Features of Data Stage
- Any to Any
- Platform Independent
- Node Configuration
- Portion Parallelism
- Pipeline Parallelism
Any to Any
Reads the data from any Source and loads it to any Target.
Any SRC ↔ Any Target
Platform Independent
Designed for one O.S, can be executed
– – >Platform generally can be either Software or Hardware.
- – > In the Data stage, Platform is w. r. t Hardware.
Hardware environment
- Uni processing Environment
Hard disk à CPU – – > RAM
- Symmetric Multi-Processing: – (SMP)
can have 32–64 CPU that is Hard disk with multiple CPU‘S
Massively Parallel processing:- (MPP)
- Collection of different SMPS
Node Configuration
- The best feature of the Data stage
- It is a technique of creating logical CPUs
Node – – > logical CPU (or) instance of (physical) CPU
àIt is an S/W which will Create virtual CPU’S
- Data Stage is Executed on logical CPU’S
- TO run a job in the Data stage, WE require at least 1 Node.
EX:- ETL
UNI Process
Hard disk – – > CPU – – > RAM
- To access 1000 records, it takes 10 mins.
SMP 
- To access 1000 records, with 4 CPU’S it takes 2.5 min
Node config:
- Uni Processing – – > Virtual SMF
S is not using the max. capabilities of CPU, So Node config. is an S/W Which drives into different Nodes. That is Boost up the Capabilities & Energy level of CPU
Partition parallelism
– – > Horizontal Combining
– – > Combining primary rows with Secondary rows w. r. t Key column values
Pipeline Parallelism
Simultaneously doing the extraction of Transforming and loading jobs.