Download Session Title - Lenoir

Preventing, Diagnosing,
and Resolving the 20
Most Common Dashboard
Performance Problems
Dr. Bjarne Berg
Comerit
© 2012 Wellesley Information Services. All rights reserved.
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
1
Problem #1: Back End — Build on a Solid
Performance Foundation
Modularize the data and create
sub-sets of data for really fast
dashboarding
Generic “metrics” data tables
can be created for
summarized KPI and
scorecard dashboards
The summary, or snapshot data
can be accessed much faster
than underlying data tables with
millions of records
Problem #2: Back End — Dashboard Performance
Architecture
In this example, the company uses snapshots for performance reasons
•

Dashboards for
executive users

Pre-delivered SAP
BusinessObjects
Web Intelligence
reports for casual users

Ad hoc SAP BusinessObjects Web
Intelligence reports for power users
The dashboards are only built on
the low-volume daily snapshot
cube (this is also placed in SAP
NetWeaver BW Accelerator for very
high performance)
3
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
4
Problem #3: Query Read Modes
•
There are three query read modes that determine the
amount of data to be fetched from a database and sent to
the application server
1. Read all data
 All data is read from a database and stored in user
memory space
2. Read data during navigation
 Data is read from a database only on demand during
navigation
3. Read data during navigation and when expanding the hierarchy
 Data is read when requested by users in navigation
Reading data during navigation minimizes the impact on the
application server resources because only data that the user requires
will be retrieved
5
Problem #4: Reduce the Use of Conditions & Exceptions Reporting
•
Conditions and exceptions are usually processed by the
application server
 This generates additional data transfer between database and
application servers
•
If conditions and exceptions have to be used, the amount of data
to be processed should be minimized with filters
 When multiple drilldowns are required, separate the drill-down
steps by using free characteristics rather than rows and
columns
•
BENEFIT: This results in a smaller initial result set, and therefore
faster query processing and data transport as compared to a
query where all characteristics are in rows
This approach separates the drill-down steps. In addition to accelerating query
processing, it provides the user more manageable portions of data.
Performance Settings for SAP BW Query Execution
This decides how many records are read during navigation
Examine the
request status
when reading
the InfoProvider
In SAP NetWeaver
BW 7.x the BI
Analytical engine
can read deltas into
the cache. Does not
invalidate existing
query cache.
Turn off/on parallel
processing
Displays the level of
statistics collected
When will the
query program be
regenerated based
on database
statistics?
7
Problem #5: Filters in BW Queries Used in Dashboards
•
Using filters contributes to reducing the number of database
reads and the size of the result set
 Thereby significantly improving query runtimes
Filters are especially
valuable when associated
with large dimensions,
where there is a large
number of characteristics
such as customers and
document numbers
8
Problem #6: The RSRT Transaction to Examine Slow Queries
P1 of 3
The RSRT transaction is one of the
most beneficial transactions to
examine the query performance and
to conduct “diagnostics” on slow
queries from the SAP NetWeaver
BW system
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Do You Need an Aggregate — Some Hints
P2 of 3
This suggests that an Aggregate
would have been beneficial
10
Get Database Info
P3 of 3
In this example, the Basis
team should be involved to
research why the Oracle
settings are not per SAP’s
recommendation
The RSRT and RSRV codes
are key for debugging and
analyzing slow queries
HINT: Track front-end data transfers and OLAP
performance by using RSTT in SAP NetWeaver BW 7.3
(RSRTRACE in SAP BW 3.5)
11
Problem #7: Debug Queries Using the RSRT Transaction
Using RSRT you can execute the
query and see each breakpoint,
thereby debugging the query and
seeing where the execution is
slow
Try running slow queries in debug mode
with parallel processing deactivated to
see if they run faster
12
Problem #8: The Performance Killers — Restrictive Key Figures
•
When Restrictive Key Figures (RKF) are included in a query,
conditioning is done for each of them during query execution
 This is very time consuming and a high number of RKFs can
seriously hurt query performance
•
My Recommendation: Reduce RKFs in the query to as few as
possible
 Also, define calculated key figures and RKFs on the
InfoProvider level instead of locally within the query. Why?
Benefit: Formulas within an InfoProvider are returned at runtime and held in cache
Drawback: Local formulas and selections are calculated with each navigation step
13
#9: Dashboard Performance Killers — Calculated Key Figures
•
•
Calculated Key Figures (CKF) are computed during
runtime, and many CKFs can slow down the query
performance
How to fix this
 Many of the CKF can be done during data loads and physically stored
in the InfoProvider
 This reduces the number of computations and the query can use
simple table reads instead
 Do not use total rows when not required (this requires additional
processing on the OLAP side)
Recommendation for OLAP universes
• RKF and CKF should be built as part of the
underlying BEx query to use the SAP NetWeaver BW
back-end processing for better performance
• Queries with a larger set of such KFs should use the
“Use Selection of Structure Members” option in the
Query Monitor (RSRT) to leverage the OLAP engine
14
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
15
Functionality vs. Performance — What Wins?
16
Problem #10: Dashboard Performance Hint — The Number
of Rows in the Result Set
Limit the number
of rows in your
result set to
between 100 – 500
In exceptional
cases when you
have leveraged
other performancetuning methods,
you may extend
this to up to 1,000
rows
The Length of each record (# of columns) and
the data type also impacts performance
Returning query result sets with few records of a numeric type or with
keys and indicators provides for the best dashboard performance
17
Divide and Get Performance
Drill-down options
•
•
Link to Details
Dashboard
Split your dashboards into logical units and get new data when drilldowns are executed
This keeps the result set for each query small and also decreases the load time for each
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dashboard
Problem #11: Excel Performance Considerations — What
to Avoid
•
•
The logic you build into your Excel spreadsheet is also compiled
into the Flash file when you export it
Since some “daisy-chain” functions are very time consuming, you
should be careful not to add too many conditions in the data
 Lookup functions and conditioning that should be avoided
include:
 Lookups





Mid strings (MID)
Right and left strings (RIGHT/LEFT)
Horizontal Lookups (HLOOKUP)
Vertical Lookups (VLOOKUP)
Condition



General conditioning (IF)
Count if a condition is true (COUNTIF)
Sum if a condition is true (SUMIF)
Complex logic and nested logic create large SWF files and take a long time to open. Try to
keep as much of the calculations and logic in the query instead of the spreadsheet.
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Problem #13: Dashboard Objects That Can Cause Slow Performance
These are dashboard objects that you need
to carefully consider before employing
20
Problem #12: The BI Analytical Engine and Sorting
•
•
Sorting is done by the BI Analytical Engine
 Like all computer systems, sorting data in a
report with large result sets can be time consuming
Reduce the number of sorts in the “default view”
 This will provide the users with data faster. They can then
choose to sort the data themselves.
User Sorts themselves
Hint: Reducing the text in the query will also speed up the query processing time
21
Sizing Servers Correctly (#14): The Sizing Tool
SAP has
provided a sizing
tool for the BI
environments. It
is based on
Flash and is
actually a
dashboard itself.
Output Area
(Sizing Results)
Download it from
SDN at:
http://tinyurl.com/9yo5ag4
Input Areas
(items and users)
This tool can help you size your BI 4.0 environments
with a few key assumptions and inputs.
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The Sizing Tool – Entering Users
First, you have
to enter the
estimated
active
concurrent
users (ACU) for
the following
user types:
• Information
Consumers
• Business
• Expert
Users
Users
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The Sizing Tool –On-Line Help User Definitions
The tool provides on-line
definitions of the user types
and guidelines on how to
determine Active Concurrent
Users (ACU). This is defined as
approximate 10% of the active
users.
Many dashboard users is large
organizations may be classified
as Information Consumers .
They may not wait 5 minutes
between clicks, but typically do
little drill-down and filtering.
24
The Sizing Tool – Assumptions
• The
next step is to make an assumption on the size of dashboards.
• The sizing tool classifies small dashboards as having 25 rows in the
result set, medium having 250, and large dashboards having 2,500 rows.
Assumptions: the tool was based on supporting two queries per
dashboards, and benchmarked was for accessing two relational data
sources. One with 6 dimensions with 77,000 entries and 400,000 line
items, and one with 6 dimensions with 7,000 rows and 40,000 line items.
25
The Sizing Tool – Output
The output of the tool is measured in SAP Application Performance Standard (SAPS).
100 SAPS is defined as 2,000 fully business processed order line items per hour.
It is a measure that hardware vendors can use to decide which of their configurations
can meet your performance requirements. All hardware vendors are familiar with this
measure and this is what you will provide them when requesting a hardware quote. 26
The Sizing Tool – Memory Requirements
The sizing tool also provide a sizing estimate for the
hardware memory required for each of the tiers.
This is measured in Gigabytes
27
The Sizing Tool – Terminology
If you get stuck on the
terminology used in SAP
sizing and performance
benchmarking, there is a
link to the SAP benchmark
glossary in the tool.
There are also performance benchmark and installation guides
available on SAP Marketplace for individual software components.
28
The Sizing Tool – Saving your Sizing example
Your BI and dashboard sizing effort can be saved or printed
from the tool and you can have many scenarios
29
The Sizing Tool – Demo
DEMO
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The Sizing Tool – Companion Guide
•
With the BI sizing tool, there is also
a sizing companion guide written
by Jason DeMelo.
•
This document explains how each
tool was benchmarked and the
assumptions made when building
the sizing tool.
•
You can download it from:
•
https://service.sap.com/~sapdownload/011000358700000307202011E/S
BO_BI_4_0_Companion_V4.pdf (requires log-on)
Involve your basis team in the sizing effort and also make sure that
the assumptions you made are realistic from a functional standpoint
(i.e. how complex and intensive are your dashboards really).
31
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
32
Problem #15: It Is All About Performance, Performance,
Performance
•
It is hard to build a fast dashboard with many
queries and panels without SAP NetWeaver
BW Accelerator or SAP HANA
 This provides in-memory processing of queries
that is 10 to 1000 times faster
What we simply do is place the data in-memory and access it faster
 For BWA, there is also some limited OLAP functionality that can
be built into SAP NetWeaver BW Accelerator 7.3, but most data
processing still occurs in the BI Analytical engine (unlike HANA
which does it all in-memory)
You can also place non-SAP data in-memory for HANA and BWA using
SAP BusinessObjects Data Services
33
Looking Inside SAP HANA — In-Memory Computing Engine
(IMCE)
AAAA
Metadata
Authorization
Transaction
Manager
Manager
Manager
Relational
Engine
SQL Script
SQL Parser
-Row Store
-Column Store
Calculation
Disk Storage
Data
Volumes
Log
Session
Manager
MDX
Engine
Volumes
Load
Controller
BusinessObjects Data Services
Replication Server
Inside the Computing Engine of SAP HANA we have many different components
that manage the access and storage of the data. This include MDX and SQL
access, as well as Load Controller (LC) and the Replication Server.
SAP HANA — Vendors and Appliance Options
•
The vendors that provide SAP HANA solutions include Cisco, Dell, IBM,
Intel, HP, and Fujitsu as of Sept. 2012
•
SAP HANA generally consists of:






The database and database clients
HANA studio (P2 repository)
Load controller and Sybase replication server
The host agent and LM structure files
Op. Sys. configuration, SAPCAR & SAP JVM
The update manager for SAP HANA
Fujitsu
IBM System x3950 X5
*per node (can link several servers together)
HP DL 580 G7
Dell R910
Cisco UCS C460 M2
Reporting and BI Tools on HANA
A great benefit is the real-time loading of SAP HANA from
ERP. This can provide real-time analytics to end-users.
HANA Appliance
ERP
SQL (JDBC / ODBC)
BICS
Real-time
Database
In
DBSQL
Sybase
Replication
Server
Memory
Others
Computing
Engine
SQL (JDBC / ODBC)
BusinessObjects Data Services
SAP BW
SAP BusinessObjects 4.0
MDX (ODBO)
3rd Party
Currently, HANA supports Excel 2010 standard MDX
Number of Queries
SAP NetWeaver BW Accelerator Performance Increases — Real Example
Number of Queries
Seconds
The major
improvement is to
make query
executions more
predictable and
faster overall
Seconds
37
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
38
Problem #16: Different Uses of the MDX and OLAP Cache
•
The OLAP Cache is used by SAP NetWeaver BW as the core
in-memory data set
 It retrieves the data from the server if the data set is available
•
The Cache is based on First in  Last out
 This means that the query result set that was accessed by one
user at 8:00 am may no longer be available in-memory when
another user is accessing it at 1:00 pm
 Therefore, queries may appear to run slower sometimes
The MDX cache is used by MDX-based
interfaces, including the OLAP universe
39
Use the BEx Broadcaster to Pre-Fill the Cache
Distribution Types
•
•
You can increase query speed by
broadcasting the query result of commonly
used queries to the cache
Users do not need to execute the query from
the database
 Instead the result is already in the system
memory (much faster)
40
The Memory Cache Size
•
•
•
The OLAP Cache is, by default, 100MB for local and 200MB for
global use
 This may be too low ...
Look at available
hardware and work
with you Basis team
to see if you can
increase this
If you decide to
increase the cache,
use the transaction code RSCUSTV14
The OLAP Cache is not used when a query contains a Virtual Key
Figure or virtual characteristics, or when the query is accessing
a transactional DSO or a virtual InfoProvider
Monitor Application Servers and Adjust Cache Size
To monitor the usage of the cache on each of the application servers,
use transaction code RSRCACHE and also periodically review the
analysis of load distribution using ST03N – Expert Mode
P.S.! The size of the OLAP Cache is physically limited by the
amount of memory set in system parameter rsdb/esm/buffersize_kb
The settings are available in RSPFPAR and RZ11
42
Problem #17: Correct Aggregates Are Easy to Build
We can create proposals from
the query, last navigation by
users, or by BW statistics
Create aggregate proposals based on queries
that are performing poorly
•
Create aggregate proposals based
on BW statistics. For example:
 Select the runtime of queries to
be analyzed
 Select the time period to be
analyzed
 Only those queries executed in
this time period will be
reviewed to create the proposal
43
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
44
Problem #18: Performance Testing — Load and Stress
Load testing is done to 20% of the named users
 Turn
off the cache (we assume all hits “new data”)
 Execute the dashboard URLs using a tool or simple JavaScript
 Monitor database, portal, and BI system load
 Log response time and have multiple browsers and PCs hitting the data from
multiple locations (network testing)
Stress testing is done at 40% of named user base
 The
test is done the same way as on the load testing, just with more “users”
 The system may not be able to pass at this level, but the break-points are identified
All dashboard systems should be load tested
to 20% of user base prior to Go-Live
45
Problem #19: Server Locations and Network Capacity
•
Having a central global install of SAP BusinessObjects BI 4.x with
many users can cause significant network load and performance
issues
Consider the network topology, capacity, and the user
locations before implementing global dashboards
46
EarlyWatch Reports (#20) in SAP Solution Manager
•
•
•
EarlyWatch reports provide a simple way to confirm how your
system is running and to catch problems
 A “goldmine” for system recommendations
EarlyWatch Reports have been available since SAP Solution
Manager version 3.2 SP8
The more statistics cubes you have activated in SAP NetWeaver
BW, the better usage information you will get
 Depending on your version of SAP NetWeaver BW, you can
activate 11-13 InfoCubes
 Also, make sure you capture statistics at the query level (set
it to “all”)
System issues can be hard to pin-down without access to
EarlyWatch Reports. Monitoring reports allow you to tune the
system before a user complains.
47
Information About a Pending “Disaster”
This system is
about to crash
The system is
growing by 400+ GB
per month, the app
server is 100%
utilized, and the DB
server is at 92%
This customer
needed to improve
the hardware to get
the query
performance to an
acceptable level
48
The Dashboard Performance Checklist
1. The hardware servers — Check sizing
2. The server locations and networks — Check loads
3. Query review — Look at database & calculation time, & design
4. Interface review — Make sure you are using the best for the data source
5. Dashboard review — Look at Excel logic, container usage, number of Flash
6.
7.
8.
9.
objects, sorts, size of result set, and simplification opportunities
In-memory review — Look at cache usage, hit rations, and SAP NetWeaver BW
Accelerator usage
Review data sources — Examine if snapshots can be leveraged and look for
possibilities to create aggregates
Examine compatibilities between browsers, Flash, and Microsoft office versions
Review PC performance issues — Memory, disk, and processors
Performance is complex, look at more than one area
(e.g., Web portal bottlenecks and LDAP servers)
49
What We’ll Cover …
•
•
•
•
•
•
•
Backend Database Data Design
Exploring query performance
Dashboard design and Hardware Sizing
Increasing query performance with infrastructure and in-memory
processing
Leveraging pre-caching capabilities and aggregates
EarlyWatch Reports, Performance Testing and Server location
Wrap-up
50
Resources
•
Tuning SAP BusinessObjects Solutions for Optimal
Performance: Tips from the Trenches by Chris Dinkel

•
SAP Business Objects Tuning by Steve Bickerton

•
The SAP BusinessObjects seminar (SAPinsider, 2011)
wp.broadstreetdata.com/wp-content/uploads/BOCXSpeaker-Performance-Tuning_-Steve-Bickerton.pdf
SDN Sizing Tool

http://tinyurl.com/9yo5ag4
51
7 Key Points to Take Home
•
•
•
•
•
•
•
Dashboards are all about performance, performance, and
performance
You have to spend time on the back end performance tuning
Avoid direct querying of high data volumes, create summaries
instead
Consider in-memory processing for all critical dashboards
Your interface to the data will impact the performance —
Avoid MDX
Size your hardware one size “too big” — It is hard to make a
second first impression
Use a gradual rollout of your dashboards, monitor the
performance, and conduct load and stress tests before any
major go-lives
52
Your Turn!
How to contact me:
Dr. Bjarne Berg
[email protected]
53
Disclaimer
SAP, R/3, mySAP, mySAP.com, SAP NetWeaver®, Duet®, PartnerEdge, and other SAP products and services mentioned herein as well as their
respective logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries all over the world. All other product
and service names mentioned are the trademarks of their respective companies. Wellesley Information Services is neither owned nor controlled by
SAP.
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