DB2 11 and z13 for Hybrid Transactional and Analytical SAP applications

DB2 11 and z13 for Hybrid Transactional
and Analytical SAP applications
Johannes Schuetzner [email protected]
Senior Technical Staff Member, IBM Systems
SAP on DB2 for z/OS Development
Chicago, May 19, 2015
Agenda
• Evolving SAP Workloads and SAP Core Data Services
• DB2 11 Optimizations for SAP Core Data Services
• SAP Rapid Replenishment Planning
• z13 SMT for SAP Analytical Workloads
• SAP Zero Downtime Option
© 2015 IBM Corporation
2
Market Trends Foster Growing SAP Workloads
Mobile access
Anywhere, Anytime
SAP
Application
Database
Single global
instance
Need to scale and to avoid downtime
© 2015 IBM Corporation
3
A Paradigm Change in SAP Application Programming
Data-To-Code:
Intensive
computations in
Application
Programming
Models
<code>
APPLICATION
layer
Code-ToData:
Database
Intensive
computations
in DATABASE
layer
From Traditional Approach
To Data Centric Approach
• Avoid costly computation on
• Get the algorithm to the data
• Only transfer computation results to
database level
• Transfer data to application server
the application server
and compute there
© 2015 IBM Corporation
4
SAP Core Data Services
Motivation
What application developer intends to express:
SELECT id, name,
deliveryAddress.zipCode
FROM Employee WHERE ...
Capturing intent requires:
Ÿ declarative languages (vs. imperative ones)
Ÿ domain-specific languages
Ÿ sufficiently rich level of semantics
© 2015 IBM Corporation
5
SAP Core Data Services
Motivation
What application developer has to write in plain SQL:
SELECT c.id, c.name, a.zipCode FROM Customer c
LEFT OUTER JOIN Customer2Address c2a ON c2a.customer = c.id
LEFT OUTER JOIN Address a ON c2a.address = a.id
AND a.type = ’deliveryAddr’
WHERE ...
… because of :
lacking support for relationships as first-class citizen
© 2015 IBM Corporation
6
SAP Core Data Services
Motivation
What we frequently see as actual code:
customers = SELECT * FROM Customer
foreach c in customers do
Motivation for SAP Core Data Services
Pulldatamodelingaswellasretrievalandprocessing
ofdatatoahighersemanticlevel:
Close totheconceptualthinking ofdomain experts
write c.id
write c.name
addresses = SELECT * FROM Address a, Customer2Address c2a
WHERE a.id = c2a.address AND c2a.customer = :c.id
foreach a in addresses do
if a.type = ‘deliveryAddr’ then
write a.zipCode
end
end
… with detrimental effects on performance due to imperative programming!
© 2015 IBM Corporation
7
SAP Core Data Services
Overview about Architecture & Setup
Eclipse
• ABAP in Eclipse with SAP plug-in
•
Connected to an SAP system
•
Changes end up in SAP Data Dictionary
HANA Studio
ABAP in Eclipse
CDS Editor
(text &
graphical)
• CDS DDL sources from ABAP
CDS Editor
(text &
graphical)
containing CDS views are translated to
DB2 views
•
Created like any other DDIC object
•
Additional features like SAP-supplied
scalar UDFs are created in DB2 during
CDS initialization
ABAP
DDL
RDL
Backend
DDL
Query
Lang
Query Lang
CDS-DDL Backend
CDS-DDL Backend
HANA
DB2 and others
© 2015 IBM Corporation
8
SAP Core Data Services
Key Principles
• CDS is…
– Domain-specific
à DSLs, close to conceptual thinking, ER Modeling
– Intentional
à declarative, functional approach
– Extensible
à both on a model- (thru extensions) and meta
model level (thru annotations)
– Reflexive
à as SQL, extended to annotations
• …, while it is not(!):
– Rocket science
à SQL, ER Modeling, … as others
– Abstraction
à it enhances SQL, not on top of SQL
– Does not change SQL INSERT / UPDATE / DELETE on tables
© 2015 IBM Corporation
9
SAP Core Data Services
Data Definition Language
CDS DDL = SQL DDL + …
•
Entities with structured and custom-defined types
Associations i.e. captured relationships
• Annotations to extend the meta models
•
•
Calculated Fields pre-defined in data models
Custom-defined Type
Entity
Association
Calculated Field
Structured Field
type Amount {
value : Decimal;
currency : Association to Currency;
}
entity Address {
streetAddress; zipCode; city; // snipped type defs
kind : enum { home, business };
}
entity Employee {
addresses : Association[0..*] to Address;
homeAddress = addresses[kind=home];
salary : Amount;
}
© 2015 IBM Corporation
10
SAP Core Data Services
Intrinsic View Building
•
Views are projections on other entities
– Follow concept of reflexive view definitions in standard SQL
define view EmployeesInOrg
as
SELECT from Employee {
ID, name,
salary,
orgunit {
name,
Query in CDS QL
manager,
},
homeAddress
}
© 2015 IBM Corporation
11
SAP Core Data Services
Query Language (QL)
SAP database interface maps to DB2 SQL
CDSQL=SQLSELECT+…
•
DB2processesstandardSQLstatementsforCDSDDL +QL
Ÿ Pathexpressionsalong associations
SELECT id, name, deliveryAddress.zipCode FROM Customer WHERE ...
Ÿ XPath-likefilterexpressionsinpaths
SELECT name, addresses[type=deliveryAddr].city AS deliveryAddress,
addresses[type=invoiceAddr].city AS invoiceAddress FROM Customer …
Ÿ Nestedprojection clausesà structuredresultsets
SELECT
id, name,
deliveryAddress { streetAddress, zipCode, city
}
FROM Customer WHERE ...
…thusleveragingtherichsemanticsfromDDL.
© 2015 IBM Corporation
12
CDS View Example 1
DDL source incl.
expression and
annotation
DB2 DDL
© 2015 IBM Corporation
13
CDS View Example 2
CREATE VIEW "ZZJCMTSTCDSV2“
AS SELECT
"SFLIGHT"."MANDT" AS "MANDT",
"SFLIGHT"."CARRID",
"SFLIGHT"."CONNID",
"SFLIGHT"."PAYMENTSUM" AS "ORIGINALSUM",
"SFLIGHT"."CURRENCY" AS "ORIGINALCURRENCY",
CAST( ROUND( CAST( CURRENCY_CONVERSION( "SFLIGHT",
"SFLIGHT"."CURRENCY",
CAST( G'USD' AS VARGRAPHIC ( 000005) ),
CAST( G'20010101' AS VARGRAPHIC ( 000008) ),
G'M',
CAST( G'000' AS VARGRAPHIC ( 000003) ),
G'X',
G'X',
G'X',
G'X',
G' ',
DDL source with CURRENCY
CONVERSION
G'FAIL_ON_ERROR' )
AS DECIMAL ( 000017, 000002) ),
CAST( 000002 AS BIGINT ) )
AS DECIMAL ( 000026, 000005) ) AS "CONVERTEDSUM",
G'USD' AS "TARGETCURRENCY“
FROM
"SFLIGHT" "SFLIGHT"
WHERE
DB2 DDL
"SFLIGHT"."CURRENCY" = G'EUR'
© 2015 IBM Corporation
14
CDS View Example 3
CREATE FUNCTION
"ZZJCMTSTCDSV3"
( "IV_CONNID" VARGRAPHIC (000004) )
RETURNS TABLE
(
"MANDT" VARGRAPHIC (000003),
"CARRID" VARGRAPHIC (000003),
"CONNID" VARGRAPHIC (000004),
DDL source for view with parameter
DB2 DDL
"FLDATE" VARGRAPHIC (000008)
)
LANGUAGE SQL
SPECIFIC "ZZJCMTSTCDSV3"
READS SQL DATA NO EXTERNAL ACTION NOT
DETERMINISTIC
PARAMETER CCSID UNICODE
ABAP SQL
Query
RETURN
SELECT
"SFLIGHT"."MANDT" AS "MANDT",
"SFLIGHT"."CARRID",
"SFLIGHT"."CONNID",
"SFLIGHT"."FLDATE"
FROM
"SFLIGHT" "SFLIGHT" WHERE
"SFLIGHT"."CONNID" = "ZZJCMTSTCDSV3"."IV_CONNID"
© 2015 IBM Corporation
15
CDS - Strategic SAP data modelling
• Available across SAP database platforms
• Defines business objects as database views that contain SQL queries
•
CDS not applicable to cluster- or pool-tables (i.e. RFBLG, ATAB)
• Eclipse as development tool for CDS (not SE80)
• Application code easier to read with better performance
• CDS heavily utilizes database views
•
Hierarchical stack of views – up to 10 levels of views or more
– Views can use scalar and table functions of database
•
Application logic running within the database via scalar UDFs
– With DB2: SQLPL UDFs with static SQL
– UDFs contain no SQL or very simple SQL lookup queries
– CREATE FUNCTION automatically performs bind in DB2
• SQL statements get more complex - analytical queries
• Less traffic between database server and application server
© 2015 IBM Corporation
16
DB2 for z/OS – Optimized for SAP:
History of tight collaboration
DB211
DB210
-Full 64-bit runtime support
-Reducing internal latch
-contention
-Workfile spanned records, PBG support, and inmemory enhancements
-Auto-stats
DB29
DB2V8
-Optimistic locking
-Modify early code without requiring an IPL
-APPEND option for inserts
-- VS Constraints / - Unicode
-- Automate BackupRecovery
-- 64bit DB2 Connect for zLinux
-- Multiple DISTINCT Clauses
------
Lock Contention on SAP Cluster Tables
Fast Retrieval of Most Recent Value
Create Deferred Index Enhancement
Provide DSTATS Functionality
Convert Column Type
-----
Altering CLUSTER Option
Adding Columns to Index
Index-only Access Path for VARCHAR
Changing Number of Partitions
-- Partitioning Nonclustering Keys
------
Control Center Enhancement
DRDA Performance
Longer Table Names
Transparent ROWID
features
Array Fetch, Insert
-…
50+
explicitly
requested by
SAP
-Relief for sequential key insert
-LOB performance and scalability
-Utilities CPU reduction
-Faster restart of data sharing
-CLONE Table: fast replacement of one table with
another
-Renaming column, index, and schema
-Table space that can add partitions, as needed for
growth
-Improve ability to create an index online and rebuild
it
-Online reorganization with no BUILD2 phase
-Parallel unload and reload during REORG
-Automatic objects creation
-64-bit exploitation by DDF
-Autonomic re-optimization
-Index compression
-Database ROLEs
-Trusted security context
-Cross query block optimization
…..
40+ features
for SAP
-Default SAP settings for DB2
-Access path stability and hints enhancements
-Hash access path
-Parallel index update at insert
-Numerous optimizer enhancements
-Enabling MEMBER CLUSTER for UTS
-Query parallelism enhancements: lifting
restrictions
-More granular DBA privileges
-More online schema changes for table spaces,
tables and indexes
via online REORG
-Automatically delete CF structures before/during
first DB2 restart
-Allow non-NULL default values for inline LOBs
-Loading and unloading tables with LOBs
-Full Decimal Floating Point support
-‘Last committed’ locking semantics
-Easier SQL paging through result sets
-Online REORG for LOB
features
-Online add log
…..
for SAP
40+
-Out-of-the-box CPU savings
-Index-ability for mismatched data type/length
-Transform OR predicates to IN-list also for "IS
NULL"
-Reduction of overflow records
-Index skipping
-Index look-aside for DPSIs
-LIKE predicate enhancements for
CHAR/GRAPHIC
-Suppress NULL index entries
-Real-time stats on demand
-Enhance DSNACCOX
-Inline stats support all Runstats options
-REORG without reclustering (SORTDATA NO
SHRLEVEL CHANGE)
-New buffer pool statistics
-Default profile for RUNSTATS USE PROFILE
-Stored procedure ADMIN_COMMAND_MVS
-IFCID 225: IRLM virtual storage monitoring
-Enhanced workfile monitoring
-Enhanced client info fields
-DROP COLUMN
-REORG gets drain on whole partititioned
tablespace
-Streamlined REORG switch phase
-REORG can remove data sets of empty PBG
partitions
-Automatically cleanup pseudo-deleted index
entries
features
-Online ALTER REBALANCE
for
SAP
-Online ALTER limitkey
-…..
17
© 2015 IBM Corporation
40+
SAP Core Data Services
Exploiting Sophisticated SQL Functionality
SAP NetWeaver 7.40 SP5
Aggregate functions:
•
•
MIN, MAX, AVG, SUM, COUNT
•
GROUP BY & HAVING
•
Literals in SELECT list & ON-condition
•
ON-condition with !=, <, >, ...
•
New capabilities via "built-in" annotations
•
Buffering
•
End-user texts for elements
•
"Key"-elements in views
•
Reference fields for Amounts / Quantities
•
"Simple" CASE (in SELECT list)
•
Arithmetic Operators: -, + and *
•
Number Functions: CEIL(), MOD()
•
Type Conversion: CAST() to DDIC types
•
String Functions: SUBSTRING(), LPAD()
SAP NetWeaver 7.40 SP8
• Views with parameters
• Conversion Functions (Currency, Unit)
• Arithmetic Support: "Open Division"
• For INT-, DEC- and FLTP-types
• Support of additional Functions
• Number Functions: ROUND, FLOOR,
CEIL, ABS
• String Functions: REPLACE,
CONCAT, COALESCE, LIKE
• Searched CASE
Fullysupported by
DB210&11
© 2015 IBM Corporation
18
DB2 11 Optimizations for SAP Core Data Services
•
CDS allows application developers to perform arithmetics in SELECT
statements
• DECFLOAT type becomes more relevant – casting for better precision
• DB2 11 optimizes DECFLOAT processing by
– Exploiting DECFLOAT hardware support of z Systems
– Streamlining normalization of DECFLOAT values
•
CDS allows applications to define and consume complex views, UDFs
(user-defined functions) and table UDFs
• DB2 11 introduces support for multiple SET control statements
– SET (X1, X2) = (SELECT C1, C2 FROM T1 WHERE ... )
• DB2 11 introduces global variables
– Named memory variables that can be read and written to from within a DB2 thread
• DB2 10+ APAR PI12047 enables SELECT on table UDF without correlation name
• DB2 10+ APAR PI29116 enables calling UDFs if DECFLOAT rounding mode does
not match
© 2015 IBM Corporation
19
DB2 11 Optimizations for SAP Core Data Services
•
CDS can result in applications submitting more complex queries
• DB2 11 more efficiently exploits indexes
– DB2 internally transforms predicates so that they become indexable, e.g.:
WHERE YEAR(DATE_COL) = 2012 à WHERE DATE_COL BETWEEN ‘2012-01-01’
AND ‘2012-12-31’
WHERE SUBSTR(CITY,1,3) <= ‘ROMA’à WHERE CITY <=
(< DB2_derived_boundary>)
– DB2 internally transforms query for single matching index access, e.g.:
à WHERE C1 IN (?, NULL)
WHERE C1 IN (1, 2) OR C1 IS NULL à WHERE C1 IN (1,2,NULL)
WHERE C1 = ? OR C1 IS NULL
– DB2 can use index access for certain CASE expressions, e.g.:
SELECT * FROM T1
WHERE COL = CASE (CAST(? AS INT))
WHEN (1) THEN 'CA'
WHEN (2) THEN 'NY'
ELSE 'AL' END;
© 2015 IBM Corporation
20
DB2 11 Optimizations for SAP Core Data Services
•
CDS can result in applications submitting more complex queries
• DB2 11 allows pruning of partitions for query processing in joins
• DB2 11 enables more comprehensive push down of predicates to subqueries
• DB2 11 optimizes performance of SQL GROUP BY and DISTINCT clauses
– Better sort avoidance, early out processing
– Index skipping:
Use index lookaside (current leaf high key and non-leaf) to get the next key greater than
current key
© 2015 IBM Corporation
21
SAP Rapid Replenishment Planning
• Example for SAP application exploiting CDS and code pushdown to database
•
Part of SAP Retail industry solution
• Performance optimization of existing SAP ERP Retail Replenishment
•
ERP Retail Replenishment: Transaction WRP1 (ABAP report RWRPLPRO)
•
Rapid Replenishment Planning: New transaction WRP1R (new ABAP report RWRPLRRP)
• Parallel usage with classic replenishment planning possible
• No migration efforts from classic replenishment planning (besides tests and job
definition)
•
Existing master data, transaction data and customizing is used without any changes
• CDS-based replacement of core functionality in existing replenishment process
•
Some simplifications of the planning process (e.g., consideration of MM forecast only)
© 2015 IBM Corporation
22
SAP Rapid Replenishment Planning:
Detailed comparison of sample run
OldSAPERPRetailReplenishment job:
System:
QQ2
Instance: lsemt01_QQ2_00
Record: 10:08:23 - 10:13:05
RWRPLPRO
Analysis of time in work process
NewSAPRapid Replenishment Planning job:
System:
QQ2
Instance: lsemt01_QQ2_00
Record: 09:44:17 - 09:45:44
RWRPLRRP
Analysis of time in work process
Total time in workprocs 282.197 ms
Total time in workprocs 87.233 ms
Wait for work process
Wait for work process
1 ms
Processing time
110.713 ms
Processing time
Load time
13 ms
Load time
1 ms
7.818 ms
12 ms
Generating time
0 ms
Generating time
0 ms
Roll (in+wait) time
1 ms
Roll (in+wait) time
1 ms
Database request time
Enqueue time
Total DB2 CPU time:
171.462 ms
9 ms
28.400 ms
Database request time
Enqueue time
Total DB2 CPU time:
79.398 ms
4 ms
62.400 ms
© 2015 IBM Corporation
23
SAP Rapid Replenishment Planning
• Rapid Replenishment Planning executes different types of batch jobs
• Measurements done on same hardware (CPU / memory)
• CDS-based optimization shipped as part of SP08 for ERP 6.0 EHP 7
•
See SAP Notes 2051280 and 2142546
Usecase
MeasurementsonDB2forz/OS
Runtime
classicjob
Runtime
CDS-based job
Acceleration
1(sequential)
0.17sec
0.15sec
1.1x
2(sequential)
0.39 sec
0.23sec
1.7x
3(sequential)
14.26sec
4.60 sec
3.1x
4(sequential)
300.45sec
85.84 sec
3.5x
5(sequential)
417.22 sec
88.93 sec
4.7x
6(parallel)
571.66 sec
121.63 sec
4.7x
© 2015 IBM Corporation
24
z13 SMT for SAP Analytical Workloads
•
SMT-2 enables second hardware thread per core
• Can overlap each other for more effective pipeline use
• Appears as another logical processor to the operating system
•
Individual threads run slower but dispatcher delays
are reduced
• zIIP with SMT is about 1.4x of zIIP without SMT
Workload running SAP
CDSanalyticalqueries
Configuration
#of
jobs
Elapsed
time
External
throughput rate
(per hour)
%CP
utilization
%zIIP
utilization
Internal
throughput
rate(per hour)
6CPs+2zIIPs
4
1491.7sec
2606.4
79.0%
48.0%
3659.5
6CPs+2zIIPswithSMT
4
1390.0sec
2797.1
77.7%
46.2%
4004.9
6CPs+3zIIPs
4
1388.5 sec
2800.2
77.8%
45.7%
4175.0
More capacity:
9.5% total
38% for zIIPs
© 2015 IBM Corporation
25
SAP Zero Downtime Option (ZDO) to enable
SAP Online Lifecycle Management
CustomerSystem
Shadow/
UpgradeSystem
Normalproduction
n Norestrictions
Upgradeuptime
n Systemused
productively
n Restrictionsapply
Normalproduction
n Norestrictions
Release n + m
Schema
UserSwitch
SmartSwitch
Alias+View
Release n
Release n + m
Bridge
time
BridgePhase
n Online Userswitchto
differentSchema
n Tableseither
n Copied
n Cloned w/replay
n Sharedw/views
n Read-only
Release n
Shadow
Release n
Shadowsystemcreation
n Export/Cloned content
n AdaptRepository Tables
n ShadowImport
n BridgeSetup
SmartSwitch
Upgrade
n Application Import
n Conversions
n AIMsandXPRAs
n Customertransports
Releasen+m Test
Release n+m
© 2015 IBM Corporation
26
DB2 11 Optimizations for SAP Zero Downtime Option
To non-disruptively switch tables accessed by applications, SAP
introduces Smart Switch concept
•
•
•
•
Needs to rename tables under the covers
This needs to work while SQL DML statements access the table and also if views exist
DB2 11 APAR PI32291 enables smart invalidation of views for RENAME TABLE
statements
SAP defines triggers requiring certain semantics
•
•
DB2 11 introduces autonomic stored procedure with own commit scope
•
CREATE PROCEDURE ... AUTONOMOUS
DB2 11 APAR PI36733 enables immediate DROP TRIGGER
•
Support for DROP COLUMN
•
•
ALTER TABLE .... DROP COLUMN as pending DDL
SAPZDObasedon
DB211
© 2015 IBM Corporation
27
Thank you
Johannes Schuetzner
[email protected]
© 2015 IBM Corporation
28
Trademarks
The following are trademarks of the International Business Machines Corporation in the United States and/or other countries.
DS6000*
BlueMix
GUARDIUM* MQSeries*
Rational*
UrbanCode
z/OS*
DS8000*
CICS*
HyperSwap
OMEGAMON*
Redbooks*
WebSphere*
zSecure
FICON*
COGNOS*
IBM*
Parallel Sysplex*
SmartCloud*
Z13
z Systems
GDPS*
DB2*
IBM (logo)*
RACF*
Tivoli*
zEnterprise*
z/VM*
* Registered trademarks of IBM Corporation
These are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. A current list of IBM trademarks is
available on the web at “Copyright and trademark information” at: http://www.ibm.com/legal/us/en/copytrade.shtml
The following are trademarks or registered trademarks of other companies.
LinkedIn, the LinkedIn logo, the IN logo and InMail are registered trademarks or trademarks of LinkedIn Corporation and its affiliates in the United States and/or other countries.
Java and all Java based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates.
Linux is the registered trademark of Linus Torvalds in the U.S. and other countries.
Adobe, the Adobe logo, Acrobat, PostScript, and Reader are either trademarks or registered trademarks of Adobe Systems Incorporated in the United States and/or other countries.
Microsoft, Windows, Excel, Outlook, and PowerPoint are registered trademarks of Microsoft Corporation.
Oracle and Java are registered trademarks of Oracle and/or its affiliates.
UNIX, X/Open, OSF/1, and Motif are registered trademarks of the Open Group.
OpenStack is a trademark of OpenStack LLC. The OpenStack trademark policy is available on the OpenStack website.
SAP, R/3, SAP NetWeaver, ByDesign, SAP BusinessObjects Explorer, StreamWork, and other SAP products and services mentioned herein as well as their respective logos are
trademarks or registered trademarks of SAP SE in Germany and other countries.
All other product and service names mentioned are the trademarks of their respective companies.
Data contained in this document serves informational purposes only. National product specifications may vary.
Notes:
Performance is in Internal Throughput Rate (ITR) ratio based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput that
any user will experience will vary depending upon considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the
workload processed. Therefore, no assurance can be given that an individual user will achieve throughput improvements equivalent to the performance ratios stated here.
IBM hardware products are manufactured from new parts, or new and serviceable used parts. Regardless, our warranty terms apply.
All customer examples cited or described in this presentation are presented as illustrations of the manner in which some customers have used IBM products and the results they may have
achieved. Actual environmental costs and performance characteristics will vary depending on individual customer configurations and conditions.
All statements regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.
Information about non-IBM products is obtained from the manufacturers of those products or their published announcements. IBM has not tested those products and cannot confirm the
performance, compatibility, or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products.
© 2015 IBM Corporation
29
Legal information
Please note
IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion. Information
regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision.
The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or
functionality. Information about potential future products may not be incorporated into any contract. The development, release, and timing of any future
features or functionality described for our products remains at our sole discretion.
Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The
actual throughput or performance that any user will experience will vary depending upon many factors, including
considerations such as the amount of multiprogramming in the user’s job stream, the I/O configuration, the storage
configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results
similar to those stated here.
Availability. References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM
operates.
The workshops, sessions and materials have been prepared by IBM or the session speakers and reflect their own views. They are provided for
informational purposes only, and are neither intended to, nor shall have the effect of being, legal or other guidance or advice to any participant. While
efforts were made to verify the completeness and accuracy of the information contained in this presentation, it is provided AS-IS without warranty of any
kind, express or implied. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this presentation or any other
materials. Nothing contained in this presentation is intended to, nor shall have the effect of, creating any warranties or representations from IBM
or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software.
All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have
achieved. Actual environmental costs and performance characteristics may vary by customer. Nothing contained in these materials is intended to, nor
shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or other results.
© 2015 IBM Corporation
30