How does PCA scale in distributed systems and big data pipelines?

PCA scales using distributed matrix factorization or incremental approaches.

In large-scale systems, PCA is implemented using distributed computing frameworks. Data is partitioned across nodes, partial covariance or SVD computations are aggregated, or incremental PCA is used to process streaming batches. This avoids memory bottlenecks.