Optimal partition count factors: (1) Data size—target 100MB–1GB per partition to avoid small files. (2) Query patterns—partition by filter columns (date, region). (3) Parallelism—partitions = parallelism in Spark; balance with overhead. (4) File count—too many partitions = small files, Namenode pressure (HDFS). (5) Skew—avoid high-cardinality columns that cause imbalance. Rule of thumb: num_partitions ≈ sqrt(data_size_GB) or match core count for single job....
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