PySpark
PySpark vs Dask: what are the key differences for large dataset processing?
Answer:
PySpark is preferred for robust distribution and high scalability when managing very large datasets across clusters. Dask, while efficient for parallel computing, offers greater flexibility and native integration with Python data libraries, making it well suited to custom Python workflows but less scalable.
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