TabularPreprocessing

Tabular data preprocessing step

SageMaker step type	Processing
Node type	internal (consumes upstream, produces downstream)
Container entry point	tabular_preprocessing.py
Interface file	steps/interfaces/tabular_preprocessing.step.yaml

Compute

Compute kind	sklearn

Functionality

Tabular preprocessing script that combines data shards, loads column signature, cleans/processes label field, splits data into train/test/val, and outputs in configurable format (CSV/TSV/Parquet). Supports streaming mode for large datasets.

Inputs (dependencies)

Input	Type	Required	Compatible producers
DATA	processing_output	yes	CradleDataLoading, DummyDataLoading, RedshiftDataLoading, DataLoad, ProcessingStep, BedrockProcessing, StratifiedSampling
DATA_SECONDARY	processing_output	no	CradleDataLoading, DummyDataLoading, RedshiftDataLoading, DataLoad, ProcessingStep, BedrockProcessing, StratifiedSampling
SIGNATURE	processing_output	no	CradleDataLoading, DummyDataLoading

Outputs

Output	Type
processed_data	processing_output

Consumers (downstream steps)

Steps that declare this step as a compatible input source:

• BatchTransform

• BedrockBatchProcessing

• BedrockProcessing

• CurrencyConversion

• DataUploading

• EdxUploading

• FeatureSelection

• GraphSubgraphExtraction

• LabelRulesetExecution

• LightGBMMTModelEval

• LightGBMMTModelInference

• LightGBMMTTraining

• LightGBMModelEval

• LightGBMModelInference

• LightGBMTraining

• MissingValueImputation

• ModelMetricsComputation

• PiperMetricGeneration

• PseudoLabelMerge

• PyTorchModelEval

• PyTorchModelInference

• PyTorchTraining

• RiskTableMapping

• SOPAInstructionTuning

• SlipboxKnowledgeRouting

• StratifiedSampling

• TSAModelCalibration

• TSAModelEval

• TSAPreprocessing

• TSATraining

• TemporalSequenceNormalization

• TokenizerTraining

• XGBoostModelEval

• XGBoostModelInference

• XGBoostTraining

• XgboostMtModelEval

• XgboostMtTraining

Framework requirements

Package	Version
pandas	>=1.3.0
numpy	>=1.21.0
scikit-learn	>=1.0.0

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