denom TYPE i,
w_numer TYPE i,
w_conv TYPE i,
w_ttlcnt TYPE i,
w_cnt TYPE i,
v_topofpage(1),
w_meng LIKE mard-labst,
w_meng LIKE mbew-lbkum,
*sapscript values
w_title(20) TYPE c. "Summary / Detail Report
DATA: lv_peinh LIKE mbew-peinh, "Price Unit
lv_verpr LIKE mbew-verpr. "Moving Price
proram comes here
SELECTION-SCREEN BEGIN OF BLOCK blk1 WITH FRAME TITLE text-001.
SELECT-OPTIONS: s_werks FOR mseg-werks,
s_lgort FOR mseg-lgort,
s_matnr FOR mara-matnr,
s_saknr FOR ska1-saknr,
S_ERDAT FOR VBAK-ERDAT.
PARAMETERS: pck_detl RADIOBUTTON GROUP rep1,
pck_summ RADIOBUTTON GROUP rep1,
pck_dtsm RADIOBUTTON GROUP rep1 DEFAULT 'X'.
SELECTION-SCREEN END OF BLOCK blk1.
top of the page
TOP-OF-PAGE.
PERFORM f_top_of_page.
FORM f_top_of_page .
IF v_topofpage = 'D'.
*-->Report header for detail report
WRITE:/2 'Printed By :', sy-uname,
80 'Stock Aging Report - Detail',
180 'Printed on:', sy-datum, sy-timlo,
220 'Page:', sy-pagno.
WRITE:/,/,/.
WRITE:/2 'Storage',
10 'Matl ID',
22 'Matl Description',
61 'UOM',
78 '<--=<QTY ON THIS DATE -->',
78 '<-- =< 10 days -->',
112 '<--11 to 30 days -->',
148 '<--31 to 60 days -->',
181 '<--61 to 90 days -->',
216 '<-- > 90 days -->',
/2 'Location',
76 'Qty',
92 'Value'.
112 'Qty',
128 'Value',
148 'Qty',
164 'Value',
181 'Qty',
195 'Value',
216 'Qty',
231 'Value'.
WRITE:/2 sy-uline(235).
ELSE.
*-->Report header for Summary report
WRITE:/2 'Printed By :', sy-uname,
80 'Stock Aging Report - Summary',
180 'Printed on:', sy-datum, sy-timlo,
220 'Page:', sy-pagno.
WRITE:/,/,/.
WRITE:/2 'Storage',
10 'Matl ID',
22 'Matl Description',
61 'UOM',
78 '<--< QTY ON THIS DATE -->',
78 '<-- < 10 days -->',
112 '<--11 to 30 days -->',
148 '<--31 to 60 days -->',
181 '<--61 to 90 days -->',
216 '<-- > 90 days -->',
/2 'Location',
76 'Qty',
92 'Value'.
112 'Qty',
128 'Value',
148 'Qty',
164 'Value',
181 'Qty',
195 'Value',
216 'Qty',
231 'Value'.
WRITE:/2 sy-uline(235).
ENDIF.
ENDFORM. " f_top_of_page
*start-of-selection
*PERFOM f_data_selection.
FORM f_data_selection.
SELECT a~werks
a~lgort
a~matnr
a~saknr
a~lbkum
a~erdat
a~labst
a~umlme
a~insme
a~einme
a~speme
a~retme
b~verpr "this field no long been used
c~maktx
d~meins
INTO CORRESPONDING FIELDS OF TABLE ta_material
FROM mard AS a
INNER JOIN makt AS c ON amatnr = cmatnr
INNER JOIN mara AS d ON amatnr = dmatnr
WHERE a~matnr IN s_matnr
AND a~werks IN s_werks
AND a~lgort IN s_lgort
AND a~saknr IN s_saknr
AND a~erdat IN s_erdat
AND c~spras = 'EN'.
*--> SC01 - End of Insertion **
*-->Select material documents
SELECT a~mblnr
a~mjahr
a~zeile
a~meins
a~menge
a~werks
a~lgort
a~matnr
b~budat
INTO CORRESPONDING FIELDS OF TABLE ta_mseg
FROM mseg AS a INNER JOIN mkpf AS b
ON amblnr = bmblnr
AND amjahr = bmjahr
FOR ALL ENTRIES IN ta_material
WHERE matnr = ta_material-matnr
AND a~werks = ta_material-werks
AND a~lgort = ta_material-lgort
AND algort NE aumlgo
AND a~shkzg = 'S'
AND a~smbln EQ space
AND a~smblp EQ space.
*--> SC03 - Start of Insertion **
If MBLNR exist in MSEG-SMBLN and this
record's SHKZG = 'H'. Remove it from the table.
This is becuase this particular record has already been reverse.
LOOP AT ta_mseg.
SELECT SINGLE *
FROM mseg
WHERE smbln = ta_mseg-mblnr
*->Begin of KL02+ -
and SMBLP = ta_mseg-zeile.
AND shkzg = 'H'. "return. " KL02-
*->End of KL02+ -
IF sy-subrc = 0.
DELETE ta_mseg.
ENDIF.
ENDLOOP.
*--> SC03 - Enf of Insertion **
ENDFORM. " f_data_selection
*IMPORTANT , NEED TO CHECK LATER
FORM f_data_preparation.
*-->Append data for report details
LOOP AT ta_material.
DATA: ta_msegtemp LIKE ta_mseg OCCURS 2 WITH HEADER LINE.
*-->Loop at all material documents into a temp table
REFRESH ta_msegtemp. CLEAR ta_msegtemp.
LOOP AT ta_mseg WHERE matnr = ta_material-matnr AND
werks = ta_material-werks AND
lgort = ta_material-lgort.
ta_msegtemp = ta_mseg. APPEND ta_msegtemp.
ENDLOOP.
*-->Add up all the stock for the material
CLEAR w_mengb.
w_mengb = ta_material-labst +
ta_material-umlme +
ta_material-insme +
ta_material-einme +
ta_material-speme +
ta_material-retme.
IF w_mengb IS INITIAL.
CONTINUE.
ENDIF.
*-->sort msegtemp by posting date
SORT ta_msegtemp BY budat DESCENDING.
*-->get the values from the material documents into the report output
LOOP AT ta_msegtemp.
*->Begin of KL02- -
CALL FUNCTION 'HRCM_TIME_PERIOD_CALCULATE'
EXPORTING
begda = ta_msegtemp-budat
endda = sy-datum
IMPORTING
NOYRS =
nomns = w_mths
nodys = w_days
EXCEPTIONS
invalid_dates = 1
overflow = 2
OTHERS = 3
*->End of KL02- -
*->Begin of KL02+ -
*-->Get the days difference btw two dates
clear w_days.
w_days = sy-datum - ta_msegtemp-budat.
*--> Include today's date into calculation
w_days = w_days + 1.
*->End of KL02+ -
check base unit, do conversion
IF ta_material-meins <> ta_msegtemp-meins.
CALL FUNCTION 'MD_CONVERT_MATERIAL_UNIT'
EXPORTING
i_matnr = ta_material-matnr
i_in_me = ta_msegtemp-meins
i_out_me = ta_material-meins
i_menge = ta_msegtemp-menge
IMPORTING
e_menge = ta_msegtemp-menge
EXCEPTIONS
error_in_application = 1
error = 2
OTHERS = 3.
ENDIF.
*--> SC01 - Start of Insertion **
SELECT SINGLE peinh
verpr
INTO (lv_peinh,
lv_verpr)
FROM mbew
WHERE matnr = ta_material-matnr
AND bwkey = ta_material-werks.
IF sy-subrc = 0.
ta_material-verpr = lv_verpr.
ENDIF.
*--> SC01 - End of Insertion **
*-->check whether the mseg value is LE than the stock value
IF ta_msegtemp-menge LE w_mengb.
*-->Days < 10 days
IF w_days LE 1 AND w_days EQ 366.
i_mat2-meng0 = i_mat2-meng0 + ta_msegtemp-menge.
IF NOT lv_peinh EQ 0.
i_mat2-value0 = ( i_mat2-meng0 / lv_peinh ) *
ta_material-verpr."+SC01
ENDIF.
**-->Days 11 - 30 days
ELSEIF w_days >= 11 AND w_days =< 30.
i_mat2-meng1 = i_mat2-meng1 + ta_msegtemp-menge.
IF NOT lv_peinh EQ 0.
i_mat2-value1 = ( i_mat2-meng1 / lv_peinh ) *
*ta_material-verpr."+SC01
ENDIF.
**-->Days 31-60 days
ELSEIF w_days >= 31 AND w_days =< 60.
i_mat2-meng2 = i_mat2-meng2 + ta_msegtemp-menge.
IF NOT lv_peinh EQ 0.
i_mat2-value2 = ( i_mat2-meng2 / lv_peinh ) *
*ta_material-verpr."+SC01
ENDIF.
**-->Days 61-90 days
ELSEIF w_days >= 61 AND w_days =< 90.
i_mat2-meng3 = i_mat2-meng3 + ta_msegtemp-menge.
IF NOT lv_peinh EQ 0.
i_mat2-value3 = ( i_mat2-meng3 / lv_peinh ) *
*ta_material-verpr.
ENDIF.
**-->Days > 90 days
ELSEIF w_days > 90.
i_mat2-meng4 = i_mat2-meng4 + ta_msegtemp-menge.
IF NOT lv_peinh EQ 0.
i_mat2-value4 = ( i_mat2-meng4 / lv_peinh ) *
*ta_material-verpr.
ENDIF.
ENDIF.
*->End of KL002+
w_mengb = w_mengb - ta_msegtemp-menge.
ELSE.
IF NOT w_mengb LE 0 .
IF NOT lv_peinh EQ 0.
**->End of KL001+
i_mat2-value0 = ( i_mat2-meng0 / lv_peinh )
*ta_material-verpr."+SC01
**->Begin of KL001+
ENDIF.
ELSEIF w_days GE 22.
i_mat2-meng3 = i_mat2-meng3 + w_mengb.
IF NOT lv_peinh EQ 0.
i_mat2-value3 = ( i_mat2-meng3 / lv_peinh )
*ta_material-verpr.
ENDIF.
**->End of KL001+
ENDIF.
**--> SC02 - End of Insertioin **
ENDIF.
*->End of KL002-
*->Begin of KL002+
*--> < 10 days
IF w_days EQ 1 AND w_days LE 366.
i_mat2-meng0 = i_mat2-meng0 + ta_msegtemp-menge.
IF NOT lv_peinh EQ 0.
i_mat2-value0 = ( i_mat2-meng0 / lv_peinh ) *
ta_material-verpr."+SC01
ENDIF.
ELSEIF w_days >= 11 AND w_days =< 30.
i_mat2-meng1 = i_mat2-meng1 + w_mengb.
IF NOT lv_peinh EQ 0.
i_mat2-value1 = ( i_mat2-meng1 / lv_peinh ) *
*ta_material-verpr.
ENDIF.
**--> 31 - 60 days
ELSEIF w_days >= 31 AND w_days =< 60.
i_mat2-meng2 = i_mat2-meng2 + w_mengb.
IF NOT lv_peinh EQ 0.
i_mat2-value2 = ( i_mat2-meng2 / lv_peinh ) *
*ta_material-verpr.
ENDIF.
**--> 61 - 90 days
ELSEIF w_days >= 61 AND w_days =< 90.
i_mat2-meng3 = i_mat2-meng3 + w_mengb.
IF NOT lv_peinh EQ 0.
i_mat2-value3 = ( i_mat2-meng3 / lv_peinh ) *
*ta_material-verpr.
ENDIF.
**--> > 90 days
ELSEIF w_days > 90.
i_mat2-meng4 = i_mat2-meng4 + w_mengb.
IF NOT lv_peinh EQ 0.
i_mat2-value4 = ( i_mat2-meng4 / lv_peinh ) *
*ta_material-verpr.
ENDIF.
ENDIF.
*->End of KL002+
w_mengb = 0.
ENDIF. " check stock value NE zero
ENDIF. "check Mat doc amount is LE than the stock value
ENDIF.
ENDLOOP. " msegtemp
*-->append i_mat2 values
i_mat2-werks = ta_material-werks.
i_mat2-lgort = ta_material-lgort.
i_mat2-matnr = ta_material-matnr.
i_mat2-maktx = ta_material-maktx.
i_mat2-meins = ta_material-meins.
APPEND i_mat2. CLEAR i_mat2.
ENDLOOP. " ta_material
*-->Append data for summary data
DATA: i_lgort LIKE i_mat2 OCCURS 2 WITH HEADER LINE.
i_lgort[] = i_mat2[].
SORT i_lgort BY werks lgort.
DELETE ADJACENT DUPLICATES FROM i_lgort COMPARING werks lgort.
DATA: v_cnt0(5), v_cnt1(5), v_cnt2(5), v_cnt3(5), v_cnt4(5),
v_value0 LIKE i_matsum-value0.
v_value1 LIKE i_matsum-value1,
v_value2 LIKE i_matsum-value2,
v_value3 LIKE i_matsum-value3,
v_value4 LIKE i_matsum-value4.
LOOP AT i_lgort.
CLEAR v_cnt0. CLEAR v_value0.
CLEAR v_cnt1. CLEAR v_value1.
CLEAR v_cnt2. CLEAR v_value2.
CLEAR v_cnt3. CLEAR v_value3.
CLEAR v_cnt4. CLEAR v_value4.
LOOP AT i_mat2 WHERE lgort = i_lgort-lgort AND
werks = i_lgort-werks.
IF NOT i_mat2-meng0 IS INITIAL.
v_cnt0 = v_cnt0 + 1.
v_value0 = v_value0 + i_mat2-value0.
ENDIF.
IF NOT i_mat2-meng1 IS INITIAL.
v_cnt1 = v_cnt1 + 1.
v_value1 = v_value1 + i_mat2-value1.
ENDIF.
IF NOT i_mat2-meng2 IS INITIAL.
v_cnt2 = v_cnt2 + 1.
v_value2 = v_value2 + i_mat2-value2.
ENDIF.
IF NOT i_mat2-meng3 IS INITIAL.
v_cnt3 = v_cnt3 + 1.
v_value3 = v_value3 + i_mat2-value3.
ENDIF.
IF NOT i_mat2-meng4 IS INITIAL.
v_cnt4 = v_cnt4 + 1.
v_value4 = v_value4 + i_mat2-value4.
ENDIF.
ENDLOOP.
CLEAR i_matsum.
i_matsum-lgort = i_mat2-lgort.
IF v_cnt0 NE space.
i_matsum-cnt0 = v_cnt0.
i_matsum-value0 = v_value0.
APPEND i_matsum.
ENDIF.
CLEAR i_matsum.
i_matsum-lgort = i_mat2-lgort.
IF v_cnt1 NE space.
i_matsum-cnt1 = v_cnt1.
i_matsum-value1 = v_value1.
APPEND i_matsum.
ENDIF.
CLEAR i_matsum.
i_matsum-lgort = i_mat2-lgort.
IF v_cnt2 NE space.
i_matsum-cnt2 = v_cnt2.
i_matsum-value2 = v_value2.
APPEND i_matsum.
ENDIF.
CLEAR i_matsum.
i_matsum-lgort = i_mat2-lgort.
IF v_cnt3 NE space.
i_matsum-cnt3 = v_cnt3.
i_matsum-value3 = v_value3.
APPEND i_matsum.
ENDIF.
CLEAR i_matsum.
i_matsum-lgort = i_mat2-lgort.
IF v_cnt4 NE space.
i_matsum-cnt4 = v_cnt4.
i_matsum-value4 = v_value4.
APPEND i_matsum.
ENDIF.
ENDLOOP.
ENDFORM. "f_data_preparation
*IMPORTANT , NEED TO CHECK LATER
FORM f_display_data .
IF pck_dtsm = 'X'.
*-->Display detail
v_topofpage = 'D'.
PERFORM f_display_detail.
*-->display summary
v_topofpage = 'S'.
NEW-PAGE.
PERFORM f_display_summary.
ELSEIF pck_detl = 'X'.
*-->Display detail
v_topofpage = 'D'.
PERFORM f_display_detail.
ELSEIF pck_summ = 'X'.
*-->display summary
v_topofpage = 'S'.
PERFORM f_display_summary.
ENDIF.
ENDFORM. " f_display_data
FORM f_display_detail .
v_topofpage = 'D'.
SORT i_mat2 BY werks lgort.
*DATA: v_count(5),
DATA: v_count,
v_va1 LIKE i_mat2-value0.
v_va2 LIKE i_mat2-value0,
v_va3 LIKE i_mat2-value0,
v_va4 LIKE i_mat2-value0,
v_va5 LIKE i_mat2-value0.
LOOP AT i_mat2.
WRITE:/2 i_mat2-lgort,
10 i_mat2-matnr,
22 i_mat2-maktx(38),
61 i_mat2-meins,
64 i_mat2-meng0,
82 i_mat2-value0.
100 i_mat2-meng1,
118 i_mat2-value1,
136 i_mat2-meng2,
154 i_mat2-value2,
169 i_mat2-meng3,
186 i_mat2-value3,
204 i_mat2-meng4,
222 i_mat2-value4.
*-->Set counter and add up all values by lgort
v_count = v_count + 1.
v_va1 = v_va1 + i_mat2-value0.
v_va2 = v_va2 + i_mat2-value1.
v_va3 = v_va3 + i_mat2-value2.
v_va4 = v_va4 + i_mat2-value3.
v_va5 = v_va5 + i_mat2-value4.
AT END OF lgort.
WRITE:/10 'Cnt:',
15 v_count,
55 'Subtotal',
82 v_va1.
118 v_va2,
154 v_va3,
186 v_va4,
222 v_va5.
CLEAR v_count. CLEAR v_va1.
CLEAR v_va2. CLEAR v_va3. CLEAR v_va4. clear v_va5.
ENDAT.
ENDLOOP.
ENDFORM. " f_display_detail
FORM f_display_summary .
v_topofpage = 'S'.
LOOP AT i_matsum.
IF NOT i_matsum-cnt0 IS INITIAL.
WRITE:/2 i_matsum-lgort,
10 'Cnt:',15 i_matsum-cnt0,
82 i_matsum-value0.
ENDIF.
IF NOT i_matsum-cnt1 IS INITIAL.
WRITE:/2 i_matsum-lgort,
10 'Cnt:',15 i_matsum-cnt1,
118 i_matsum-value1.
ENDIF.
IF NOT i_matsum-cnt2 IS INITIAL.
WRITE:/2 i_matsum-lgort,
10 'Cnt:',15 i_matsum-cnt2,
154 i_matsum-value2.
ENDIF.
IF NOT i_matsum-cnt3 IS INITIAL.
WRITE:/2 i_matsum-lgort,
10 'Cnt:', 15 i_matsum-cnt3,
186 i_matsum-value3.
ENDIF.
IF NOT i_matsum-cnt4 IS INITIAL.
WRITE:/2 i_matsum-lgort,
10 'Cnt:', 15 i_matsum-cnt4,
222 i_matsum-value4.
ENDIF.
ENDLOOP.
ENDFORM. " f_display_summary -
How to speed up the deletion of 11million records from the table
Hi,
How to speed up the deletion of 11million records from the table.
I need expiditious reply. Please do the needfull in advising
RegardsPlease try to understand the question.Well it would help if you would answer some of the questions you have been asked as your question is not complete and clear and no matter how hard we try, we really need you to try and ask the question properly.
So as previously asked
Which simply supports the idea that we need:
1) better definition of the business purpose (why)
2) oracle version
3) operating system
4) hardware configuration
to give a moderately accurate answer.
I would like to add
5) How many rows in total in the table to begin with.
6) What is your delete statement
7) Is this a one time operation or will it happen regularly
8) Can you use partitioning. -
How can we delete a line from the table control .
hi all
how can we delete a line from the table control .
situation is.
created table control in se51 which will display the data of a table.
how could i select a line from the table control ?
how could i delete the selected lines form the table.
thanks in advanceChange the Table Control attributes such that user can only select a single record(row).
<u>Tip to delete a selected record</u>
1) write a module 'Mark' in the PAI as below
PROCESS AFTER INPUT.
MODULE cancel AT EXIT-COMMAND.
LOOP WITH CONTROL table_view.
MODULE read_table_control.
FIELD flag MODULE mark ON INPUT.
ENDLOOP.
MODULE user_command_0100.
2) Module Mark is below.
MODULE mark INPUT.
CHECK flag = 'X'.
x = table_view-top_line + sy-stepl - 1.
Delete itab INDEX x.
ENDMODULE. " mark INPUT
Table_view is the TableControl Name.
'flag' is of type char(1) available in the Internal table which was assigned to the select option in the table control.
<u>award if uesful</u>
Regards,
Sudheer -
Selected rows appear in random order when selected from ADF Table
Hi All,
I am working in ADF 10.1.3
I have a ADF Table with a multi select option associated with a DataBean, My requirement is when I select multiple rows from the table and click on some button to goto next page, the selected rows are not getting populated as per the selection order.
Example: If I select 1st,3rd,5th,7th,9th rows from the ADF Table then in the next page I see the results as 3rd,1st,5th,9th,7th. - Randomly it is getting displayed.
I am using the following code to get the records from Multi select ADF Table.
I am adding the selected records to a List.
selectedRowSet = this.getTable1().getSelectionState().getKeySet();
rowSetIter = selectedRowSet.iterator();
if (selectedRowSet.size() > 0)
Integer index = Integer.parseInt((String) rowSetIter.next());
Object rowData = this.getTable1().getRowData(index.intValue());
The order is getting jumbled when I see the final list.
Pls help me in this.
ThanksHi Frank,
Thanks for the update.
We are using 10.1.3.3 and already our application in QA Testing. User need this to be fixed. Is there any work around for this problem?
Thanks
JP -
How to truncate the values from the table
Hi All,
I am working on an issue..where we are first deleting all the records from the table and then based on few conditions we are putting the records back in that table...when we tried to run this program along with few others those who are doing almost the same stuff we are having issues...we tried to schedule few jobs related to these programs only...but after a ceratin amount of time couple of jobs got canceled...I was talking to my basis guy and he said the problem is ratehr then truncating the records from the table we are deleting the records and it's taking lots and lots of space to execute...so we need to truncate the records from the table insted of deleting it...we are using the following the statement right now:
DELETE FROM ZTUS_PG.
COMMIT WORK.
So can you please tell me how can we truncate the values from this table instead of just deleting them and what would be effect of this.
Thanks,
Rajeev GuptaI don't think basis is saying you should delete all the records from the table. They are saying remove the table and it's contents (a much faster thing to do). I'm not sure this the right thing to do, but you can have a look at:
http://publib.boulder.ibm.com/infocenter/db2luw/v9/index.jsp?topic=/com.ibm.db2.udb.apdv.sample.doc/doc/admin_scripts/s-truncate-db2.htm
Something like:
EXEC SQL.
TRUNCATE TABLE ZTUS_PG REUSE STORAGE
ENDEXEC.
COMMIT WORK. "Empty table is committed here
Rob
Edited by: Rob Burbank on Dec 1, 2008 4:06 PM
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