Performance issue - Loading and Calculating

Hi, I am having 5 GB of data. It is taking 1 hr to load and 30 min to calculate. I did the following things to improve the performance. 1) Sort the data and loading them in the order of largest sparse first, followed by smallest and dense 2) Enabled parallel load, gave 6 threads for prepare and 4 for writing. 3) Increased data file cache as 400MB and data cache as 50MB, then index cache as 100MB. 4) Calculation only for 4 dimensions, out of 9. In that 2 are dense and 2 are sparse. 5) Calculation with parallel calculation having 3 threads and CALCTASKDIMS as 2. But i am not getting any improvements. While doing the calculation i got following message in the logs. I feel that CALCTASKDIM is not working [Fri Jan 6 22:01:54 2006]Local/tcm2006/tcm2006/biraprd/Info(1012679) Calculation task schedule [2870,173,33,10,4,1] [Fri Jan 6 22:01:54 2006]Local/tcm2006/tcm2006/biraprd/Info(1012680) Parallelizing using [1] task dimensions. Usage of Calculator cache caused reduction in task dimensions [Fri Jan 6 22:33:54 2006]Local/tcm2006/tcm2006/biraprd/Info(1012681) Empty tasks [2434,115,24,10,2,0] Can any one help me what the above log message is telling and what are the other things to be done to imrpove the performance. Regards prsan

its not the problem with ur calc task dim. Calculation task schedule [2870,173,33,10,4,1] indicates that ur parell calc can start with 2870calculations in parallel, after which 173 can be performed inparallel then 33 ,10,4 and 1. Empty tasks [2434,115,24,10,2,0] means these manytasks dont need any calculation- either because there is no data orthey are marked clean due to intelligent calc. the problem lies with your cal cache setting. try increaing thecal cache settings in ur cfg file and use calcache high setting inyour calc. hope this works

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 CUST_LEVEL1.customer_email as CUSTOMER_EMAIL,
 CUST_LEVEL2.*
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 (select XML_FILE from dual) p,
 XMLTable(
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 mainq
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I CANNOT MANAGE TO INSERT 4000 records in less than 30 minutes!
Can you help or advise how to reduce this to reasonable timings?
Thanks

Simplified example on a few attributes :
-- INSERT INTO tmp_xml VALUES ( xml_file );
INSERT ALL
INTO newsletters (brandid, customer_email, dw_website_tag)
VALUES (p_brandid, customer_email, p_website)
INTO newsletters_c_att (brandid, customer_email, customer_no, customer_type, title, first_name, last_name)
VALUES (p_brandid, customer_email, customer_no, customer_type, title, first_name, last_name)
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FROM tmp_xml t
 , XMLTable(
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 , '/custom-objects/custom-object'
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 , customer_no varchar2(256) path 'object-attribute[@attribute-id="customer-no"]/value'
 , customer_type varchar2(256) path 'object-attribute[@attribute-id="customer_type"]/value'
 , title varchar2(256) path 'object-attribute[@attribute-id="title"]/value'
 , first_name varchar2(64) path 'object-attribute[@attribute-id="first_name"]/value'
 , last_name varchar2(64) path 'object-attribute[@attribute-id="last_name"]/value'
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Bryan

Hi Bryan,
First let me make sure I understand your situation. It sounds like you've already built the sequence that can programmatically build a sequence of template functions then populate using a Property Loader step in the generated sequence. You are hoping to remove that Property Loader from the generated sequence and instead have the generating sequence load the properties and embed them as defaults in the generated sequence. This way you would avoid having to run the Property Load step every time you ran this sequence. Is this correct?
Assuming it is, I believe this exceeds the capabilities of the Property Loader functionality. It isn't designed to "push" properties to another sequence. Therefore your options are to either stick with the Property Loader step at the beginning of your generated sequence or implement the parsing and assigning of the CSV to manually populate the template steps.
Please post back if I misunderstood you or you have additional questions.

QUERY PERFORMANCE AND DATA LOADING PERFORMANCE ISSUES

WHAT ARE QUERY PERFORMANCE ISSUES WE NEED TO TAKE CARE PLEASE EXPLAIN AND LET ME KNOW T CODES...PLZ URGENT
WHAT ARE DATALOADING PERFORMANCE ISSUES WE NEED TO TAKE CARE PLEASE EXPLAIN AND LET ME KNOW T CODES PLZ URGENT
WILL REWARD FULL POINT S
REGARDS
GURU

BW Back end
Some Tips -
1)Identify long-running extraction processes on the source system. Extraction processes are performed by several extraction jobs running on the source system. The run-time of these jobs affects the performance. Use transaction code SM37 Background Processing Job Management to analyze the run-times of these jobs. If the run-time of data collection jobs lasts for several hours, schedule these jobs to run more frequently. This way, less data is written into update tables for each run and extraction performance increases.
2)Identify high run-times for ABAP code, especially for user exits. The quality of any custom ABAP programs used in data extraction affects the extraction performance. Use transaction code SE30 ABAP/4 Run-time Analysis and then run the analysis for the transaction code RSA3 Extractor Checker. The system then records the activities of the extraction program so you can review them to identify time-consuming activities. Eliminate those long-running activities or substitute them with alternative program logic.
3)Identify expensive SQL statements. If database run-time is high for extraction jobs, use transaction code ST05 Performance Trace. On this screen, select ALEREMOTE user and then select SQL trace to record the SQL statements. Identify the time-consuming sections from the results. If the data-selection times are high on a particular SQL statement, index the DataSource tables to increase the performance of selection (see no. 6 below). While using ST05, make sure that no other extraction job is running with ALEREMOTE user.
4)Balance loads by distributing processes onto different servers if possible. If your site uses more than one BW application server, distribute the extraction processes to different servers using transaction code SM59 Maintain RFC Destination. Load balancing is possible only if the extraction program allows the option
5)Set optimum parameters for data-packet size. Packet size affects the number of data requests to the database. Set the data-packet size to optimum values for an efficient data-extraction mechanism. To find the optimum value, start with a packet size in the range of 50,000 to 100,000 and gradually increase it. At some point, you will reach the threshold at which increasing packet size further does not provide any performance increase. To set the packet size, use transaction code SBIW BW IMG Menu on the source system. To set the data load parameters for flat-file uploads, use transaction code RSCUSTV6 in BW.
6)Build indexes on DataSource tables based on selection criteria. Indexing DataSource tables improves the extraction performance, because it reduces the read times of those tables.
7)Execute collection jobs in parallel. Like the Business Content extractors, generic extractors have a number of collection jobs to retrieve relevant data from DataSource tables. Scheduling these collection jobs to run in parallel reduces the total extraction time, and they can be scheduled via transaction code SM37 in the source system.
8). Break up your data selections for InfoPackages and schedule the portions to run in parallel. This parallel upload mechanism sends different portions of the data to BW at the same time, and as a result the total upload time is reduced. You can schedule InfoPackages in the Administrator Workbench.
You can upload data from a data target (InfoCube and ODS) to another data target within the BW system. While uploading, you can schedule more than one InfoPackage with different selection options in each one. For example, fiscal year or fiscal year period can be used as selection options. Avoid using parallel uploads for high volumes of data if hardware resources are constrained. Each InfoPacket uses one background process (if scheduled to run in the background) or dialog process (if scheduled to run online) of the application server, and too many processes could overwhelm a slow server.
9). Building secondary indexes on the tables for the selection fields optimizes these tables for reading, reducing extraction time. If your selection fields are not key fields on the table, primary indexes are not much of a help when accessing data. In this case it is better to create secondary indexes with selection fields on the associated table using ABAP Dictionary to improve better selection performance.
10)Analyze upload times to the PSA and identify long-running uploads. When you extract the data using PSA method, data is written into PSA tables in the BW system. If your data is on the order of tens of millions, consider partitioning these PSA tables for better performance, but pay attention to the partition sizes. Partitioning PSA tables improves data-load performance because it's faster to insert data into smaller database tables. Partitioning also provides increased performance for maintenance of PSA tables for example, you can delete a portion of data faster. You can set the size of each partition in the PSA parameters screen, in transaction code SPRO or RSCUSTV6, so that BW creates a new partition automatically when a threshold value is reached.
11)Debug any routines in the transfer and update rules and eliminate single selects from the routines. Using single selects in custom ABAP routines for selecting data from database tables reduces performance considerably. It is better to use buffers and array operations. When you use buffers or array operations, the system reads data from the database tables and stores it in the memory for manipulation, improving performance. If you do not use buffers or array operations, the whole reading process is performed on the database with many table accesses, and performance deteriorates. Also, extensive use of library transformations in the ABAP code reduces performance; since these transformations are not compiled in advance, they are carried out during run-time.
12)Before uploading a high volume of transaction data into InfoCubes, activate the number-range buffer for dimension IDs. The number-range buffer is a parameter that identifies the number of sequential dimension IDs stored in the memory. If you increase the number range before high-volume data upload, you reduce the number of reads from the dimension tables and hence increase the upload performance. Do not forget to set the number-range values back to their original values after the upload. Use transaction code SNRO to maintain the number range buffer values for InfoCubes.
13)Drop the indexes before uploading high-volume data into InfoCubes. Regenerate them after the upload. Indexes on InfoCubes are optimized for reading data from the InfoCubes. If the indexes exist during the upload, BW reads the indexes and tries to insert the records according to the indexes, resulting in poor upload performance. You can automate the dropping and regeneration of the indexes through InfoPackage scheduling. You can drop indexes in the Manage InfoCube screen in the Administrator Workbench.
14)IDoc (intermediate document) archiving improves the extraction and loading performance and can be applied on both BW and R/3 systems. In addition to IDoc archiving, data archiving is available for InfoCubes and ODS objects.
Hope it Helps
Chetan
@CP..

Generic extraction loading and performances issues

hi,
any one can give the details about the generic extraction loading as well as performance issues.
advance thanks
regards
praveen

Hi,
when there is no suitable business content datasource we go for creating generic data source.
by using generic data source we can extract data present in single or multiple tables.
If the data is present in the single table we go for generic data source extracting from table.
If the data that is to be extracted is present in multiple tables and the relation between the tables is one to one and if there is a common field in both the tables we create a view on these tables and create a generic data source extracting from view.
if you want to extract data from different tables and there is no common field we create a info set on these tables and create a generic datasource extracting from query.
if you want to extarc the data from different tables and the relation is one to many or many to many we create a generic data source from function module.
If we extarct from function module ,at run time it has to execute the code and brings the data to BW.so it degrades the loading performance.
regards,

Performance issue - Loading and Calculating

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