db2 analytics accelerator · 2020-03-24 · data and ai on ibm zdata and ai on ibm z db2 analytics...
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© 2019 IBM Corporation1
Data and AI on IBM Z Data and AI on IBM Z
Db2 Analytics AcceleratorProvider of Data Gravity
Ed Lynch
IBM z Data & AI Presales Engineer
© 2019 IBM Corporation2
Data and AI on IBM Z Data and AI on IBM Z
Agenda
• Db2 Analytics Accelerator Overview
• Features of IDAA
• Approaches to Using IDAA
• Benefits
Db2 Analytics Accelerator
© 2019 IBM Corporation3
Data and AI on IBM Z Data and AI on IBM Z
Traditional Approach to Analytic Systems
Operational
Applications
Transaction Processing
Shared Everything DB
High volume business transactions and batch
processing running concurrently
Analytic Applications
Data Store, Business
Intelligence, Predictive
Analytics
Shared Nothing DB
/ Columnar DB
Low volume complex
queries and batch
reporting
Latency?
Security?
Data Governance?
Complexity?
Data transfer
© 2019 IBM Corporation4
Data and AI on IBM Z Data and AI on IBM Z
The Hybrid VisionDelivering Business Critical Analytics
Transactional Processing, Traditional Analytics &
Business Critical Analytics
Hybrid DB
High volume business transactions and batch
reporting running concurrently with complex
queries
Combined Workloads
Reduced Latency. Greater Security.
Improved Data Governance. Reduced Complexity.
© 2019 IBM Corporation5
Data and AI on IBM Z Data and AI on IBM Z
Take the analysis to the data
• Avoid all the pitfalls of moving the data
Simplified infrastructure with more resiliency
• One copy of the data not dozens
Much more secure
• Z security built in
Lower cost
• Saves money (Infrastructure, SW, and people)
Much lower analytics latency
• Low to no latency with transactional data
A Data Gravity approach performs analytics
where the majority of the data originates
By far, the best place to analyze
Z data is on IBM Z
Db2 Analytics Accelerator and Data Gravity Benefits
© 2019 IBM Corporation6
Data and AI on IBM Z Data and AI on IBM Z
Db2 Analytics Accelerator and Db2 for z/OS
WHATAn integrated, hybrid workload-optimized database management system
HOWRuns each query workload efficiently in its optimal environment
WHYTo ensure the greatest performance and cost efficiency
TransactionProcessing
HTAP AnalyticalWorkload
WOWExploit IBM Z data in-place to improve efficiency, drive smarter outcomes and gain competitive differentiation
© 2019 IBM Corporation7
Data and AI on IBM Z Data and AI on IBM Z
Deep DB2 integration within z SystemsApplications
Application Interfaces(standard SQL dialects)
DBA Tools, z/OS Console . . .
Operational Interfaces(e.g. DB2 Commands)
Data
Manager
Buffer
ManagerIRLM
IBM DB2
Analytics
Accelerator
. . .Log
Manager
DB2 for z/OS
Superior availability,
reliability, security
Workloadmanagement
z/OS onz Systems
Superior
performance
on analytic
queries
© 2019 IBM Corporation8
Data and AI on IBM Z Data and AI on IBM Z
Query execution process flow
Ac
ce
lera
tor D
RD
A R
eq
ue
stor
ApplicationInterface
Heartbeat (availability and performance indicators)
Application
Optimizer
Query execution run-time for queries
that cannot be or should not be
routed to Accelerator
Heartbeat
Queries executed
with Accelerator
Queries executed
without Accelerator
© 2019 IBM Corporation9
Data and AI on IBM Z Data and AI on IBM Z
Powered by Db2 with BLU Acceleration (Db2 Warehouse)
• Fast ingest for incremental updates, and thereby low HTAP query delay!• IBM’s premier analytics engine across many products• Latest analytics technology innovations• SQL compatibility across all IBM products• High degree of concurrent users and queries
In-memory column processingwith dynamic movement of data
from storage
Multi-core and SIMD parallelism
(Single instructionMultiple Data)
Patented compression technique preserves order -- data can be used without decompressing
Skips unnecessary processing of irrelevant data
© 2019 IBM Corporation10
Data and AI on IBM Z Data and AI on IBM Z
SQL functionality support and restrictions
•Improved Db2 for z/OS SQL support on Accelerator V7 (compared to V5)• All data types supported except LOBs or XML
• Improved Db2 for z/OS function support on the Accelerator
• Still some not supported, e.g ACOS, ASIN, CLOB, ..
• Correlated subquery support
• Recursive SQL support
• Special register support
•Restrictions: • No user defined functions (except inline SQL scalar UDF, compiled SQL scalar UDF)
• No multiple encoding schemes in the same statement
Knowledge Center: Conditions for query routing to an acceleratorhttps://www.ibm.com/support/knowledgecenter/en/SS4LQ8_7.1.0/com.ibm.datatools.aqt.doc/gui/concepts/c_idaa_query_offloading_criteria.html
© 2019 IBM Corporation11
Data and AI on IBM Z Data and AI on IBM Z
Pass-through support for Db2 Warehouse built-in functions Enhancing Db2’s native SQL Capabilities with the Accelerator
• Many built-in functions that are supported by the underlaying DBMS (Db2 Warehouse) in the Accelerator are not supported natively by Db2 for z/OS (yet).
• Some of them can now be used in SQL queries routed to the Accelerator with the new Built-In-Function (BIF) Pass-through support
• Db2 for z/OS is ”aware” of the Accelerator, when parsing the SQL statement.
• If a BIF is referenced, which is only available on the Accelerator, the Db2 for z/OS parser validates the signature and allows its invocation within the rewritten SQL.
• Db2 for z/OS still needs to validate parameters, return types, …. Therefore the pass-through is limited to commonly requested BIFs.
• Supported BIFs
• OLAP/Aggregate functions: CUME_DIST, FIRST_VALUE, LAG, LAST_VALUE, LEAD, NTH_VALUE, NTILE, PERCENT_RANK, RATIO_TO_REPORT
• Scalar functions: REGEXP_COUNT, REGEXP_INSTR, REGEXP_LIKE, REGEXP_REPLACE, REGEXP_SUBSTR
• Db2 12 only, FL504
© 2019 IBM Corporation12
Data and AI on IBM Z Data and AI on IBM Z
Agenda
• Db2 Analytics Accelerator Overview
• Features of IDAA
• Approaches to Using IDAA
• Benefits
Db2 Analytics Accelerator
© 2019 IBM Corporation13
Data and AI on IBM Z Data and AI on IBM Z
Accelerator on IBM Integrated Analytics System
• Pre-configured hardware and software for easy deployment, management, and high performance
• Secure, flexible and elastic data storage –easy to deploy and manage
Accelerator on IBM Z
• Deep integration with IBM Z offers a unified homogeneity of service, support and operations
• Flexible capacity to respond to peak analytic workload requirements
Flexible, integrated deployment options
Db2 Analytics AcceleratorHigh-speed analysis of enterprise data for real-time insight
Uniform experience – transition easily between deployment options with one API and one database engine
© 2019 IBM Corporation14
Data and AI on IBM Z Data and AI on IBM Z
Db2 Analytics Accelerator Version 7.5
Db2 Analytics Accelerator Version 7.5 delivers:
• Integrated Synchronization a new advanced data synchronization technique
• A wider range of scalability for Db2 Analytics Accelerator on IBM Z deployments -- from very small to very large
General Availability: December 6, 2019
© 2019 IBM Corporation15
Data and AI on IBM Z Data and AI on IBM Z
Incremental update architecture with CDC
Applications executing I/U/D Statements on replicated tables
Accelerator Users enabling tablesfor replication
CDC Capture
Agent
Table T1
CDC
Replication
Engine
Db2 Log Data
Table T2
Table T3
Table T1
Table T2
Table T3
CDCAccess Server
Accelerator
Server
Manages Subscription
T2
Committed Data
T3T1
Stored Procedures
© 2019 IBM Corporation16
Data and AI on IBM Z Data and AI on IBM Z
Db2 Analytics Accelerator Version 7.5Integrated Synchronization
Integrated, low-latency data coherence protocol between Db2 for z/OS and the Db2 Warehouse
• zIIP enabled
• Complete application transparency
• Enterprise-grade HTAP enabler
• Simplified administration, packaging, upgrades, support . . .
Deeper integration between Db2 for z/OS and Db2 Analytics Accelerator to provide insight from the most current transactional data
© 2019 IBM Corporation17
Data and AI on IBM Z Data and AI on IBM Z
Integrated Synchronization - Db2/Z to-Accelerator data synchronization
Applications executingI/U/D Statements on replicated tables
Accelerator Users enabling tables for replication
Table T1
Log data
processor
Db2 Log
Table T2
Table T3
Table T1
Table T2
Table T3
Accelerator
Server
Encrypted Log Data
Stored Procedures
Log Data
Provider Staging
area
Process control
© 2019 IBM Corporation21
Data and AI on IBM Z Data and AI on IBM Z
Why True HTAP?
• Single System, Single Interface
• Data coherency between Db2 and Accelerator
• Don’t worry about latency of committed data
• Queries run first when data available
• No longer need to explain to users why committed data not seen.Data used by SELECT contains corresponding commits
• e.g. Use case ”Fraud Detection”Detection query works on most recent data
• e.g. Use case “Multi form consistency”Enter data in a field on a panel. Application commits data.
=> Just entered data shown on following panels
21
© 2019 IBM Corporation22
Data and AI on IBM Z Data and AI on IBM Z
How does HTAP work?
Wait for committed data
from time of SQL request
22
Asynchronous
replication
Most
recent
committed
data
available?
no
Wait for
given
time
period
Most
recent
committed
data
required?
yes
no
Initiate
apply
Write
requests
OLTP
reads
OLAP
readsyes
© 2019 IBM Corporation23
Data and AI on IBM Z Data and AI on IBM Z
High Performance Storage SaverStoring historical data in Accelerator only
Support for partitioned-by-range tables, for example:
Time-based partitions, where only the recent partitions are used in a transactional context
(frequent data changes, short running queries), but the entire table is used for analytics,
regulatory/audit purposes, etc. (data intensive, complex queries)
Active
Part #1Part #1
Part #2 Part #3 Part #4
Part #5 Part #6 Part #7 HistoricalNo longer present on
DB2 Storage
Query from Application to either Active only or Active and Historical
© 2019 IBM Corporation24
Data and AI on IBM Z Data and AI on IBM Z
Non-accelerator DB2 table
• Data in DB2 only
Accelerator-shadow table
• Data in DB2 and the Accelerator
Accelerator-archived table / partition
• Empty read-only partition in DB2
• Partition data is in Accelerator only
Accelerator-only table (AOT)
• “Proxy table” in DB2
• Data is in Accelerator only
Accelerator-only table type in DB2 for z/OSCreation (DDL) and access remains through DB2 for z/OS in all cases
Table 1
Table 4
Table 3
Table 2
Table 4
Table 3
Table 2
© 2019 IBM Corporation25
Data and AI on IBM Z Data and AI on IBM Z
Accelerator-only tablesSupporting in-database transformation and multi-step processing
Introduction of Accelerator-only tables (AOT)
to store intermediate or final results of data
transformation or reporting processes
▪ Can be used to store a set of data in Db2 Analytics Accelerator only, not on Db2 for z/OS, without using the High Performance Storage Saver functionality
▪ Accelerate in-database data transformations and data movement processes
▪ Reduced need of data movement processes to other platforms for data transformation purposes
▪ Enables multi-step reporting on the Accelerator
▪ Saves disk space and CPU cost on IBM Z currently used for transformations and reporting steps
▪ Allow data preparation steps for data mining and other advanced analytics to execute on the Accelerator
© 2019 IBM Corporation26
Data and AI on IBM Z Data and AI on IBM Z
Multi-step reporting applications with DB2 for z/OSWith Accelerator-only tables: Temporary objects and processing on the Accelerator
Temporary results
2Temporary results
1Temporary results
Reports and Dashboards
n
Multi-Step Report
n
1
2
Reporting Application
Credit Card
Transaction History
Customer
Summary Mart
Credit Card
Transaction History
Customer
Summary Mart
Data for transactional and analytical processing
© 2019 IBM Corporation27
Data and AI on IBM Z Data and AI on IBM Z
Using Accelerator-only tables and ELT logic in the Accelerator(In-database transformation)
Transaction Processing
Systems (OLTP)
Analytics
Advantages: • Simpler to manage
• Better performance and reduced latency Data for transactional and analytical processing
Customer
Transactions
Customer
Data
Customer Transaction Summary and History AOTs
Customer Summary
Mart AOTs
Customer
Transactions
Customer
Data
ELT logic
© 2019 IBM Corporation28
Data and AI on IBM Z Data and AI on IBM Z
Data scientist work areaUsing Accelerator-only tables for ad-hoc analysis
Transaction Processing
Systems (OLTP)
Data for transactional and analytical processing
Customer
Transactions
Customer
Data
Customer
Transactions
Customer
Data
Work database John
Work Area AOTs
Work database Bob
Work Area AOTs
Data Scientist John
Data Scientist Bob
© 2019 IBM Corporation29
Data and AI on IBM Z Data and AI on IBM Z
Integrate more data sources for analyticsLoad external data to the accelerator and combine it with data from Db2 for z/OS for reporting and analytics
Transaction Processing
Systems (OLTP)
Analytics
Data for transactional and analytical processing
Customer
Transactions
Customer
Data
Combined result in AOTs
Customer
Transactions
Customer
Data
Related data from
other sourcesExternal
Files
Imagecopy
DB2 Analytics Accelerator Loader
VSAM &
Flat FileOracle
IMSOther
Relational
non z
© 2019 IBM Corporation30
Data and AI on IBM Z Data and AI on IBM Z
Db2 Analytics Accelerator Loader for z/OS*
• Significant cost & time reduction by eliminating manual ETL processes of non-Db2 data
• Insight into more data types such as IMS, VSAM, sequential files, Oracle, Adabas, etc.
• Ensure High Availability for critical analytics applications
• Protect critical analytics data with backup & restore strategy
• Support cascading changes made to replicated tables to reduce data latency
• Enhance use of Accelerator-only tables with one-step load and load resume
Extend analytic capabilities by bringingnon-Db2 data to IBM Db2 Analytics
Accelerator and IBM Z
*Separately licensed option
© 2019 IBM Corporation31
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Connectivity options
▪ residing in the same LPAR
▪ residing in different LPARs
▪ residing in different CECs
Full flexibility for DB2 systems:
Multiple DB2 systems can connect
to a single Accelerator
A single DB2 system can connect
to multiple Accelerators
Multiple DB2 systems can connect
to multiple Accelerators
▪ being independent (non-data sharing)
▪ belonging to the same data sharing group
▪ belonging to different data sharing groups
© 2019 IBM Corporation32
Data and AI on IBM Z Data and AI on IBM Z
Federation support
• Without Federation: Data from Db2 subsystems sharing same accelerator is fully isolated
• With Federation: Grant read access to a table from another Db2 subsystem
• Prerequisites:
• Data from different DB2 systems is loaded into the same accelerator
DB2R DB2O1….
Accelerator
SELECT
….
DB2O2
….
© 2019 IBM Corporation33
Data and AI on IBM Z Data and AI on IBM Z
Agenda
• Db2 Analytics Accelerator Overview
• Features of IDAA
• Approaches to Using IDAA
• Benefits
Db2 Analytics Accelerator
© 2019 IBM Corporation34
Data and AI on IBM Z Data and AI on IBM Z
Typical Approaches – The “Blue Birds”
• Accelerate Existing Queries
▪ Accelerate Existing Complex Queries – static & dynamic (e.g. QMF, Cognos,..)
▪ Run Costly Queries More Frequently -> Increased Business Value
▪ Run “Abandoned Queries” -> New Business Opportunity
• Cost Savings
▪ CPU Savings & Reduced Elapsed Times
▪ Db2 Index Elimination &/or Reduction – storage savings
• “Online Archive” via High Performance Storage Saver Feature
▪ Save on DB2 storage, data maintenance, and data access costs
▪ Immediate Access – zero recall time of archived data
▪ Instantaneous & Simultaneous Access to Current & Archived Data
© 2019 IBM Corporation35
Data and AI on IBM Z Data and AI on IBM Z
Typical Approaches – “Effort Required”
• In Accelerator Database Analytics – go from ETL to ELT using AOTs
• Single Centralized Hybrid Data Store
▪ Shift Query Workload back to Db2 for z/OS with IDAA
▪ Eliminate costs of separate DWH, ODS, and DataMarts
▪ ETL / Replication Cost Elimination
▪ Have seen 20-40% of zCPU Burned for ETL and Replication Purposes
▪ Convert “Transactional Batch Workloads” and Batch Jobs that perform “Application Joins” to use IDAA eligible queries▪ Requires consolidating multiple SQL calls into single calls
▪ Reduction of supporting Application code
© 2019 IBM Corporation36
Data and AI on IBM Z Data and AI on IBM Z
Agenda
• Db2 Analytics Accelerator Overview
• Features of IDAA
• Approaches to Using IDAA
• Benefits
Db2 Analytics Accelerator
© 2019 IBM Corporation37
Data and AI on IBM Z Data and AI on IBM Z
Productivity Improvements
Productivity
ImprovementBenefits of Time Savings▪ Dramatic Query Elapsed Time Reductions
− Saved Time for End Users
− Improved Customer Service/Support
− End User Satisfaction
− Revenue Growth Opportunities
▪ Online Archive – No Waiting for Recall, Access to Active & Archive
▪ Administration Time Savings
− Fewer Database Maintenance Jobs to Create/Maintain
− Faster Maintenance Execution
− DBA Time Savings
− Less Time Analyzing & Tuning Queries, & Testing
© 2019 IBM Corporation38
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Cost Reduction Opportunities
▪ Infrastructure Simplification – Eliminate/Reduce
− Same Tooling (Dev/Test/Admin/Monitoring)
− Security of System z
− ETL & ETL Creation/Maintenance Costs
− Replication
− Eliminate DataMarts (system, storage, maintenance)
− Eliminate Network Impact of Data Movement
− Fewer Copies of Data = Reduced Storage Costs
− Lower Latency = Improved Business Value
− Fewer Systems to Provision, Operate, Maintain, Power, Cool, &
Provision
− Simplify Data Governance
Cost
Reduction
© 2019 IBM Corporation39
Data and AI on IBM Z Data and AI on IBM Z
New Business Opportunities
New Business
Opportunities
For Customers & Customer Service
▪ Operational Analytics
▪ Real-time Business Dashboards
▪ Real-time Reporting
▪ Reduced Time to Market
− Leveraging Existing Transactional Data
− Don’t have to Wait to Design DWH or Data Lake
− Don’t have to Wait to Build DWH or Data Lake
▪ Low Latency – Improved Business Value
▪ Run Workloads More Frequently
▪ Brush Dust off of “Shelved Projects”- Shift in Cost Equation
© 2019 IBM Corporation40
Data and AI on IBM Z Data and AI on IBM Z
Learn more!
• What’s available?• Product videos
• Guided demo
• Hands-on lab
Visit the Db2 Analytics Accelerator on IBM Demos: http://ibm.biz/Acceleratordemos
© 2019 IBM Corporation41
Data and AI on IBM Z Data and AI on IBM Z
Summary
• Db2 Analytics Accelerator Overview
• Features of IDAA
• Approaches to Using IDAA
• Benefits
Db2 Analytics Accelerator
© 2019 IBM Corporation42
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Appendix – Deployment Options Detail
© 2019 IBM Corporation43
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Db2 Analytics Accelerator V7.5, deployment on IBM Integrated Analytics System (IIAS)
• Hardware appliance
• A full solution that provides all components out of the box – including optimized hardware and software
• All components provided by IBM in a balanced, performance-optimized configuration
• HW, which includes the rack, the physical servers and the storage
• SW stack including the Linux operating system, the Docker software as well as the Docker container and the infrastructure management
• IBM Power hardware for the appliance, balanced and optimized for price/performance
© 2019 IBM Corporation44
Data and AI on IBM Z Data and AI on IBM Z
IBM Db2 Analytics Accelerator on IIAS Product components
OSA-Express
10 GbE
CLIENT
• Data Studio with Db2 Analytics Accelerator Studio Plug-in
• Data Server Manager 2.1.5 or higher
IBM Z
Db2 for z/OS enabled forIBM Db2 Analytics Accelerator
incl. Stored procedures
IBM Db2 Analytics
AcceleratorUsers/
Applications
Dedicated highly availablenetwork connection
IBM Integrated Analytics System
OSA-Express
10 GbE
Pa
tch
Pa
ne
l
© 2019 IBM Corporation45
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IBM Integrated Analytics System Configurations
IBM Power 8 S822L 24 core server 3.02GHz
M4002-0031/3 Rack
M4002-0062/3 Rack
M4002-010Full Rack
M4002-020Double Rack
M4002-040Quad Rack
Servers 3 5 7 13 25
Cores 72 120 168 312 600
Memory 1.5 TB 2.5 TB 3.5 TB 6.5 TB 12.5 TB
Flash Storage Capacity
27 TB 54 TB 81 TB 162 TB 324 TB
© 2019 IBM Corporation46
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Db2 Analytics Accelerator Version 7.5, deployment on IBM Z
• A software appliance running on IBM Z
• Packages the SW stack into an IBM Secure Service Container to deliver a fully self-managed appliance running in a SSC LPAR that can be deployed in minutes
• Integrates seamlessly into the customer’s Z environment and leverages known LPAR-, memory and CPU management procedures, including call home support for enterprise hardware components.
• Uses customer-provided storage to hold the accelerator-side data
Existing
Co
mp
on
en
ts
SE / HCM
PR/SM LPAR CPU Memory
Storage (SAN)Filesystem
IBM Secure Service Container
Customer’s Storage
Management
Docker container
Db2 Warehouse engine
Authentication
Acceleratorserver
WorkloadMonitoring
Systems Manager
Additional future functionality
Docker supported OS + management
De
livere
d as p
art of
Acce
lerato
r Solu
tion
© 2019 IBM Corporation47
Data and AI on IBM Z Data and AI on IBM Z
Db2 Analytics Accelerator on IBM Z
A fully integrated software appliance• Running on IBM Z servers in a Secure Service Container (SSC) LPAR• ”download & go” – very easy to deploy• Delivers the full SW stack including operating system,
docker engine, Db2 Warehouse engine, IDAA components, and infrastructure management
A solution leveraging IBM Z infrastructure• Runs on all IBM Z systems starting with z13 (z13, z13s, z14, z14 ZR1,
z15)• Leverage “white space” (unused capacity) in existing systems – or
dedicate a stand-alone system, e.g., LinuxONE• Leverage existing storage systems (CKD or FB) – no dedicated storage
system required• Leverage existing Z high-availability and disaster recovery solution by
integration of the accelerator with GDPS/Metro
© 2019 IBM Corporation48
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Db2 Analytics Accelerator on IBM Z
• Leverages IBM Secure Service Container− SSC security features ensure that the appliance image cannot be tampered with
and the appliance code and data are protected and kept confidential both in flight and at rest
• Accelerator on Z runs natively in an SSC LPAR on IFLs• Customizable configuration and highly flexible scaling− Single-Node: Minimum 2 IFLs / 64 GB memory, maximum 40 IFLs / 4,096 GB
− Multi-Node: Minimum 30 IFLs / 1.5 TB memory, maximum 190 IFLs / 20 TB
− Can utilize shared infrastructure such as network or storage adapters• No additional licensed software required – no z/VM, no KVM,
no Linux on Z, no Docker, no …− Accelerator not supported to run under z/VM or KVM control
• No operating system access or maintenance− No system administrator access to appliance possible
− All required updates, e.g., security fixes, component updates, etc., are delivered and installed as accelerator image updates
− All required configuration via administrative UI or configuration files
© 2019 IBM Corporation49
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IBM Db2 Analytics Accelerator on IBM ZProduct components
IBM Z
Db2 codeincluding Stored Procedures
Accelerator Appliance• Can be deployed on the
same CEC as Db2 or on a different one
Appliance UI
• Data Studio with Db2 Analytics Accelerator Studio Plug-in
• Data Server Manager 2.1.5 or higher
Dedicated highly availablenetwork connection
OSA
OSA
OSA
OSA
© 2019 IBM Corporation50
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Accelerator on IBM Z – Deployment Options
50
© 2019 IBM Corporation51
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Multi-Node Deployment – Architecture
51
Storage
Db2 z/OS
Accelerator on Z
network
Head
IDAA serverDb2 WH• Catalog• No data
partitions
HiperSocket
Data 1
Db2 WH• Data
partitions
Data 5
Db2 WH• Data
partitions…
…
LPAR Group with absolute capping
SSC LPAR SSC LPAR SSC LPAR
OSA
© 2019 IBM Corporation52
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Multi-Node Deployment – IFLs & Memory
52
Storage
Db2 z/OS
Accelerator on Z
network
Head
IDAA serverDb2 WH• Catalog• No data
partitions
HiperSocket
Data 1
Db2 WH• Data
partitions
Data 5
Db2 WH• Data
partitions…
…
LPAR Group with absolute capping
SSC LPAR SSC LPAR SSC LPAR
OSA 30 IFLs(shared)
256 GBweight=high
14 IFLs(shared)
512 GBweight=low
14 IFLs(shared)
512 GBweight=low
Performance goal:70-80 IFLs comparable to N3001-010
70 IFLs
© 2019 IBM Corporation53
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Multi-Node Deployment – Advantages
53
• Scalability of the Accelerator on Z for the most demanding workloads
• Multi-node accelerator can grow from the entry level (30 IFLs) to the largest size using all available IFLs on a system (190 IFLs on IBM z15) without ever reloading the data
• Extremely flexible adjustment of resources (IFLs, memory, storage) to optimize for the actual workload requirements− Even dynamic adjustments (add/remove IFLs, add/remove memory, add storage) are
supported and require only short or even no downtime
− True “capacity-on-demand” without any disruption (for IFL capacity)
• Maintains all advantages of the deep integration into the Z platform
© 2019 IBM Corporation54
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Multi-Node Deployment – Q&A
• Why are multiple LPARs used instead of just increasing LPAR size?➢ Current limitation of a single SSC LPAR to 128 IFLs and 10 TB memory
➢ Performance measurements have shown that the performance/throughput for a multi-LPAR configuration is better per IFL than scaling a single LPAR far beyond 40 IFLs
➢ Huge LPARs could create issues in operations / maintenance
• Does the Z system running the accelerator need to be dedicated?➢ No. Other workloads can run on the same system. However, all of the accelerator LPARs need to run on the same
system – which may mean a significant portion of the overall capacity.
➢ A single system can also run multiple accelerators – potentially using a mix of both deployment options (single-/multi-node) in the same environment
• Do all LPARs for the multi-node accelerator need to run on a single CPC?➢ Yes. Distribution of LPARs to multiple CPCs is not supported.
• When should I consider the multi-node setup over single-node?➢ If the accelerator sizing indicates resource requirements beyond 30 IFLs and/or 2 TB memory
➢ If growth projections indicate that the single-node capabilities would be exceeded “soon”
• Is there a migration path between single-node and multi-node deployment?➢ No. Such a change requires a new accelerator installation.
54
© 2019 IBM Corporation55
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