{'fraction_non_alphanumeric': 0.011152416356877323, 'fraction_numerical': 0.0, 'mean_word_length': 5.195402298850575, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Towards an analysis of range query performance in spatial data structures

In this paper, we motivate four different user defined window query classes and derive a probabilistic model for each of them. For each model, we characterize the efficiency of spatial data structures in terms of the expected number of data bucket accesses needed to perform a window query. Our analytical approach exhibits the performance phenomena independent of data structure and implementation details and whether the objects are points or non-point objects.