Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Case for Learned Spatial Indexes   Spatial data is ubiquitous. Massive amounts of data are generated every day
from billions of GPS-enabled devices such as cell phones, cars, sensors, and
various consumer-based applications such as Uber, Tinder, location-tagged posts
in Facebook, Twitter, Instagram, etc. This exponential growth in spatial data
has led the research community to focus on building systems and applications
that can process spatial data efficiently. In the meantime, recent research has
introduced learned index structures. In this work, we use techniques proposed
from a state-of-the art learned multi-dimensional index structure (namely,
Flood) and apply them to five classical multi-dimensional indexes to be able to
answer spatial range queries. By tuning each partitioning technique for optimal
performance, we show that (i) machine learned search within a partition is
faster by 11.79\% to 39.51\% than binary search when using filtering on one
dimension, (ii) the bottleneck for tree structures is index lookup, which could
potentially be improved by linearizing the indexed partitions (iii) filtering
on one dimension and refining using machine learned indexes is 1.23x to 1.83x
times faster than closest competitor which filters on two dimensions, and (iv)
learned indexes can have a significant impact on the performance of low
selectivity queries while being less effective under higher selectivities.

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The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
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The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
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The categories of this paper are: q-alg
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The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
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The categories of this paper are: stat
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The categories of this paper are: solv-int
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-ex
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The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: supr-con
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The categories of this paper are: ao-sci
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The categories of this paper are: patt-sol