Sequential File vs Dataset (DataStage)

 

Sequential File vs Dataset (DataStage)

Feature	Sequential File	Dataset
Type	Flat file (text)	DataStage internal file
Readability	Human-readable	Binary (not readable)
Usage	External data exchange	Internal processing
Performance	Slower	Faster
Parallelism	Limited	Fully parallel
Indexing	No	Optimized internally
Partition aware	No	Yes
Schema	Defined manually	Stored automatically
File extension	.txt, .csv, .dat	.ds
Storage	OS file system	DataStage managed
Best for	Source/Target	Staging / Intermediate

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🔹 Sequential File

               Used when:

·        Reading data from external systems

·        Delivering files to business or downstream apps

·        Interfaces (banking, insurance, ecommerce)

 Limitations:

·        Slower I/O

·        Metadata mismatch errors common

·        Parallel jobs create multiple part files

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🔹 Dataset

✔ Used when:

• Passing data between parallel jobs
• Staging large volumes
• Improving performance

 Advantages:

• Stored in parallel format
• No delimiter / schema mismatch issues
• Automatically manages partitioning

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🔹 Real Project Example

Bad Design ❌

Seq File → Transformer → Seq File → Transformer → Target

(Performance issue)

Good Design ✅

Seq File → Transformer → Dataset → Transformer → Target

(Faster, scalable)

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Sequential File is a flat file used to exchange data with external systems, while Dataset is an internal DataStage file optimized for parallel processing and high performance.

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🔹 When to Choose Which?

Scenario	Use
Source / Target	Sequential File
Intermediate stage	Dataset
Performance tuning	Dataset
Debugging / validation	Sequential File

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