我怎样才能放置更全面的表格？表格是垂直的。我希望它占据整个页面高度，以便所有列都有相同的空间并尊重文本。表格太小了。
代码链接：https://www.overleaf.com/read/sdtpsrdymqrj
代码：
\documentclass{article}
\usepackage[utf8]{inputenc}
\usepackage{amsmath,amsfonts}
\usepackage{algorithmic}
\usepackage{algorithm}
\usepackage{array}
\usepackage[caption=false,font=normalsize,labelfont=sf,textfont=sf]{subfig}
\usepackage{textcomp}
\usepackage{stfloats}
\usepackage{url}
\usepackage{verbatim}
\usepackage{graphicx}
\usepackage{cite}
\hyphenation{op-tical net-works semi-conduc-tor IEEE-Xplore}
% updated with editorial comments 8/9/2021
%\User defined packages
% highlight
\usepackage{color,soul}
\DeclareRobustCommand{\hlc}[1]{{\sethlcolor{lightgray}\hl{#1}}}
% todonotes
\usepackage{todonotes}
% degree symbol
\usepackage{gensymb}
% tables
\usepackage{caption}
\usepackage{csvsimple}
\usepackage{booktabs, tabularx, wrapfig}
\usepackage{array, ltablex, multirow}
\usepackage{placeins}
\usepackage{graphicx}
%\usepackage{subcaption}
\usepackage{float} % added
\usepackage[nonumberlist,nogroupskip]{glossaries}
%------ tables
\usepackage{adjustbox}
\usepackage{rotating}
\usepackage{makecell}
\usepackage{xcolor}
\colorlet{bgodd}{black!10}
\usepackage{tabularray}
\UseTblrLibrary{booktabs}
\usepackage{pdflscape}
%------
\begin{document}
\begin{table}[ht]
\caption{Test}
% from makecell
\settowidth\rotheadsize{\small Monitoring-Based}
\scriptsize
\setlength\tabcolsep{0.1mm} % let LaTeX calculate intercolumn whitespace
\rotatebox{90}{
\begin{tblr}{
colspec = {Q[l, wd=5cm] *{3}{X[c]} *{10}{X[c]}},
vline{2-Y} = {2-Z}{dotted},
vline{2,5} = {2-Z}{solid, \lightrulewidth}, % \lightrulewidth is defined in booktabs
rows = {abovesep=2pt, belowsep=2pt},
row{odd} = {bg=bgodd},
colsep = 2pt,
row{1} = {
font=\bfseries, %\linespread{0.84}\selectfont,
c, m,
},
row{2} = {
cmd=\rotcell,
rowsep=0pt
},
}
\toprule
\SetRow{bg=white}
Paper(s) &
\SetCell[c=3]{c, m} {Data\\ Sources} &&&
\SetCell[c=10]{c, m} Technique &&&&&&&&& \\
\midrule
& Log-based
& Distributed Tracing-based
& Monitoring-Based
& {Unsupervised\\ learning}
& {Supervised\\ learning}
& Reinforcement learning
& Semi-supervised learning
& Hybrid learning
& {Statistical\\ Approach}
& Causal Inference
& {Trace\\ comparison}
& Heart Beating
& SLO checks \\
\midrule
\cite{liu2020unsupervised, pahl2018all, jin2020anomaly, bogatinovski2020self} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{nedelkoski2019anomaly, gan2019leveraging, zhou2019latent} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wang2020workflow, chen2020framework, meng2021detecting} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
\textbullet & % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{li2021microservice} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{chow2014mystery} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{belhadi2021reinforcement} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
\textbullet & % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sharma2013cloudpd, zhang2016taskinsight, xu2018unsupervised, gulenko2018detecting, mariani2018localizing, wu2020microrca, wu2020performance, wang2018cloudranger, vallis2014novel, su2019robust, huang2013lof, bhaduri2011detecting,wang2012workload, lazarevic2003comparative} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sauvanaud2018anomaly, liu2015opprentice, du2018anomaly, mariani2020predicting} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{magalhaes2010detection, peiris2014pad, abdelrahman2016detection, kang2012dapa, yang2007anomaly, wang2013energy, ahad2015toward, nguyen2013fchain, tan2012prepare, gu2009online, samir2019dla} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wu2021causal, chen2014causeinfer, chen2016causeinfer, lin2018microscope} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{shan2019diagnosis} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
\textbullet % SLO checks
\\
\cite{zang2018fault} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
\textbullet & % HeartBeating
% SLO checks
\\
\cite{yagoub2018equipment, brown2018recurrent, nandi2016anomaly, jia2017logsed, fu2009execution, du2017deeplog} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{fronza2013failure, zhang2016automated, zhang2019robust, liang2007failure} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly, yang2021semi, li2021microservice} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{salfner2007using, beschastnikh2014inferring} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{he2020loghub} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\midrule
\end{tblr}
}
{\label{tab:tbl_results}}
\end{table}
\end{document}
谢谢
===== 解决方案 ======
根据@Zarko 的回答，我开发了这个解决方案：
\documentclass{article}
\usepackage{caption}
%------ tables
\usepackage{rotating}
\usepackage{makecell}
\usepackage{xcolor}
\colorlet{bgodd}{black!10}
\usepackage{tabularray}
\UseTblrLibrary{booktabs}
%------
\begin{document}
bla bla bla
\clearpage
\newpage
\clearpage
\newpage
\begin{sidewaystable*}[ht]
\centering
\caption{Papers analyzed in the survey grouped by data sources employed, and techniques used to detect anomalies.}
%\caption{Papers analyzed in the survey grouped by data sources employed, and techniques used to detect anomalies}
% from makecell
\settowidth\rotheadsize{\small Monitoring-Based}
\footnotesize
\setlength\tabcolsep{0.1mm} % let LaTeX calculate intercolumn whitespace
\begin{tblr}{
width=\textheight-3\baselineskip, % <--- added
colspec = {l *{13}{X[c]}},
vline{2-Y} = {2-Z}{dotted},
vline{2,5} = {1-Z}{solid, \lightrulewidth}, % \lightrulewidth is defined in booktabs
colsep = 1pt, % <--- changed
row{1} = {font=\bfseries, c, m},
row{2} = {cmd=\rotcell},
row{odd [3-Y]} = {bg=bgodd}, % <--- changed
}
\toprule
\SetRow{bg=white}
Paper(s) &
\SetCell[c=3]{c, m} {Data\\ Sources} &&&
\SetCell[c=10]{c, m} Technique &&&&&&&&& \\
\midrule
& Log-based
& Distributed Tracing-based
& Monitoring-Based
& {Unsupervised\\ learning}
& {Supervised\\ learning}
& Reinforcement learning
& Semi-supervised learning
& Hybrid learning
& {Statistical\\ Approach}
& Causal Inference
& {Trace\\ comparison}
& Heart Beating
& SLO checks \\
\midrule
\cite{liu2020unsupervised, pahl2018all, jin2020anomaly, bogatinovski2020self} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{nedelkoski2019anomaly, gan2019leveraging, zhou2019latent} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wang2020workflow, chen2020framework, meng2021detecting} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
\textbullet & % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{li2021microservice} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{chow2014mystery} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{belhadi2021reinforcement} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
\textbullet & % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sharma2013cloudpd, zhang2016taskinsight, xu2018unsupervised, gulenko2018detecting, mariani2018localizing, wu2020microrca, wu2020performance, wang2018cloudranger, vallis2014novel, su2019robust, huang2013lof, bhaduri2011detecting,wang2012workload, lazarevic2003comparative} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sauvanaud2018anomaly, liu2015opprentice, du2018anomaly, mariani2020predicting} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{magalhaes2010detection, peiris2014pad, abdelrahman2016detection, kang2012dapa, yang2007anomaly, wang2013energy, ahad2015toward, nguyen2013fchain, tan2012prepare, gu2009online, samir2019dla} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wu2021causal, chen2014causeinfer, chen2016causeinfer, lin2018microscope} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{shan2019diagnosis} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
\textbullet % SLO checks
\\
\cite{zang2018fault} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
\textbullet & % HeartBeating
% SLO checks
\\
\cite{yagoub2018equipment, brown2018recurrent, nandi2016anomaly, jia2017logsed, fu2009execution, du2017deeplog} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{fronza2013failure, zhang2016automated, zhang2019robust, liang2007failure} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly, yang2021semi, li2021microservice} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{salfner2007using, beschastnikh2014inferring} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{he2020loghub} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\midrule
\end{tblr}
{\label{tab:tbl_results}}
\end{sidewaystable*}
\clearpage
\newpage
bla bla
\end{document}
答案1
像这样吗？
- 表格放在横向页面中，因此表格的宽度等于
\textheight - 在这种情况下，表格标题与表格对齐，我认为标题的正确位置是什么
梅威瑟：
\documentclass{article}
\usepackage{caption}
%------ tables
\usepackage{rotating}
\usepackage{makecell}
\usepackage{xcolor}
\colorlet{bgodd}{black!10}
\usepackage{tabularray}
\UseTblrLibrary{booktabs}
\usepackage{pdflscape}
%------
\begin{document}
\begin{landscape}
\begin{table}[ht]
\caption{Test}
\label{tab:tbl_results}
\settowidth\rotheadsize{\small Monitoring-Based} % from makecell
\begin{tblr}{
colspec = {l *{13}{X[c]}},
vline{2-Y} = {2-Z}{dotted},
vline{2,5} = {1-Z}{solid, \lightrulewidth}, % \lightrulewidth is defined in booktabs
colsep = 2pt,
row{1} = {font=\bfseries, c, m},
row{2} = {cmd=\rotcell},
row{odd [3-Y]} = {bg=bgodd}, % <--- changed
\toprule
Paper(s) &
\SetCell[c=3]{c, m} {Data\\ Sources} &&&
\SetCell[c=10]{c, m} Technique &&&&&&&&& \\
\midrule
& Log-based
& Distributed Tracing-based
& Monitoring-Based
& {Unsupervised\\ learning}
& {Supervised\\ learning}
& Reinforcement learning
& Semi-supervised learning
& Hybrid learning
& {Statistical\\ Approach}
& Causal Inference
& {Trace\\ comparison}
& Heart Beating
& SLO checks \\
\midrule
\cite{liu2020unsupervised, pahl2018all, jin2020anomaly, bogatinovski2020self} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{nedelkoski2019anomaly, gan2019leveraging, zhou2019latent} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wang2020workflow, chen2020framework, meng2021detecting} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
\textbullet & % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{li2021microservice} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{chow2014mystery} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{belhadi2021reinforcement} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
\textbullet & % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sharma2013cloudpd, zhang2016taskinsight, xu2018unsupervised, gulenko2018detecting, mariani2018localizing, wu2020microrca, wu2020performance, wang2018cloudranger, vallis2014novel, su2019robust, huang2013lof, bhaduri2011detecting,wang2012workload, lazarevic2003comparative} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sauvanaud2018anomaly, liu2015opprentice, du2018anomaly, mariani2020predicting} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{magalhaes2010detection, peiris2014pad, abdelrahman2016detection, kang2012dapa, yang2007anomaly, wang2013energy, ahad2015toward, nguyen2013fchain, tan2012prepare, gu2009online, samir2019dla} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wu2021causal, chen2014causeinfer, chen2016causeinfer, lin2018microscope} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{shan2019diagnosis} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
\textbullet % SLO checks
\\
\cite{zang2018fault} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
\textbullet & % HeartBeating
% SLO checks
\\
\cite{yagoub2018equipment, brown2018recurrent, nandi2016anomaly, jia2017logsed, fu2009execution, du2017deeplog} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{fronza2013failure, zhang2016automated, zhang2019robust, liang2007failure} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly, yang2021semi, li2021microservice} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{salfner2007using, beschastnikh2014inferring} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{he2020loghub} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\bottomrule
\end{tblr}
\end{table}
\end{landscape}
\end{document}
附录（1）：
- 如果你喜欢只旋转表格并将其标题留在页面顶部，则应该定义表格的宽度
- 在这种情况下，它是关于
\textwidth- 标题空间（参见下面的 MWE）：
\documentclass{article}
\usepackage{caption}
%------ tables
\usepackage{rotating}
\usepackage{makecell}
\usepackage{xcolor}
\colorlet{bgodd}{black!10}
\usepackage{tabularray}
\UseTblrLibrary{booktabs}
%------
\begin{document}
\begin{table}[ht]
\caption{Test}
\label{tab:tbl_results}
\settowidth\rotheadsize{\small Monitoring-Based} % from makecell
\rotatebox{90}{
\begin{tblr}{width=\textheight-3\baselineskip, % <--- added
colspec = {l *{13}{X[c]}},
vline{2-Y} = {2-Z}{dotted},
vline{2,5} = {1-Z}{solid, \lightrulewidth}, % \lightrulewidth is defined in booktabs
colsep = 1pt, % <--- changed
row{1} = {font=\bfseries, c, m},
row{2} = {cmd=\rotcell},
row{odd [3-Y]} = {bg=bgodd}, % <--- changed
}
\toprule
Paper(s) & \SetCell[c=3]{c} {Data\\ Sources}
&&& \SetCell[c=10]{c, m} Technique
&&&&&&&&& \\
\midrule
& Log-based
& Distributed Tracing-based
& Monitoring-Based
& {Unsupervised\\ learning}
& {Supervised\\ learning}
& Reinforcement learning
& Semi-supervised learning
& Hybrid learning
& {Statistical\\ Approach}
& Causal Inference
& {Trace\\ comparison}
& Heart Beating
& SLO checks \\
\midrule
\cite{liu2020unsupervised, pahl2018all, jin2020anomaly, bogatinovski2020self} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{nedelkoski2019anomaly, gan2019leveraging, zhou2019latent} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wang2020workflow, chen2020framework, meng2021detecting} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
\textbullet & % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{li2021microservice} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{chow2014mystery} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{belhadi2021reinforcement} &
& % Log-based
\textbullet & % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
\textbullet & % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sharma2013cloudpd, zhang2016taskinsight, xu2018unsupervised, gulenko2018detecting, mariani2018localizing, wu2020microrca, wu2020performance, wang2018cloudranger, vallis2014novel, su2019robust, huang2013lof, bhaduri2011detecting,wang2012workload, lazarevic2003comparative} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{sauvanaud2018anomaly, liu2015opprentice, du2018anomaly, mariani2020predicting} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{magalhaes2010detection, peiris2014pad, abdelrahman2016detection, kang2012dapa, yang2007anomaly, wang2013energy, ahad2015toward, nguyen2013fchain, tan2012prepare, gu2009online, samir2019dla} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{wu2021causal, chen2014causeinfer, chen2016causeinfer, lin2018microscope} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
\textbullet & % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{shan2019diagnosis} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
\textbullet % SLO checks
\\
\cite{zang2018fault} &
& % Log-based
& % Distributed Tracing-based
\textbullet & % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
\textbullet & % HeartBeating
% SLO checks
\\
\cite{yagoub2018equipment, brown2018recurrent, nandi2016anomaly, jia2017logsed, fu2009execution, du2017deeplog} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
\textbullet & % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{fronza2013failure, zhang2016automated, zhang2019robust, liang2007failure} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
\textbullet & % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{meng2019loganomaly, yang2021semi, li2021microservice} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
\textbullet & % Semi-supervised learning
& % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{salfner2007using, beschastnikh2014inferring} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
& % Hybrid learning
\textbullet & % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\cite{he2020loghub} &
\textbullet & % Log-based
& % Distributed Tracing-based
& % Monitoring-Based
& % Unsupervised learning
& % Supervised learning
& % Reinforcement learning
& % Semi-supervised learning
\textbullet & % Hybrid learning
& % Statistical Approach
& % Causal Inference
& % Trace comparison
& % HeartBeating
% SLO checks
\\
\bottomrule
\end{tblr}
}
\end{table}
\end{document}
附录（2）：
- 为了讲究，第二个解决方案也改变了表格的方向
- 对于真正纵向的表格，它不应该是定向的，而应该减少第一列的宽度，也许还应该减少其他列中文本的行距。例如，正如在下一个 MWE 中所做的那样：
\documentclass{article}
\usepackage{caption}
%------ tables
\usepackage{rotating}
\usepackage{makecell}
\usepackage{xcolor}
\colorlet{bgodd}{black!10}
\usepackage{tabularray}
\UseTblrLibrary{booktabs}
%------
\begin{document}
\begin{table}[ht]
\caption{Test}
\label{tab:tbl_results}
\small
\settowidth\rotheadsize{Monitoring-Based} % from makecell
\begin{tblr}{
colspec = {X[2,l,m] *{13}{X[c, font=\linespread{0.84}\selectfont]}},
vline{2-Y} = {2-Z}{dotted},
vline{2,5} = {1-Z}{solid, \lightrulewidth}, % \lightrulewidth is defined in booktabs
colsep = 1pt, % <--- changed
row{1} = {font=\bfseries, c, m},
row{2} = {cmd=\rotcell},
row{odd [3-Y]} = {bg=bgodd}, % <--- changed
}
%%% table body is the same as at previous examples
\bottomrule
\end{tblr}
\end{table}
\end{document}
