Handling a 25,000 x 25,000 matrix multiplication in Qlik is quite challenging due to the limitations in memory and computational power typically required for such large matrix operations. Qlik is primarily designed for data visualization, analysis, and business intelligence, and while it can handle complex calculations, matrix operations at this scale are beyond its usual capabilities.
Memory Usage: A 25,000 x 25,000 matrix would contain 625 million elements. Qlik’s in-memory processing model might struggle with this, especially when multiplying two such large matrices, as this would require significant memory and computational resources. Performance: Even if it were technically possible to load such large matrices, the performance would be extremely slow, potentially freezing or crashing the system.
If you need to perform such large matrix multiplications, consider the use external tools that are optimized for handling large matrix operations, then import the results back into Qlik for further analysis and visualization:
Python’s NumPy library is highly efficient for large-scale matrix operations.
" import numpy as np
# Create two large matrices A = np.random.rand(25000, 25000) B = np.random.rand(25000, 25000)
# Perform matrix multiplication result = np.dot(A, B) "
After completing the matrix multiplication in Python, you can export the result and load it into Qlik for visualization.
