The document provides an overview of Teradata's Data Warehouse System Architecture, detailing its architecture, including differences between SMP and MPP systems, shared-everything vs shared-nothing architectures, and hardware architecture involving nodes and components like parsing engines and access module processors. It explains concepts such as request processing, how queries are handled, and the roles of various components to ensure efficient database operation and scalability. Key features include a parallel database system designed for extensive scalability and optimized processing of concurrent complex queries.

1. INTRODUCTION TO
TERADATA DATA WAREHOUSE
SYSTEM ARCHITECTURE
PREPARED BY: MOHAMED TAHOON

2. 1. What’s a Teradata DWH System ?
2. SMP vs MPP
3. Shared-Everything vs Shared-Nothing architecture
4. Hardware architecture
4.1 Cliques 4.2 Hot standby Nodes
5. Node architecture
5.1 PDE 5.2 Virtual Processors
5.3 Parsing Engine 5.4 Access Module Processor
5.5 Disk Arrays
6. Request Processing
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3. 3
1 What is Teradata DWH system?
• RDBMS designed to run the world’s largest databases
• Latest Intel technology nodes
• Standard access language (SQL)
• Massive Parallel Processing ‘MPP’ system
• a “Shared-Nothing” architecture
• Parallel-aware optimizer
allowing concurrent complex queries
• Linear Scalability

4. 2. SMP VS MPP
- Multiple CPU’s serving
separate processes Simultaneously
- Shared Everything
- All CPU’s Share Same Memory
- Mostly Hosted on Shared SAN
Symmetric Multi Processing Massive Parallel Processing
- Multiple CPUs runs in Parallel
serving single process
- Shared Nothing
- Each CPU have It’s Own Memory and space
- High Speed Nodes Connection [ByNet]
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5. 1. What’s a Teradata DWH System ?
2. SMP vs MPP
3. Shared-Everything vs Shared-Nothing architecture
4. Hardware architecture
4.1 Cliques 4.2 Hot standby Nodes
5. Node architecture
5.1 PDE 5.2 Virtual Processors
5.3 Parsing Engine 5.4 Access Module Processor
5.5 Disk Arrays
6. Request Processing
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6. 6
SHARED-NOTHINGSHARED-EVERYTHING
- Disk controllers and bandwidth shared
- Synchronization required across nodes
- Large scale Scalability Issue
- Best for many small statements
- Controllers dedicated to nodes
- No Cache Synchronization necessary
- Linear Scalability
- Best for Heavy statements

7. 1. What’s a Teradata DWH System ?
2. SMP vs MPP
3. Shared-Everything vs Shared-Nothing architecture
4. Hardware architecture
4.1 Cliques 4.2 Hot standby Nodes
5. Node architecture
5.1 PDE 5.2 Virtual Processors
5.3 Parsing Engine 5.4 Access Module Processor
5.5 Disk Arrays
6. Request Processing
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8. 8
4 Teradata Hardware Architecture
• SMP Nodes
> Latest Intel SMP CPUs
> Configured in 2+1 node cliques
> Linux or Windows
• BYNET Interconnect
> Fully scalable bandwidth
> 1 to 1024 nodes
• Storage
> Independent I/O per Node
> Scales per node
• Server Management
> One console for the entire system
Server Management
PE
SMP Node1
AMPPE
AMP AMP AMP
PE
SMP Node2
AMPPE
AMP AMP AMP
PE
SMP Node3
AMPPE
AMP AMP AMP
PE
SMP Node4
AMPPE
AMP AMP AMP
BYNET Interconnect

9. 4.1 CLIQUES
• Group nodes together by multiported
access to common disk array units.
• Inter-node disk array connections are
made using FibreChannel (FC) buses.
• FC paths enable redundancy to ensure
the loss of a processor node or disk
controller won’t limit data availability.
• Clique is a mechanism supports migration of VPROCs under PDE following a
node failure.
• If a node in a clique fails, VPROCs migrate to other nodes in the clique and
continue to operate while recovery occurs on their home node.
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10. 4.2 HOT STANDBY NODES
Improves availability and maintain performance levels
in the event of a node failure.
What’s a Hot Standby node:
• Is a member of each clique in the system.
• Does not normally participate in Teradata Database operations.
• Used to compensate for the loss of a node in the clique.
Using Hot Standby node Eliminates:
• Restarts that are required to bring a failed node back into service.
• Degraded service when VPROCs have migrated to other nodes in a clique.
How Hot Standby node failover works :
At node failure, all AMPs and LAN-attached PEs on the failed node migrate to the hot standby node
The hot standby node becomes the production node.
When the failed node returns to service, it becomes the new hot standby node.
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11. 1. What’s a Teradata DWH System ?
2. SMP vs MPP
3. Shared-Everything vs Shared-Nothing architecture
4. Hardware architecture
4.1 Cliques 4.2 Hot standby Nodes
5. Node architecture
5.1 PDE 5.2 Virtual Processors
5.3 Parsing Engine 5.4 Access Module Processor
5.5 Disk Arrays
6. Request Processing
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12. 5 Node Architecture (‘Shared Nothing’)
Each Teradata Node is made up of hardware and software
• Each node runs copy of OS, database SW, & virtual processes
• Each node has CPUs, system disk, memory & adapters
PE vproc
AMP
vproc
Vdisk
AMP
vproc
Vdisk
AMP
vproc
Vdisk
AMP
vproc
Vdisk
AMP
vproc
Vdisk
AMP
vproc
Vdisk
AMP
vproc
Vdisk
AMP
vproc
Vdisk
PE vproc
UNIX
PDE

13. 5.1 PARALLEL DATABASE EXTENSIONS - PDE
Software interface layer lies between O. S. & TD DB which enables The database to :
• Run in a parallel environment
• Execute Vprocs
• Apply a flexible priority scheduler to Teradata Database sessions
• Consistently manage memory, I/O, and messaging system interfaces across multiple OS platforms
PDE provides a series of parallel operating system services, which include:
• Facilities to manage parallel execution of database operations on multiple nodes.
• Dynamic distribution of database tasks.
• Coordination of task execution within and between nodes.
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14. 5.2 VIRTUAL PROCESSORS – WHAT IS IT
What is it:
• Set of software processes that run on a node under Teradata (PDE).
• Eliminate dependency on specialized physical processors
VPROC characteristics:
• Multiple VPROCs can run on an SMP platform or a node.
• VPROCs and the tasks running under them communicate using unique-address
messaging, as if they were physically isolated from one another.
• This message communication is done using the BYNET hardware and BYNET Driver.
• maximum # VPROCs in a system: 16,384 VPROCs, in a node 128.
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15. 5.2 VIRTUAL PROCESSORS – VPROC TYPES
GTW
• Gateway VPROCs provide a socket interface to Teradata Database
PE
• Parsing Engines perform session control, query parsing, security validation, query optimization
AMP
• Access Module Processors perform DB functions; Like: executing database queries.
• Database storage Distributed Across AMPs.
TVS
• Manages Teradata Database storage.
• AMPs acquire their portions of database storage through the TVS vproc.
NODE
• The node vproc handles PDE and operating system functions not directly related to AMP and PE work.
• Cannot be externally manipulated, and do not appear in the output of the Vproc Manager utility.
RSG
• Relay Services Gateway provides a socket interface for the replication agent.
• Relaydictionary changes to the Teradata Meta Data Services utility.
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16. 5.3 PARSING ENGINE ‘PE’
• Communicates with the client system on one side and with the AMPs (via the BYNET) on the other side.
• Each PE executes the database software that manages sessions, decomposes SQL statements into
steps, possibly in parallel, and returns the answer rows to the requesting client.
Parsing Engine Elements
Parser Decomposes SQL into relational data management processing steps.
Optimizer Determines the most efficient path to access data.
Generator Generates and packages steps.
Dispatcher Receives processing steps from the parser, sends them to the appropriate AMPs via BYNET.
Monitors the completion of steps and handles errors encountered during processing.
Session
Control
Manages session activities, such as logon, password validation, and logoff.
Recovers sessions following client or server failures.
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17. 5.4 ACCESS MODULE PROCESSOR ‘AMP’
• The AMP VPROC manages Teradata Database interactions with the disk subsystem.
• Each AMP manages a share of the disk storage.
Database management tasks
• Accounting
• Journaling
• Locking tables, rows, and databases
• Output data conversion
During query processing:
• Sorting
• Joining data rows
• Aggregation
File System Management
Disk Space management.
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18. 5.4 THE AMPS – REQUEST PROCESSING
• The BYNET transmits messages to and from the AMPS and PEs.
• An AMP step can be sent to one of the following:
• One AMP
• Multi-Cast (A selected set of AMPs)
• All AMPs in the system
PE communication with Amps during request processing:
1. PE 1 : Access is through a primary index and a request is for a single row
- the PE transmits steps to a single AMP
2. PE 2 : the request is for many rows (an all-AMP request):
- the PE makes the BYNET broadcast the steps to all AMPs
** To minimize system overhead, the PE can send a step to a subset of AMPs, when appropriate.
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19. 5.5 DISK ARRAYS
Logical Units ‘Lun’
• The RAID Manager uses drive groups DG
• DG is a set of drives that have been configured
into one or more LUNs.
• OS recognizes a LUN as a disk and is not aware
that it is writing on on multiple disk drives.
Vdisk
• Group of cylinders currently assigned to an AMP
• OS recognizes a LUN as a disk and is not aware
that it is writing on on multiple disk drives.
• The actual physical storage may derive from
several different storage devices
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20. 1. What’s a Teradata DWH System ?
2. SMP vs MPP
3. Shared-Everything vs Shared-Nothing architecture
4. Hardware architecture
4.1 Cliques 4.2 Hot standby Nodes
5. Node architecture
5.1 PDE 5.2 Virtual Processors
5.3 Parsing Engine 5.4 Access Module Processor
5.5 Disk Arrays
6. Request Processing
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21. 6 REQUEST PROCESSING – “LIFETIME OF A QUERY”
1. The Parser
•Checks Request cache to determine
if the request is already there
2. The Syntaxer
•checks the syntax of an incoming
request
3. The Resolver
•Adds information from the Data
Dictionary to convert database,
table, view, stored procedure, and
macro names to internal identifiers.
4. Security module
•checks privileges in the Data
Dictionary.
5. The Optimizer
•Determines the most effective way
to implement the SQL request.
6. The Optimizer
•scans the request to determine
where to place locks, then passes
the optimized parse tree to the
Generator.
7. The Generator
•Transforms the optimized parse
tree into plastic steps, caches the
steps if appropriate, and passes
them to gncApply
8. gncApply
•Takes the plastic steps produced by
the Generator, binds in
parameterized data if it exists, and
transforms it into concrete steps.
9 The Dispatcher
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22. P.45 REQUEST PROCESSING – “1. THE PARSER”
1. The Parser
• Checks if the request in Request cache:
• IF IN = > Go to Step (2) - The Syntaxer.
• IF New Request
• The Parser reuses the plastic steps found in the
cache and passes them to gncApply.
• Go to checking privileges (step 4)
• Then Go to gncApply (step 8) after.
2. The Syntaxer
•checks the syntax
3. The Resolver
•convert Object names to internal
identifiers.
4. Security module
•checks privileges
5. The Optimizer
•Determines the most effective way
to implement the SQL request.
6. The Optimizer
•scans the request to determine
where to place locks
7. The Generator
•Transforms parse tree into plastic
steps.
8. gncApply
•binds parameterized data if it exists,
transforms it into concrete steps.
9 The Dispatcher
Plastic steps are directives to the
database management system
that do not contain data values
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23. P.45 REQUEST PROCESSING – “2. SYNTAXER, 3. RESOLVER”
1. The Parser
•Checks Request cache to
determine if the request is
already there
2. The Syntaxer
• checks the syntax of new request:
• IF Wong => passes an error
message back to the requestor and
stops
• IF Correct => converts the request
to a parse tree and passes it to the
Resolver (3)
3. The Resolver
• Adds information from the Data
Dictionary (or cached copy of the
information) to convert database,
table, view, stored procedure, and
macro names to internal identifiers.
4. Security module
•checks privileges
5. The Optimizer
•Determines the most
effective way to implement
the SQL request.
6. The Optimizer
•scans the request to
determine where to place
locks
7. The Generator
•Transforms parse tree into
plastic steps.
8. gncApply
•binds parameterized data if it
exists, transforms it into
concrete steps.
9 The Dispatcher
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24. P.45 REQUEST PROCESSING – “4. SECURITY MODULE, 5. - 6. OPTIMIZER”
1. The Parser
•Checks Request cache to determine if the
request is already there
2. The Syntaxer
•checks the syntax
3. The Resolver
•convert Object names to internal identifiers.
4. The Security module
• checks privileges of accessed object vs Requestor:
• Mismatch => returns a privilege error message
• Privileged => passes the request to the Optimizer.
5. The Optimizer
• Determines the most
effective way to implement
the request (Excution plan)
6. Optimizer
• Determine what type
and where to place
Objects locks
7. The Generator
•Transforms parse tree into plastic steps.
8. gncApply
•binds parameterized data if it exists,
transforms it into concrete steps.
9 The Dispatcher
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25. P.45 REQUEST PROCESSING – “SEPARATE ORIGINAL”
1. The Parser
•Checks Request cache to determine if the request is
already there
2. The Syntaxer
•checks the syntax
3. The Resolver
•convert Object names to internal identifiers.
4. Security module
•checks privileges
5. The Optimizer
•Determines the most effective way to implement the
SQL request.
6. The Optimizer
•scans the request to determine where to place locks
7. The Generator
• Transforms the optimized parse
tree into plastic steps
• caches the steps if appropriate
• passes them to gncApply.
8. gncApply
• Binds in parameterized data if it
exists, and transform plastic
steps to concrete steps.
• passes the concrete steps to the
Dispatcher
9 The Dispatcher
Concrete steps are directives to the AMPs
that contain needed user-or session-
specific values and needed data parcels
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26. P.45 DISPATCHER – REQUEST PROCESSING
• controls the sequence in which steps are executed:
• It also passes the steps to the BYNET to be distributed to the AMPs:
• 1 The Dispatcher receives concrete steps from gncApply.
• 2 The Dispatcher places the first step on the BYNET;
• - tells the BYNET whether the step is for one AMP, several AMPS, or all AMPs;
• - waits for a completion response.
• - Whenever possible, Teradata Database performs steps in parallel to enhance performance.
• 3 The Dispatcher receives a completion response from all expected AMPs and places the next step
on the BYNET.
• It continues to do this until all the AMP steps associated with a request are done.
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