preventing, diagnosing, and resolving the 20 most common dashboard performance problems

© 2012 Wellesley Information Services. All rights reserved.

Preventing, Diagnosing,

and Resolving the 20 Most Common Dashboard Performance ProblemsDr. Bjarne BergComerit

Deployment,Testing & Change

Management

Best-in-Class Dashboards

Performance & Security

Options & Prototyping

• Scoping vs. requirements gathering • KPI definitions• Required skills and resources• Data connectivity deep dive• Key criteria to retrieve data sets

• Dashboards vs. reports• Answers to dashboard FAQs• SAP BusinessObjects Dashboards

4.0 overview• Product updates and

implementation criteria• Recent changes to dashboard

terms

• Key dashboard roll-out decisions• Mobilizing your dashboard• Support organization• Volume, stress, and UAT• Training and change management

Day 1

Day

3

Seminar Roadmap

Landscape, Connectivity &

Sizing• Hands-on lab: Build a dashboard

with BOBJ Dashboards 4.0• Sizing and scaling recommendations• User management and access

control• SAP NetWeaver® BW

Accelerator and SAP HANA

• Hands-on lab: Advanced techniques• Web service integration and Adobe

Flex Builder• Panel discussion: Dashboard Projects

•Ownership and branding•Post-production changes

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678

9

12 2

Customization, Branding & Governance

Day 2

• Common causes of poor dashboard performance

• Effective performance testing• Performance-enhancing design

techniques• Preventing unauthorized access

to dashboards• Password protection

and SSO

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13

11

5

3

We are here10

1

3

Background

• We already covered hardware sizing, compatibility, and server options in an earlier session; so now we will look at the application, design, and interfaces

• We will specifically look at dashboard design, query design, connectivity impacts, in-memory processing options, as well as dashboard performance monitoring options

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Functionality vs. Performance: What Wins?

5

What We’ll Cover …

• Choosing the right connectivity and back end • Exploring query performance• Thinking about the dashboard design• Increasing query performance with infrastructure and in-memory

processing• Leveraging pre-caching capabilities and aggregates• Obtaining strategies for performance testing: Load and stress• Looking at EarlyWatch Reports and the performance checklist• Wrap-up

Problems #1 and #2: Connectivity and Performance

• As we covered in the earlier session, the type of connectivity matters for the performance

Always pick the fastest interface available for the data source you are building dashboard onSource: SAP AG, 2012

• BICS connectors perform well

• Avoid the MDX interface(it is slow)

• Avoid direct access to theInfoProviderssince thisbypassesthe BI analyticalengine in SAP NetWeaver® BW

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Problem #3: Data Connectivity — SAP Crystal Reports and SAP BusinessObjects Live Office

• You can use transient providers to create real-time dashboards on top of SAP ERP data

• You can also use SAP Crystal Reports for detailed drill-down analysis

• If you always use the “refresh on load” option for Live Office connections, your users will experience periodic slow performance

By leveraging the aggregation in SAP Crystal Reports, you can also get faster SAP Dashboards (formerly Xcelsius®) response time 7

Problem #4: 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

Real example

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Problem #5: 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)

Real example

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Problem #6: 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 server1. 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

navigation3. 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

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Problem #7: Recommendation — Query Read Mode for Large Hierarchies• For queries involving large hierarchies, it is smart to select “Read

data during navigation” and when expanding this option to avoid reading data for the hierarchy nodes that are not expanded

• Reserve the Read all data mode for special queries I.e., when a majority of the users need a given query to slice and

dice against all dimensions, or data mining This places heavy demand on database and memory resources,

and may impact other SAP NetWeaver BW processes A query read mode can be defined on an individual query or as

a default for new queries (transaction RSRT)

Recommendations for OLAP universes and SAP BusinessObjects Web Intelligence analysis

Use of hierarchy variable is recommended Hierarchy support in SAP BusinessObjects Web Intelligence for SAP NetWeaver BW

is limited The Use Query Drill option significantly improves drill-down performance Look at the Query Stripping option for power users

Problem #8: Reduce the Use of Conditions and 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.

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Performance Settings for 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.

Displays the level of statistics collected

Turn off/on parallel processing

When will the query program be regenerated based on database statistics?

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Problem #9: Filters in 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 dimensionswhere there are a large number of characteristics, such as customers and document numbers

Problem #10: The RSRT Transaction to Examine Slow Queries

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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

Do You Need an Aggregate: Some Hints

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This suggests that an Aggregate would have been beneficial

P2 of 3

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Get Database Info

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

P3 of 3

HINT: Track front-end data transfers and OLAP performance by using RSTT in SAP NetWeaver BW 7.3 (RSRTRACE in SAP BW 3.5)

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Problem #11: 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

• After SAP BusinessObjects Enterprise XI 3.1 FP 1.1, the impact of large numbers of key figures was somewhat reduced by retrieving metadata information only when the unit/currency metadata info is selected

• However, this is still best practice

Recommendation for Key Figures in OLAP Universes

• A large number of key figures (KFs) in the BEx query will incur a significant performance penalty when running queries, regardless of whether the key figures are included in the universe

• Only include key figures used for the dashboard in the BEx query (keep it small)

• This performance impact is due to time spent loading metadata for units, executed for all measures in the query

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Problem #12: 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

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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 CKFs 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

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Problem #13: Dashboard Performance Hint — The Number of Rows in the Result Set

Limit the numberof rows in your result set to between 100-500

Returning query result sets with few records of a numeric type or with keys and indicators provides for the best dashboard performance

The Length of each record (# of columns) and the data type also impacts performance

In exceptional cases, when you have leveraged other performance-tuning methods, you may extend this to up to 1,000 rows

Divide and Get PerformanceDrill-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

dashboard 25

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Problem #14: 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 calculation and logic in the query instead of the spreadsheet.

Hint: Reducing the text in the query will also speed up the query processing time

User Sorts themselves

Problem #15: 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.

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These are dashboard objects that you need to carefully consider before employing

Problem #16: Dashboard Objects That Can Cause Slow Performance

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• It is hard to build a fast dashboard with many queries and panels without SAP NetWeaver BW Accelerator This provides in-memory processing of queries

that is 10-100 faster

Problem #17: It Is All About Performance, Performance, Performance

• What we simply do is place the data in-memory and retrieve itmuch faster 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

You can also place non-SAP data in-memory using SAP BusinessObjects Data Services 30

The major improvement is to make query executions more predictable and faster overall

Seconds

Num

ber o

f Que

ries

Num

ber o

f Que

ries

Seconds

SAP NetWeaver BW Accelerator Performance Increases: Real Example

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BI Analytical Engine’s Query Executing Priorities

Query ExecutionWithout SAP NetWeaver

BW Accelerator

Query Executionwith SAP NetWeaver

BW Accelerator

Information Broadcasting/Pre-Calculation

Query Cache

Aggregates

InfoProvider

Information Broadcasting/Pre-Calculation

Query Cache

SAP NetWeaver BW Accelerator

Aggregates can be replaced with SAP NetWeaver BW Accelerator while the memory cache is still useful

Source: SAP AG

Persistence Layer

Looking Inside SAP HANA: In-Memory Computing Engine (IMCE)

Disk Storage

Data

VolumesPage Mgmt.

BusinessObjects Data Services

Log

Volumes

Logger

Metadata

Manager

Authorization

Manager

Transaction

Manager

Relational Engine

-Row Store -Column Store

Load

Controller

SQL Script

Calculation

Engine

Replication Server

SQL Parser

MDX

Session Manager

You can also move data to SAP HANA and access the data in-memory; this creates a much faster response time for all your dashboards

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SAP HANA: Sources and Target Interfaces

ERP

Database

HANA Appliance

In-Memory

Computing

Engine

Sybase

Replication

Server

SAP BW Third Party

Semantic Layer

SAP BusinessObjects 4.0Dashboards

Crystal

Web Intelligence

Analysis – Office

Crystal

Explorer

Sybase UnwiredOthers

Third-Party Applications

Custom Web Development

Third-Party Applications

Microsoft Excel (certified)

SQL (JDBC/ODBC)

DBSQL

BICS

SQL (JDBC/ODBC)

MDX (ODBO)SAP BusinessObjects Data Services

Real-time

A great benefit is the real-time loading of SAP HANA from ERP; this can provide real-time analytics to end users

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Problem #18: 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

Use the BEx Broadcaster to Pre-Fill the Cache

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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)

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 your 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 InfoProvider38

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

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P.S.! The size of the OLAP Cache is physically limited by the amount of memory set in system parameter rsdb/esm/buffersize_kbThe settings are available in RSPFPAR and RZ11

The Four Options for OLAP Cache Persistence Settings

CACHE OLAP Persistence SettingsNote When What T-code

Default Flat file

Change the logical file BW_OLAP_CACHE when installing the system (not valid name) FILE

Optional Cluster table Medium and small result setsRSR_CACHE_DBS_IX RSR_CACHE_DB_IX

OptionalBinary Large Objects (blob) Best for large result sets

RSR_CACHE_DBS_BLRSR_CACHE_DB_BL

Available since SAP NetWeaver BW 7.0 SP 14

Blob/Cluster Enhanced

No central cache directory or lock concept (enqueue). The mode is not available by default.

Set RSR_CACHE_ACTIVATE_NEW RSADMIN VALUE=x

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Problem #19: 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 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

Create aggregate proposals based on queries that are performing poorly

Activate the Aggregate

The process of turning 'on' the aggregates is simple

1. Click on Jobs to see how the program is progressing

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Fill the Aggregate with Summary Data

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Problem #20: Performance Testing — Load and Stress

• Load testing is done to 20% of the named user base Turn off the cache (we assume all hits “new data”) Execute the dashboard URLs using a tool or a 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 to 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 testedto 20% of user base prior to Go-Live

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Bonus Problem #1: 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

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Bonus Problem #2: EarlyWatch Reports 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 allows you to tune the system before a user complains.

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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

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Bonus Problem #3: The Dashboard Performance Checklist

1. The hardware servers — Check sizing2. The server locations and networks — Check loads3. Query review — Look at database and calculation time

and design4. Interface review — Make sure you are using the best for the data source5. Dashboard review — Look at Excel logic, container usage, number of

Flash objects, sorts, size of result set, and simplification opportunities6. In-memory review — Look at cache usage, hit rations, and SAP

NetWeaver BW Accelerator usage7. Review data sources — Examine if snapshots can be leveraged, and

look for possibilities to create aggregates8. Examine compatibilities between browsers, Flash, and Microsoft office

versions9. 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)

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Where to Find More Information

• Chris Dinkel, “Tuning SAP BusinessObjects Solutions for Optimal Performance: Tips from the Trenches” (The SAP BusinessObjects Seminar, 2011).

• Steve Bickerton, “SAP BusinessObjects Tuning” (SAP AG, April 2011). www.scribd.com/doc/89894543/BOCX-Speaker-Performance-

Tuning-Steve-Bickerton• SAP Service Marketplace for sizing guidelines

https://websmp104.sap-ag.de/sizing and follow the Sizing Guidelines menu path SBO_BI_4_0_Dashboard_designer.pdf

Need to be a customer to access this Requires login credentials to the SAP Service Marketplace

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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

Your Turn!

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How to contact me:Dr. Bjarne Berg

[email protected]

DisclaimerSAP, 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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preventing, diagnosing, and resolving the 20 most common dashboard performance problems

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