CallableStatement performance delay during response

I've Oracle 8.1.6, and Java server with connection pool of 50 JDBC connections.
For each external request Java server calls one PLSQL procedure through CallableStatement.
During performance test I'm constantly pumping requests to server from 50 concurrent threads and logging response time measured around CallableStatement.executre() method.
Result in strange, I can see clear cyclical pattern: ~250 requests completed with ave. response time 30 ms, next ~250 requests competed with ave. response time ~300 ms. Next ~250 - 30 ms, next ~250 - 300 ms. and so on many times.
In attempt to explain periodic delays I added code to capture timestamps in PLSQL procedure (I had to create Java Stored Procedure for that) and I added 2 out parameters to return timestamps to Java.
Now I logged following timestamps:
A - in Java server just before CallableStatement.execute()
B - in oracle at very beginning of PLSQL procedure
C - in oracle at very end of PLSQL procedure
D - in Java server just after CallableStatement.execute()
New test shown that
a) pattern still same - my extra JSP calls didn't changed whole picture.
b) SURPRISE :
time to "send" request (B-A) is always about 5 ms.
time in PLSQL (C-B) is more or less flat and is about Long postings are being truncated to ~1 kB at this time.

I'm not sure what do you mean by "traced SQL" or how to look for wait events (I'm no good at Oracle internals, YET). If you can tell me specifically what to do I will be gratefull.
We have DBAs here and I talk to one of them. He told me without even checking database that it is warking fine :(. And proposed to run snoop when he will have time. Since I have no rights myself I'm waiting. After that I hope I will know is it JDBC driver or database.
As for JDBC version I tried latest ojdbc14.jar, classes12.zip both thin and oci8. No noticable difference.
And thanks for reply

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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

Regarding Performance concerns during the creation of Infocube

hai
im going to create the infocube on top of ODS.
Pls tell me some design tips for performance things during the creation of Infocube like partitioning , Indexes...
Basically im loading from Oracle Databasetables by using DB-COnnect .
pls tell me
i ll assing the points
bye
rizwan

hi Rizwan,
check these:
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/1955ba90-0201-0010-d3aa-8b2a4ef6bbb2
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/ce7fb368-0601-0010-64ba-fadc985a1f94
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/4c0ab590-0201-0010-bd9a-8332d8b4f09c
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/docs/library/uuid/3a699d90-0201-0010-bc99-d5c0e3a2c87b
assign points if useful ***
Thanks,
Raj

Message failed in PI: Status code 200 But Error During Response Parsing:

Hi
I have integration scenario for sending PO/PO change/Proact from R/3 to SNC, everything was working till yesterday morning and suddenly all messages are failing in SAP PI with below error. We have not done any changes. The strange thing is this is failing in dev as well as in QA.
HTTP Status Code 200 Received But Error During Response Parsing: No XI Response Received XML element Envelope missing in SOAP message header (SAP XI Extension)
I can see some messages in sxmb_moni (we have not configured this) from sender component "Integration_Server_SID" and it's failed with below message
Proxy calls are not permitted on sender or
receiver side on the IS (client)
Thanks,
Nishant

HTTP Status Code 200 Received But Error During Response Parsing: No XI Response Received
XML element {http://schemas.xmlsoap.org/soap/envelope/}Envelope missing in SOAP message header (SAP XI Extension)
Same problem answered in this discussion....check if it helps:
Re: BW to File scenario
Regards,
Abhishek.

Long delay during first resize of visible JFrame (help!)

I need to increase the size of a component in a visible JFrame (and with it the size of the frame itself). The way I did this using jdk 1.3.1 causes a problem in 1.4.0 and 1.4.1.
When a component in a visible JFrame (such as a JPanel) is resized - using a setPreferredSize()-pack() sequence, there is a VERY long delay (~ 5 seconds) before the frame is fully redrawn. This only occurs the FIRST time the component is resized. Subsequent setPreferredSize()-pack() sequences take a reasonable amount of time.
Here's a simple example:
import java.awt.*;
import javax.swing.*;
public class PackDelayTest extends JFrame {
    JPanel pan;
    int width;
    static long tm;
    public static void main(String[] argv) {
            tm = System.currentTimeMillis();
        PackDelayTest2 test = new PackDelayTest();
            elapsed("in constructor");
        test.replace(); elapsed("repack 1");
        test.replace(); elapsed("repack 2");
        test.replace(); elapsed("repack 2");
        test.replace(); elapsed("repack 2");
        System.exit(0);
    public PackDelayTest() {
        pan = new JPanel();
        pan.setLayout(new BoxLayout(pan,BoxLayout.Y_AXIS));
        getContentPane().add(pan);
        JLabel label = new JLabel("Label 0");
        pan.add(label);
        pack();
        setVisible(true);
        width = pan.getPreferredSize().width;
    public void replace() {
       Dimension d = pan.getPreferredSize();
       pan.setPreferredSize(new Dimension(++width,d.height));
       pack();
    static void elapsed(String mess) {
        long ct = System.currentTimeMillis();
        System.out.println("Elapsed milliseconds, " + mess + ": " +
                           (ct - tm));
        tm = ct;
}Running this with Sun jdk 1.3.1 yields the timings:
Elapsed milliseconds, in constructor: 2226
Elapsed milliseconds, repack 1: 26
Elapsed milliseconds, repack 2: 24
Elapsed milliseconds, repack 2: 25
Elapsed milliseconds, repack 2: 24Running the same code with jdk 1.4.1_0 yields
Elapsed milliseconds, in constructor: 1773
Elapsed milliseconds, repack 1: [bold]5747[/bold]
Elapsed milliseconds, repack 2: 32
Elapsed milliseconds, repack 2: 7
Elapsed milliseconds, repack 2: 1Note the FIVE SECOND delay during the first setPreferredSize()- pack() sequence.
This problem also occurs with 1.4.0, Blackdown 1.4.1 and IBM 1.4.0, so presumably it is something in Sun's 1.4 code.
The only way I've found to avoid the initial delay is to set frame invisible
before the setPreferredSize(), pack() sequence and visible afterwards. But of course this makes the window 'flash' and is very unplesant for users.
I've looked at the source for pack() but it hasn't gotten me anywhere. If anyone has an idea about fixing this problem or working around it, I'd appreciate hearing about it.
FYI I ran these tests under Linux, vanilla installations of SuSE 8.0 and 8.1
Thanks,
bw

It turns out that this problem occurs under SuSE (8.0 and 8.1) but NOT under Redhat 8.0
I do NOT understand how this is possible, but it is the case. Has anyone encountered any SuSE specific problems?
fyi I've reproduced the problem on two rather different i386 machines (an AMD k7 and a Pentium III thinkpad), so it certainly doesn't have anything to do with hardware.
bw

HTTP Status Code 200 Received But Error During Response Parsing

Hi Experts,
We are testing a simple Proxy(ECC) to File scenario in QA. This interface was working fine in Dev but we are getting the following error here in QA:
<?xml version="1.0" encoding="UTF-8" standalone="yes" ?>

<SAP:Error xmlns:SAP="http://sap.com/xi/XI/Message/30" xmlns:SOAP="http://schemas.xmlsoap.org/soap/envelope/" SOAP:mustUnderstand="">
<SAP:Category>XIServer</SAP:Category>
<SAP:Code area="INTERNAL">OK_BUT_NO_XI_MESSAGE</SAP:Code>
<SAP:P1 />
<SAP:P2 />
<SAP:P3 />
<SAP:P4 />
<SAP:AdditionalText />
<SAP:Stack>HTTP Status Code 200 Received But Error During Response Parsing: No XI Response Received XML element Envelope missing in SOAP message header (SAP XI Extension)</SAP:Stack>
<SAP:Retry>M</SAP:Retry>
</SAP:Error>
We searched other threads but could not get any solution. Please provide suggestions.
Thank You.
Regards,
Anandan

the problem was due to high volume message (247 MB ) ...Java stack was not able to process this huge message ,that is the reason ,it started automatically and as a result , "HTTP Status Code 200 Received But Error During Response Parsing" due to unavailability of AFW during Call adapter step in the pipeline processing...
We have done the following activities in order to solve this problem....
increase the value of icm/HTTP/max_request_size_KB to 512MB
                                    icm/wp_roll_timeout   to maximum
                                    HTTP TIMEOUT to 1800 sec
                                   icm/wp_roll_timeout   to maximum
                                     mpi/total_size_MB to maximum
                                   mpi/buffer_size to maximum
and then increased the maxthreadcount ,maxcontentlength using config tool...
and also increased the java heap size to maximum....
After doing everything ,the file has been successfully processed....
the problem has been resolved...

Urgent: Please help. how to solve the time delay during buffer read and write using vc++

I need to continuously acquire data from daqmx card, write into a file and at the same time corelate (in terms of time) the data with signals from other instruments. The current problem is that there is time delay during read and write data into buffer,thus causing misalignment of the data from multiple instruments. Is there a way to solve the delay? or Is there a way to mark the time of the data acquisition in the buffer? If I know the starting time (e.g. 0) of data acquisition and sampling rate (e.g. 1kHz), can I simply add 1ms to each data sample in the buffer? The current code is shown below.
void DataCollectionWin::ConnectDAQ()
DAQmxErrChk(DAQmxCreateTask ("", &taskHandle));
    DAQmxErrChk(DAQmxCreateAIVoltageChan(taskHandle,"Dev1/ai0,Dev1/ai1,Dev1/ai2,Dev1/ai3,Dev1/ai4,Dev1/ai5,Dev1/ai16,Dev1/ai17,Dev1/ai18,Dev1/ai19,Dev1/ai20,Dev1/ai21,Dev1/ai6,Dev1/ai7,Dev1/ai22","",DAQmx_Val_Cfg_Default,-10.0,10.0,DAQmx_Val_Volts,NULL));
  DAQmxErrChk(DAQmxCfgSampClkTiming(taskHandle,"",1000.0,DAQmx_Val_Rising,DAQmx_Val_ContSamps,60000));
  DAQmxErrChk (DAQmxRegisterEveryNSamplesEvent(taskHandle,DAQmx_Val_Acquired_Into_Buffer,50,0,EveryNCallback,NULL));// Every 50 samples the EveryNSamplesEvent will be trigured, to reduce time delay.
  DAQmxErrChk (DAQmxRegisterDoneEvent(taskHandle,0,DoneCallback,NULL));
  DAQmxErrChk (DAQmxStartTask(taskHandle));
int32 CVICALLBACK EveryNCallback(TaskHandle taskHandle, int32 everyNsamplesEventType, uInt32 nSamples, void *callbackData)
DAQmxErrChk (DAQmxReadAnalogF64(taskHandle,50,10.0,DAQmx_Val_GroupByScanNumber,data,50*15,&read,NULL));
   //memcpy(l_data,data,6000);
SetEvent(hEvent);
l_usstatus_e[0]=g_usstatus[0];// signals from other instruments that need to be corelated with the data from daq cards.
l_optstatus_e[0]=g_optstatus[0];
if( read>0 ) // write data into file
   //indicator=1;
for (i=0;i<read;i++)
{  //fprintf(datafile,"%d\t",i);
  fprintf(datafile,"%c\t",l_usstatus_s[0]);
  fprintf(datafile,"%c\t",l_usstatus_e[0]);
        fprintf(datafile,"%c\t",l_optstatus_s[0]);
  fprintf(datafile,"%c\t",l_optstatus_e[0]);
          fprintf(datafile,"%.2f\t",data[15*i]);
//   sprintf( pszTemp, "%f", data[6*i]);
// pListCtrl->SetItemText(0, 2, pszTemp);
    //pWnd->m_trackinglist.SetItemText(0, 2, pszTemp);
     fprintf(datafile,"%.2f\t",data[15*i+1]);
     fprintf(datafile,"%.2f\t",data[15*i+2]);

Hello kgy,
It is a bit of a judgment call. You should just choose the board that you think has the most to do with your issue. For example, this issue was much more focused on setting up your data acquisition task than the Measurement Studio environment/tools, so the MultifunctionDAQ board would have been the best place for it. As for moving your post to another board, I do not believe that is possible.
Regards,
Dan King

No Response - Severe Delay in Response

I don't know what happened since I added no new hardware or software but one day it was all working fine the next I started having severe problems.
I did a repair installation and it didn't work so I completely uninstalled and then re-installed (after a reboot) and it still is acting up.
None of my other software, Adobe or otherwise, is acting strangely, only Premiere. I'm open to any suggestion because this is really freaking me out.
I was capturing SD footage via a Canon XL1s and having no problems. After about half of the tapes were done I quit for the night. The next morning when I went to start capturing again, Premiere locked up after opening the capture window. I tried a second camera (a Sony HDR-HC9) but had the same problems. I swapped out data cables, same problem.
Then I noticed that playback controls of the video already on the timeline had severe delays, up to 3 minutes, before responding to "play" and "stop/pause". I also noticed similar long delays when selecting windows within the project and even in the pulldown menus.
I deleted the current project and created a new one but the problems persisted. I opened old projects that I KNOW are good, but the problem persisted in these as well.
When I close out Premiere the "Adobe Premiere Pro.exe" process stays active in the task manager for up to 5 minutes after I closed the program.
Other then the minutes long delays in response, if I wait for it, the software seems to operate properly but will often just lock up and I have to do an "End Program" to get out of the lock up.
As I mentioned, I have completely uninstalled and reinstalled the software and none of my other software seems to be affected. WTF!
Alienware Desktop PC
Dual 2.8 Ghz Pentiums
2G RAM
WinXP w/SP3
PPro CS3 (part of Premium Production Package)

You can try resetting the preference file to the defaults by holding
down the shift key while you start Premiere and keeping it held down
till the splash screen displays.

Excessive (?) cluster delays during shutdown of storage enabled node.

We are experiencing significant delays when shutting down a storage enabled node. At the moment, this is happening in a benchmark environment. If these delays were to occur in production, however, they would push us well outside of our acceptable response times, so we are looking for ways to reduce/eliminate the delays.
Some background:
- We're running in a 'grid' style arrangement with a dedicated cache tier.
- We're running our benchmarks with a vanilla distributed cache -- binary storage, no backups, no operations other than put/get.
- We're allocating a relatively large number of partitions (1973), basing that number on the total potential cluster storage and the '50MB per partition' rule.
- We're using JSW to manage startup/shutdown, calling DefaultCacheServer.main() to start the cache server, and using the shutdown hook (from the operational config) to shutdown the instance.
- We're currently running all of the dedicated cache JVMs on a single machine (that won't be the case in production, of course), with a relatively higher ratio of JVMs to cores --> about 2 to 1.
- We're using a simple benchmarking client that is issuing a combination of puts/gets against the distributed cache. The ids for these puts/gets are randomized (completely synthetic, i know).
- We're currently handling all operations on the distributed service thread (i.e. thread count is zero).
What we see:
- When adding a new node to a cluster under steady load (~50% CPU idle avg) , there is a very slight degradation, but only very slight. There is no apparent pause, and the maximum operation times against the cluster might barely exceed ~100 ms.
- When later removing that node from the cluster (kill the JVM, triggering the coherence supplied shutdown hook), there is an obvious, extended pause. During this time, the maximum operation times against the cluster are as high as 5, 10, or even 15 seconds.
At the beginning of the pause, a client will see this message:
2010-07-13 22:23:53.227/55.738 Oracle Coherence GE 3.5.3/465 <D5> (thread=Cluster, member=10): Member 8 left service Management with senior member 1
During the length of the pause, the cache server logging indicates that primary partitions are being shuffled around.
When the partition shuffle is complete, the clients become immediately responsive, and display these messages:
2010-07-13 22:23:58.935/61.446 Oracle Coherence GE 3.5.3/465 <D5> (thread=Cluster, member=10): Member 8 left service hibL2-distributed with senior member 1
2010-07-13 22:23:58.973/61.484 Oracle Coherence GE 3.5.3/465 <D5> (thread=Cluster, member=10): MemberLeft notification for Member 8 received from Member(Id=8, Timestamp=2010-07-13 22:23:21.378, Address=x.x.x.x:8001, MachineId=47282, Location=site:xxx.com,machine:xxx,process:30552,member:xxx-S02, Role=server)
2010-07-13 22:23:58.973/61.484 Oracle Coherence GE 3.5.3/465 <D5> (thread=Cluster, member=10): Member(Id=8, Timestamp=2010-07-13 22:23:58.973, Address=x.x.x.x:8001, MachineId=47282, Location=site:xxx.com,machine:xxx,process:30552,member:xxx-S02, Role=server) left Cluster with senior member 1
2010-07-13 22:23:59.135/61.646 Oracle Coherence GE 3.5.3/465 <D5> (thread=Cluster, member=10): TcpRing: disconnected from member 8 due to the peer departure
Note that there was almost nothing actually in the entire cluster-wide cache at this point -- maybe 10 MB of data at most.
Any thoughts on how we could eliminate (or nearly eliminate) these pauses on shutdown?

Increasing the number of threads associated with the distributed service does not seem to have a noticable effect. I might try it in a larger scale test, just to make sure, but initial indications are not positive.
From the client side, the operations seem hung behind the DistributedCache$BinaryMap.waitForPartitionRedistribution() method. The call stack is listed below.
"main" prio=10 tid=0x09a75400 nid=0x6f02 in Object.wait() [0xb7452000]
java.lang.Thread.State: TIMED_WAITING (on object monitor)
at java.lang.Object.wait(Native Method)
at com.tangosol.coherence.component.util.daemon.queueProcessor.service.grid.DistributedCache$BinaryMap.waitForPartitionRedistribution(DistributedCache.CDB:96)
- locked <0x9765c938> (a com.tangosol.coherence.component.util.daemon.queueProcessor.service.grid.DistributedCache$BinaryMap$Contention)
at com.tangosol.coherence.component.util.daemon.queueProcessor.service.grid.DistributedCache$BinaryMap.waitForRedistribution(DistributedCache.CDB:10)
at com.tangosol.coherence.component.util.daemon.queueProcessor.service.grid.DistributedCache$BinaryMap.ensureRequestTarget(DistributedCache.CDB:21)
at com.tangosol.coherence.component.util.daemon.queueProcessor.service.grid.DistributedCache$BinaryMap.get(DistributedCache.CDB:16)
at com.tangosol.util.ConverterCollections$ConverterMap.get(ConverterCollections.java:1547)
at com.tangosol.coherence.component.util.daemon.queueProcessor.service.grid.DistributedCache$ViewMap.get(DistributedCache.CDB:1)
at com.tangosol.coherence.component.util.SafeNamedCache.get(SafeNamedCache.CDB:1)
at com.ea.nova.coherence.lt.GetRandomTask.main(GetRandomTask.java:90)
Any help appreciated!

Performance - htmlb vs. response.write() vs. JspDynPage

Hi,
I have the following question.
During our tests it seems some iViews were causing a significantly higher load on the CPU than others.
In some occasions, these iViews contained nothing more than some simple
response.write("<b>Some HTML tags etc.</b>");
lines, nothing fancy.
Other iViews, which incorporated HTMLB objects in the Java classes or used JSP files to render the output, caused much less load on the CPU.
I know this is not a fully objective statement, but could it be the response.write() statements are performing less efficient?
If so, what would be the reason then?
Hope someone could answer this question
With kind regards,
Robin van het Hof

no ideas?

How to avoid delay during analog output generation by changing its frequency?

Windows XP
LabVIEW 7.1
PCI-6036E + BNC-2120
Hi,
I am going to create a vi to generate an engine speed sensor signal (a simple square wave with specific missed pulses, in my case 58 pulses “teeth” and 2 missed pulses “missed teeth”) as an analog output but in addition give me the opportunity to control parameters for example frequency online to simulate the engine speed changes during running that vi. For this purpose I have started with “Continuous Generation.vi” which is available in NI Example Finder under the following path:
Hardware Input and Output > Traditional DAQ > Analog Output > Continuous Generation.vi
Then I modified it towards above mentioned goal, all related vi s are attached. The main vi is: "Motor Signal Generator_1.12.vi"
At the first try it looks that it works properly but when have a look on that more accurately with Oscilloscope (fortunately I have a good one: Agilent 54621A – 60 MHz, 200 Ms/s) obviously there is a gap (delay or Jitter) whenever I change the engine speed. It is also attached in Signal generation_problem report.doc file.
Note: Small gaps are OK and related to predefined missed teeth but the big one is happened during changing engine speed.
As far as I understand it is related to the time which case structure in AO C-GEN sub-vi needs for AO reconfiguration each time after changing the engine speed (update rate). How can I get rid of this delay or gap during signal generation and generating completely continuous signal?
I have to mention that obviously I changed the frequency by changing the update rate. The other possibility is to change the number of updates in one period (refer to "generate arb frequency.vi" in NI site: http://sine.ni.com/apps/we/niepd_web_display.display_epd4?p_guid=B45EACE3E48F56A4E034080020E74861) which resulted in no delay however then I can not change the frequency continuously but step by step (for example jump from 5Khz to 2.5KHz immediately) and this can not pass to my application.
Any hint is appreciated.
regards
Attachments:
Signal_generation_NIsupport.zip ‏81 KB

Hi Roozbeh,
The following example will allow you to vary the pulse train frequency during run time.
Thanks,
Lesley Y.
Attachments:
GenDigPulseTrain-ChangingSpecs.vi ‏75 KB

Database migration to MAXDB and Performance problem during R3load import

Hi All Experts,
We want to migrate our SAP landscape from oracle to MAXDB(SAPDB). we have exported database of size 1.2 TB by using package and table level splitting method in 16 hrs.
Now I am importing into MAXDB. But the import is running very slow (more than 72 hrs).
Details of import process as per below.
We have been using distribution monitor to import in to target system with maxdb database 7.7 release. We are using three parallel application servers to import and with distributed R3load processes on each application servers with 8 CPU.
Database System is configured with 8CPU(single core) and 32 GB physical RAM. MAXDB Cache size for DB instance is allocated with 24GB. As per SAP recommendation We are running R3load process with parallel 16 CPU processes. Still import is going too slow with more that 72 hrs. (Not acceptable).
We have split 12 big tables in to small units using table splitting , also we have split packages in small to run in parallel. We maintained load order in descending order of table and package size. still we are not able to improve import performance.
MAXDB parameters are set as per below.
CACHE_SIZE 3407872
MAXUSERTASKS 60
MAXCPU 8
MAXLOCKS 300000
CAT_CACHE_SUPPLY 262144
MaxTempFilesPerIndexCreation 131072
We are using all required SAP kernel utilities with recent release during this process. i.e. R3load ,etc
So Now I request all SAP as well as MAXDB experts to suggest all possible inputs to improve the R3load import performance on MAXDB database.
Every input will be highly appreciated.
Please let me know if I need to provide more details about import.
Regards
Santosh

Hello,
description of parameter:
MaxTempFilesPerIndexCreation(from version 7.7.0.3)
Number of temporary result files in the case of parallel indexing
The database system indexes large tables using multiple server tasks. These server tasks write their results to temporary files. When the number of these files reaches the value of this parameter, the database system has to merge the files before it can generate the actual index. This results in a decline in performance.
as for max value, I wouldn't exceed the max valuem for 26G value 131072 should be sufficient. I used same value for 36G CACHE SIZE
On the other side, do you know which task is time consuming? is it table import? index creation?
maybe you can run migtime on import directory to find out
Stanislav

Switch: delay during the first change of children

Hello,
in my scene graph I use a Switch. This Switch has three children, whereof always one is visible. Depending on the viewing direction, I change the active Child. It works very well, but
there is still alittle problem, when the change between the children is done for the first time. I mean, when i start the program the first child is active. During changing the
viewing direction the second child will become active, in this moment there is a little delay. The same when the third child is activated for the first time. After that the change of
the children works fluently.
I think in the beginning, the other children have to be loaded in the buffer. How can I do this, before showing my canvas?!
Perhaps you can give me some methods, which I should use, that would it make easier.
With kind regards
Gunnar Schroeder

Hi,
I'm sorry I can't answer your question, but do I understand that you are using the SwitchInterpolator to change the View object of your View graph?
I'm looking to do something like that in my game: top view vs. first person view.
Was it difficult, it is just a matter of adding a SwitchGroup to your View graph?
Thanks!

Interesting performance anomaly during video encode

I just noticed an interesting anomaly while my iDVD6 project was encoding video. I found that if I cover up the 'Creating Your DVD' progress bar and preview window with a Finder window, that video encoding seems to move a whole lot faster. I could tell by listening to the disk activity which seemed to be occurring about twice as fast. When I moved the Finder window away and exposed progress bar/preview window, then disk activity slowed down.
I opened Activity Monitor and looked at CPU% which showed about 70-80% with progress bar/preview window exposed. After covering up, the CPU% increased from 125-150% So apparently exposing progress bar/preview window slows things down quite a bit during video encode. I tried same trick during audio encode, and it made no difference. CPU% was about 7-8% during audio encode.
I was wondering if anyone in this discussion group noticed this performance anomaly previously.
Paul

Hi Paul
Yes I noted some relatively related phenomena during the rendering process
in FinalCutExpress that just selecting Finder seemed to speed things up.
Second: Please don't rely on the Activity monitor and most so when it says
iDVD doesn't answer. It's just rubisch. iDVD keeps on working - just wait and see.
Yours Bengt W

HELP: Delay HTTP Response

Hi,
I'm trying to use a simple HTTP Servlet to provide a synchronous interface to an inheritantly asynchronous systems.
For example
1. Client does HTTP POST
2. Servlet receives request (via doPost)
3. Servlet generates an internal asynchronous request
4. Servlet receives an internal asynchronous response
5. Servlet returns the HTTP response
6. Client receives the HTTP response
How can I get my servlet to delay sending the HTTP response once I've exited the doPost() method (or is there a more clever way to do this?
Thanks.
Chris

You can't. But you could control when you leave doPost() by sleeping for the requisite amount of time.
Of course you can't control what the network of processes between your servlet and the client does or how long it takes, but I suppose you have taken care of that in some way.

CallableStatement performance delay during response

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