DML performance in different databases

Hi ALL:
I am testing a procedure in the company's two different databases, 800D( development database) and 800P2(integration testing). The following is my procedure:
PROCEDURE GET_FLORIST_TELEPHONES IS
cursor c1 is select id from ats_florists where status = 'A' ;
n number:=0;
begin
for x in c1 loop
declare
temp_tel ats_telephones.tlfn_number%type;
begin
select tlfn_number into temp_tel from ats_telephones
where fit_id = x.id
and tlfn_type = 'WP' and rownum = 1;
n:=n+1;
insert into florist_telephones
(fit_id,
tlfn_number)
values( x.id,
temp_tel);
if mod(n,1000) = 0 then
commit;
clear_message;
end if;
exception
when no_data_found then
null;
end;
end loop;
end:
Basically what I am trying here to do here is to populate our clients' phone numbers from a master table (ats_telephones) into a temproray table (florist_phones). Please note this procedure resides in the form's (4.5) program units.
When I tested it in the 800D (both in the backend and front end) the all process took about 30 seconds (about 50,000 records),
but when I call the same procedure in 800p2 from forms it will take about 2 hours to populate almost the same amount of data. However, when I call this procedure from SQL*PLUS intead of forms in the same database(800P2), it takes only 30 seconds. Can anyone help me solve this problem? Many thanks.
Kevin

Is there a reason for using rownum?
Try the procedure without the rownum clause.
<BLOCKQUOTE><font size="1" face="Verdana, Arial">quote:</font><HR>Originally posted by kl279c:
Hi ALL:
I am testing a procedure in the company's two different databases, 800D( development database) and 800P2(integration testing). The following is my procedure:
PROCEDURE GET_FLORIST_TELEPHONES IS
cursor c1 is select id from ats_florists where status = 'A' ;
n number:=0;
begin
for x in c1 loop
declare
temp_tel ats_telephones.tlfn_number%type;
begin
select tlfn_number into temp_tel from ats_telephones
where fit_id = x.id
and tlfn_type = 'WP' and rownum = 1;
n:=n+1;
insert into florist_telephones
(fit_id,
tlfn_number)
values( x.id,
temp_tel);
if mod(n,1000) = 0 then
commit;
clear_message;
end if;
exception
when no_data_found then
null;
end;
end loop;
end:
Basically what I am trying here to do here is to populate our clients' phone numbers from a master table (ats_telephones) into a temproray table (florist_phones). Please note this procedure resides in the form's (4.5) program units.
When I tested it in the 800D (both in the backend and front end) the all process took about 30 seconds (about 50,000 records),
but when I call the same procedure in 800p2 from forms it will take about 2 hours to populate almost the same amount of data. However, when I call this procedure from SQL*PLUS intead of forms in the same database(800P2), it takes only 30 seconds. Can anyone help me solve this problem? Many thanks.
Kevin <HR></BLOCKQUOTE>
null

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Compare performance of two different databases...idea of a report to us?

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Regards,
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Hello,
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Performance optimization during database selection.

hi gurus,
pls any explain about this...
Strong knowledge of performance optimization during database selection.
regards,
praveen

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 create a view consisting of data from tables in2 different databases

Using Oracle 10.2g
I have 2 databases Gus and haggis on Comqdhb schema.
glink indicates a databse link between Haggis and Gus
In Gus there are tables student,subject,grade,school containing columns like upn...
STUDENT
upn
academicYear
SUBJECT
subject
GRADE
examlevel
grade
SCHOOL
sn
In HAGGIS there are tables student,grade,teacher containing columns upn...desc below.
STUDENT
upn
GRADE
grade
upn
academicyear
level
Create view in your HAGGIS database which will join all of the exam grades together. You should have one view which will produce the following relation :
examGrade(upn, subject, examlevel, sn, grade,academicYear)
so I need to create a view which gets the data from both the tables in both the databases.
create view as examGrade(upn, subject, examlevel, sn, grade,academicYear) as select s.upn
But i am not getting how to select a column from 2 tables in different databases
I mean if i said
select upn from comqdhb.student@glink,comqdhb.student;
select upn from comqdhb.student@glink,comqdhb.student
ERROR at line 1:
ORA-00918: column ambiguously defined
help me out,Thank you.

Thank you for the reply will follow up the code format
Create views in your HAGGIS schema database which will join all of the exam grades together. You should have one view which will produce the following relation :
examGrade(upn, subject, examlevel, sn, grade,academicYear)
I understand that there wont be duplication when we use conditions
If i query
select count(upn)
from   comqdhb.student@glink I get 9000
but after the union
create view examGrade(upn, subject, examlevel, sn, grade,academicYear)
as
select distinct s.upn as upn
,                  g.subject as subject
,                  g."LEVEL" as examlevel
,                  g.grade as grades
,                  '9364097'
,                  to_number(g.academicyear) as academicyear
from             comqdhb.student s
,                   comqdhb.grade g
where           s.upn=g.upn
union
select            s.upn
,                   sb.subject
,                   g.elevel
,                   g.grade
,                   s.acyr
,                   sc.sn
from              comqdhb.subject@glink sb
,                   comqdhb.student@glink s
,                    comqdhb.gradevalues@glink g
,                    comqdhb.school@glink sc,
,                    comqdhb.studentingroup@glink sg
,                    comqdhb.teachinggroup@glink tg
where            sb.sid=tg.sid
and                tg.gid=sg.gid
and                sg.upn=s.upn
and                g."LEVEL"=tg.elevel
and                s.school=sc.id
and                sc.id=tg.id; returns
count(upn) from exam gradeIt gets stuck actually sometimes it returns
932002 some results.
2:
Another problem i am having which i am trying to solve and written up my ideas but haven't been getting the expected results.Hope you can help.Thank you.
Information:
=======
All children take exams at the age of 16 called a General Certificate of SecondaryEducation (GCSE).
They have to study and take exams in Mathematics, English and Science, and can take other subjects such as History, French, Art etc. Most students will study between 5 and 10 different subjects before taking their GCSEs.
For each exam, a student is awarded a grade from A*, A, B,C,D,E,F,G,U,X An A* grade is the best grade achievable and an X is the worst grade.
In order to analyze how students have performed, each grade is mapped to a numeric value as follows:
Grade Numerical score
A* 8
A 7
B 6
C 5
D 4
E 3
F 2
G 1
U 0
X 0
Now why i need this avgGCSE is because i have to create a view containing avgGCSE of the students it is used in the next question where a condition is avgGCSE is between 6.5 and 7
In order to calculate the avgGCSE the idea is to calculate the grades of the students and map the grades to their corresponding scores/values
add them all up and div by the total no of grades to get the avg.
desc comqdhb.STUDENT@glink;
STUDENT
=======
UPN
FNAME
CNAME
DOB
GENDER
PREVIOUSSCHOOL
XGCSE
SCHOOL
ACYR
STUDENTINGROUP
=============
UPN
GID
STARTDATE
ENDDATE
GRADE
GRADEVALUES
===========
GRADE
LEVEL
VALUE
I have a opinion that xgcse in STUDENT table refers to the avgGCSE which i want to calculate as when i asked my professor as to what xgcse he said that he forgot to take it out of the table and it is not necessary while creating avggcse.
select *
from comqdhb.student@glink
where xgcse<6.5; Displaying a result
returns:
UPN FAMILYNAME COMMONNAME DATEOFBIR GENDER PREVIOUSSCHOOL XGCSE SCHOOL ACYR
===========================================================================
1011 KIMBERLY ABBOT 07-JUL-79 f none 3.93500948 2 2
select *
from comqdhb.student@glink
where xgcse between 6.5 and 7 and upn = 1386; Displaying a result
returns:
UPN FAMILYNAME COMMONNAME DATEOFBIR GENDER PREVIOUSSCHOOL XGCSE SCHOOL ACYR
===========================================================================
1386 STEPHANIE AANNESSON 15-JAN-79 f none 6.88873 2 2 so if xgcse is the avgGCSE then upn 1011 has avggcse<6.5 and 1386 has avggcse >6.5
my idea was backward strategy like so now if we find out upn 1368 has suppose xgcse(avggcse)>6.5 how to extract the avggcse for the particular upn We need to map grades from GRADEVALUES to grade in STUDENTINGROUP and map upn from studentingroup to upn in student to output the values for the corresponding grades from GRADEVALUES
select grade
from comqdhb.studentingroup@glink
where upn = 1011;
Result:
GRADE
=====
D
F
B
E
C
E
E
B
8 rows selected. Mapping each grade to the corresponding value and calculating we get
32/8=4 total(values to corresponding grades)/no of grades.
But the xgcse for upn 1011 is 3.935 and i am getting 4!! maybe xgcse isn't avggrade but ? is the procedure by me correct for calculating avggcse
select grade
from comqdhb.studentingroup@glink
where upn = 1386;
Result:
GRADE
======
A*
A*
A*
A*
B
A*
A*
A
B
B
B
11 rows selected. grade to the corresponding value and calculating we get
79/11=7.12 total(values to corresponding grades)/no of grades.
But the xgcse for upn 1011 is 6.88... and i am getting 7.12!!
But another problem
when i say
select   g.value,g.grade
from     comqdhb.gradevalues@glink g
,        comqdhb.studentingroup@glink sg
where    g.grade=sg.grade
and      sg.upn=1011;
result:
======
VALUE GRADE
===========
100 B
100 B
   80 C
   60 D
   40 E
   40 E
   40 E
   20 F
    6 B
    6 B
    5 C
VALUE GRADE
=============
    4 D
    3 E
    3 E
    3 E
    2 F
16 rows selected.
select   distinct g.value,g.grade
from     comqdhb.gradevalues@glink g
,        comqdhb.studentingroup@glink sg
where    g.grade=sg.grade
and      sg.upn=1011;
result:
======
VALUE GRADE
============
     2 F
   100 B
     6 B
     3 E
    60 D
     5 C
     4 D
    80 C
    40 E
    20 F
10 rows selected. I am getting only 8 for the query
select grade
from comqdhb.studentingroup@glink
where upn = 1386; here its becomming 10 and also its displaying values as 100 and ...
select distinct *
from   comqdhb.gradevalues@glink;
GRADEVALUES
===========
LEVEL      GRADE           VALUE
================================
a          A                 120
a          B                 100
a          C                  80
a          D                  60
a          E                  40
a          F                  20
a          U                   0
a          X                   0
g          A                   7
g          A*                  8
g          B                   6
LEVEL      GRADE           VALUE
================================
g          C                   5
g          D                   4
g          E                   3
g          F                   2
g          G                   1
g          U                   0
g          X                   0
18 rows selected. I was hoping if i could map the grades and get the values and calculate avggrade by total(values)/count(values)that would be it but here there are values like 100...
select sum(g.value)/count(g.grade) as avggrade
from    comqdhb.gradevalues@glink g
,         comqdhb.studentingroup@glink sg
where g.grade=sg.grade
and     sg.upn=1386;
avggrade
========
37.4375 the avggrade cant be this big and when i map each grade i obtained for 1368 like a to 7+b to 6 so on i get avggrade 7.12
kindly help.
Edited by: Trooper on Dec 15, 2008 4:49 AM

Interactive report performance problem over database link - Oracle Gateway

Hello all;
This is regarding a thread Interactive report performance problem over database link that was posted by Samo.
The issue that I am facing is when I use Oracle function like (apex_item.check_box) the query slow down by 45 seconds.
query like this: (due to sensitivity issue, I can not disclose real table name)
SELECT apex_item.checkbox(1,b.col3)
, a.col1
, a.col2
FROM table_one a
, table_two b
WHERE a.col3 = 12345
AND a.col4 = 100
AND b.col5 = a.col5
table_one and table_two are remote tables (non-oracle) which are connected using Oracle Gateway.
Now if I run above queries without apex_item.checkbox function the query return or response is less than a second but if I have apex_item.checkbox then the query run more than 30 seconds. I have resolved the issues by creating a collection but it’s not a good practice.
I would like to get ideas from people how to resolve or speed-up the query?
Any idea how to use sub-factoring for the above scenario? Or others method (creating view or materialized view are not an option).
Thank you.
Shaun S.

Hi Shaun
Okay, I have a million questions (could you tell me if both tables are from the same remote source, it looks like they're possibly not?), but let's just try some things first.
By now you should understand the idea of what I termed 'sub-factoring' in a previous post. This is to do with using the WITH blah AS (SELECT... syntax. Now in most circumstances this 'materialises' the results of the inner select statement. This means that we 'get' the results then do something with them afterwards. It's a handy trick when dealing with remote sites as sometimes you want the remote database to do the work. The reason that I ask you to use the MATERIALIZE hint for testing is just to force this, in 99.99% of cases this can be removed later. Using the WITH statement is also handled differently to inline view like SELECT * FROM (SELECT... but the same result can be mimicked with a NO_MERGE hint.
Looking at your case I would be interested to see what the explain plan and results would be for something like the following two statements (sorry - you're going have to check them, it's late!)
WITH a AS
(SELECT /*+ MATERIALIZE */ *
FROM table_one),
b AS
(SELECT /*+ MATERIALIZE */ *
FROM table_two),
sourceqry AS
(SELECT b.col3 x
       , a.col1 y
       , a.col2 z
FROM table_one a
    , table_two b
WHERE a.col3 = 12345
AND   a.col4 = 100
AND   b.col5 = a.col5)
SELECT apex_item.checkbox(1,x), y , z
FROM sourceqry
WITH a AS
(SELECT /*+ MATERIALIZE */ *
FROM table_one),
b AS
(SELECT /*+ MATERIALIZE */ *
FROM table_two)
SELECT apex_item.checkbox(1,x), y , z
FROM table_one a
    , table_two b
WHERE a.col3 = 12345
AND   a.col4 = 100
AND   b.col5 = a.col5If the remote tables are at the same site, then you should have the same results. If they aren't you should get the same results but different to the original query.
We aren't being told the real cardinality of the inners select here so the explain plan is distorted (this is normal for queries on remote and especially non-oracle sites). This hinders tuning normally but I don't think this is your problem at all. How many distinct values do you normally get of the column aliased 'x' and how many rows are normally returned in total? Also how are you testing response times, in APEX, SQL Developer, Toad SQLplus etc?
Sorry for all the questions but it helps to answer the question, if I can.
Cheers
Ben
http://www.munkyben.wordpress.com
Don't forget to mark replies helpful or correct ;)

Select query based on joining of tables from different database is taking too long

Hi Team,
Select query on table with millions of records is taking very long time. It took 50mins, the below query is joining on multiple table from two databases DB1.dbo.Table1 contains 100 million records and also Table3 and Table4 (of different database) might
contain close to 1million records.
Select T1.*
From DB1.dbo.Table1 T1
Join DB1.dbo.Table2 T2 on RTRIM(T1.Col3) = RTRIM(T2.Col3)
Join Table4 CA on RTRIM(T1.Col1) + T2.Col2 = CA.Col1
Join Table3 U on CA.Col2 = U.Col2 AND RTRIM(T2.Col2) = U.Col3
Where U.Col4 NOT IN ('A1', 'A2', 'A3', 'A4', 'A5', 'A6','A7','A8','A9')
And (T1.flg IS NULL OR T1.flg = 'N')
And LTRIM(RTRIM(T2.Col2)) NOT IN ('B1','B2')
How can i improve the performance of this query. Actual thing is update the data in Db1.dbo.table1 based on the conditions but if the select is taking close to 1hr then update will take hours together. Indexes already implemented on all the tables.
Thanks,
Eshwar.
Please don't forget to Marked as Answer if my post solved your problem and use Vote As Helpful if a post was useful. It will helpful to other users.

Thanks.
Join Table4 CA on RTRIM(T1.Col1) + T2.Col2 = CA.Col1
This join is not working with spaces if Rtrim is not used.
Thanks! Eshwar.
Please don't forget to Marked as Answer if my post solved your problem and use Vote As Helpful if a post was useful. It will helpful to other users.

About listeners for different databases in the same ORACLE_HOME

Hello experts, I have a doubt
I have installed 3 different databases in the same server which OS is Suse Enterprise 10. At this moment I have just one listener that registers all the services. The number of connections are big for two of the three databases so I do not know what might be the best practices for this environment. I have some question I would like you suggestion for me:
DB version: 11.1.0.7
Should I have three listener, one for each database?
Is a good practice to have only one listener for multiple instances in the same server?
Are there differents between have only one listener for all the instance and have one listener for instance?
What about the performance?
Than you in advance, I hope you can guide me.

Best practice is not to have multiple databases on one server, depending on resources.
Should I have three listener, one for each database?
No. That is pretty undesirable and requires more administration.
Is a good practice to have only one listener for multiple instances in the same server?
Yes. Remember the listener is only a broker and there are no permanent connections between client, listener and database.
Are there differents between have only one listener for all the instance and have one listener for instance?
Yes. The latter is an administration nightmare.
What about the performance?
Who cares? The only factors are
listener.log becomes too big --> set up proper cleanup procedures
The number of semaphores is exceeded (Unix) or no more threads can be created (Microsoft winblows), which will give rise to ora-12500.
Sybrand Bakker
Senior Oracle DBA

Joining tables in different databases

Hi,
I know we can access multiple databases like Oracle, Informix etc. through a single toplink session using session broker. Also in toplink documentation it says there is a work around for joining tables that exists in different databases i.e. joining an Oracle table with an Informix Table. If anyone had tried this or if it is possible, please let me know how to do this.
Thanks..

If I could know, how to perform or some sample code, for the following two steps it would be great.
Write descriptor ammendment code to bind together that go from (A) to (B) and (B) to (A).
Be sure to map the ammendment descriptors in the mapping workbench.Or please point me to the right toplink documentation or examples.
Thanks a lot for your help.

Different Database structure migartion

In second version of our software we change the database structure.
Now we need to migrate data from version 1 to version 2 that have different database structure.
Is Streaming or any other oracle feature provides possibility or I should write code by hand?

I sugeest you migrate the tables individaully having in mind the DML and DDL statements
hitting the database from the application end. You need to do a mapping for both the databse.
Do the events from your old application still update the same tables as the new application
You need to really think this out to avoid having complications in your new version.
I dont think stream option is the best at this stage rather export/import of tables would be the best option
then you can think of stream to update your new version at run time.

View running slowly on different database

Hi,
I have an issue where a view which runs quickly on two different databases runs slowly on a 3rd database. The database schema is the same on all 3 machines. The two databases that run the view quickly are v.9.2.0.1.0, and v.10.2.0.2.0, the 3rd database that runs the view slowly is v.9.2.0.7.0. The physical machine that the 3rd database runs on is the fastest machine.
On the poorly performing database, if I set autotrace on, then I get this:
Statistics
36 recursive calls
0 db block gets
618169 consistent gets
10 physical reads
0 redo size
406 bytes sent via SQL*Net to client
499 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
obviously, the sheer number of consistent get's has to be the source of the problem.
explain plan doesn't reveal anything obvious.
I'm struggling to resolve the issue. Any help or pointers would be appreciated.

The indexes are the same. I've also tried rebuilding the indexes.
Auto traces for the other 2 boxes
Statistics
0 recursive calls
0 db block gets
221 consistent gets
0 physical reads
0 redo size
379 bytes sent via SQL*Net to client
499 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
1 rows processed
Statistics
0 recursive calls
0 db block gets
2 consistent gets
0 physical reads
0 redo size
255 bytes sent via SQL*Net to client
369 bytes received via SQL*Net from client
1 SQL*Net roundtrips to/from client
0 sorts (memory)
0 sorts (disk)
0 rows processed

Persisting Entities in different databases

Hello! In our compony we need to store information in two different databases. To check if this is possible I've written a simple program, in which part of the entities is stored in one DB, and the other part - in another. And I have an error during deployment whith the following stack trace:
Deployment Error -- Exception [TOPLINK-0] (Oracle TopLink Essentials - 2006.4 (Build 060412)): oracle.toplink.essentials.exceptions.IntegrityException
Descriptor Exceptions:
Exception [TOPLINK-94] (Oracle TopLink Essentials - 2006.4 (Build 060412)): oracle.toplink.essentials.exceptions.DescriptorException
Exception Description: Descriptors must have a table name defined.
Descriptor: RelationalDescriptor(entity.Specification --> [])
Exception [TOPLINK-74] (Oracle TopLink Essentials - 2006.4 (Build 060412)): oracle.toplink.essentials.exceptions.DescriptorException
Exception Description: The primary key fields are not set for this descriptor.
Descriptor: RelationalDescriptor(entity.Specification --> [])
Exception [TOPLINK-108] (Oracle TopLink Essentials - 2006.4 (Build 060412)): oracle.toplink.essentials.exceptions.DescriptorException
Exception Description: Cannot find value in class indicator mapping in parent descriptor [null].
Descriptor: RelationalDescriptor(entity.Specification --> [])All I want is to store Specification entity and SalesLineItem entity in different databases, while there's a OneToOne unidirectional relationship between them. Here is part of SalesLineItem entity:
@Entity
public class SalesLineItem implements Serializable {
     private int quantity;
     private Specification productSpec;
     private int id;
     private Sale sale;
     @OneToOne
     public Specification getSpecification() {
          return this.productSpec;
     }And here's my persistence.xml:
<?xml version="1.0" encoding="UTF-8"?>
<persistence version="1.0" xmlns="http://java.sun.com/xml/ns/persistence">
<persistence-unit name="pu1" transaction-type="JTA">
    <jta-data-source>jdbc/__default</jta-data-source>
    <class>entity.Payment</class>
    <class>entity.Sale</class>
    <class>entity.SalesLineItem</class>
    <exclude-unlisted-classes>true</exclude-unlisted-classes>
    <properties>
      <property name="toplink.ddl-generation" value="drop-and-create-tables"/>
      <property name="toplink.platform.class.name" value="oracle.toplink.essentials.platform.database.DerbyPlatform"/>
    </properties>
</persistence-unit>
<persistence-unit name="pu2" transaction-type="JTA">
    <jta-data-source>jdbc/__resource</jta-data-source>
    <class>entity.Catalog</class>
    <class>entity.Specification</class>
    <exclude-unlisted-classes>true</exclude-unlisted-classes>
    <properties>
      <property name="toplink.ddl-generation" value="drop-and-create-tables"/>
      <property name="toplink.platform.class.name" value="oracle.toplink.essentials.platform.database.DerbyPlatform"/>
    </properties>
</persistence-unit>
</persistence>Then, I suppose, I create two EntityManger is session beans, each associated with one specific persistence unit.
When I use one database (one pesistence-unit in persistence.xml), everything works fine. I wonder, if it's possible to persist entities in a such way that entities with relationships between them are stored in different databases. Any help is greatly appreciated.

If I could know, how to perform or some sample code, for the following two steps it would be great.
Write descriptor ammendment code to bind together that go from (A) to (B) and (B) to (A).
Be sure to map the ammendment descriptors in the mapping workbench.Or please point me to the right toplink documentation or examples.
Thanks a lot for your help.

How to compare 2 different database to get table name which are not present in second database

How to compare 2 different database to get table name which are not present in second database

Sorry cannot test it right now
use db1
go
select * from sys.tables t where not exists
(select * from db2.sys.tables s where t.object_id=s.object_id)
Best Regards,Uri Dimant SQL Server MVP,
http://sqlblog.com/blogs/uri_dimant/
MS SQL optimization: MS SQL Development and Optimization
MS SQL Consulting:
Large scale of database and data cleansing
Remote DBA Services:
Improves MS SQL Database Performance
SQL Server Integration Services:
Business Intelligence

Restoring a database from a different database

I want to restore database new2db from newdb. both dbs are on different sql server instances.
I have backup of newdb called newdb_july.bkup.
I ran the below command :
restore database new2db from disk = 'c:\mssql\backup\newdb_july.bkup' with file=1,
move 'newdb' to 'C:\Program Files\Microsoft SQL Server\MSSQL10.MSSQLSERVER\MSSQL\DATA\new2db.mdf',
move 'newdb_log' to 'C:\Program Files\Microsoft SQLServer\MSSQL10.MSSQLSERVER\MSSQL\DATA\new2db_log.ldf',
replace,norecovery,stats=10
the restore completed successfully but the database is still in 'Restoring' status.
how do I get the database in active accessible status?
appreciate the feedback.

Yes norecovery if you want to restore more tlog or diff backup files... If you use recovery then you cant further restore any more tlog or diff backup's..
WITH RECOVERY includes both the redo and undo phases and recovers the database; additional backups cannot be restored. This is the default.
If the roll forward set has not been rolled forward far enough to be consistent with the database, the undo phase cannot occur. The Database Engine issues an error and recovery stops.
If the whole roll forward set is consistent with the database, recovery is performed, and the database can be brought online.
WITH NORECOVERY omits the undo phase to preserve uncommitted transactions. Omitting the undo phase allows for restoring other backups to roll the database further forward in time. Occasionally, RESTORE WITH NORECOVERY rolls forward data
to where it is consistent with the database. In these cases, the Database Engine issues an informational message stating that the roll forward set can now be recovered by using the RECOVERY option.
With the REPLACE option, restore allows you to overwrite an existing database with whatever database is in the backup set, even if the specified database name differs from the database name recorded in the backup set. This can result in
accidentally overwriting a database by a different database.
Raju Rasagounder Sr MSSQL DBA

How to join tables on different databases

In the company I work in, we've got some java applications working on two different instances which "hide" to each others (one on 10g and the other on 8i). Some decoding tables, which should common to both of them, are only present on 8i one.
I've been told that java works 'cause it allows to connect to both of databases and then report the information on front end applications.
The question is this: since we'll have to get reports on both of databases, is it possible to perform queries by using tools like oracle forms, oracle reports, sql developers, ... for joining the tables of the two different databases as java does? We have to get how to accede directly to the two instances for getting data from both of them for reporting activities. I remind you that we cannot use dblinks between the two databases for internal security reasons.
Thanks in advance!

Even java can't join between tables on two databases if the db links are not created.
So it essentially works that it fetches the data from one db and then from another db ( using two different db connctions) and then you can utlize these data and perform some joining.
Coming back to database world. It can be done like the usual dw approach.
1. Connect to a third db:
2. Get data from one database
3. get data from other database.
now do all the joins that you want to do

Synch Between Tables in Two different Databases

Synch between Two Tables in two different Databases.
I have two identical tables, table T1 in Database D1 and table T1 in Database D2. User can insert/update/delete/select from both of these tables in respective databases. Being said that how can keep them in Synch? Any thing added/modified/deleted should reflect in other. We like this to be Real-Time.
We are thinking of creating a cross (two way) DB link between them and then update/insert/delete both the tables when changing one. Any suggestions?
Thanks

One of my colleagues used snapshot in their previous projects, but he told me that the performance of it wind down while the records in tables increase. I have no idea about the exact situation, but I'm believing we'd think twice about it.
eilison
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