Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimation from Partially Sampled Distributed Traces   Sampling is often a necessary evil to reduce the processing and storage costs
of distributed tracing. In this work, we describe a scalable and adaptive
sampling approach that can preserve events of interest better than the widely
used head-based sampling approach. Sampling rates can be chosen individually
and independently for every span, allowing to take span attributes and local
resource constraints into account. The resulting traces are often only
partially and not completely sampled which complicates statistical analysis. To
exploit the given information, an unbiased estimation algorithm is presented.
Even though it does not need to know whether the traces are complete, it
reduces the estimation error in many cases compared to considering only
complete traces.

6
The categories of this paper are: astro-ph
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
33
The categories of this paper are: plasm-ph
31
The categories of this paper are: ao-sci
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga