IBMHadoopofferingTechline-Systems2015

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© Copyright IBM Corporation 2015
IBM Solution for Hadoop offering
a modest experience as Techline POWER
Daniela Zuppini
Consulting IT Specialist
IBM

Session objectives
• What is Hadoop
• How to proceed
• IBM Solution for Hadoop POWER System edition
• IBM Data Engine for Analytics
• Network
• Software

Techline
Techline Mission
To be a strong technical sales partner
• To be your technical sales support supplier of choice.
• Providing pre-sales technical expertise for client opportunities,
helping you to win business.
• Local links to technical sales making us highly available and
responsive.
• Using our global structure to deliver efficient and consistent service.

Techline Products supported
• IBM Systems
• Power Systems – AIX, IBM i
• Pure Systems (Power & Hybrid)
• z System – z/OS, z/VM, z/VSE
• System Storage – Disk, Tape
• z System Software
• Linux on all IBM platforms
• Solutions
• ISV Sizing
• IT Optimisation, Virtualisation
• Cloud, Analytics, Mobile, Social, Security
• GTS Services
• Security Services (Appliances and Software)
• Security Services (MSS and PSS)
• Softek TDMF
• Tivoli Live Monitoring Services (TLMS)
• IBM Software Sizing

How to contact Techline
*Business Partners http://www.ibm.com/partnerworld/techline
IBM Raise a request: http://w3.ibm.com/support/techline/eu/trg/form.html
Quick Chat: https://ibm.biz/SASHA_EU
* Techline Access is limited to Advanced and Premier level Business Partners and Members who purchase a Valuepack

What is Hadoop
Innovation is also the capability to combine
existing practices and ideas in a new way
διαίρει κα βασίλευεὶ
Better known as
DIVIDE ET IMPERA

What is Hadoop
Suppose to have a very very simple algorithm
if word then return (word,1)
Suppose to execute this operation in massive parallel way
On a very large amount of input data es. all latin literature production
if you split input files into blocks
and distribute across all nodes
you can obtain
you the
roman emperor hit parade in short time
This parallelism is possible because each block of data is independent from the other
And the order of data processing is not relevant.

Hadoop framework basic components
• EXECUTE: MAP/REDUCE
input output in the form of (key,value) pairs
mapper and reducer executed in parallel
No order control for maps or reducer execution
batch data processing engine
Java code
• STORAGE: HDFS
Data spread across cluster nodes
Write once /read many
sequential read of large files
Optimized to process large file
3 data replica across nodes
Input data
Map Map Map
Reduce Reduce Reduce
shuffle & sort space
Output data

Hadoop architecture
3W replication
Name NodeJob Tracker
Data node &
Task tracker
data blocks
Standby Name Node
Cluster network
Data node &
Task tracker
Data node &
Task tracker
map reduce
distributed file system

What should I use Hadoop for?
• log and machine data analysis
leave the page after seeing the cost of shipping?
are certain products abandoned more than others?
• preprocess and transform data for DW
Explore data determining what data can be moved to the DW
• Fraud detection
capture deviation from standard usage
• Risk modeling
customer churn prediction to predict risk client moving to competitor
• Social sentiment analysis
analyzing social activities to predict ratings of popular events

Hadoop solve my problem?
Hadoop is not a good choice for
•For intense calculations with little or no data
•When your processing cannot be easily made parallel
•When your data is not self-contained
•When you need interactive results
•Not a RDBMS replacement
Yes if you can rewrite your algorithms as maps and reduces.
If not, then no.

How to proceed
Do not start from a bunch of servers and storage
approach from the perspective of a solution
•Engage Big Data Systems Center
email to BDSC@US.IBM.COM or
Submit Online Request: https://ibm.biz/BdFfcV for IBMers
Analyze your input requirements
Obtain sizing and reference architecture
•Engage IBM Montpellier Client Center - Power Linux Center
email to christophe.menichetti@fr.ibm.com or
BDSC - IOT Europe Leader
Big Data Power Linux Workshop / benchmark / Showcase / Architecture
•Contact Techline
IBM: http://w3.ibm.com/support/techline
BP: http://www.ibm.com/partnerworld/techline
transform HW architecture into a configuration proposal

What to ask to customer
• Workload definition:
– Will any of the workload be MapReduce and/or NoSQL, BigSQL, Hbase ?
– Does the customer consider the workload simple, medium or complex
– Are there any response time or thru-put requirements ?
• For the Ingestion of data:
– What is the peak ingestion rate required for the data?
– Please describe what type of data (structured, unstructured, semi-
structured)?
• Capacity sizing.
– What is the raw data size ( in TB) the environment is initially required ?
– What is the compression rate the customer assumes ?
– What is the data growth rate over what period of time?
• What are the High Availability requirements for the BigInsights environment ?
• What are the Disaster recovery requirements ?
– What is the RTO (Recovery Time Objective) and RPO (recovery Point
Objective) for the environment ?
• Does the customer expect to use GPFS or HDFS ?
• Do we need to include Linux licenses in the configuration ? (or do they have an
enterprise Lic.)

BDSC SIZING
Attention to these points
Compression rate
If compression rate =35% the calculation perfomed are
If the Raw data is 100 GB
(Raw data + replication) is 100 * 3 = 300 GB
(Raw data + replication + 25%ShuffleSort)=300 GB + (300 GB * 0.25) = 375 GB
Applying 35% compression rate = (375 GB * 0.35) =131.25GB

IBM Solution for Hadoop POWER System edition
Map/Reduce
&
GPFS/FPO
Data node + Metadata
Platform Symphony
Job tracker
Management Nodes
Data Nodes
Platform Symphony
Job tracker
Platform Symphony
Job tracker
Cluster network
Map/Reduce
&
GPFS/FPO
Map/Reduce
&
GPFS/FPO
This architecture refers to IBM Biginsight V3

Basic components
• Hadoop management nodes
This node provides the Job Tracker function and a web interface that enables
users to access the cluster and run their applications.
Production cluster
minimum of three Management nodes.
for HA minimum six Management nodes
Non-production cluster
it is acceptable one Management Node.
• Data nodes
House IBM GPFS (or the Hadoop HDFS as an alternative) and the
MapReduce. Number of data nodes depends on workload and amount of data
• Edge nodes
These nodes act as a boundary between the Big Data cluster and the
outside (client) environment.
• System management node
This node is an administrative console designed to cover cluster deployment
and management operations.

Data Node POD based design
Large POD – A
S822L w/ 1 DCS3700: 60 x 3.5” 7.2K RPM 4 TB LFF SAS +
12 x 2.5” 10K RPM 1.2 TB SFF SAS
254.4 TB
Small POD
S822L w/ Internal Drives: 12 x 2.5” 10K RPM 1.2 TB SFF SAS
14.3 TB
Medium POD
S822L w/ EXP24S: 36 x 2.5” 10K RPM 1.2 TB SFF SAS
43.2 TB
Large POD – B
S822L w/ 1 DCS3700: 60 x 3.5” 7.2K RPM 4 TB LFF SAS +
24 x 2.5” 10K RPM 1.2 TB SFF SAS
268.8 TB
Big Data clusters are built using a simple building block approach to tailor the
mix of CPU and storage to application requirements
A POD is represented by server S822L + storage EXP24S/DCS3700

MEDIUM POD
S822L is a special edition for Linux
POWER8 dual-chip module (DCM) processors
20 cores @ 3.42 GHz or 24 cores @ 3.02 GHz fully activated
128GB or 256GB and up to 1024 GB of memory
Twelve SFF-3 Bays/DVD Bay with 12x disks 2.5” 10K RPM 1.2 TB SFF SAS
Split feature to 6+6 SFF-3 Bays: Add a second SAS Controller
One Expansion EXP24S with 24 x disks 2.5” 10K RPM 1.2 TB SFF SAS
Hot-swap PCIe Gen 3 slots 9 adapter slots
2x EL3B PCIe3 LP RAID SAS ADAPTER to connect EXP24S/DCS3700
1x #5260 PCIe2 LP 4-port 1GbE Adapter for cluster management network
For data network 3 alternatives:
2x #EL27 PCIe2 LP 2-Port 10GbE RoCE SFP+ Adapter + 4x #EN02 cables
2x #EC3A PCIe3 LP 2-Port 40GbE NIC RoCE QSFP+ Adapter + 4x #EB2H cables
2x #EL3D PCIe3 LP 2-port 56Gb FDR IB Adapter x16 + 4x #EB4A cables

Medium POD storage connection
EXP24S modes are set by IBM manufacturing
EXP24S must be in Mode 1 #EJR2: one set of 24 disk bays
EXP24S
#EL3B
#EL3B
#ECBU
#ECBU
EXP24S Best price performance per IO bandwith

How to calculate total cluster data space
Space for shuffle/sort data
workload dependent
rule of thumb +25% of total disk space
Number of replicas
Default 3 replicas
Compression rate
dependent on customer data type
user data and shuffle/sort space can be compressed
as in sizing tool compression rate = 1-%compression
Total Disk Space =
(User raw data + 25%) * N. replicas * compression rate

POSH solution in econfig
POD is S822L/S812L with direct connection to EXP24S/DCS3700 used in RAID0
• No preconfigured Solution
• standard POWER + Storage configuration
• HA management nodes have 2 static lpars
no POWERVM
• EXP24S is the server expansion #EL1S
2x#EL3B per node + 2x#ECBUcables
• DCS3700 is the storage product 1818-80C
available in Peripheral section of econfig
2x#EL3B per node + 4x#ECC5 cables
• Consider 40U as rack available space
• Consider 3-phase power
• Add TOR switches

IBM Solution for Hadoop with IDEA
GPFS/native RAID
Data node
map/reduce
Platform Symphony
HA Job tracker
Platform Symphony
HA Job tracker
Workload Management Nodes
Analytic Nodes
GPFS/native RAID
Data node
map/reduce map/reduce
Cluster network
Platform Symphony
Job tracker

IBM Data Engine for Analytics
IBM Data Engine for Analytics is based on
IBM Elastic Storage

IDEA in econfig
Available in Hardware Solutions as preconfigured set of components
5146-S22 Analytic/Workload Management node
24-core 3.34 GHz processor and 256 GB memory
Max 16 analytic nodes x rack
Workload management node default HA
Split bus to boot 2 lpars
Network adapters for external connectivity
#EL27 PCIe2 LP 2-Port 10GbE RoCE SFP+ Adapter (without Optics)
#EL2Z PCIe2 LP 2-Port 10GbE RoCE SR Adapter (Optics) - EC29
#EC3A PCIe3 LP 2-Port 40GbE NIC RoCE QSFP+ Adapter
#EL3D PCIe3 LP 2-port x16 56Gb FDR IB Adapter
ESS 5146 models GL2 or GL4
Select the model then select 2 or 4 TB disks
Mes upgrade via scale out
8147-21L management node
HMC
Ethernet switches configurable with IDEA
G8052 7120-48E
G8124E 7120-24L
G8264 7120-64C

How to calculate total IDEA cluster data space
Space for shuffle/sort data
workload dependent
rule of thumb +25% of total disk space
Compression rate
dependent on customer data type
user data and shuffle/sort space can be compressed
as in BDSC sizing tool compression rate = 1-%compression
Fit Total Disk Space with ESS Available file system capacity
Total Disk Space = (User raw data + 25%) * compression rate

Cluster Network
• data network
 Dedicated to Map/reduce
 Needs its own VLAN and subnet (for example, 10.1.x.x as per predefined
configuration)
 Typically it’s private cluster and the interface to the client’s corporate data network
is obtained using one or more edge nodes
• management network
 For management of all nodes: for provisioning the operating system, deploying
software components and applications, monitoring, and workload management.
 Traffic not related to map-reduce
 Needs its own VLAN and subnet
• service network
 Support HMC operations via FSP, but Hadoop has no dependency on it
 Hardware-level management functions include power-cycling the node, hardware
status monitoring, firmware configuration, and hardware console access
 Needs its own VLAN and subnet

IDEA Cluster Network

IBM machine
type/model
SPECIFICATIONS Use Cases
7120-24L
G7028 • 24× 1 GbE RJ45 ports
• 4x 10 GbE SFP+ ports
• Service network
7120-48E
G8052
• 48x 1 GbE RJ45 ports
• 4x 10 GbE SFP+ ports
• Service network
• OS mgmnt network
7120-64C
G8264
• 48x 10 Gb SFP+ ports
• 4x 40 Gb QSFP+ ports, or
(16x 10Gb SPF+ ports)
• Data network
• OS mgmnt network
LENOVO
G8316
• 16 QSFP+ 40GbE ports, or (64x
10Gb SPF+ ports)
• Data network
• Core switch for small
cluster
LENOVO
G8332
• 32 QSFP+ 40GbE ports, or (128x
10Gb SPF+ ports)
• Data network
• Core switch for large
cluster
http://www-03.ibm.com/systems/networking/switches/rack.html
TOR Switch

Adapter and cabling
 1GbE adapter
Adapter: #5260 PCIe2 LP 4-port 1GbE
Cable: CAT5E Ethernet
#1111 1m / #1112 10m / #1113 25m
10GbE adapter
Adapter: #EL27 PCIe2 LP 2-Port 10GbE RoCE SFP+
Cable: 10Gb E'Net Cable SFP+ Act Twinax Copper
Connects to switch with 10GbE SFP+ port
#EN02 3m (9.8ft) / #EN03 5m (16.4-ft)
 40GbE adapter
Adapter: #EC3A PCIe3 LP 2-Port 40GbE NIC RoCE QSFP+
Cables: DAC cable IBM Passive QSFP+ to QSFP+
Connects to switch with 40GbE QSFP+ port
#EB2H 3m (9.8ft) / #ECBN 5m (16.4-ft) /#ECBP 7m (23.1-ft)
 Infiniband adapter
Adapter: #EL3D PCIe3 LP 2-port 56Gb FDR IB Adapter x16
Cables: FDR IB SWITCH OPTICAL CABLE, QSFP/QSFP
#EB4A 3m / #EB4B 5m

BigInsight Enterprise Edition V3.0
IBM GPFS-FPO 3.5 and Platform Symphony MR are included with BigInsight V3

SW to be configured with econfig
Data/Analytic/Managememt Node
•Red Hat Linux AS v6 for POWER basic license per socket
1/3 yr support+ maintenance from Red Hat
Or
1 yr IBM support + 1/3 yr maintenance from Red Hat
•IBM Platform Cluster Manager Advanced Edition V4 per Server
•GPFS licenses included with Biginsight Enterprise edition
ESS Server
•Red Hat Enterprise Linux v7 for POWER basic license per socket
1/3 yr support+ maintenance from Red Hat
Or
1 yr IBM support + 1/3 yr maintenance from Red Hat
•IBM GPFS V4 standard Edition per socket +
•IBM GPFS Native RAID for GPFS Server v4 per Server
•IBM Platform Cluster Manager Advanced Edition V4 per Server

Lab Services 6911-400
If the solution contains an ESS you have to add Lab Services
1. For each 8247-21L (EMS): 3 units
2. For each pair of 8247-22L: add 2 units
3. Minimum # of units is 5 units, even if above resolves to less than 5
units.
Example IDEA with GL2 and 5 Analytic nodes and 3 workload management nodes
GL2 + service Management node = 5 Units
8 S822L nodes = 8 Units
TOTAL = 13 Units
Lab services are in econfig in tab LAB Services

Special notices
IBM, the IBM logo, ibm.com AIX, AIX (logo), AIX 6 (logo), AS/400, BladeCenter, Blue Gene, ClusterProven, DB2, ESCON, i5/OS, i5/OS (logo), IBM Business Partner (logo),
IntelliStation, LoadLeveler, Lotus, Lotus Notes, Notes, Operating System/400, OS/400, PartnerLink, PartnerWorld, PowerPC, pSeries, Rational, RISC System/6000,
RS/6000, THINK, Tivoli, Tivoli (logo), Tivoli Management Environment, WebSphere, xSeries, z/OS, zSeries, AIX 5L, Chiphopper, Chipkill, Cloudscape, DB2 Universal
Database, DS4000, DS6000, DS8000, EnergyScale, Enterprise Workload Manager, General Purpose File System, , GPFS, HACMP, HACMP/6000, HASM, IBM Systems
Director Active Energy Manager, iSeries, Micro-Partitioning, POWER, PowerExecutive, PowerVM, PowerVM (logo), PowerHA, Power Architecture, Power Everywhere,
Power Family, POWER Hypervisor, Power Systems, Power Systems (logo), Power Systems Software, Power Systems Software (logo), POWER2, POWER3, POWER4,
POWER4+, POWER5, POWER5+, POWER6, POWER6+, System i, System p, System p5, System Storage, System z, Tivoli Enterprise, TME 10, Workload Partitions
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