MLTransform One-Hot Encoding Performance

Pipeline: MLTransform One-Hot Encoding for Categorical Features Type: Batch only Host: 50 × n1-standard-2 (2 vCPUs, 7.5 GB RAM)

The following graphs show various metrics when running the MLTransform One-Hot Encoding pipeline using Apache Beam’s MLTransform TFT integration. See the glossary for definitions.

Full pipeline implementation is available here.

What is the estimated cost to run the pipeline?

RunTime and EstimatedCost

How has various metrics changed when running the pipeline for different Beam SDK versions?

AvgThroughputBytesPerSec by Version

AvgThroughputElementsPerSec by Version

How has various metrics changed over time when running the pipeline?

AvgThroughputBytesPerSec by Date

AvgThroughputElementsPerSec by Date