DP in Data Engineering

Concepts: pyDPDataEng, pyEditDistance, pyPartitioning

DP is not just for LeetCode. Data engineering is full of optimization problems with overlapping subproblems. If you can connect a DP problem to a real system in the interview, you move from 'strong algorithm' to 'strong DE judgment.' Here are four real applications that come up in senior DE interviews and system design discussions. Optimal Dataset Partitioning for Load Balancing You have n data files of varying sizes. You want to split them into K partitions for parallel processing, minimizing the maximum partition size (minimizing the bottleneck). This is the classic 'painter's partition problem,' a well-known DP problem. dp[i][j] = minimum possible maximum partition size when partitioning the first i files into j partitions. The recurrence iterates over where to split the last partition.