Fast Data Processing Matters
In an age where data is a key to success, the ability to rapidly interpret and make sense of large volumes of information can set a business apart. Alteryx, recognized as a powerful data blending tool known for its analytics capabilities, offers the Alteryx Multi-threaded Processing (AMP) Engine to boost efficiency and speed like never before.
Here, I’ll outline what the AMP engine is and how it differs from the original engine. You can also download a video with insights and workflows: Link to the Alteryx AMP Engine Materials
What is Alteryx Engine?
The Alteryx Engine acts as a processor, handling each record within a workflow. Users have the option to select either the original engine (E1) or the AMP engine.
What is E1?
The original Alteryx engine (E1) handles data processing tasks sequentially, one after another, which can be time-consuming and inefficient.
What is AMP?
Imagine owning the fastest car in the data processing world – that’s the Alteryx Multi-threaded Processing (AMP) engine. It works by processing your data in parallel segments. AMP has been available since version 20.2 and became the default engine as of version 22.1.
Why is This Important?
Remember a time when your computer was running slowly? Frustrating, isn’t it? Now, imagine your data tasks completing three times faster. That’s the power of the AMP Engine. Optimized for computers with multiple cores and threads, it transforms heavy data processing into swift, effortless work.
When Should You Expect Quicker Outcomes?
The AMP Engine is highly effective when processing large datasets on high-powered machines, especially in cases requiring quick data transformation and integration. However, since AMP isn’t yet supported by all Alteryx tools, it’s important to verify tool compatibility before making the switch.
Output Differences
Some tools might produce records in a different sequence when a workflow is run with the AMP engine versus the original engine. Listed below are the tools impacted by this change.
It Can Be Up to 3 Times Faster with the AMP Engine
Our tests suggest that in some instances, AMP can execute workflows up to three times faster than the original engine in specific scenarios. This improvement can be a significant benefit for businesses that handle large volumes of data on a regular basis. Imagine reducing a three-hour task to just one – that’s the efficiency AMP brings.
When is the AMP Engine most efficient, and when does it work slower?
1.Prep & Blend Activities
In the E1 engine, the Sort & Join tools operate as single-threaded processes during the final merge, meaning that on a machine with 8 logical processors, only one processor is engaged (resulting in 12.5% CPU utilization). However, with the AMP engine, the Sort & Join tools can leverage all 8 logical processors, achieving 100% CPU utilization.
2.Spatial Analysis
The Spatial Info tool has been completely converted, offering the advantage of multi-threaded execution. The Find Nearest tool, on the other hand, is partially converted, as it still relies on the original E1 engine for distance calculations.
3.Predictive Analysis
For workflows involving predictive tools, the execution time remained identical for both the E1 and AMP engines, as these tools have not been converted to run on the AMP engine. A significant amount of time can be consumed by R processes, which are externally launched and executed outside the engine’s control.
So, when AMP and when E1?
In most standard preparation, blending, and analysis tasks within Alteryx, AMP delivers better performance than E1, offering improvements even in workflows that mix converted and non-converted tools. However, for tasks outside AMP’s range – such as those involving R or Python processes – or for workflows with unconverted tools, E1 is the recommended option.
In some instances, such as when using Multi-Row Formula tools or specific Spatial workflows, AMP may run slower and require adjustments to function optimally. AMP’s benefits are more noticeable with larger datasets. For smaller data sizes or on lower-powered hardware, it’s advisable to use E1 instead.
How to Check if You Are Using the AMP Engine?
To verify, look in the Results window for the message: This is AMP Engine.
Requirements
- The AMP engine requires a minimum of 400 MB of memory per workflow thread to operate.
- The original engine needs at least 64 MB to execute a workflow. 63 MB produces an error.
- The default memory usage for AMP is 25% of the machine’s available memory.
A Few Important Facts to Remember
AMP Engine – Performance on the Alteryx Server
While the AMP engine processes workflows at a higher speed, it has a limitation: fewer workflows can be run simultaneously on the Server compared to the original engine (E1). This limitation poses a challenge for maximizing server efficiency. A possible workaround is to use AMP for developing and testing workflows, then switch to E1 when deploying them to the Alteryx Server.
This strategy allows for a greater number of workflows to run in parallel on the Server, enhancing resource utilization and boosting overall performance.
Conclusion: Don’t Get Left Behind
In the highly competitive field of data analytics, achieving greater speed, insight, and efficiency can be a game-changer. The Alteryx AMP Engine boosts your data processing capabilities. Don’t forget, you can download our AMP Engine Materials here.
