Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Combining Aggregation and Sampling (Nearly) Optimally for Approximate
  Query Processing   Sample-based approximate query processing (AQP) suffers from many pitfalls
such as the inability to answer very selective queries and unreliable
confidence intervals when sample sizes are small. Recent research presented an
intriguing solution of combining materialized, pre-computed aggregates with
sampling for accurate and more reliable AQP. We explore this solution in detail
in this work and propose an AQP physical design called PASS, or
Precomputation-Assisted Stratified Sampling. PASS builds a tree of partial
aggregates that cover different partitions of the dataset. The leaf nodes of
this tree form the strata for stratified samples. Aggregate queries whose
predicates align with the partitions (or unions of partitions) are exactly
answered with a depth-first search, and any partial overlaps are approximated
with the stratified samples. We propose an algorithm for optimally partitioning
the data into such a data structure with various practical approximation
techniques.

29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
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The categories of this paper are: alg-geom
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
20
The categories of this paper are: acc-phys
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga