Transcript 20 Tips and Tricks to Improve Data Load Performance Jesper Christensen

20 Tips and Tricks
to Improve Data
Load Performance
Jesper Christensen
COMERIT
© 2012 Wellesley Information Services. All rights reserved.
In This Session …
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Gain insight into SAP NetWeaver® BW data load processes, how
they work, and what tools are available to monitor and optimize
their performance
Receive best practices to maximize data load performance while
reducing long-term maintenance costs
Understand the benefits of optimized data load processes
Find out how to enable version history to track code changes and
how to create reusable ETL logic to improve throughput and
reduce data load time
Get tips on when and how to use customer exits in DataSources
and variables to manage risk and reduce maintenance costs
Identify the challenges and benefits of semantic partitioning and
the importance of efficient data models
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What We’ll Cover …
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Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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SAP NetWeaver BW Data Load Processing Overview
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SAP NetWeaver BW data load processing consists of three main
activities:
 Extraction = Collecting the data in the source systems and
preparing it before sending it to SAP NetWeaver BW
 Transformation = Transforming the data using routines,
lookups, formulas, etc.
 Load = Updating the data into InfoProviders’ DataStore Objects
(DSOs), cubes, and master data
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Dataflow in SAP NetWeaver BW
Source: SAP
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Extraction Interface Types
Source: help.sap.com
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DataSources Supported by SAP NetWeaver Extraction
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SAP NetWeaver BW Service API
 Allows data from SAP systems in standardized form to be
extracted and accessed directly
 These can be SAP application systems or SAP NetWeaver
BW systems
File interface
 The file interface permits the extraction from and direct access
to files, such as csv files
Web services
 Permit you to send data to the SAP NetWeaver BW system
under external control
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DataSources Supported by SAP NetWeaver Extraction
(cont.)
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Universal Data (UD) Connect
 Permits the extraction from and direct access to relational data
Database (DB) Connect
 Permits the extraction from and direct access to data located in
tables or views of a database management system
Staging Business Application Programming Interfaces (BAPIs)
 Open interfaces that SAP BusinessObjects DataServices and
certified third-party tools can use to extract data from older
systems
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Extraction Time Can Be Split into Two Categories
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Extraction time
 DB time to select the data to be extracted
 Logic applied during extraction such as joins, lookups, and
filtering
Middleware and network time
 The time used to transfer the data from the source system to
the target SAP NetWeaver BW system
 Interface types such as Web services and Universal Data (UD)
Connect are good for small amounts of data and cannot handle
large volumes
 Fixed format files are larger to transfer but faster to load into
SAP NetWeaver BW
 WAN Network time can become a bottleneck during peak hours
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Transformation Types
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SAP NetWeaver BW supports the 3.x and the 7.x versions of
transforming the data
 3.x is using Transfer rules and Update rules
 Two steps of logic to process the dataset
 Loads to different targets must be processed together
 Used to have better performance than transformations
 Old method; no more development or performance
enhancements; do not continue to use
 7.x is using transformations
 Is using a single step of logic to process the dataset
 Loads to different targets can be processed independently
 Better performance
 Always use this option for new development
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Loading Data to Information Providers Types
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Loading of the data to InfoProviders differs depending on type
 DSO
 Update of the activation queue
 Activation of data (update of active table and changelog)
 SID determination
 Should in general be switched off for DSOs
 Master data
 Update of master data tables
 SID determination
 Check duplicate key values
 Very time consuming for time-dependent attributes
 Attribute change run to activate the master data
 Generate navigation data
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Loading Data to Information Providers Types (cont.)
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Loading of the data to InfoProviders differs depending on type
(cont.)
 Cubes
 Update of data to the InfoCube star schema
 SID determination
 Roll up data to aggregates
 Update data to SAP NetWeaver BW Accelerator (SAP
NetWeaver BWA)
Performance considerations for loading the data
 Ensure that the database parameters are in place
 Implement the correct SAP NetWeaver BW settings for your
InfoProviders
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What We’ll Cover …
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Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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Tip 01: SAP NetWeaver BW 7.x Statistics
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SAP NetWeaver BW includes a great statistics tool
 It collects information on most SAP NetWeaver BW-specific
activity
 Such as data loads and queries
 It’s delivered as business content
 So you must activate it just like all business content
 How to Activate Admin Cockpit document on help.sap.com
 http://help.sap.com/saphelp_nw04s/helpdata/en/46/f9bd550d4
0537de10000000a1553f6/frameset.htm
Tip 01: SAP NetWeaver BW 7.x Statistics (cont.)
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Define standard measure that can
be monitored on a daily, weekly,
and monthly basis to evaluate
data load performance trends
 Records processed per minute
or Time to process 1 million
records
 Time spent on extraction
 Time spent in transformations
 Top 10 long running loads
 Total time spent for Attribute
and Hierarchy change runs
Use the standard queries and
reports as a starting point
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Tip 02: See Details About Performance in the Monitor
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The load monitor transaction code RSMO gives more details
about the processing steps
 InfoPackage details
 Data Transfer Process (DTP) details
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Tip 03: Use SE30 to Test Performance
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Transaction code SE30 ABAP Runtime Analysis gives a detailed
view of performance
Remember to set
the accuracy to
Low
Run
transaction
code RSA3
Note: SE30 can also be used for transformations by simulating the DTP run
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Tip 03: Use SE30 to Test Performance (cont.)
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Detailed Runtime will show you the bottlenecks
Sort descending based on
Net Time and you will see
your bottleneck on the top
What We’ll Cover …
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Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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Tip 04: Implement the Correct DB Parameters
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Key DB parameters
 SAP has recommended some parameter values for SAP
NetWeaver BW that usually improve performance
 Expect to evaluate these parameter settings frequently, though,
to ensure that the DB operates optimally
 See three key SAP Notes:
 830576 – Parameter recommendations for Oracle 10g
 387946 – Use of locally managed tablespaces for
BW systems
 1044441 – Basis parameterization for NW 7.0 BI systems
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Tip 05: Manage Database Statistics
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DB statistics are also crucial for
SAP NetWeaver BW performance
 The DB will not know the most
optimal execution path for an
SQL statement without DB
statistics
 To set up DB statistics:
 Set up BRCONNECT job
using DB20 to recalculate DB
statistics
 Use program RSANAORA to
analyze specific tables
DB statistics can run very slowly under Oracle when
you use SAP NetWeaver BW programs or DB
statistics. Make sure you use BRCONNECT.
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Tip 06: Build Secondary Indices
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The select statements used during extraction or during
user exit enhancements should always use a database
index
 Build secondary indices in transaction code SE11
or on the DSO objects used in select statements
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What We’ll Cover …
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Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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Tip 07: Coding Tips — Dynamic Calls
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Code the extractor user exits so that they call a dynamic program
per DataSource
 Isolate the code per DataSource in a self-contained program
 Minimize risk that a syntax error in code for one DataSource
impacts extraction from all other DataSources
Example
 Program name = ZBW + <DataSource name>
 Form name = DOZBW + <DataSource name>
This same technique can be used with customer exit variable
code
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Tip 07: Coding Tips — Dynamic Calls (cont.)
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Illustration: Sample dynamic program call
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Tip 08: Coding Tips — Field Symbols
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Performance consideration: Where possible, use field symbols to
populate fields in the data package
 The move costs of a LOOP ... INTO statement depend on the
size of a table line
 The larger the line size, the longer the move will take
 By applying a LOOP... ASSIGNING statement you can attach a
field symbol to the table lines and operate directly on the line
contents
 This is a much faster way to access the internal table lines
without moving their contents
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Tip 08: User Exit — Field Symbols
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Illustration: Sample use of field symbols
User Exit (without field-symbols)
User Exit (with field-symbols)
REPORT YBWZDS_AGR_USER.
*****************************************************************
* Form called dynamically must start with DOYBW + <DataSource>
*****************************************************************
REPORT YBWZDS_AGR_USER.
*****************************************************************
* Form called dynamically must start with DOZBW + <DataSource>
*****************************************************************
FORM DOYBWZDS_AGR_USER
TABLES C_T_DATA STRUCTURE ZOXBWD0001.
FORM DOYBWZDS_AGR_USER
TABLES C_T_DATA STRUCTURE ZOXBWD0001.
data: l_logsys type logsys.
l_s_data like ZOXBWD0001.
data: l_logsys type logsys.
field-symbols: <fs> like c_t_data.
select single logsys from t000
into l_logsys
where mandt = sy-mandt.
loop at c_t_data into l_s_data.
l_s_data-load_dt = sy-datum.
l_s_data-logsys = l_logsys.
modify c_t_data from l_s_data index sy-tabix.
endloop.
ENDFORM.
select single logsys from t000
into l_logsys
where mandt = sy-mandt.
loop at c_t_data assigning <fs>.
<fs>-load_dt = sy-datum.
<fs>-logsys = l_logsys.
endloop.
ENDFORM.
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Tip 09: Coding Tips — Read Instead of Loop
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Use a READ statement to access a table rather than a LOOP
WHERE
 The cost of a LOOP WHERE is much higher than a READ with
table key or binary search statement
 The READ can also be used prior to a loop statement that does
require a LOOP to then use a LOOP FROM INDEX instead of
LOOP WHERE
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Tip 09: User Exit: Read Instead of Loop
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Illustration: Sample use of field symbols
User Exit (without read)
User Exit (with read)
REPORT YBW2LIS_13_VDITM.
*****************************************************************
* Form called dynamically must start with DOYBW + <DataSource>
*****************************************************************
REPORT YBWZDS_AGR_USER.
*****************************************************************
* Form called dynamically must start with DOZBW + <DataSource>
*****************************************************************
FORM DOYBW2LIS_13_VDITM
TABLES C_T_DATA STRUCTURE ZOXBWD0001.
FORM DOYBWZDS_AGR_USER
TABLES C_T_DATA STRUCTURE ZOXBWD0001.
data: l_logsys type logsys.
l_s_data like ZOXBWD0001.
data: l_logsys type logsys,
l_idx type sy-tabix.
field-symbols: <fs> like c_t_data,
<fs1> like VBAP.
field-symbols: <fs> like c_t_data,
<fs1> like VBAP.
Loop at c_t_data assigning <fs>.
Loop at itab assigning <fs1>
where VBELN = c_t_data-VEBLN.
c_t_data-NETVALUE = c_t_data-NETVALUE + <fs>- NETWR.
endloop.
Endloop.
Loop at c_t_data assigning <fs>.
READ TABLE ITAB WITH TABLE KEY VBELN = c_t_data-VEBLN
BINARY SEARCH.
L_idx = sy-tabix.
ENDFORM.
Loop at itab assigning <fs1> FROM INDEX l_idx.
check <fs>-VBELN = c_t_data-VEBLN.
c_t_data-NETVALUE = c_t_data-NETVALUE + <fs>- NETWR.
endloop.
endloop.
ENDFORM.
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Tip 10: Delta Enable Generic DataSources
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Improve extract performance by creating delta-enabled generic
DataSources
Simple:
 By date
 By timestamp
 By sequential number (unique table key)
Complex:
 Pointers – ABAP techniques can be used to record an array of
pointers to identify new and changed records
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Tip 10: Delta Enable Generic DataSources (cont.)
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Illustration: Delta enabling a generic DataSource
Ensure that you set the upper or lower
limits correctly based on the data you are
extracting!
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Tip 11: Lookups
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Do not use single selects for lookups!
For better performance:
 Use start routines to read lookup data to an internal table
 Read internal table to populate field values in routines
For best performance:
 Add lookup fields to InfoSource
 Use start routine and field symbols to populate blank fields for
entire data package at one time (see illustration on slide titled
“User Exit — Field Symbols”)
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Tip 12: Program Includes
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Use includes for all complex routine logic
Access logic by using “perform” statements
Increase portability of transformation logic
 Use same read statements for multiple lookups
 Reduce risk of errors in obscure places
Decrease maintenance cost of complex update rules
 One place to go to fix/enhance logic
 Code is consistent and easier to follow
Enable version management of code
 Track changes over time
 Compare between systems
 Revert to previous versions
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Tip 12: Program Includes (cont.)
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Illustration – Select into internal table
Start routine
Program include
FORM startup
TABLES
MONITOR STRUCTURE RSMONITOR "user defined monitoring
MONITOR_RECNO STRUCTURE RSMONITORS
DATA_PACKAGE STRUCTURE DATA_PACKAGE
USING
RECORD_ALL LIKE SY-TABIX
SOURCE_SYSTEM LIKE RSUPDSIMULH-LOGSYS
CHANGING ABORT LIKE SY-SUBRC. "set ABORT <> 0 to cancel update
*
*$*$ begin of routine - insert your code only below this line *-*
*****************************************************************
* INITIALIZATION (ONE-TIME PER DATA PACKET) *********************
* TO READ FROM DATABASE (ALL RECORDS FOR DATA PACKAGE) **********
*****************************************************************
* FORM READ_USR02_TO_MEMORY_FOR_0BWTC_C02
*---------------------------------------------------------------*
Form READ_USR02_TO_MEMORY_FOR_0BWTC_C02
TABLES
MONITOR
STRUCTURE RSMONITOR
DATA_PACKAGE STRUCTURE /BIC/CS80BWTC_C02
USING
RECORD_ALL
LIKE
SY-TABIX
SOURCE_SYSTEM LIKE
RSUPDSIMULH-LOGSYS
CHANGING ABORT
LIKE
SY-SUBRC.
* fill the internal tables "MONITOR" and/or "MONITOR_RECNO",
* to make monitor entries
perform READ_USR02_TO_MEMORY_FOR_0BWTC_C02
TABLES
MONITOR
DATA_PACKAGE
USING
RECORD_ALL
SOURCE_SYSTEM
CHANGING ABORT.
* if abort is not equal zero, the update process will be canceled
* ABORT = 0.
*$*$ end of routine - insert your code only before this line *-*
* Refresh the internal table.
refresh: GT_USR02.
* Read USR02 user data to memory for this data package
select * into corresponding fields of table GT_USR02
from USR02
FOR ALL ENTRIES IN DATA_PACKAGE
where BNAME = DATA_PACKAGE-TCTUSERNM
order by primary key.
* if abort is not equal zero, the update process will be canceled
ABORT = 0.
ENDFORM.
"READ_USR02_TO_MEMORY_FOR_0BWTC_C02
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Tip 12: Program Includes (cont.)
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Illustration – Include perform statements
Update routine
Program include
FORM compute_key_field
TABLES
MONITOR STRUCTURE RSMONITOR "user defined monitoring
USING
COMM_STRUCTURE LIKE /BIC/CS0BWTC_C02
RECORD_NO LIKE SY-TABIX
RECORD_ALL LIKE SY-TABIX
SOURCE_SYSTEM LIKE RSUPDSIMULH-LOGSYS
CHANGING RESULT LIKE /BI0/V0BWTC_C02T-USERGROUP
RETURNCODE LIKE SY-SUBRC
ABORT LIKE SY-SUBRC. "set ABORT <> 0 to cancel update
*
*$*$ begin of routine - insert your code only below this line*-*
* fill the internal table "MONITOR", to make monitor entries
PERFORM READ_GT_USR02
USING
COMM_STRUCTURE-TCTUSERNM
RECORD_NO
RECORD_ALL
SOURCE_SYSTEM
CHANGING GS_USR02
ABORT.
*****************************************************************
* RECORD PROCESSING (RUN PER RECORD) ****************************
* TO READ FROM MEMORY (ONE RECORD) ******************************
*****************************************************************
* FORM READ_GT_USR02
*---------------------------------------------------------------*
FORM READ_GT_USR02
USING
TCTUSERNM
LIKE USR02-BNAME
RECORD_NO
LIKE SY-TABIX
RECORD_ALL
LIKE SY-TABIX
SOURCE_SYSTEM LIKE RSUPDSIMULH-LOGSYS
CHANGING GS_USR02
ABORT
LIKE SY-SUBRC. "ABORT<>0 cancels update
STATICS: L_RECORD LIKE SY-TABIX.
IF RECORD_NO <> L_RECORD.
L_RECORD = RECORD_NO.
CLEAR GS_USR02.
*
RESULT = GS_USR02-CLASS.
*if abort is not equal zero, the update process will be canceled
*$*$ end of routine - insert your code only before this line *-*
ENDFORM.
Read user data from internal table GT_USR02
READ TABLE GT_USR02
WITH KEY BNAME = TCTUSERNM
INTO GS_USR02.
ENDIF.
ENDFORM.
"READ_GT_USR02
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Tip 13: Use Start and End Routines
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Start routines can be used to process the data efficiently prior to
starting the single records processing
 The most efficient place to delete records from the data
package prior to spending time on processing them
End routines in SAP NetWeaver 7.x allows for processing of the
data after it has been passed through the transformation
 It is the most efficient place to copy data records (e.g., for
generating year-to-date figures)
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What We’ll Cover …
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Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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Tip 14: Data Modeling: Defining Dimensions
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Use as many dimensions as possible
 Separate common filter characteristics into own dimension
Use line-item dimensions for high cardinality characteristics such
as document numbers
 Do not set the high cardinality flag!
Define related characteristics in the same dimension
 Calculate expected number of dimensional entries
 Try not to exceed 10% of expected fact table entries
 Verify the dimension design after the first dataloads using
program SAP_INFOCUBE_DESIGNS
Add all relevant time characteristics
 If 0CALMONTH is lowest granularity, add 0CALMONTH2,
0CALQUARTER, 0CALQUART1, 0HALFYEAR, and 0CALYEAR
 Provides greatest reporting flexibility without need to reload
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Tip 15: Implement Semantic Partitioning
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What is it?
 An architectural design to enable parallel data loading and
query execution
 Partitioning criteria: Year, Region, or Actual/Plan
Source: SAP
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Tip 15: Implement Semantic Partitioning (cont.)
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Benefits of semantic partitioning:
 Reduction in SAP NetWeaver BWA footprint (when partitioned
by year)
 Parallel data loading (when not partitioned by year)
 Parallel query execution
 Best case when partitioning criterion is set as constant
 Almost as good to create variables to filter on 0INFOPROV
 Archival of a single InfoCube does not impact others
 Easier DB maintenance
Performance benefits are so significant …
semantic partitioning should be deployed
on virtually every data model!
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Tip 15: Implement Semantic Partitioning (cont.)
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Example: Semantic partitioning by year
MultiProvider
History
(Summarized)
ALL years
Write-Optimized (No SIDs)
Ex: Current
Current
Current
Current
Current
Year
Year
Year
Year
Year
Current Year – 3
Current Year - 2
Current Year - 1
Current Year
Current Year + 1
Current Year – 3
Current Year - 2
Current Year - 1
Current Year
Current Year + 1
+ 1 =
=
- 1 =
- 2 =
- 3 =
2010
2009
2008
2007
2006
DataSource
Source: SAP
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What We’ll Cover …
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Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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Tip 16: Switch Off SID Determination for DSOs
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Switch off SID determination for DSOs that are not used in
reporting
 SID determination is required only for report DSOs and take up
40-70% of the activation time
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Tip 17: Activate Parallel Processing
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Parallel processing is
possible for most steps
in SAP NetWeaver BW
 DTP Parallel
Processing

DSO settings
 Transaction code
RSODSO_SETTINGS
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Tip 18: Compress Data
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Compression of InfoCubes helps with two things in the dataflow:
 Makes the tables that are updated smaller and hence faster to
update
 The process variant that drops and recreates the indices during
loading in a process deletes only the indices on the F-fact table
and hence the time to rebuild indices is much faster
Recommendation
 Compress data that is older than 2-8 days depending on your
load schedule
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Tip 19: Implement Number Range Buffering of DIMs and
SIDs
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The number range tables (NRIV) are called for every new distinct
record that is loaded to SAP NetWeaver BW as either master data
or dimension in an InfoCube
 The NRIV table is accessed with a select for update statement,
which can be quite slow
 Buffering should be done as follows:
 Determine the large number ranges (Document numbers,
Dimensions with documents or many distinct values)
 Goto t-code SNRO and set up buffering
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Tip 20: Implement SAP NetWeaver BW Accelerator
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SAP NetWeaver BWA is superior to aggregates when it comes to
improving performance
Aggregates require continuous tuning as the data and query
requirements change over time
SAP NetWeaver BWA requires limited maintenance effort in
comparison
If you can afford it, you should invest in SAP NetWeaver BWA
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Tip 20: Implement SAP NetWeaver BW Accelerator (cont.)
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Disk speed is growing slower than other hardware components
Technology Drivers
1990
2010
CPU
0.05
253.31
MIPS/$
MIPS/$
Memory
0.02
50.15
MB/$
MB/$
216
264
Addressable
Memory
Network
Speed
Disk
Data Transfer
100
100
Mbps
Gbps
5
600
MBPS
MBPS
Architectural Drivers
Improvement
5066x
2502x
248x
1000 x
120x
1990
2010
Disk-based data
storage
In-memory data
stores
Simple
consumption of
apps (fat client
UI, EDI)
Multi-channel
UI, high event
volume, cross
industry value
chains
Generalpurpose,
applicationagnostic
database
Applicationaware and
intelligent data
management
Source: 1990 numbers SAP AG,
2010 numbers, Dr. Berg
Physical hard drive speeds grew by only 120 times
since 1990.47All other hardware components grew faster.
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Tip 20: Implement SAP NetWeaver BW Accelerator (cont.)
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In this example, the
average query
execution took 58.8
seconds; after
SAP NetWeaver
BW Accelerator,
the average query
took 17.9 seconds
(295% faster overall)
Source: SAP
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Tip 20: Implement SAP NetWeaver BW Accelerator (cont.)
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With SAP NetWeaver BW 7.3,
you can have data in SAP
NetWeaver BW Accelerator;
InfoCubes are not required
This saves the loading time to
the BW cube start schema
You should implement SAP
NetWeaver BWA if you want to
consistently improve query
performance and data load performance
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Tip 20: Implement SAP NetWeaver BW Accelerator (cont.)
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SAP NetWeaver BWA is an appliance, but it does require some
maintenance activities to keep it running smoothly
 Monitor SAP NetWeaver BWA utilization to avoid overloading
 The rule of thumb is that you should have data that is less
than 50% of the memory size
 Overloading SAP NetWeaver BWA will cause performance
degradation
 Compress the cubes and rebuild indices on a regular basis
 SAP NetWeaver BWA is not a cheap toy. The licensing is
based on blades used.
 Avoid using more space than needed by dropping and
rebuilding the SAP NetWeaver BWA indices on a regular
basis
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Tip 20: Implement SAP NetWeaver BW Accelerator (cont.)
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Avoid aggregates but consider as a back up for SAP NetWeaver
BW Accelerator
 They come at a cost
 Additional step in data loading
 Longer runtime for master data and hierarchy activations
Before aggregate creation:
• Gather information about end-user
query requirements and drill-down
patterns
• You can suggest aggregates based on
query design
• Execute the query multiple times using
realistic drill-down scenarios
After aggregate creation:
• Allow time for users to execute queries
and collect SAP NetWeaver BW statistics
• You can suggest aggregates based on
SAP NetWeaver BW statistics
• Analyze the use of aggregates
• Modify aggregates for optimization
Check that the query is using the aggregate via
RSRT
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What We’ll Cover …
•
•
•
•
•
•
•
Loading data in SAP NetWeaver BW
Finding performance bottlenecks
Optimizing the database
Optimizing the ABAP code
Optimizing the data models
Optimizing the data updates
Wrap-up
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Resources
•
Joe Darlak of COMERIT, SAP NetWeaver BI and Portals 2010
conference (Orlando, Florida)
 Practical Tips to Improve Data Loading Performance and
Efficiency in SAP NetWeaver by Up to 75%
•
Training
 BW360 BW – Performance and Administration class
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7 Key Points to Take Home
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Use the SAP NetWeaver BW statistics to find data loads that
require optimization – target to optimize top 5-10 every month
Use SE30 to analyze ABAP runtime for DataSources and
transformations
Review and implement the recommended database parameters for
SAP NetWeaver BW
Ensure that all SQL statements used in the data loading process
are using indices and that statistics are calculated for the tables
Make sure that the ABAP coding used in extraction exits and
transformation is optimized
Review and optimize the data models to avoid unnecessary
processing
Use parallel processing during data loading and updates
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Your Turn!
How to contact me:
Jesper Moselund Christensen
[email protected]
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