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Big Data Processing
Unified Batch and Stream Processing
★ 4.5
Distributed Machine Learning
★ 3.6
pip install apache-beampip install mahoutpip install apache-beampip install mahoutPython data engineers use Apache Beam to write portable data pipelines that run locally for testing and deploy to Google Dataflow or Flink in production without code changes. The Python SDK's `PCollection` API chains transforms — `ReadFromBigQuery | Map(transform_fn) | WriteToBigQuery` — enabling the same pipeline logic to handle both batch backfills and live streaming.
Python data engineers interact with Apache Mahout indirectly — Mahout's distributed linear algebra runs on Spark, which Python engineers invoke via PySpark. Mahout's recommendation and clustering algorithms are used in feature engineering pipelines for ML applications where standard scikit-learn algorithms are too slow for the dataset size.
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