Merging Data and Moving Average | Dataford Interview Questions

A Booz Allen Hamilton AI Studio pipeline receives two unsorted datasets containing measurements for the same feature. Write a function that merges records with matching timestamps by averaging their feature values, then calculates a trailing moving average over the merged measurements.

Formal Specification

Implement merge_and_moving_average(dataset_a, dataset_b, feature, window).

dataset_a and dataset_b are lists of dictionaries. Each dictionary contains an integer timestamp and the requested numeric feature.
Timestamps are unique within each dataset, but may occur in both datasets.
For a timestamp present in both datasets, first average the two feature values.
Return a list of dictionaries sorted by ascending timestamp. Each result must contain the timestamp and moving_average.
The moving average for position i uses the current merged value and up to window - 1 immediately preceding merged values. Near the beginning, use all available values.

Constraints

1 <= len(dataset_a) + len(dataset_b) <= 200,000
1 <= window <= len(dataset_a) + len(dataset_b)
Timestamps are integers in [-10^9, 10^9]
Feature values are finite integers or floating-point numbers
Every record contains the requested feature

Function Signature

def merge_and_moving_average(dataset_a, dataset_b, feature, window):

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