Tackling Duplicate Data in StreamSets Pipelines with JDBC Origins
Gordon Burns
Strategic Consulting Manager | Transforms data challenges into solutions | Data Project Delivery Expert | Award-winning Data Professional | Data-Driven Decision Maker
Data and ELT processes are more common than ever and tools such as StreamSets are at the forefront. With that in mind I wanted to talk about a common hiccup: duplicate data in pipelines pulling from JDBC sources. Let's look at why this happens and how to fix it using pipeline finishers.
How Duplicate Data Sneaks In
Imagine you're handling a StreamSets pipeline, grabbing data from a JDBC source like an oracle database. The problem? You're not using pipeline finishers, and all of a sudden duplicate data creeps in. Here's why:
- Data Timing Confusion: Streams flow non-stop. Without pipeline finishers, your pipeline might lose track of processed data, fetching it multiple times and at times causing the pipeline to run indefinitely.
- Missing Checkpoints: Pipeline finishers set checkpoints to remember where the process left off.
- No De-duplication logic: Pipeline finishers can weed out duplicates. Without this logic, all data gets processed, including repeats.
- Incomplete Data: Crashes or glitches may mean partial data processing. A finisher helps restart from the last checkpoint, not the beginning.
- Database Surprises: Source databases may change mid-process, causing data disruption and duplicates.
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How to solve Duplicate Data with Pipeline Finishers
To get rid of duplicate data in your JDBC-driven StreamSets pipeline, pipeline finishers are your superheroes:
- Stay in Control: Finishers keep tabs on data processing, marking checkpoints to avoid duplicates.
- Handle Errors Smoothly: Configure finishers to manage errors gracefully, ensuring no data gets duplicated or lost.
- De-duplication Magic : Implement de-duplication logic in your finisher to process only unique records.
- Quick Recovery: When hiccups happen, the finisher helps resume from where you left off, not square one.
In a nutshell, don't let duplicate data slow you down. Supercharge your data pipelines with pipeline finishers—they'll keep things clean, efficient, and headache-free!