Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SOSD: A Benchmark for Learned Indexes   A groundswell of recent work has focused on improving data management systems
with learned components. Specifically, work on learned index structures has
proposed replacing traditional index structures, such as B-trees, with learned
models. Given the decades of research committed to improving index structures,
there is significant skepticism about whether learned indexes actually
outperform state-of-the-art implementations of traditional structures on
real-world data. To answer this question, we propose a new benchmarking
framework that comes with a variety of real-world datasets and baseline
implementations to compare against. We also show preliminary results for
selected index structures, and find that learned models indeed often outperform
state-of-the-art implementations, and are therefore a promising direction for
future research.

10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex