Slowly Changing Dimensions (SCD) with Spark
Slowly Changing Dimensions (SCDs) are a fundamental pattern in data warehousing that addresses a simple but critical question: what happens when your reference data changes over time?
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NumPy - Expand Dimensions (np.expand_dims, np.newaxis)
• np.expand_dims() and np.newaxis both add dimensions to arrays, but np.newaxis offers more flexibility for complex indexing while np.expand_dims() provides clearer intent in code
NumPy - Array Shape and Dimensions (shape, ndim, size)
NumPy arrays are n-dimensional containers with well-defined dimensional properties. Every array has a shape that describes its structure along each axis. The ndim attribute tells you how many…