Results for “partitioning”

4 skills

Design reliable, scalable, and maintainable data systems by applying principles from storage engines, replication, partitioning, transactions, and consistency models.

More results

Scales pandas and NumPy workflows to datasets larger than memory using parallel and distributed computing, with support for dataframes, arrays, bags, and custom task graphs.

162-use-e70e84f3

Provides guidance on using Apache Spark RDDs, including creation, transformations, actions, and performance considerations.

cupynumeric-parallel-data-load

Load sharded datasets (npy, Parquet, HDF5, raw binary) into distributed cuPyNumeric arrays using manual partitioning and Legate task launches.