From 03e3a1bd153bf7c3bf13216964fb17463a26aaae Mon Sep 17 00:00:00 2001 From: Mendes Date: Mon, 18 Jul 2022 22:35:29 +0200 Subject: Added the latex report on the optimal layout algorithm --- doc/optimal_layout_report/figures/flow.pdf | Bin 0 -> 12947 bytes doc/optimal_layout_report/figures/flow.svg | 2205 +++++++++++ doc/optimal_layout_report/figures/mini_node.pdf | Bin 0 -> 18288 bytes doc/optimal_layout_report/figures/mini_node.svg | 3962 ++++++++++++++++++++ doc/optimal_layout_report/figures/mini_zone.pdf | Bin 0 -> 7446 bytes doc/optimal_layout_report/figures/mini_zone.svg | 1562 ++++++++ doc/optimal_layout_report/figures/naive.pdf | Bin 0 -> 18347 bytes doc/optimal_layout_report/figures/naive.svg | 3899 +++++++++++++++++++ doc/optimal_layout_report/optimal_layout.aux | 32 + doc/optimal_layout_report/optimal_layout.log | 303 ++ doc/optimal_layout_report/optimal_layout.pdf | Bin 0 -> 279062 bytes .../optimal_layout.synctex.gz | Bin 0 -> 84542 bytes 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a/doc/optimal_layout_report/optimal_layout.tex b/doc/optimal_layout_report/optimal_layout.tex new file mode 100644 index 00000000..843e0be6 --- /dev/null +++ b/doc/optimal_layout_report/optimal_layout.tex @@ -0,0 +1,394 @@ +\documentclass[]{article} + +\usepackage{amsmath,amssymb} + +\usepackage{graphicx,xcolor} + +\usepackage{algorithm,algpseudocode,float} + +\renewcommand\thesubsubsection{\Alph{subsubsection})} + +%opening +\title{Optimal partition assignment in Garage} +\author{Mendes Oulamara} + +\begin{document} + +\maketitle + +\section{Introduction} + +\subsection{Context} + +Garage is an open-source distributed storage service blablabla$\dots$ + +Every object to be stored in the system falls in a partition given by the last $k$ bits of its hash. There are $N=2^k$ partitions. Every partition will be stored on distinct nodes of the system. The goal of the assignment of partitions to nodes is to ensure (nodes and zone) redundancy and to be as efficient as possible. + +\subsection{Formal description of the problem} + +We are given a set of nodes $V$ and a set of zones $Z$. Every node $v$ has a non-negative storage capacity $c_v\ge 0$ and belongs to a zone $z_v\in Z$. We are also given a number of partition $N>0$ (typically $N=256$). + +We would like to compute an assignment of three nodes to every partition. That is, for every $1\le i\le N$, we compute a triplet of three distinct nodes $T_i=(T_i^1, T_i^2, T_i^3) \in V^3$. We will impose some redundancy constraints to this assignment, and under these constraints, we want our system to have the largest storage capacity possible. To link storage capacity to partition assignment, we make the following assumption: +\begin{equation} + \tag{H1} + \text{\emph{All partitions have the same size $s$.}} +\end{equation} +This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored large objects. + +Every node $v$ needs to store $n_v = \#\{ 1\le i\le N ~|~ v\in T_i \}$ partitions (where $\#$ denots the number of indices in the set). Hence the partitions stored by $v$ (and hence all partitions by our assumption) have there size bounded by $c_v/n_v$. This remark leads us to define the optimal size that we will want to maximize: + +\begin{equation} + \label{eq:optimal} + \tag{OPT} +s^* = \min_{v \in V} \frac{c_v}{n_v}. +\end{equation} + +When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption: +\begin{equation} + \tag{H2} + \text{\emph{Updates of capacity happens rarely relatively to object storing.}} +\end{equation} +This assumption justifies that when we compute the new assignment, it is worth to optimize the partition size \eqref{eq:optimal} first, and then, among the possible optimal solution, to try to minimize the number of partition transfers. + +For now, in the following, we ask the following redundancy constraint: + +\textbf{Mode 3-strict:} every partition needs to be assignated to three nodes belonging to three different zones. + +\section{Properties of an optimal 3-strict assignment} + +\subsection{Optimal assignment} +\label{sec:opt_assign} + +For every zone $z\in Z$, define the zone capacity $c_z = \sum_{v, z_v=z} c_v$ and define $C = \sum_v c_v = \sum_z c_z$. + +One can check that the best we could be doing to maximize $s^*$ would be to use the nodes proportionally to their capacity. This would yield $s^*=C/(3N)$. This is not possible because of (i) redundancy constraints and (ii) integer rounding but it gives and upper bound. + +\subsubsection*{Optimal utilization} + +We call an \emph{utilization} a collection of non-negative integers $(n_v)_{v\in V}$ such that $\sum_v n_v = 3N$ and for every zone $z$, $\sum_{v\in z} n_v \le N$. We call such utilization \emph{optimal} if it maximizes $s^*$. + +We start by computing a node sub-utilization $(\hat{n}_v)_{v\in V}$ such that for every zone $z$, $\sum_{v\in z} \hat{n}_v \le N$ and we show that there is an optimal utilization respecting the constraints and such that $\hat{n}_v \le n_v$ for every node. + +Assume that there is a zone $z_0$ such that $c_{z_0}/C \ge 1/3$. Then for any $v\in z_0$, we define +$$\hat{n}_v = \left\lfloor\frac{c_v}{c_{z_0}}N\right\rfloor.$$ +This choice ensures for any such $v$ that +$$ +\frac{c_v}{\hat{n}_v} \ge \frac{c_{z_0}}{N} \ge \frac{C}{3N} +$$ +which is the universal upper bound on $s^*$. Hence any optimal utilization $(n_v)$ can be modified to another optimal utilization such that $n_v\ge \hat{n}_v$ + +Because $z_0$ cannot store more than $N$ partition occurences, in any assignment, at least $2N$ partitions must be assignated to the zones $Z\setminus\{z_0\}$. Let $C_0 = C-c_{z_0}$. Suppose that there exists a zone $z_1\neq z_0$ such that $c_{z_1}/C_0 \ge 1/2$. Then, with the same argument as for $z_0$, we can define +$$\hat{n}_v = \left\lfloor\frac{c_v}{c_{z_1}}N\right\rfloor$$ +for every $v\in z_1$. + +Now we can assign the remaining partitions. Let $(\hat{N}, \hat{C})$ to be +\begin{itemize} + \item $(3N,C)$ if we did not find any $z_0$; + \item $(2N,C-c_{z_0})$ if there was a $z_0$ but no $z_1$; + \item $(N,C-c_{z_0}-c_{z_1})$ if there was a $z_0$ and a $z_1$. +\end{itemize} +Then at least $\hat{N}$ partitions must be spread among the remaining zones. Hence $s^*$ is upper bounded by $\hat{C}/\hat{N}$ and without loss of generality, we can define, for every node that is not in $z_0$ nor $z_1$, +$$\hat{n}_v = \left\lfloor\frac{c_v}{\hat{C}}\hat{N}\right\rfloor.$$ + +We constructed a sub-utilization $\hat{n}_v$. Now notice that $3N-\sum_v \hat{n}_v \le \# V$ where $\# V$ denotes the number of nodes. We can iteratively pick a node $v^*$ such that +\begin{itemize} + \item $\sum_{v\in z_{v^*}} \hat{n}_v < N$ where $z_{v^*}$ is the zone of $v^*$; + \item $v^*$ maximizes the quantity $c_v/(\hat{n}_v+1)$ among the vertices satisfying the first condition (i.e. not in a saturated zone). +\end{itemize} +We iterate these instructions until $\sum_v \hat{n}_v= 3N$, and at this stage we define $(n_v) = (\hat{n}_v)$. It is easy to prove by induction that at every step, there is an optimal utilization that is pointwise larger than $\hat{n}_v$, and in particular, that $(n_v)$ is optimal. + +\subsubsection*{Existence of an optimal assignment} + +As for now, the \emph{optimal utilization} that we obtained is just a vector of numbers and it is not clear that it can be realized as the utilization of some concrete assignment. Here is a way to get a concrete assignment. + +Define $3N$ tokens $t_1,\ldots, t_{3N}\in V$ as follows: +\begin{itemize} + \item Enumerate the zones $z$ of $Z$ in any order; + \item enumerate the nodes $v$ of $z$ in any order; + \item repeat $n_v$ times the token $v$. +\end{itemize} +Then for $1\le i \le N$, define the triplet $T_i$ to be +$(t_i, t_{i+N}, t_{i+2N})$. Since the same nodes of a zone appear contiguously, the three nodes of a triplet must belong to three distinct zones. + +However simple, this solution to go from an utilization to an assignment has the drawback of not spreading the triplets: a node will tend to be associated to the same two other nodes for many partitions. Hence, during data transfer, it will tend to use only two link, instead of spreading the bandwith use over many other links to other nodes. To achieve this goal, we will reframe the search of an assignment as a flow problem. and in the flow algorithm, we will introduce randomness in the order of exploration. This will be sufficient to obtain a good dispersion of the triplets. + +\begin{figure} + \centering + \includegraphics[width=0.9\linewidth]{figures/naive} + \caption{On the left, the creation of a concrete assignment with the naive approach of repeating tokens. On the right, the zones containing the nodes.} +\end{figure} + +\subsubsection*{Assignment as a maximum flow problem} + +We describe the flow problem via its graph $(X,E)$ where $X$ is a set of vertices, and $E$ are directed weighted edges between the vertices. For every zone $z$, define $n_z=\sum_{v\in z} n_v$. + +The set of vertices $X$ contains the source $\mathbf{s}$ and the sink $\mathbf{t}$; a vertex $\mathbf{x}_z$ for every zone $z\in Z$, and a vertex $\mathbf{y}_i$ for every partition index $1\le i\le N$. + +The set of edges $E$ contains +\begin{itemize} + \item the edge $(\mathbf{s}, \mathbf{x}_z, n_z)$ for every zone $z\in Z$; + \item the edge $(\mathbf{x}_z, \mathbf{y}_i, 1)$ for every zone $z\in Z$ and partition $1\le i\le N$; + \item the edge $(\mathbf{y}_i, \mathbf{t}, 3)$ for every partition $1\le i\le N$. +\end{itemize} + +\begin{figure}[b] + \centering + \includegraphics[width=0.6\linewidth]{figures/flow} + \caption{Flow problem to compute and optimal assignment.} +\end{figure} + +We first show the equivalence between this problem and and the construction of an assignment. Given some optimal assignment $(n_v)$, define the flow $f:E\to \mathbb{N}$ that saturates every edge from $\mathbf{s}$ or to $\mathbf{t}$, takes value $1$ on the edge between $\mathbf{x}_z$ and $\mathbf{y}_i$ if partition $i$ is stored in some node of the zone $z$, and $0$ otherwise. One can easily check that $f$ thus defined is indeed a flow and is maximum. + +Reciprocally, by the existence of maximum flows constructed from optimal assignments, any maximum flow must saturate the edges linked to the source or the sink. It can only take value 0 or 1 on the other edge, and every partition vertex is associated to exactly three distinct zone vertices. Every zone is associated to exactly $n_z$ partitions. + +A maximum flow can be constructed using, for instance, Dinic's algorithm. This algorithm works by discovering augmenting path to iteratively increase the flow. During the exploration of the graph to find augmenting path, we can shuffle the order of enumeration of the neighbours to spread the associations between zones and partitions. + +Once we have such association, we can randomly distribute the $n_z$ edges picked for every zone $z$ to its nodes $v\in z$ such that every such $v$ gets $n_z$ edges. This defines an optimal assignment of partitions to nodes. + + +\subsection{Minimal transfer} + +Assume that there was a previous assignment $(T'_i)_{1\le i\le N}$ corresponding to utilizations $(n'_v)_{v\in V}$. We would like the new computed assignment $(T_i)_{1\le i\le N}$ from some $(n_v)_{v\in V}$ to minimize the number of partitions that need to be transferred. We can imagine two different objectives corresponding to different hypotheses: +\begin{equation} + \tag{H3A} + \label{hyp:A} + \text{\emph{Transfers between different zones cost much more than inside a zone.}} +\end{equation} +\begin{equation} + \tag{H3B} + \label{hyp:B} + \text{\emph{Changing zone is not the largest cost when transferring a partition.}} +\end{equation} + +In case $A$, our goal will be to minimize the number of changes of zone in the assignment of partitions to zone. More formally, we will maximize the quantity +$$ +Q_Z := +\sum_{1\le i\le N} +\#\{z\in Z ~|~ z\cap T_i \neq \emptyset, z\cap T'_i \neq \emptyset \} +.$$ + +In case $B$, our goal will be to minimize the number of changes of nodes in the assignment of partitions to nodes. We will maximize the quantity +$$ +Q_V := +\sum_{1\le i\le N} \#(T_i \cap T'_i). +$$ + +It is tempting to hope that there is a way to maximize both quantity, that having the least discrepancy in terms of nodes will lead to the least discrepancy in terms of zones. But this is actually wrong! We propose the following counter-example to convince the reader: + +We consider eight nodes $a, a', b, c, d, d', e, e'$ belonging to five different zones $\{a,a'\}, \{b\}, \{c\}, \{d,d'\}, \{e, e'\}$. We take three partitions ($N=3$), that are originally assigned with some utilization $(n'_v)_{v\in V}$ as follows: +$$ +T'_1=(a,b,c) \qquad +T'_2=(a',b,d) \qquad +T'_3=(b,c,e). +$$ +This assignment, with updated utilizations $(n_v)_{v\in V}$ minimizes the number of zone changes: +$$ +T_1=(d,b,c) \qquad +T_2=(a,b,d) \qquad +T_3=(b,c,e'). +$$ +This one, with the same utilization, minimizes the number of node changes: +$$ +T_1=(a,b,c) \qquad +T_2=(e',b,d) \qquad +T_3=(b,c,d'). +$$ +One can check that in this case, it is impossible to minimize both the number of zone and node changes. + +Because of the redundancy constraint, we cannot use a greedy algorithm to just replace nodes in the triplets to try to get the new utilization rate: this could lead to blocking situation where there is still a hole to fill in a triplet but no available node satisfies the zone separation constraint. To circumvent this issue, we propose an algorithm based on finding cycles in a graph encoding of the assignment. As in section \ref{sec:opt_assign}, we can explore the neigbours in a random order in the graph algorithms, to spread the triplets distribution. + + +\subsubsection{Minimizing the zone discrepancy} + + +First, notice that, given an assignment of partitions to \emph{zones}, it is easy to deduce an assignment to \emph{nodes} that minimizes the number of transfers for this zone assignment: For every zone $z$ and every node $v\in z$, pick in any way a set $P_v$ of partitions that where assigned to $v$ in $T'$, to $z_v$ in $T$, with the cardinality of $P_v$ smaller than $n_v$. Once all these sets are chosen, complement the assignment to reach the right utilization for every node. If $\#P_v > n_v$, it means that all the partitions that could stay in $v$ (i.e. that were already in $v$ and are still assigned to its zone) do stay in $v$. If $\#P_v = n_v$, then $n_v$ partitions stay in $v$, which is the number of partitions that need to be in $v$ in the end. In both cases, we could not hope for better given the partition to zone assignment. + +Our goal now is to find a assignment of partitions to zones that minimizes the number of zone transfers. To do so we are going to represent an assignment as a graph. + +Let $G_T=(X,E_T)$ be the directed weighted graph with vertices $(\mathbf{x}_i)_{1\le i\le N}$ and $(\mathbf{y}_z)_{z\in Z}$. For any $1\le i\le N$ and $z\in Z$, $E_T$ contains the arc: +\begin{itemize} + \item $(\mathbf{x}_i, \mathbf{y}_z, +1)$, if $z$ appears in $T_i'$ and $T_i$; + \item $(\mathbf{x}_i, \mathbf{y}_z, -1)$, if $z$ appears in $T_i$ but not in $T'_i$; + \item $(\mathbf{y}_z, \mathbf{x}_i, -1)$, if $z$ appears in $T'_i$ but not in $T_i$; + \item $(\mathbf{y}_z, \mathbf{x}_i, +1)$, if $z$ does not appear in $T'_i$ nor in $T_i$. +\end{itemize} +In other words, the orientation of the arc encodes whether partition $i$ is stored in zone $z$ in the assignment $T$ and the weight $\pm 1$ encodes whether this corresponds to what happens in the assignment $T'$. + +\begin{figure}[t] + \centering + \begin{minipage}{.40\linewidth} + \centering + \includegraphics[width=.8\linewidth]{figures/mini_zone} + \end{minipage} + \begin{minipage}{.55\linewidth} + \centering + \includegraphics[width=.8\linewidth]{figures/mini_node} + \end{minipage} + \caption{On the left: the graph $G_T$ encoding an assignment to minimize the zone discrepancy. On the right: the graph $G_T$ encoding an assignment to minimize the node discrepancy.} +\end{figure} + + +Notice that at every partition, there are three outgoing arcs, and at every zone, there are $n_z$ incoming arcs. Moreover, if $w(e)$ is the weight of an arc $e$, define the weight of $G_T$ by +\begin{align*} +w(G_T) := \sum_{e\in E} w(e) &= \#Z \times N - 4 \sum_{1\le i\le N} \#\{z\in Z ~|~ z\cap T_i = \emptyset, z\cap T'_i \neq \emptyset\} \\ +&=\#Z \times N - 4 \sum_{1\le i\le N} 3- \#\{z\in Z ~|~ z\cap T_i \neq \emptyset, z\cap T'_i \neq \emptyset\} \\ +&= (\#Z-12)N + 4 Q_Z. +\end{align*} +Hence maximizing $Q_Z$ is equivalent to maximizing $w(G_T)$. + +Assume that their exist some assignment $T^*$ with the same utilization $(n_v)_{v\in V}$. Define $G_{T^*}$ similarly and consider the set $E_\mathrm{Diff} = E_T \setminus E_{T^*}$ of arcs that appear only in $G_T$. Since all vertices have the same number of incoming arcs in $G_T$ and $G_{T^*}$, the vertices of the graph $(X, E_\mathrm{Diff})$ must all have the same number number of incoming and outgoing arrows. So $E_\mathrm{Diff}$ can be expressed as a union of disjoint cycles. Moreover, the edges of $E_\mathrm{Diff}$ must appear in $E_{T^*}$ with reversed orientation and opposite weight. Hence, we have +$$ + w(G_T) - w(G_{T^*}) = 2 \sum_{e\in E_\mathrm{Diff}} w(e). +$$ +Hence, if $T$ is not optimal, there exists some $T^*$ with $w(G_T) < w(G_{T^*})$, and by the considerations above, there must exist a cycle in $E_\mathrm{Diff}$, and hence in $G_T$, with negative weight. If we reverse the edges and weights along this cycle, we obtain some graph. Since we did not change the incoming degree of any vertex, this is the graph encoding of some valid assignment $T^+$ such that $w(G_{T^+}) > w(G_T)$. We can iterate this operation until there is no other assignment $T^*$ with larger weight, that is until we obtain an optimal assignment. + + + +\subsubsection{Minimizing the node discrepancy} + +We will follow an approach similar to the one where we minimize the zone discrepancy. Here we will directly obtain a node assignment from a graph encoding. + +Let $G_T=(X,E_T)$ be the directed weighted graph with vertices $(\mathbf{x}_i)_{1\le i\le N}$, $(\mathbf{y}_{z,i})_{z\in Z, 1\le i\le N}$ and $(\mathbf{u}_v)_{v\in V}$. For any $1\le i\le N$ and $z\in Z$, $E_T$ contains the arc: +\begin{itemize} + \item $(\mathbf{x}_i, \mathbf{y}_{z,i}, 0)$, if $z$ appears in $T_i$; + \item $(\mathbf{y}_{z,i}, \mathbf{x}_i, 0)$, if $z$ does not appear in $T_i$. +\end{itemize} +For any $1\le i\le N$ and $v\in V$, $E_T$ contains the arc: +\begin{itemize} + \item $(\mathbf{y}_{z_v,i}, \mathbf{u}_v, +1)$, if $v$ appears in $T_i'$ and $T_i$; + \item $(\mathbf{y}_{z_v,i}, \mathbf{u}_v, -1)$, if $v$ appears in $T_i$ but not in $T'_i$; + \item $(\mathbf{u}_v, \mathbf{y}_{z_v,i}, -1)$, if $v$ appears in $T'_i$ but not in $T_i$; + \item $(\mathbf{u}_v, \mathbf{y}_{z_v,i}, +1)$, if $v$ does not appear in $T'_i$ nor in $T_i$. +\end{itemize} +Every vertex $\mathbb{x}_i$ has outgoing degree 3, every vertex $\mathbf{y}_{z,v}$ has outgoing degree 1, and every vertex $\mathbf{u}_v$ has incoming degree $n_v$. +Remark that any graph respecting these degree constraints is the encoding of a valid assignment with utilizations $(n_v)_{v\in V}$, in particular no partition is stored in two nodes of the same zone. + +We define $w(G_T)$ similarly: +\begin{align*} + w(G_T) := \sum_{e\in E_T} w(e) &= \#V \times N - 4\sum_{1\le i\le N} 3-\#(T_i\cap T'_i) \\ + &= (\#V-12)N + 4Q_V. +\end{align*} + +Exactly like in the previous section, the existence of an assignment with larger weight implies the existence of a negatively weighted cycle in $G_T$. Reversing this cycle gives us the encoding of a valid assignment with a larger weight. Iterating this operation yields an optimal assignment. + + +\subsubsection{Linear combination of both criteria} + +In the graph $G_T$ defined in the previous section, instead of having weights $0$ and $\pm 1$, we could be having weights $\pm\alpha$ between $\mathbf{x}$ and $\mathbf{y}$ vertices, and weights $\pm\beta$ between $\mathbf{y}$ and $\mathbf{u}$ vertices, for some $\alpha,\beta>0$ (we have positive weight if the assignment corresponds to $T'$ and negative otherwise). Then +\begin{align*} + w(G_T) &= \sum_{e\in E_T} w(e) = + \alpha \big( (\#Z-12)N + 4 Q_Z\big) + + \beta \big( (\#V-12)N + 4 Q_V\big) \\ + &= \mathrm{const}+ 4(\alpha Q_Z + \beta Q_V). +\end{align*} +So maximizing the weight of such graph encoding would be equivalent to maximizing a linear combination of $Q_Z$ and $Q_V$. + + +\subsection{Algorithm} +We give a high level description of the algorithm to compute an optimal 3-strict assignment. The operations appearing at lines 1,2,4 are respectively described by Algorithms \ref{alg:util},\ref{alg:opt} and \ref{alg:mini}. + + + +\begin{algorithm}[H] + \caption{Optimal 3-strict assignment} + \label{alg:total} + \begin{algorithmic}[1] + \Function{Optimal 3-strict assignment}{$N$, $(c_v)_{v\in V}$, $T'$} + \State $(n_v)_{v\in V} \leftarrow$ \Call{Compute optimal utilization}{$N$, $(c_v)_{v\in V}$} + \State $(T_i)_{1\le i\le N} \leftarrow$ \Call{Compute candidate assignment}{$N$, $(n_v)_{v\in V}$} + \If {there was a previous assignment $T'$} + \State $T \leftarrow$ \Call{Minimization of transfers}{$(T_i)_{1\le i\le N}$, $(T'_i)_{1\le i\le N}$} + \EndIf + \State \Return $T$. + \EndFunction + \end{algorithmic} +\end{algorithm} + +We give some considerations of worst case complexity for these algorithms. In the following, we assume $N>\#V>\#Z$. The complexity of Algorithm \ref{alg:total} is $O(N^3\# Z)$ if we assume \eqref{hyp:A} and $O(N^3 \#Z \#V)$ if we assume \eqref{hyp:B}. + +Algorithm \ref{alg:util} can be implemented with complexity $O(\#V^2)$. The complexity of the function call at line \ref{lin:subutil} is $O(\#V)$. The difference between the sum of the subutilizations and $3N$ is at most the sum of the rounding errors when computing the $\hat{n}_v$. Hence it is bounded by $\#V$ and the loop at line \ref{lin:loopsub} is iterated at most $\#V$ times. Finding the minimizing $v$ at line \ref{lin:findmin} takes $O(\#V)$ operations (naively, we could also use a heap). + +Algorithm \ref{alg:opt} can be implemented with complexity $O(N^3\times \#Z)$. The flow graph has $O(N+\#Z)$ vertices and $O(N\times \#Z)$ edges. Dinic's algorithm has complexity $O(\#\mathrm{Vertices}^2\#\mathrm{Edges})$ hence in our case it is $O(N^3\times \#Z)$. + +Algorithm \ref{alg:mini} can be implented with complexity $O(N^3\# Z)$ under \eqref{hyp:A} and $O(N^3 \#Z \#V)$ under \eqref{hyp:B}. +The graph $G_T$ has $O(N)$ vertices and $O(N\times \#Z)$ edges under assumption \eqref{hyp:A} and respectively $O(N\times \#Z)$ vertices and $O(N\times \#V)$ edges under assumption \eqref{hyp:B}. The loop at line \ref{lin:repeat} is iterated at most $N$ times since the distance between $T$ and $T'$ decreases at every iteration. Bellman-Ford algorithm has complexity $O(\#\mathrm{Vertices}\#\mathrm{Edges})$, which in our case amounts to $O(N^2\# Z)$ under \eqref{hyp:A} and $O(N^2 \#Z \#V)$ under \eqref{hyp:B}. + +\begin{algorithm} + \caption{Computation of the optimal utilization} + \label{alg:util} + \begin{algorithmic}[1] +\Function{Compute optimal utilization}{$N$, $(c_v)_{v\in V}$} + \State $(\hat{n}_v)_{v\in V} \leftarrow $ \Call{Compute subutilization}{$N$, $(c_v)_{v\in V}$} \label{lin:subutil} + \While{$\sum_{v\in V} \hat{n}_v < 3N$} \label{lin:loopsub} + \State Pick $v\in V$ minimizing $\frac{c_v}{\hat{n}_v+1}$ and such that + $\sum_{v'\in z_v} \hat{n}_{v'} < N$ \label{lin:findmin} + \State $\hat{n}_v \leftarrow \hat{n}_v+1$ + \EndWhile + \State \Return $(\hat{n}_v)_{v\in V}$ +\EndFunction +\State + +\Function{Compute subutilization}{$N$, $(c_v)_{v\in V}$} + \State $R \leftarrow 3$ +\For{$v\in V$} +\State $\hat{n}_v \leftarrow \mathrm{unset}$ +\EndFor +\For{$z\in Z$} +\State $c_z \leftarrow \sum_{v\in z} c_v$ +\EndFor +\State $C \leftarrow \sum_{z\in Z} c_z$ +\While{$\exists z \in Z$ such that $R\times c_{z} > C$} +\For{$v\in z$} +\State $\hat{n}_v \leftarrow \left\lfloor \frac{c_v}{c_z} N \right\rfloor$ +\EndFor +\State $C \leftarrow C-c_z$ +\State $R\leftarrow R-1$ +\EndWhile +\For{$v\in V$} +\If{$\hat{n}_v = \mathrm{unset}$} +\State $\hat{n}_v \leftarrow \left\lfloor \frac{Rc_v}{C} N \right\rfloor$ +\EndIf +\EndFor +\State \Return $(\hat{n}_v)_{v\in V}$ +\EndFunction + \end{algorithmic} +\end{algorithm} + +\begin{algorithm} + \caption{Computation of a candidate assignment} + \label{alg:opt} + \begin{algorithmic}[1] + \Function{Compute candidate assignment}{$N$, $(n_v)_{v\in V}$} + \State Compute the flow graph $G$ + \State Compute the maximal flow $f$ using Dinic's algorithm with randomized neighbours enumeration + \State Construct the assignment $(T_i)_{1\le i\le N}$ from $f$ + \State \Return $(T_i)_{1\le i\le N}$ + \EndFunction + \end{algorithmic} +\end{algorithm} + + +\begin{algorithm} + \caption{Minimization of the number of transfers} + \label{alg:mini} + \begin{algorithmic}[1] + \Function{Minimization of transfers}{$(T_i)_{1\le i\le N}$, $(T'_i)_{1\le i\le N}$} + \State Construct the graph encoding $G_T$ + \Repeat \label{lin:repeat} + \State Find a negative cycle $\gamma$ using Bellman-Ford algorithm on $G_T$ + \State Reverse the orientations and weights of edges in $\gamma$ + \Until{no negative cycle is found} + \State Update $(T_i)_{1\le i\le N}$ from $G_T$ + \State \Return $(T_i)_{1\le i\le N}$ + \EndFunction + \end{algorithmic} +\end{algorithm} + + + +\section{TODO} + +- reunion deux fleurs : autres modes, autres contraintes + +\end{document} + -- cgit v1.2.3 From 81083dd415664d9c2d35e52eba13826b952c38e6 Mon Sep 17 00:00:00 2001 From: Mendes Date: Fri, 19 Aug 2022 21:21:41 +0200 Subject: Added a first draft version of the algorithm and analysis for the non-strict mode. --- doc/optimal_layout_report/optimal_layout.aux | 15 ++-- doc/optimal_layout_report/optimal_layout.log | 77 ++++++++++----------- doc/optimal_layout_report/optimal_layout.pdf | Bin 279062 -> 289460 bytes .../optimal_layout.synctex.gz | Bin 84542 -> 107678 bytes doc/optimal_layout_report/optimal_layout.tex | 77 ++++++++++++++++++++- 5 files changed, 120 insertions(+), 49 deletions(-) (limited to 'doc') diff --git a/doc/optimal_layout_report/optimal_layout.aux b/doc/optimal_layout_report/optimal_layout.aux index fe8b0891..9e779514 100644 --- a/doc/optimal_layout_report/optimal_layout.aux +++ b/doc/optimal_layout_report/optimal_layout.aux @@ -7,26 +7,29 @@ \@writefile{toc}{\contentsline {subsection}{\numberline {2.1}Optimal assignment}{2}{}\protected@file@percent } \newlabel{sec:opt_assign}{{2.1}{2}} \@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces On the left, the creation of a concrete assignment with the naive approach of repeating tokens. 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PDF statistics: - 127 PDF objects out of 1000 (max. 8388607) - 90 compressed objects within 1 object stream + 135 PDF objects out of 1000 (max. 8388607) + 96 compressed objects within 1 object stream 0 named destinations out of 1000 (max. 500000) 21 words of extra memory for PDF output out of 10000 (max. 10000000) diff --git a/doc/optimal_layout_report/optimal_layout.pdf b/doc/optimal_layout_report/optimal_layout.pdf index 84265135..667798fe 100644 Binary files a/doc/optimal_layout_report/optimal_layout.pdf and b/doc/optimal_layout_report/optimal_layout.pdf differ diff --git a/doc/optimal_layout_report/optimal_layout.synctex.gz b/doc/optimal_layout_report/optimal_layout.synctex.gz index 376399c7..59241b07 100644 Binary files a/doc/optimal_layout_report/optimal_layout.synctex.gz and b/doc/optimal_layout_report/optimal_layout.synctex.gz differ diff --git a/doc/optimal_layout_report/optimal_layout.tex b/doc/optimal_layout_report/optimal_layout.tex index 843e0be6..594c7ecc 100644 --- a/doc/optimal_layout_report/optimal_layout.tex +++ b/doc/optimal_layout_report/optimal_layout.tex @@ -54,6 +54,10 @@ For now, in the following, we ask the following redundancy constraint: \textbf{Mode 3-strict:} every partition needs to be assignated to three nodes belonging to three different zones. +\textbf{Mode 3:} every partition needs to be assignated to three nodes. We try to spread the three nodes over different zones as much as possible. + +\textbf{Remark: (TODO):} The algorithms below directly adapt to a redundancy of $r$ instead of 3. + \section{Properties of an optimal 3-strict assignment} \subsection{Optimal assignment} @@ -384,11 +388,80 @@ The graph $G_T$ has $O(N)$ vertices and $O(N\times \#Z)$ edges under assumption \end{algorithmic} \end{algorithm} +\newpage + +\section{Computation of a 3-non-strict assignment} + +\subsection{Choices of optimality} + +In this mode, we primarily want to store every partition on three nodes, and only secondarily try to spread the nodes among different zone. So we make the choice of not taking the zone repartition in the criterion of optimality. + +We try to maximize $s^*$ defined in \eqref{eq:optimal}. So we can compute the optimal utilizations $(n_v)_{v\in V}$ with the only constraint that $n_v \le N$ for every node $v$. As in the previous section, we start with a sub-utilization proportional to $c_v$ (and capped at $N$), and we iteratively increase the $\hat{n}_v$ that is less than $N$ and maximizes the quantity $c_v/(\hat{n}_v+1)$, until the total sum is $3N$. + +\subsection{Computation of a candidate assignment} + +To compute a candidate assignment (that does not optimize zone spreading nor distance to a previous assignment yet), we can use the folowing flow problem. + +Define the oriented weighted graph $(X,E)$. The set of vertices $X$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices +$\mathbf{x}_p, \mathbf{u}^+_p, \mathbf{u}^-_p$ for every partition $p$, vertices $\mathbf{y}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{z}_v$ for every node $v$. + +The set of edges is composed of the following arcs: +\begin{itemize} + \item ($\mathbf{s}$,$\mathbf{x}_p$, 3) for every partition $p$; + \item ($\mathbf{x}_p$,$\mathbf{u}^+_p$, 3) for every partition $p$; + \item ($\mathbf{x}_p$,$\mathbf{u}^-_p$, 2) for every partition $p$; + \item ($\mathbf{u}^+_p$,$\mathbf{y}_{p,z}$, 1) for every partition $p$ and zone $z$; + \item ($\mathbf{u}^-_p$,$\mathbf{y}_{p,z}$, 2) for every partition $p$ and zone $z$; + \item ($\mathbf{y}_{p,z}$,$\mathbf{z}_v$, 1) for every partition $p$, zone $z$ and node $v\in z$; + \item ($\mathbf{z}_v$, $\mathbf{t}$, $n_v$) for every node $v$; +\end{itemize} + +One can check that any maximal flow in this graph corresponds to an assignment of partitions to nodes. In such a flow, all the arcs from $\mathbf{s}$ and to $\mathbf{t}$ are saturated. The arc from $\mathbf{y}_{p,z}$ to $\mathbf{z}_v$ is saturated if and only if $p$ is associated to~$v$. +Finally the flow from $\mathbf{x}_p$ to $\mathbf{y}_{p,z}$ can go either through $\mathbf{u}^+_p$ or $\mathbf{u}^-_p$. -\section{TODO} -- reunion deux fleurs : autres modes, autres contraintes +\subsection{Maximal spread and minimal transfers} +Notice that if the arc $\mathbf{u}_p^+\mathbf{y}_{p,z}$ is not saturated but there is some flow in $\mathbf{u}_p^-\mathbf{y}_{p,z}$, then it is possible to transfer a unit of flow from the path $\mathbf{x}_p\mathbf{u}_p^-\mathbf{y}_{p,z}$ to the path $\mathbf{x}_p\mathbf{u}_p^+\mathbf{y}_{p,z}$. So we can always find an equivalent maximal flow $f^*$ that uses the path through $\mathbf{u}_p^-$ only if the path through $\mathbf{u}_p^+$ is saturated. + +We will use this fact to consider the amount of flow going through the vertices $\mathbf{u}^+$ as a measure of how well the partitions are spread over nodes belonging to different zones. If the partition $p$ is associated to 3 different zones, then a flow of 3 will cross $\mathbf{u}_p^+$ in $f^*$ (i.e. a flow of 0 will cross $\mathbf{u}_p^+$). If $p$ is associated to two zones, a flow of $2$ will cross $\mathbf{u}_p^+$. If $p$ is associated to a single zone, a flow of $1$ will cross $\mathbf{u}_p^+$. + +Let $N_1, N_2, N_3$ be the number of partitions associated to respectively 1,2 and 3 distinct zones. We will optimize a linear combination of these variables using the discovery of positively weighted circuits in a graph. + +At the same step, we will also optimize the distance to a previous assignment $T'$. Let $\alpha> \beta> \gamma \ge 0$ be three parameters. + +Given the flow $f$, let $G_f=(X',E_f)$ be the multi-graph where $X' = X\setminus\{\mathbf{s},\mathbf{t}\}$. The set $E_f$ is composed of the arcs: +\begin{itemize} +\item As many arcs from $(\mathbf{x}_p, \mathbf{u}^+_p,\alpha), (\mathbf{x}_p, \mathbf{u}^+_p,\beta), (\mathbf{x}_p, \mathbf{u}^+_p,\gamma)$ (selected in this order) as there is flow crossing $\mathbf{u}^+_p$ in $f$; +\item As many arcs from $(\mathbf{u}^+_p, \mathbf{x}_p,-\gamma), (\mathbf{u}^+_p, \mathbf{x}_p,-\beta), (\mathbf{u}^+_p, \mathbf{x}_p,-\alpha)$ (selected in this order) as there is flow crossing $\mathbf{u}^-_p$ in $f$; +\item As many copies of $(\mathbf{x}_p, \mathbf{u}^-_p,0)$ as there is flow through $\mathbf{u}^-_p$; +\item As many copies of $(\mathbf{u}^-_p,\mathbf{x}_p,0)$ so that the number of arcs between these two vertices is 2; +\item $(\mathbf{u}^+_p,\mathbf{y}_{p,z}, 0)$ if the flow between these vertices is 1, and the opposite arc otherwise; +\item as many copies of $(\mathbf{u}^-_p,\mathbf{y}_{p,z}, 0)$ as the flow between these vertices, and as many copies of the opposite arc as 2~$-$~the flow; +\item $(\mathbf{y}_{p,z},\mathbf{z}_v, \pm1)$ if it is saturated in $f$, with $+1$ if $v\in T'_p$ and $-1$ otherwise; +\item $(\mathbf{z}_v,\mathbf{y}_{p,z}, \pm1)$ if it is not saturated in $f$, with $+1$ if $v\notin T'_p$ and $-1$ otherwise. +\end{itemize} +To summarize, arcs are oriented left to right if they correspond to a presence of flow in $f$, and right to left if they correspond to an absence of flow. They are positively weighted if we want them to stay at their current state, and negatively if we want them to switch. Let us compute the weight of such graph. + +\begin{multline*} + w(G_f) = \sum_{e\in E_f} w(e_f) \\ + = + (\alpha - \beta -\gamma) N_1 + (\alpha +\beta - \gamma) N_2 + (\alpha+\beta+\gamma) N_3 + \\ + + \#V\times N - 4 \sum_p 3-\#(T_p\cap T'_p) \\ + =(\#V-12+\alpha-\beta-\gamma)\times N + 4Q_V + 2\beta N_2 + 2(\beta+\gamma) N_3 \\ +\end{multline*} + +As for the mode 3-strict, one can check that the difference of two such graphs corresponding to the same $(n_v)$ is always eulerian. Hence we can navigate in this class with the same greedy algorithm that discovers positive cycles and flips them. + +The function that we optimize is +$$ +2Q_V + \beta N_2 + (\beta+\gamma) N_3. +$$ +The choice of parameters $\beta$ and $\gamma$ should be lead by the following question: For $\beta$, where to put the tradeoff between zone dispersion and distance to the previous configuration? For $\gamma$, do we prefer to have more partitions spread between 2 zones, or have less between at least 2 zones but more between 3 zones. + +The quantity $Q_V$ varies between $0$ and $3N$, it should be of order $N$. The quantity $N_2+N_3$ should also be of order $N$ (it is exactly $N$ in the strict mode). So the two terms of the function are comparable. + \end{document} -- cgit v1.2.3 From d38fb6c2500c20cc6fabf3192fa7c136675788c5 Mon Sep 17 00:00:00 2001 From: Mendes Date: Thu, 8 Sep 2022 12:43:33 +0200 Subject: ignore log files in commit --- doc/optimal_layout_report/.gitignore | 4 + doc/optimal_layout_report/optimal_layout.aux | 35 --- doc/optimal_layout_report/optimal_layout.log | 298 --------------------- .../optimal_layout.synctex.gz | Bin 107678 -> 0 bytes doc/optimal_layout_report/optimal_layout.tex | 7 + 5 files changed, 11 insertions(+), 333 deletions(-) create mode 100644 doc/optimal_layout_report/.gitignore delete mode 100644 doc/optimal_layout_report/optimal_layout.aux delete mode 100644 doc/optimal_layout_report/optimal_layout.log delete mode 100644 doc/optimal_layout_report/optimal_layout.synctex.gz (limited to 'doc') diff --git a/doc/optimal_layout_report/.gitignore b/doc/optimal_layout_report/.gitignore new file mode 100644 index 00000000..3bd5cbf6 --- /dev/null +++ b/doc/optimal_layout_report/.gitignore @@ -0,0 +1,4 @@ +optimal_layout.aux +optimal_layout.log +optimal_layout.synctex.gz + diff --git a/doc/optimal_layout_report/optimal_layout.aux b/doc/optimal_layout_report/optimal_layout.aux deleted file mode 100644 index 9e779514..00000000 --- a/doc/optimal_layout_report/optimal_layout.aux +++ /dev/null @@ -1,35 +0,0 @@ -\relax -\@writefile{toc}{\contentsline {section}{\numberline {1}Introduction}{1}{}\protected@file@percent } -\@writefile{toc}{\contentsline {subsection}{\numberline {1.1}Context}{1}{}\protected@file@percent } -\@writefile{toc}{\contentsline {subsection}{\numberline {1.2}Formal description of the problem}{1}{}\protected@file@percent } -\newlabel{eq:optimal}{{{OPT}}{1}} -\@writefile{toc}{\contentsline {section}{\numberline {2}Properties of an optimal 3-strict assignment}{2}{}\protected@file@percent } -\@writefile{toc}{\contentsline {subsection}{\numberline {2.1}Optimal assignment}{2}{}\protected@file@percent } -\newlabel{sec:opt_assign}{{2.1}{2}} -\@writefile{lof}{\contentsline {figure}{\numberline {1}{\ignorespaces On the left, the creation of a concrete assignment with the naive approach of repeating tokens. 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diff --git a/doc/optimal_layout_report/optimal_layout.synctex.gz b/doc/optimal_layout_report/optimal_layout.synctex.gz deleted file mode 100644 index 59241b07..00000000 Binary files a/doc/optimal_layout_report/optimal_layout.synctex.gz and /dev/null differ diff --git a/doc/optimal_layout_report/optimal_layout.tex b/doc/optimal_layout_report/optimal_layout.tex index 594c7ecc..cb0d2479 100644 --- a/doc/optimal_layout_report/optimal_layout.tex +++ b/doc/optimal_layout_report/optimal_layout.tex @@ -462,6 +462,13 @@ The choice of parameters $\beta$ and $\gamma$ should be lead by the following qu The quantity $Q_V$ varies between $0$ and $3N$, it should be of order $N$. The quantity $N_2+N_3$ should also be of order $N$ (it is exactly $N$ in the strict mode). So the two terms of the function are comparable. +\section{TODO} + +Ajouter des affichages, voir https://pad.deuxfleurs.fr/pad/#/2/pad/view/rrKyASaaGKDIX4QICZCMP4f50M+nq5EMCvfvFQOsyXw/ + + \end{document} + + -- cgit v1.2.3 From c4adbeed515c571369453d23c7f1d84b1db994ec Mon Sep 17 00:00:00 2001 From: Mendes Date: Sat, 10 Sep 2022 13:51:12 +0200 Subject: Added the section with description proofs of the parametric assignment computation in the optimal layout report --- doc/optimal_layout_report/.gitignore | 3 +- doc/optimal_layout_report/optimal_layout.bib | 11 ++ doc/optimal_layout_report/optimal_layout.pdf | Bin 289460 -> 395187 bytes doc/optimal_layout_report/optimal_layout.tex | 258 +++++++++++++++++++++++++-- 4 files changed, 260 insertions(+), 12 deletions(-) create mode 100644 doc/optimal_layout_report/optimal_layout.bib (limited to 'doc') diff --git a/doc/optimal_layout_report/.gitignore b/doc/optimal_layout_report/.gitignore index 3bd5cbf6..52deb7ad 100644 --- a/doc/optimal_layout_report/.gitignore +++ b/doc/optimal_layout_report/.gitignore @@ -1,4 +1,5 @@ optimal_layout.aux optimal_layout.log optimal_layout.synctex.gz - +optimal_layout.bbl +optimal_layout.blg diff --git a/doc/optimal_layout_report/optimal_layout.bib b/doc/optimal_layout_report/optimal_layout.bib new file mode 100644 index 00000000..9552b11d --- /dev/null +++ b/doc/optimal_layout_report/optimal_layout.bib @@ -0,0 +1,11 @@ + +@article{even1975network, + title={Network flow and testing graph connectivity}, + author={Even, Shimon and Tarjan, R Endre}, + journal={SIAM journal on computing}, + volume={4}, + number={4}, + pages={507--518}, + year={1975}, + publisher={SIAM} +} diff --git a/doc/optimal_layout_report/optimal_layout.pdf b/doc/optimal_layout_report/optimal_layout.pdf index 667798fe..c85803e8 100644 Binary files a/doc/optimal_layout_report/optimal_layout.pdf and b/doc/optimal_layout_report/optimal_layout.pdf differ diff --git a/doc/optimal_layout_report/optimal_layout.tex b/doc/optimal_layout_report/optimal_layout.tex index cb0d2479..b2898adb 100644 --- a/doc/optimal_layout_report/optimal_layout.tex +++ b/doc/optimal_layout_report/optimal_layout.tex @@ -1,6 +1,7 @@ \documentclass[]{article} \usepackage{amsmath,amssymb} +\usepackage{amsthm} \usepackage{graphicx,xcolor} @@ -8,9 +9,11 @@ \renewcommand\thesubsubsection{\Alph{subsubsection})} +\newtheorem{proposition}{Proposition} + %opening \title{Optimal partition assignment in Garage} -\author{Mendes Oulamara} +\author{Mendes} \begin{document} @@ -22,25 +25,25 @@ Garage is an open-source distributed storage service blablabla$\dots$ -Every object to be stored in the system falls in a partition given by the last $k$ bits of its hash. There are $N=2^k$ partitions. Every partition will be stored on distinct nodes of the system. The goal of the assignment of partitions to nodes is to ensure (nodes and zone) redundancy and to be as efficient as possible. +Every object to be stored in the system falls in a partition given by the last $k$ bits of its hash. There are $P=2^k$ partitions. Every partition will be stored on distinct nodes of the system. The goal of the assignment of partitions to nodes is to ensure (nodes and zone) redundancy and to be as efficient as possible. \subsection{Formal description of the problem} -We are given a set of nodes $V$ and a set of zones $Z$. Every node $v$ has a non-negative storage capacity $c_v\ge 0$ and belongs to a zone $z_v\in Z$. We are also given a number of partition $N>0$ (typically $N=256$). +We are given a set of nodes $\mathbf{N}$ and a set of zones $\mathbf{Z}$. Every node $n$ has a non-negative storage capacity $c_n\ge 0$ and belongs to a zone $z\in \mathbf{Z}$. We are also given a number of partition $P>0$ (typically $P=256$). -We would like to compute an assignment of three nodes to every partition. That is, for every $1\le i\le N$, we compute a triplet of three distinct nodes $T_i=(T_i^1, T_i^2, T_i^3) \in V^3$. We will impose some redundancy constraints to this assignment, and under these constraints, we want our system to have the largest storage capacity possible. To link storage capacity to partition assignment, we make the following assumption: +We would like to compute an assignment of nodes to partitions. We will impose some redundancy constraints to this assignment, and under these constraints, we want our system to have the largest storage capacity possible. To link storage capacity to partition assignment, we make the following assumption: \begin{equation} \tag{H1} \text{\emph{All partitions have the same size $s$.}} \end{equation} This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored large objects. -Every node $v$ needs to store $n_v = \#\{ 1\le i\le N ~|~ v\in T_i \}$ partitions (where $\#$ denots the number of indices in the set). Hence the partitions stored by $v$ (and hence all partitions by our assumption) have there size bounded by $c_v/n_v$. This remark leads us to define the optimal size that we will want to maximize: +Every node $n$ wille store some number $k_n$ of partitions. Hence the partitions stored by $n$ (and hence all partitions by our assumption) have there size bounded by $c_n/k_n$. This remark leads us to define the optimal size that we will want to maximize: \begin{equation} \label{eq:optimal} \tag{OPT} -s^* = \min_{v \in V} \frac{c_v}{n_v}. +s^* = \min_{n \in N} \frac{c_n}{k_n}. \end{equation} When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption: @@ -52,11 +55,246 @@ This assumption justifies that when we compute the new assignment, it is worth t For now, in the following, we ask the following redundancy constraint: +\textbf{Parametric node and zone redundancy:} Given two integer parameters $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$, we ask every partition to be stored on $\rho_\mathbf{N}$ distinct nodes, and these nodes must belong to at least $\rho_\mathbf{Z}$ distinct zones. + + \textbf{Mode 3-strict:} every partition needs to be assignated to three nodes belonging to three different zones. \textbf{Mode 3:} every partition needs to be assignated to three nodes. We try to spread the three nodes over different zones as much as possible. -\textbf{Remark: (TODO):} The algorithms below directly adapt to a redundancy of $r$ instead of 3. +\textbf{Warning:} This is a working document written incrementaly. The last version of the algorithm is the \textbf{parametric assignment} described in the next section. + + +\section{Computation of a parametric assignment} +\textbf{Attention : }We change notations in this section. + +Notations : let $P$ be the number of partitions, $N$ the number of nodes, $Z$ the number of zones. Let $\mathbf{P,N,Z}$ be the label sets of, respectively, partitions, nodes and zones. +Let $s^*$ be the largest partition size achievable with the redundancy constraints. Let $(c_n)_{n\in \mathbf{N}}$ be the storage capacity of every node. + +In this section, we propose a third specification of the problem. The user inputs two redundancy parameters $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$. We compute an assignment $\alpha = (\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}})_{p\in \mathbf{P}}$ such that every partition $p$ is associated to $\rho_\mathbf{N}$ distinct nodes $\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}}$ and these nodes belong to at least $\rho_\mathbf{Z}$ distinct zones. + +If the layout contained a previous assignment $\alpha'$, we try to minimize the amount of data to transfer during the layout update by making $\alpha$ as close as possible to $\alpha'$. + +In the following subsections, we describe the successive steps of the algorithm we propose to compute $\alpha$. + +\subsubsection*{Algorithm} + +\begin{algorithmic}[1] + \Function{Compute Layout}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, $\alpha'$} + \State $s^* \leftarrow$ \Call{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$} + \State $G \leftarrow G(s^*)$ + \State $f \leftarrow$ \Call{Compute Candidate Assignment}{$G$, $\alpha'$} + \State $f^* \leftarrow$ \Call{Minimize transfer load}{$G$, $f$, $\alpha'$} + \State Build $\alpha^*$ from $f^*$ + \State \Return $\alpha^*$ + \EndFunction +\end{algorithmic} + +\subsubsection*{Complexity} +As we will see in the next sections, the worst case complexity of this algorithm is $O(P^2 N^2)$. The minimization of transfer load is the most expensive step, and it can run with a timeout since it is only an optimization step. Without this step (or with a smart timeout), the worst cas complexity can be $O((PN)^{3/2}\log C)$ where $C$ is the total storage capacity of the cluster. + +\subsection{Determination of the partition size $s^*$} + +Again, we will represent an assignment $\alpha$ as a flow in a specific graph $G$. We will not compute the optimal partition size $s^*$ a priori, but we will determine it by dichotomy, as the largest size $s$ such that the maximal flow achievable on $G=G(s)$ has value $\rho_\mathbf{N}P$. We will assume that the capacities are given in a small enough unit (say, Megabytes), and we will determine $s^*$ at the precision of the given unit. + +Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$. + +The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices +$\mathbf{p, p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$. + +The set of arcs $E$ contains: +\begin{itemize} + \item ($\mathbf{s}$,$\mathbf{p}$, $\rho_\mathbf{N}$) for every partition $p$; + \item ($\mathbf{p}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$; + \item ($\mathbf{p}$,$\mathbf{p}^+$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$; + \item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$; + \item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$; + \item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$; + \item ($\mathbf{n}$, $\mathbf{t}$, $\lfloor c_n/s \rfloor$) for every node $n$. +\end{itemize} + +In the following complexity calculations, we will use the number of vertices and edges of $G$. Remark from now that $\# V = O(PZ)$ and $\# E = O(PN)$. + +\begin{proposition} + An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$. +\end{proposition} +\begin{proof} + Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through every $\mathbf{p}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes. + + In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$. +\end{proof} + +\textbf{Implementation remark:} In the flow algorithm, while exploring the graph, we explore the neighbours of every vertex in a random order to heuristically spread the association between nodes and partitions. + +\subsubsection*{Algorithm} +With this result mind, we can describe the first step of our algorithm. All divisions are supposed to be integer division. +\begin{algorithmic}[1] + \Function{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$} + + \State Build the graph $G=G(s=1)$ + \State $ f \leftarrow$ \Call{Maximal flow}{$G$} + \If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$} + + \State \Return Error: capacities too small or constraints too strong. + \EndIf + + \State $s^- \leftarrow 1$ + \State $s^+ \leftarrow 1+\frac{1}{\rho_\mathbf{N}}\sum_{n \in \mathbf{N}} c_n$ + + \While{$s^-+1 < s^+$} + \State Build the graph $G=G(s=(s^-+s^+)/2)$ + \State $ f \leftarrow$ \Call{Maximal flow}{$G$} + \If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$} + \State $s^+ \leftarrow (s^- + s^+)/2$ + \Else + \State $s^- \leftarrow (s^- + s^+)/2$ + \EndIf + \EndWhile + + \State \Return $s^-$ + \EndFunction +\end{algorithmic} + +\subsubsection*{Complexity} + +To compute the maximal flow, we use Dinic's algorithm. Its complexity on general graphs is $O(\#V^2 \#E)$, but on graphs with edge capacity bounded by a constant, it turns out to be $O(\#E^{3/2})$. The graph $G$ does not fall in this case since the capacities of the arcs incoming to $\mathbf{t}$ are far from bounded. However, the proof of this complexity works readily for graph where we only ask the edges \emph{not} incoming to the sink $\mathbf{t}$ to have their capacities bounded by a constant. One can find the proof of this claim in \cite[Section 2]{even1975network}. +The dichotomy adds a logarithmic factor $\log (C)$ where $C=\sum_{n \in \mathbf{N}} c_n$ is the total capacity of the cluster. The total complexity of this first function is hence +$O(\#E^{3/2}\log C ) = O\big((PN)^{3/2} \log C\big)$. + +\subsubsection*{Metrics} +We can display the discrepancy between the computed $s^*$ and the best size we could hope for a given total capacity, that is $C/\rho_\mathbf{N}$. + +\subsection{Computation of a candidate assignment} + +Now that we have the optimal partition size $s^*$, to compute a candidate assignment, it would be enough to compute a maximal flow function $f$ on $G(s^*)$. This is what we do if there was no previous assignment $\alpha'$. + +If there was some $\alpha'$, we add a step that will heuristically help to obtain a candidate $\alpha$ closer to $\alpha'$. to do so, we fist compute a flow function $\tilde{f}$ that uses only the partition-to-node association appearing in $\alpha'$. Most likely, $\tilde{f}$ will not be a maximal flow of $G(s^*)$. In Dinic's algorithm, we can start from a non maximal flow function and then discover improving paths. This is what we do in starting from $\tilde{f}$. The hope\footnote{This is only a hope, because one can find examples where the construction of $f$ from $\tilde{f}$ produces an assignment $\alpha$ that is not as close as possible to $\alpha'$.} is that the final flow function $f$ will tend to keep the associations appearing in $\tilde{f}$. + +More formally, we construct the graph $G_{|\alpha'}$ from $G$ by removing all the arcs $(\mathbf{x}_{p,z},\mathbf{n}, 1)$ where $p$ is not associated to $n$ in $\alpha'$. We compute a maximal flow function $\tilde{f}$ in $G_{|\alpha'}$. $\tilde{f}$ is also a valid (most likely non maximal) flow function in $G$. We compute a maximal flow function $f$ on $G$ by starting Dinic's algorithm on $\tilde{f}$. + +\subsubsection*{Algorithm} +\begin{algorithmic}[1] + \Function{Compute Candidate Assignment}{$G$, $\alpha'$} + \State Build the graph $G_{|\alpha'}$ + \State $ \tilde{f} \leftarrow$ \Call{Maximal flow}{$G_{|\alpha'}$} + \State $ f \leftarrow$ \Call{Maximal flow from flow}{$G$, $\tilde{f}$} + \State \Return $f$ + \EndFunction +\end{algorithmic} + +\textbf{Remark:} The function ``Maximal flow'' can be just seen as the function ``Maximal flow from flow'' called with the zero flow function as starting flow. + +\subsubsection*{Complexity} +From the consideration of the last section, we have the complexity of the Dinic's algorithm $O(\#E^{3/2}) = O((PN)^{3/2})$. + +\subsubsection*{Metrics} + +We can display the flow value of $\tilde{f}$, which is an upper bound of the distance between $\alpha$ and $\alpha'$. It might be more a Debug level display than Info. + +\subsection{Minimization of the transfer load} + +Now that we have a candidate flow function $f$, we want to modify it to make its associated assignment as close as possible to $\alpha'$. Denote by $f'$ the maximal flow associated to $\alpha'$, and let $d(f, f')$ be distance between the associated assignments\footnote{It is the number of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$ saturated in one flow and not in the other.}. +We want to build a sequence $f=f_0, f_1, f_2 \dots$ of maximal flows such that $d(f_i, \alpha')$ decreases as $i$ increases. The distance being a non-negative integer, this sequence of flow functions must be finite. We now explain how to find some improving $f_{i+1}$ from $f_i$. + +For any maximal flow $f$ in $G$, we define the oriented weighted graph $G_f=(V, E_f)$ as follows. The vertices of $G_f$ are the same as the vertices of $G$. $E_f$ contains the arc $(v_1,v_2, w)$ between vertices $v_1,v_2\in V$ with weight $w$ if and only if the arc $(v_1,v_2)$ is not saturated in $f$ (i.e. $c(v_1,v_2)-f(v_1,v_2) \ge 1$, we also consider reversed arcs). The weight $w$ is: +\begin{itemize} + \item $-1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in only one of the two flows $f,f'$; + \item $+1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in either both or none of the two flows $f,f'$; + \item $0$ otherwise. +\end{itemize} + +If $\gamma$ is a simple cycle of arcs in $G_f$, we define its weight $w(\gamma)$ as the sum of the weights of its arcs. We can add $+1$ to the value of $f$ on the arcs of $\gamma$, and by construction of $G_f$ and the fact that $\gamma$ is a cycle, the function that we get is still a valid flow function on $G$, it is maximal as it has the same flow value as $f$. We denote this new function $f+\gamma$. + +\begin{proposition} + Given a maximal flow $f$ and a simple cycle $\gamma$ in $G_f$, we have $d(f+\gamma, f') - d(f,f') = w(\gamma)$. +\end{proposition} +\begin{proof} + Let $X$ be the set of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$. Then we can express $d(f,f')$ as + \begin{align*} + d(f,f') & = \#\{e\in X ~|~ f(e)\neq f'(e)\} + = \sum_{e\in X} 1_{f(e)\neq f'(e)} \\ + & = \frac{1}{2}\big( \#X + \sum_{e\in X} 1_{f(e)\neq f'(e)} - 1_{f(e)= f'(e)} \big). + \end{align*} + We can express the cycle weight as + \begin{align*} + w(\gamma) & = \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)}. + \end{align*} + Remark that since we passed on unit of flow in $\gamma$ to construct $f+\gamma$, we have for any $e\in X$, $f(e)=f'(e)$ if and only if $(f+\gamma)(e) \neq f'(e)$. + Hence + \begin{align*} + w(\gamma) & = \frac{1}{2}(w(\gamma) + w(\gamma)) \\ + &= \frac{1}{2} \Big( + \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)} \\ + & \qquad + + \sum_{e\in X, e\in \gamma} 1_{(f+\gamma)(e)\neq f'(e)} + 1_{(f+\gamma)(e)= f'(e)} + \Big). + \end{align*} + Plugging this in the previous equation, we find that + $$d(f,f')+w(\gamma) = d(f+\gamma, f').$$ +\end{proof} + +This result suggests that given some flow $f_i$, we just need to find a negative cycle $\gamma$ in $G_{f_i}$ to construct $f_{i+1}$ as $f_i+\gamma$. The following proposition ensures that this greedy strategy reaches an optimal flow. + +\begin{proposition} + For any maximal flow $f$, $G_f$ contains a negative cycle if and only if there exists a maximal flow $f^*$ in $G$ such that $d(f^*, f') < d(f, f')$. +\end{proposition} +\begin{proof} + Suppose that there is such flow $f^*$. Define the oriented multigraph $M_{f,f^*}=(V,E_M)$ with the same vertex set $V$ as in $G$, and for every $v_1,v_2 \in V$, $E_M$ contains $(f^*(v_1,v_2) - f(v_1,v_2))_+$ copies of the arc $(v_1,v_2)$. For every vertex $v$, its total degree (meaning its outer degree minus its inner degree) is equal to + \begin{align*} + \deg v & = \sum_{u\in V} (f^*(v,u) - f(v,u))_+ - \sum_{u\in V} (f^*(u,v) - f(u,v))_+ \\ + & = \sum_{u\in V} f^*(v,u) - f(v,u) = \sum_{u\in V} f^*(v,u) - \sum_{u\in V} f(v,u). + \end{align*} + The last two sums are zero for any inner vertex since $f,f^*$ are flows, and they are equal on the source and sink since the two flows are both maximal and have hence the same value. Thus, $\deg v = 0$ for every vertex $v$. + + This implies that the multigraph $M_{f,f^*}$ is the union of disjoint simple cycles. $f$ can be transformed into $f^*$ by pushing a mass 1 along all these cycles in any order. Since $d(f^*, f') Date: Wed, 21 Sep 2022 14:39:59 +0200 Subject: New version of the algorithm that calculate the layout. It takes as paramters the replication factor and the zone redundancy, computes the largest partition size reachable with these constraints, and among the possible assignation with this partition size, it computes the one that moves the least number of partitions compared to the previous assignation. This computation uses graph algorithms defined in graph_algo.rs --- doc/optimal_layout_report/optimal_layout.pdf | Bin 395187 -> 395308 bytes doc/optimal_layout_report/optimal_layout.tex | 17 ++++++++--------- 2 files changed, 8 insertions(+), 9 deletions(-) (limited to 'doc') diff --git a/doc/optimal_layout_report/optimal_layout.pdf b/doc/optimal_layout_report/optimal_layout.pdf index c85803e8..0af34161 100644 Binary files a/doc/optimal_layout_report/optimal_layout.pdf and b/doc/optimal_layout_report/optimal_layout.pdf differ diff --git a/doc/optimal_layout_report/optimal_layout.tex b/doc/optimal_layout_report/optimal_layout.tex index b2898adb..005e7b50 100644 --- a/doc/optimal_layout_report/optimal_layout.tex +++ b/doc/optimal_layout_report/optimal_layout.tex @@ -100,13 +100,12 @@ Again, we will represent an assignment $\alpha$ as a flow in a specific graph $G Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$. The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices -$\mathbf{p, p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$. +$\mathbf{p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$. The set of arcs $E$ contains: \begin{itemize} - \item ($\mathbf{s}$,$\mathbf{p}$, $\rho_\mathbf{N}$) for every partition $p$; - \item ($\mathbf{p}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$; - \item ($\mathbf{p}$,$\mathbf{p}^+$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$; + \item ($\mathbf{s}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$; + \item ($\mathbf{s}$,$\mathbf{p}^-$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$; \item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$; \item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$; \item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$; @@ -119,7 +118,7 @@ In the following complexity calculations, we will use the number of vertices and An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$. \end{proposition} \begin{proof} - Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through every $\mathbf{p}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes. + Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through $\mathbf{p^+}$ and $\mathbf{p^-}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes. In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$. \end{proof} @@ -272,16 +271,16 @@ The distance $d(f,f')$ is bounded by the maximal number of differences in the as The detection of negative cycle is done with the Bellman-Ford algorithm, whose complexity should normally be $O(\#E\#V)$. In our case, it amounts to $O(P^2ZN)$. Multiplied by the complexity of the outer loop, it amounts to $O(P^3ZN)$ which is a lot when the number of partitions and nodes starts to be large. To avoid that, we adapt the Bellman-Ford algorithm. -The Bellman-Ford algorithm runs $\#V$ iterations of an outer loop, and an inner loop over $E$. The idea is to compute the shortest paths from a source vertex $v$ to all other vertices. After $k$ iterations of the outer loop, the algorithm has computed all shortest path of length at most $k$. All shortest path have length at most $\#V$, so if there is an update in the last iteration of the loop, it means that there is a negative cycle in the graph. The observation that will enable us to improve the complexity is the following: +The Bellman-Ford algorithm runs $\#V$ iterations of an outer loop, and an inner loop over $E$. The idea is to compute the shortest paths from a source vertex $v$ to all other vertices. After $k$ iterations of the outer loop, the algorithm has computed all shortest path of length at most $k$. All simple paths have length at most $\#V-1$, so if there is an update in the last iteration of the loop, it means that there is a negative cycle in the graph. The observation that will enable us to improve the complexity is the following: \begin{proposition} - In the graph $G_f$ (and $G$), all simple paths and cycles have a length at most $6N$. + In the graph $G_f$ (and $G$), all simple paths have a length at most $4N$. \end{proposition} \begin{proof} - Since $f$ is a maximal flow, there is no outgoing edge from $\mathbf{s}$ in $G_f$. One can thus check than any simple path of length 6 must contain at least to node of type $\mathbf{n}$. Hence on a cycle, at most 6 arcs separate two successive nodes of type $\mathbf{n}$. + Since $f$ is a maximal flow, there is no outgoing edge from $\mathbf{s}$ in $G_f$. One can thus check than any simple path of length 4 must contain at least two node of type $\mathbf{n}$. Hence on a path, at most 4 arcs separate two successive nodes of type $\mathbf{n}$. \end{proof} -Thus, in the absence of negative cycles, shortest paths in $G_f$ have length at most $6N$. So we can do only $6N$ iterations of the outer loop in Bellman-Ford algorithm. This makes the complexity of the detection of one set of cycle to be $O(N\#E) = O(N^2 P)$. +Thus, in the absence of negative cycles, shortest paths in $G_f$ have length at most $4N$. So we can do only $4N+1$ iterations of the outer loop in Bellman-Ford algorithm. This makes the complexity of the detection of one set of cycle to be $O(N\#E) = O(N^2 P)$. With this improvement, the complexity of the whole algorithm is, in the worst case, $O(N^2P^2)$. However, since we detect several cycles at once and we start with a flow that might be close to the previous one, the number of iterations of the outer loop might be smaller in practice. -- cgit v1.2.3 From 8be862aa193ebe3081d1a74c3c5fc493ae9c82b0 Mon Sep 17 00:00:00 2001 From: Jonathan Davies Date: Mon, 2 Jan 2023 13:35:26 +0000 Subject: Changed all instances of 'key new' to 'key create' to make it consistent as bucket commands issued normally around the same time. --- doc/book/connect/apps/index.md | 8 ++++---- doc/book/connect/backup.md | 2 +- doc/book/connect/repositories.md | 4 ++-- doc/book/quick-start/_index.md | 2 +- 4 files changed, 8 insertions(+), 8 deletions(-) (limited to 'doc') diff --git a/doc/book/connect/apps/index.md b/doc/book/connect/apps/index.md index 737351a0..78d9310d 100644 --- a/doc/book/connect/apps/index.md +++ b/doc/book/connect/apps/index.md @@ -36,7 +36,7 @@ Second, we suppose you have created a key and a bucket. As a reminder, you can create a key for your nextcloud instance as follow: ```bash -garage key new --name nextcloud-key +garage key create nextcloud-key ``` Keep the Key ID and the Secret key in a pad, they will be needed later. @@ -138,7 +138,7 @@ a reasonable trade-off for some instances. Create a key for Peertube: ```bash -garage key new --name peertube-key +garage key create peertube-key ``` Keep the Key ID and the Secret key in a pad, they will be needed later. @@ -252,7 +252,7 @@ As such, your Garage cluster should be configured appropriately for good perform This is the usual Garage setup: ```bash -garage key new --name mastodon-key +garage key create mastodon-key garage bucket create mastodon-data garage bucket allow mastodon-data --read --write --key mastodon-key ``` @@ -378,7 +378,7 @@ Supposing you have a working synapse installation, you can add the module with p Now create a bucket and a key for your matrix instance (note your Key ID and Secret Key somewhere, they will be needed later): ```bash -garage key new --name matrix-key +garage key create matrix-key garage bucket create matrix garage bucket allow matrix --read --write --key matrix-key ``` diff --git a/doc/book/connect/backup.md b/doc/book/connect/backup.md index 48a2d7be..919e78c3 100644 --- a/doc/book/connect/backup.md +++ b/doc/book/connect/backup.md @@ -20,7 +20,7 @@ If you still want to use Borg, you can use it with `rclone mount`. Create your key and bucket: ```bash -garage key new my-key +garage key create my-key garage bucket create backup garage bucket allow backup --read --write --key my-key ``` diff --git a/doc/book/connect/repositories.md b/doc/book/connect/repositories.md index 4b14bb46..66365d64 100644 --- a/doc/book/connect/repositories.md +++ b/doc/book/connect/repositories.md @@ -23,7 +23,7 @@ You can configure a different target for each data type (check `[lfs]` and `[att Let's start by creating a key and a bucket (your key id and secret will be needed later, keep them somewhere): ```bash -garage key new --name gitea-key +garage key create gitea-key garage bucket create gitea garage bucket allow gitea --read --write --key gitea-key ``` @@ -118,7 +118,7 @@ through another support, like a git repository. As a first step, we will need to create a bucket on Garage and enabling website access on it: ```bash -garage key new --name nix-key +garage key create nix-key garage bucket create nix.example.com garage bucket allow nix.example.com --read --write --key nix-key garage bucket website nix.example.com --allow diff --git a/doc/book/quick-start/_index.md b/doc/book/quick-start/_index.md index ac55d2f7..ab83b75a 100644 --- a/doc/book/quick-start/_index.md +++ b/doc/book/quick-start/_index.md @@ -206,7 +206,7 @@ one key can access multiple buckets, multiple keys can access one bucket. Create an API key using the following command: ``` -garage key new --name nextcloud-app-key +garage key create nextcloud-app-key ``` The output should look as follows: -- cgit v1.2.3 From e3cc7a89b063aa40de96ee788288ae9b51cc1522 Mon Sep 17 00:00:00 2001 From: Mendes Date: Mon, 9 Jan 2023 16:05:20 +0100 Subject: First draft of t a preprint describing the layout computation algorithm --- .../figures/flow_graph_param.pdf | Bin 0 -> 33269 bytes .../figures/flow_graph_param.svg | 7817 ++++++++++++++++++++ doc/optimal_layout_report/geodistrib.pdf | Bin 0 -> 358520 bytes doc/optimal_layout_report/geodistrib.tex | 317 + 4 files changed, 8134 insertions(+) create mode 100644 doc/optimal_layout_report/figures/flow_graph_param.pdf create mode 100644 doc/optimal_layout_report/figures/flow_graph_param.svg create mode 100644 doc/optimal_layout_report/geodistrib.pdf create mode 100644 doc/optimal_layout_report/geodistrib.tex (limited to 'doc') diff --git 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+\usepackage{amsmath,amssymb} +\usepackage{amsthm} + +\usepackage{stmaryrd} + +\usepackage{graphicx,xcolor} +\usepackage{hyperref} + +\usepackage{algorithm,algpseudocode,float} + +\renewcommand\thesubsubsection{\Alph{subsubsection})} + +\newtheorem{proposition}{Proposition} + +%opening +\title{An algorithm for geo-distributed and redundant storage in Garage} +\author{Mendes Oulamara \\ \emph{mendes@deuxfleurs.fr}} +\date{} + +\begin{document} + +\maketitle + +\begin{abstract} + Garage +\end{abstract} + +\section{Introduction} + +Garage\footnote{\url{https://garagehq.deuxfleurs.fr/}} is an open-source distributed object storage service tailored for self-hosting. It was designed by the Deuxfleurs association\footnote{\url{https://deuxfleurs.fr/}} to enable small structures (associations, collectives, small companies) to share storage resources to reliably self-host their data, possibly with old and non-reliable machines. + +To achieve these reliability and availability goals, the data is broken into \emph{partitions} and every partition is replicated over 3 different machines (that we call \emph{nodes}). When the data is queried, a consensus algorithm allows to fetch it from one of the nodes. A \emph{replication factor} of 3 ensures the best guarantees in the consensus algorithm \cite{ADD RREF}, but this parameter can be different. + +Moreover, if the nodes are spread over different \emph{zones} (different houses, offices, cities\dots), we can ask the data to be replicated over nodes belonging to different zones, to improve the storage robustness against zone failure (such as power outage). To do so, we set a \emph{redundancy parameter}, that is no more than the replication factor, and we ask that any partition is replicated over this number of zones at least. + +In this work, we propose a repartition algorithm that, given the nodes specifications and the replication and redundancy parameters, computes an optimal assignation of partitions to nodes. We say that the assignation is optimal in the sense that it maximizes the size of the partitions, and hence the effective storage capacity of the system. + +Moreover, when a former assignation exists, which is not optimal anymore due to nodes or zones updates, our algorithm computes a new optimal assignation that minimizes the amount of data to be transferred during the assignation update (the \emph{transfer load}). + +We call the set of nodes cooperating to store the data a \emph{cluster}, and a description of the nodes, zones and the assignation of partitions to nodes a \emph{cluster layout} + +\subsection{Notations} + +Let $k$ be some fixed parameter value, typically 8, that we call the ``partition bits''. +Every object to be stored in the system is split into data blocks of fixed size. We compute a hash $h(\mathbf{b})$ of every such block $\mathbf{b}$, and we define the $k$ last bits of this hash to be the partition number $p(\mathbf{b})$ of the block. This label can take $P=2^k$ different values, and hence there are $P$ different partitions. We denote $\mathbf{P}$ the set of partition labels (i.e. $\mathbf{P}=\llbracket1,P\rrbracket$). + +We are given a set $\mathbf{N}$ of $N$ nodes and a set $\mathbf{Z}$ of $Z$ zones. Every node $n$ has a non-negative storage capacity $c_n\ge 0$ and belongs to a zone $z_n\in \mathbf{Z}$. We are also given a replication parameter $\rho_\mathbf{N}$ and a redundancy parameter $\rho_\mathbf{Z}$ such that $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$ (typical values would be $\rho_N=3$ and $\rho_Z=2$). + +Our goal is to compute an assignment $\alpha = (\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}})_{p\in \mathbf{P}}$ such that every partition $p$ is associated to $\rho_\mathbf{N}$ distinct nodes $\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}} \in \mathbf{N}$ and these nodes belong to at least $\rho_\mathbf{Z}$ distinct zones. Among the possible assignations, we choose one that \emph{maximizes} the effective storage capacity of the cluster. If the layout contained a previous assignment $\alpha'$, we \emph{minimize} the amount of data to transfer during the layout update by making $\alpha$ as close as possible to $\alpha'$. These maximization and minimization are described more formally in the following section. + +\subsection{Optimization parameters} + +To link the effective storage capacity of the cluster to partition assignment, we make the following assumption: +\begin{equation} + \tag{H1} + \text{\emph{All partitions have the same size $s$.}} +\end{equation} +This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored blocks. + +Every node $n$ wille store some number $p_n$ of partitions (it is the number of partitions $p$ such that $n$ appears in the $\alpha_p$). Hence the partitions stored by $n$ (and hence all partitions by our assumption) have there size bounded by $c_n/p_n$. This remark leads us to define the optimal size that we will want to maximize: + +\begin{equation} + \label{eq:optimal} + \tag{OPT} +s^* = \min_{n \in N} \frac{c_n}{p_n}. +\end{equation} + +When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption: +\begin{equation} + \tag{H2} + \text{\emph{Nodes updates happen rarely relatively to block operations.}} +\end{equation} +This assumption justifies that when we compute the new assignment $\alpha$, it is worth to optimize the partition size \eqref{eq:optimal} first, and then, among the possible optimal solution, to try to minimize the number of partition transfers. More formally, we minimize the distance between two assignments defined by +\begin{equation} + d(\alpha, \alpha') := \#\{ (n,p) \in \mathbf{N}\times\mathbf{P} ~|~ n\in \alpha_p \triangle \alpha'_p \} +\end{equation} +where the symmetric difference $\alpha_p \triangle \alpha'_p$ denotes the nodes appearing in one of the assignations but not in both. + +\section{Computation of an optimal assignment} + +The algorithm that we propose takes as inputs the cluster layout parameters $\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, that we defined in the introduction, together with the former assignation $\alpha'$ (if any). The computation of the new optimal assignation $\alpha^*$ is done in three successive steps that will be detailed in the following sections. The first step computes the largest partition size $s^*$ that an assignation can achieve. The second step computes an optimal candidate assignment $\alpha$ that achieves $s^*$ and a heuristic is used in the computation to make it hopefully close to $\alpha'$. The third steps modifies $\alpha$ iteratively to reduces $d(\alpha, \alpha')$ and yields an assignation $\alpha^*$ achieving $s^*$, and minimizing $d(\cdot, \alpha')$ among such assignations. + +We will explain in the next section how to represent an assignment $\alpha$ by a flow $f$ on a weighted graph $G$ to enable the use of flow and graph algorithms. The main function of the algorithm can be written as follows. + +\subsubsection*{Algorithm} + +\begin{algorithmic}[1] + \Function{Compute Layout}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, $\alpha'$} + \State $s^* \leftarrow$ \Call{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$} + \State $G \leftarrow G(s^*)$ + \State $f \leftarrow$ \Call{Compute Candidate Assignment}{$G$, $\alpha'$} + \State $f^* \leftarrow$ \Call{Minimize transfer load}{$G$, $f$, $\alpha'$} + \State Build $\alpha^*$ from $f^*$ + \State \Return $\alpha^*$ + \EndFunction +\end{algorithmic} + +\subsubsection*{Complexity} +As we will see in the next sections, the worst case complexity of this algorithm is $O(P^2 N^2)$. The minimization of transfer load is the most expensive step, and it can run with a timeout since it is only an optimization step. Without this step (or with a smart timeout), the worst cas complexity can be $O((PN)^{3/2}\log C)$ where $C$ is the total storage capacity of the cluster. + +\subsection{Determination of the partition size $s^*$} + +We will represent an assignment $\alpha$ as a flow in a specific graph $G$. We will not compute the optimal partition size $s^*$ a priori, but we will determine it by dichotomy, as the largest size $s$ such that the maximal flow achievable on $G=G(s)$ has value $\rho_\mathbf{N}P$. We will assume that the capacities are given in a small enough unit (say, Megabytes), and we will determine $s^*$ at the precision of the given unit. + +Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$ (see Figure \ref{fig:flowgraph}). + +The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices +$\mathbf{p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$. + +The set of arcs $E$ contains: +\begin{itemize} + \item ($\mathbf{s}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$; + \item ($\mathbf{s}$,$\mathbf{p}^-$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$; + \item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$; + \item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$; + \item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$; + \item ($\mathbf{n}$, $\mathbf{t}$, $\lfloor c_n/s \rfloor$) for every node $n$. +\end{itemize} + +\begin{figure} + \centering + \includegraphics[width=\linewidth]{figures/flow_graph_param} + \caption{An example of graph $G(s)$. Arcs are oriented from left to right, and unlabeled arcs have capacity 1. In this example, nodes $n_1,n_2,n_3$ belong to zone $z_1$, and nodes $n_4,n_5$ belong to zone $z_2$.} + \label{fig:flowgraph} +\end{figure} + +In the following complexity calculations, we will use the number of vertices and edges of $G$. Remark from now that $\# V = O(PZ)$ and $\# E = O(PN)$. + +\begin{proposition} + An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$. +\end{proposition} +\begin{proof} + Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through $\mathbf{p^+}$ and $\mathbf{p^-}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes. + + In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$. +\end{proof} + +\textbf{Implementation remark:} In the flow algorithm, while exploring the graph, we explore the neighbours of every vertex in a random order to heuristically spread the associations between nodes and partitions. + +\subsubsection*{Algorithm} +With this result mind, we can describe the first step of our algorithm. All divisions are supposed to be integer divisions. +\begin{algorithmic}[1] + \Function{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$} + + \State Build the graph $G=G(s=1)$ + \State $ f \leftarrow$ \Call{Maximal flow}{$G$} + \If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$} + + \State \Return Error: capacities too small or constraints too strong. + \EndIf + + \State $s^- \leftarrow 1$ + \State $s^+ \leftarrow 1+\frac{1}{\rho_\mathbf{N}}\sum_{n \in \mathbf{N}} c_n$ + + \While{$s^-+1 < s^+$} + \State Build the graph $G=G(s=(s^-+s^+)/2)$ + \State $ f \leftarrow$ \Call{Maximal flow}{$G$} + \If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$} + \State $s^+ \leftarrow (s^- + s^+)/2$ + \Else + \State $s^- \leftarrow (s^- + s^+)/2$ + \EndIf + \EndWhile + + \State \Return $s^-$ + \EndFunction +\end{algorithmic} + +\subsubsection*{Complexity} + +To compute the maximal flow, we use Dinic's algorithm. Its complexity on general graphs is $O(\#V^2 \#E)$, but on graphs with edge capacity bounded by a constant, it turns out to be $O(\#E^{3/2})$. The graph $G$ does not fall in this case since the capacities of the arcs incoming to $\mathbf{t}$ are far from bounded. However, the proof of this complexity function works readily for graphs where we only ask the edges \emph{not} incoming to the sink $\mathbf{t}$ to have their capacities bounded by a constant. One can find the proof of this claim in \cite[Section 2]{even1975network}. +The dichotomy adds a logarithmic factor $\log (C)$ where $C=\sum_{n \in \mathbf{N}} c_n$ is the total capacity of the cluster. The total complexity of this first function is hence +$O(\#E^{3/2}\log C ) = O\big((PN)^{3/2} \log C\big)$. + +\subsubsection*{Metrics} +We can display the discrepancy between the computed $s^*$ and the best size we could have hoped for the given total capacity, that is $C/\rho_\mathbf{N}$. + +\subsection{Computation of a candidate assignment} + +Now that we have the optimal partition size $s^*$, to compute a candidate assignment it would be enough to compute a maximal flow function $f$ on $G(s^*)$. This is what we do if there is no former assignation $\alpha'$. + +If there is some $\alpha'$, we add a step that will heuristically help to obtain a candidate $\alpha$ closer to $\alpha'$. We fist compute a flow function $\tilde{f}$ that uses only the partition-to-node associations appearing in $\alpha'$. Most likely, $\tilde{f}$ will not be a maximal flow of $G(s^*)$. In Dinic's algorithm, we can start from a non maximal flow function and then discover improving paths. This is what we do by starting from $\tilde{f}$. The hope\footnote{This is only a hope, because one can find examples where the construction of $f$ from $\tilde{f}$ produces an assignment $\alpha$ that is not as close as possible to $\alpha'$.} is that the final flow function $f$ will tend to keep the associations appearing in $\tilde{f}$. + +More formally, we construct the graph $G_{|\alpha'}$ from $G$ by removing all the arcs $(\mathbf{x}_{p,z},\mathbf{n}, 1)$ where $p$ is not associated to $n$ in $\alpha'$. We compute a maximal flow function $\tilde{f}$ in $G_{|\alpha'}$. The flow $\tilde{f}$ is also a valid (most likely non maximal) flow function on $G$. We compute a maximal flow function $f$ on $G$ by starting Dinic's algorithm on $\tilde{f}$. + +\subsubsection*{Algorithm} +\begin{algorithmic}[1] + \Function{Compute Candidate Assignment}{$G$, $\alpha'$} + \State Build the graph $G_{|\alpha'}$ + \State $ \tilde{f} \leftarrow$ \Call{Maximal flow}{$G_{|\alpha'}$} + \State $ f \leftarrow$ \Call{Maximal flow from flow}{$G$, $\tilde{f}$} + \State \Return $f$ + \EndFunction +\end{algorithmic} + +~ + +\textbf{Remark:} The function ``Maximal flow'' can be just seen as the function ``Maximal flow from flow'' called with the zero flow function as starting flow. + +\subsubsection*{Complexity} +With the considerations of the last section, we have the complexity of the Dinic's algorithm $O(\#E^{3/2}) = O((PN)^{3/2})$. + +\subsubsection*{Metrics} + +We can display the flow value of $\tilde{f}$, which is an upper bound of the distance between $\alpha$ and $\alpha'$. It might be more a Debug level display than Info. + +\subsection{Minimization of the transfer load} + +Now that we have a candidate flow function $f$, we want to modify it to make its corresponding assignation $\alpha$ as close as possible to $\alpha'$. Denote by $f'$ the maximal flow corresponding to $\alpha'$, and let $d(f, \alpha')=d(f, f'):=d(\alpha,\alpha')$\footnote{It is the number of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$ saturated in one flow and not in the other.}. +We want to build a sequence $f=f_0, f_1, f_2 \dots$ of maximal flows such that $d(f_i, \alpha')$ decreases as $i$ increases. The distance being a non-negative integer, this sequence of flow functions must be finite. We now explain how to find some improving $f_{i+1}$ from $f_i$. + +For any maximal flow $f$ in $G$, we define the oriented weighted graph $G_f=(V, E_f)$ as follows. The vertices of $G_f$ are the same as the vertices of $G$. $E_f$ contains the arc $(v_1,v_2, w)$ between vertices $v_1,v_2\in V$ with weight $w$ if and only if the arc $(v_1,v_2)$ is not saturated in $f$ (i.e. $c(v_1,v_2)-f(v_1,v_2) \ge 1$, we also consider reversed arcs). The weight $w$ is: +\begin{itemize} + \item $-1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in only one of the two flows $f,f'$; + \item $+1$ if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in either both or none of the two flows $f,f'$; + \item $0$ otherwise. +\end{itemize} + +If $\gamma$ is a simple cycle of arcs in $G_f$, we define its weight $w(\gamma)$ as the sum of the weights of its arcs. We can add $+1$ to the value of $f$ on the arcs of $\gamma$, and by construction of $G_f$ and the fact that $\gamma$ is a cycle, the function that we get is still a valid flow function on $G$, it is maximal as it has the same flow value as $f$. We denote this new function $f+\gamma$. + +\begin{proposition} + Given a maximal flow $f$ and a simple cycle $\gamma$ in $G_f$, we have $d(f+\gamma, f') - d(f,f') = w(\gamma)$. +\end{proposition} +\begin{proof} + Let $X$ be the set of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$. Then we can express $d(f,f')$ as + \begin{align*} + d(f,f') & = \#\{e\in X ~|~ f(e)\neq f'(e)\} + = \sum_{e\in X} 1_{f(e)\neq f'(e)} \\ + & = \frac{1}{2}\big( \#X + \sum_{e\in X} 1_{f(e)\neq f'(e)} - 1_{f(e)= f'(e)} \big). + \end{align*} + We can express the cycle weight as + \begin{align*} + w(\gamma) & = \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)}. + \end{align*} + Remark that since we passed on unit of flow in $\gamma$ to construct $f+\gamma$, we have for any $e\in X$, $f(e)=f'(e)$ if and only if $(f+\gamma)(e) \neq f'(e)$. + Hence + \begin{align*} + w(\gamma) & = \frac{1}{2}(w(\gamma) + w(\gamma)) \\ + &= \frac{1}{2} \Big( + \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)} \\ + & \qquad + + \sum_{e\in X, e\in \gamma} 1_{(f+\gamma)(e)\neq f'(e)} + 1_{(f+\gamma)(e)= f'(e)} + \Big). + \end{align*} + Plugging this in the previous equation, we find that + $$d(f,f')+w(\gamma) = d(f+\gamma, f').$$ +\end{proof} + +This result suggests that given some flow $f_i$, we just need to find a negative cycle $\gamma$ in $G_{f_i}$ to construct $f_{i+1}$ as $f_i+\gamma$. The following proposition ensures that this greedy strategy reaches an optimal flow. + +\begin{proposition} + For any maximal flow $f$, $G_f$ contains a negative cycle if and only if there exists a maximal flow $f^*$ in $G$ such that $d(f^*, f') < d(f, f')$. +\end{proposition} +\begin{proof} + Suppose that there is such flow $f^*$. Define the oriented multigraph $M_{f,f^*}=(V,E_M)$ with the same vertex set $V$ as in $G$, and for every $v_1,v_2 \in V$, $E_M$ contains $(f^*(v_1,v_2) - f(v_1,v_2))_+$ copies of the arc $(v_1,v_2)$. For every vertex $v$, its total degree (meaning its outer degree minus its inner degree) is equal to + \begin{align*} + \deg v & = \sum_{u\in V} (f^*(v,u) - f(v,u))_+ - \sum_{u\in V} (f^*(u,v) - f(u,v))_+ \\ + & = \sum_{u\in V} f^*(v,u) - f(v,u) = \sum_{u\in V} f^*(v,u) - \sum_{u\in V} f(v,u). + \end{align*} + The last two sums are zero for any inner vertex since $f,f^*$ are flows, and they are equal on the source and sink since the two flows are both maximal and have hence the same value. Thus, $\deg v = 0$ for every vertex $v$. + + This implies that the multigraph $M_{f,f^*}$ is the union of disjoint simple cycles. $f$ can be transformed into $f^*$ by pushing a mass 1 along all these cycles in any order. Since $d(f^*, f') Date: Mon, 9 Jan 2023 16:06:47 +0100 Subject: change in gitignore --- doc/optimal_layout_report/.gitignore | 8 ++++++++ 1 file changed, 8 insertions(+) (limited to 'doc') diff --git a/doc/optimal_layout_report/.gitignore b/doc/optimal_layout_report/.gitignore index 52deb7ad..d5e59136 100644 --- a/doc/optimal_layout_report/.gitignore +++ b/doc/optimal_layout_report/.gitignore @@ -3,3 +3,11 @@ optimal_layout.log optimal_layout.synctex.gz optimal_layout.bbl optimal_layout.blg + +geodistrib.aux +geodistrib.bbl +geodistrib.blg +geodistrib.log +geodistrib.out +geodistrib.synctex.gz + -- cgit v1.2.3 From e7e164a280dfc1c4adf9d6da6f3b2a9674eca4bd Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Fri, 9 Jun 2023 16:23:21 +0200 Subject: Make fsync an option for meta and data --- doc/book/reference-manual/configuration.md | 45 ++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) (limited to 'doc') diff --git a/doc/book/reference-manual/configuration.md b/doc/book/reference-manual/configuration.md index 38062bab..de253393 100644 --- a/doc/book/reference-manual/configuration.md +++ b/doc/book/reference-manual/configuration.md @@ -10,6 +10,8 @@ Here is an example `garage.toml` configuration file that illustrates all of the ```toml metadata_dir = "/var/lib/garage/meta" data_dir = "/var/lib/garage/data" +metadata_fsync = true +data_fsync = false db_engine = "lmdb" @@ -124,6 +126,49 @@ convert-db -a -i \ Make sure to specify the full database path as presented in the table above, and not just the path to the metadata directory. +### `metadata_fsync` + +Whether to enable synchronous mode for the database engine or not. +This is disabled (`false`) by default. + +This reduces the risk of metadata corruption in case of power failures, +at the cost of a significant drop in write performance, +as Garage will have to pause to sync data to disk much more often +(several times for API calls such as PutObject). + +Using this option reduces the risk of simultaneous metadata corruption on several +cluster nodes, which could lead to data loss. + +If multi-site replication is used, this option is most likely not necessary, as +it is extremely unlikely that two nodes in different locations will have a +power failure at the exact same time. + +(Metadata corruption on a single node is not an issue, the corrupted data file +can always be deleted and reconstructed from the other nodes in the cluster.) + +Here is how this option impacts the different database engines: + +| Database | `metadata_fsync = false` (default) | `metadata_fsync = true` | +|----------|------------------------------------|-------------------------------| +| Sled | default options | *unsupported* | +| Sqlite | `PRAGMA synchronous = OFF` | `PRAGMA synchronous = NORMAL` | +| LMDB | `MDB_NOMETASYNC` + `MDB_NOSYNC` | `MDB_NOMETASYNC` | + +Note that the Sqlite database is always ran in `WAL` mode (`PRAGMA journal_mode = WAL`). + +### `data_fsync` + +Whether to `fsync` data blocks and their containing directory after they are +saved to disk. +This is disabled (`false`) by default. + +This might reduce the risk that a data block is lost in rare +situations such as simultaneous node losing power, +at the cost of a moderate drop in write performance. + +Similarly to `metatada_fsync`, this is likely not necessary +if geographical replication is used. + ### `block_size` Garage splits stored objects in consecutive chunks of size `block_size` -- cgit v1.2.3 From 511e07ecd489fa72040171fe908323873a57ac19 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 4 May 2023 11:49:23 +0200 Subject: fix mpu counter (add missing workers) and report info at appropriate places --- doc/drafts/admin-api.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index 9a697a59..e0252f71 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -535,7 +535,10 @@ Example response: ], "objects": 14827, "bytes": 13189855625, - "unfinshedUploads": 0, + "unfinishedUploads": 1, + "unfinishedMultipartUploads": 1, + "unfinishedMultipartUploadParts": 11, + "unfinishedMultipartUploadBytes": 41943040, "quotas": { "maxSize": null, "maxObjects": null -- cgit v1.2.3 From 52376d47caf747f5cf93a21e5c15e4e6b8d991ee Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 13:45:27 +0200 Subject: admin api: change cluster status/layout to use lists and not maps (fix #377) --- doc/drafts/admin-api.md | 119 ++++++++++++++++++++++++++++++++---------------- 1 file changed, 80 insertions(+), 39 deletions(-) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index e0252f71..b1a8f402 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -56,7 +56,7 @@ See `/v0/health` for an API that also returns JSON output. ### Cluster operations -#### GetClusterStatus `GET /v0/status` +#### GetClusterStatus `GET /v1/status` Returns the cluster's current status in JSON, including: @@ -70,67 +70,93 @@ Example response body: ```json { "node": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f", - "garage_version": "git:v0.8.0", - "knownNodes": { - "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": { + "garageVersion": "git:v0.9.0-dev", + "garageFeatures": [ + "k2v", + "sled", + "lmdb", + "sqlite", + "metrics", + "bundled-libs" + ], + "rustVersion": "1.68.0", + "dbEngine": "LMDB (using Heed crate)", + "knownNodes": [ + { + "id": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f", "addr": "10.0.0.11:3901", "is_up": true, "last_seen_secs_ago": 9, "hostname": "node1" }, - "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": { + { + "id": "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff", "addr": "10.0.0.12:3901", "is_up": true, "last_seen_secs_ago": 1, "hostname": "node2" }, - "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": { + { + "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27", "addr": "10.0.0.21:3901", "is_up": true, "last_seen_secs_ago": 7, "hostname": "node3" }, - "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": { + { + "id": "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b", "addr": "10.0.0.22:3901", "is_up": true, "last_seen_secs_ago": 1, "hostname": "node4" } - }, + ], "layout": { "version": 12, - "roles": { - "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": { + "roles": [ + { + "id": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f", "zone": "dc1", - "capacity": 4, + "capacity": 10737418240, "tags": [ "node1" ] }, - "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": { + { + "id": "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff", "zone": "dc1", - "capacity": 6, + "capacity": 10737418240, "tags": [ "node2" ] }, - "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": { + { + "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27", "zone": "dc2", - "capacity": 10, + "capacity": 10737418240, "tags": [ "node3" ] } - }, - "stagedRoleChanges": { - "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": { + ], + "stagedRoleChanges": [ + { + "id": "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b", + "remove": false, "zone": "dc2", - "capacity": 5, + "capacity": 10737418240, "tags": [ "node4" ] } - } + { + "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27", + "remove": true, + "zone": null, + "capacity": null, + "tags": null, + } + ] } } ``` @@ -198,7 +224,7 @@ Example response: ] ``` -#### GetClusterLayout `GET /v0/layout` +#### GetClusterLayout `GET /v1/layout` Returns the cluster's current layout in JSON, including: @@ -212,42 +238,54 @@ Example response body: ```json { "version": 12, - "roles": { - "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": { + "roles": [ + { + "id": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f", "zone": "dc1", - "capacity": 4, + "capacity": 10737418240, "tags": [ "node1" ] }, - "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": { + { + "id": "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff", "zone": "dc1", - "capacity": 6, + "capacity": 10737418240, "tags": [ "node2" ] }, - "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": { + { + "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27", "zone": "dc2", - "capacity": 10, + "capacity": 10737418240, "tags": [ "node3" ] } - }, - "stagedRoleChanges": { - "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": { + ], + "stagedRoleChanges": [ + { + "id": "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b", + "remove": false, "zone": "dc2", - "capacity": 5, + "capacity": 10737418240, "tags": [ "node4" ] } - } + { + "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27", + "remove": true, + "zone": null, + "capacity": null, + "tags": null, + } + ] } ``` -#### UpdateClusterLayout `POST /v0/layout` +#### UpdateClusterLayout `POST /v1/layout` Send modifications to the cluster layout. These modifications will be included in the staged role changes, visible in subsequent calls @@ -259,8 +297,9 @@ the layout. Request body format: ```json -{ - : { +[ + { + "id": , "capacity": , "zone": , "tags": [ @@ -268,9 +307,11 @@ Request body format: ... ] }, - : null, - ... -} + { + "id": , + "remove": true + } +] ``` Contrary to the CLI that may update only a subset of the fields -- cgit v1.2.3 From 35c108b85d2b70ad28cd93bfd412607a89b9acf9 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 13:53:19 +0200 Subject: admin api: switch GetClusterHealth to camelcase (fix #381 again) --- doc/drafts/admin-api.md | 40 ++++++++++++++++++++-------------------- 1 file changed, 20 insertions(+), 20 deletions(-) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index b1a8f402..c80147ef 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -52,7 +52,7 @@ Returns an HTTP status 200 if the node is ready to answer user's requests, and an HTTP status 503 (Service Unavailable) if there are some partitions for which a quorum of nodes is not available. A simple textual message is also returned in a body with content-type `text/plain`. -See `/v0/health` for an API that also returns JSON output. +See `/v1/health` for an API that also returns JSON output. ### Cluster operations @@ -161,21 +161,21 @@ Example response body: } ``` -#### GetClusterHealth `GET /v0/health` +#### GetClusterHealth `GET /v1/health` Returns the cluster's current health in JSON format, with the following variables: -- `status`: one of `Healthy`, `Degraded` or `Unavailable`: - - Healthy: Garage node is connected to all storage nodes - - Degraded: Garage node is not connected to all storage nodes, but a quorum of write nodes is available for all partitions - - Unavailable: a quorum of write nodes is not available for some partitions -- `known_nodes`: the number of nodes this Garage node has had a TCP connection to since the daemon started -- `connected_nodes`: the nubmer of nodes this Garage node currently has an open connection to -- `storage_nodes`: the number of storage nodes currently registered in the cluster layout -- `storage_nodes_ok`: the number of storage nodes to which a connection is currently open +- `status`: one of `healthy`, `degraded` or `unavailable`: + - healthy: Garage node is connected to all storage nodes + - degraded: Garage node is not connected to all storage nodes, but a quorum of write nodes is available for all partitions + - unavailable: a quorum of write nodes is not available for some partitions +- `knownNodes`: the number of nodes this Garage node has had a TCP connection to since the daemon started +- `connectedNodes`: the nubmer of nodes this Garage node currently has an open connection to +- `storageNodes`: the number of storage nodes currently registered in the cluster layout +- `storageNodesOk`: the number of storage nodes to which a connection is currently open - `partitions`: the total number of partitions of the data (currently always 256) -- `partitions_quorum`: the number of partitions for which a quorum of write nodes is available -- `partitions_all_ok`: the number of partitions for which we are connected to all storage nodes responsible of storing it +- `partitionsQuorum`: the number of partitions for which a quorum of write nodes is available +- `partitionsAllOk`: the number of partitions for which we are connected to all storage nodes responsible of storing it Contrarily to `GET /health`, this endpoint always returns a 200 OK HTTP response code. @@ -183,14 +183,14 @@ Example response body: ```json { - "status": "Degraded", - "known_nodes": 3, - "connected_nodes": 2, - "storage_nodes": 3, - "storage_nodes_ok": 2, - "partitions": 256, - "partitions_quorum": 256, - "partitions_all_ok": 0 + "status": "degraded", + "knownNodes": 3, + "connectedNodes": 3, + "storageNodes": 4, + "storageNodesOk": 3, + "partitions": 256, + "partitionsQuorum": 256, + "partitionsAllOk": 64 } ``` -- cgit v1.2.3 From 2c83006608aba91c9520d75cec3bcc3787c274b2 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 13:54:34 +0200 Subject: admin api: fix doc in drafts --- doc/drafts/admin-api.md | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index c80147ef..668de1bd 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -85,29 +85,29 @@ Example response body: { "id": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f", "addr": "10.0.0.11:3901", - "is_up": true, - "last_seen_secs_ago": 9, + "isUp": true, + "lastSeenSecsAgo": 9, "hostname": "node1" }, { "id": "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff", "addr": "10.0.0.12:3901", - "is_up": true, - "last_seen_secs_ago": 1, + "isUp": true, + "lastSeenSecsAgo": 1, "hostname": "node2" }, { "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27", "addr": "10.0.0.21:3901", - "is_up": true, - "last_seen_secs_ago": 7, + "isUp": true, + "lastSeenSecsAgo": 7, "hostname": "node3" }, { "id": "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b", "addr": "10.0.0.22:3901", - "is_up": true, - "last_seen_secs_ago": 1, + "isUp": true, + "lastSeenSecsAgo": 1, "hostname": "node4" } ], -- cgit v1.2.3 From 4a82f6380e6a7d7c841477fc914fd96e6c09adad Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 14:15:51 +0200 Subject: admin api: move all endpoints to v1/ by default (v0/ still supported) --- doc/drafts/admin-api.md | 44 ++++++++++++++++++++++---------------------- 1 file changed, 22 insertions(+), 22 deletions(-) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index 668de1bd..79ea7e8c 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -194,7 +194,7 @@ Example response body: } ``` -#### ConnectClusterNodes `POST /v0/connect` +#### ConnectClusterNodes `POST /v1/connect` Instructs this Garage node to connect to other Garage nodes at specified addresses. @@ -319,7 +319,7 @@ Contrary to the CLI that may update only a subset of the fields values must be specified. -#### ApplyClusterLayout `POST /v0/layout/apply` +#### ApplyClusterLayout `POST /v1/layout/apply` Applies to the cluster the layout changes currently registered as staged layout changes. @@ -336,7 +336,7 @@ Similarly to the CLI, the body must include the version of the new layout that will be created, which MUST be 1 + the value of the currently existing layout in the cluster. -#### RevertClusterLayout `POST /v0/layout/revert` +#### RevertClusterLayout `POST /v1/layout/revert` Clears all of the staged layout changes. @@ -357,7 +357,7 @@ existing layout in the cluster. ### Access key operations -#### ListKeys `GET /v0/key` +#### ListKeys `GET /v1/key` Returns all API access keys in the cluster. @@ -376,7 +376,7 @@ Example response: ] ``` -#### CreateKey `POST /v0/key` +#### CreateKey `POST /v1/key` Creates a new API access key. @@ -388,7 +388,7 @@ Request body format: } ``` -#### ImportKey `POST /v0/key/import` +#### ImportKey `POST /v1/key/import` Imports an existing API key. @@ -402,8 +402,8 @@ Request body format: } ``` -#### GetKeyInfo `GET /v0/key?id=` -#### GetKeyInfo `GET /v0/key?search=` +#### GetKeyInfo `GET /v1/key?id=` +#### GetKeyInfo `GET /v1/key?search=` Returns information about the requested API access key. @@ -474,11 +474,11 @@ Example response: } ``` -#### DeleteKey `DELETE /v0/key?id=` +#### DeleteKey `DELETE /v1/key?id=` Deletes an API access key. -#### UpdateKey `POST /v0/key?id=` +#### UpdateKey `POST /v1/key?id=` Updates information about the specified API access key. @@ -501,7 +501,7 @@ The possible flags in `allow` and `deny` are: `createBucket`. ### Bucket operations -#### ListBuckets `GET /v0/bucket` +#### ListBuckets `GET /v1/bucket` Returns all storage buckets in the cluster. @@ -543,8 +543,8 @@ Example response: ] ``` -#### GetBucketInfo `GET /v0/bucket?id=` -#### GetBucketInfo `GET /v0/bucket?globalAlias=` +#### GetBucketInfo `GET /v1/bucket?id=` +#### GetBucketInfo `GET /v1/bucket?globalAlias=` Returns information about the requested storage bucket. @@ -587,7 +587,7 @@ Example response: } ``` -#### CreateBucket `POST /v0/bucket` +#### CreateBucket `POST /v1/bucket` Creates a new storage bucket. @@ -627,13 +627,13 @@ or no alias at all. Technically, you can also specify both `globalAlias` and `localAlias` and that would create two aliases, but I don't see why you would want to do that. -#### DeleteBucket `DELETE /v0/bucket?id=` +#### DeleteBucket `DELETE /v1/bucket?id=` Deletes a storage bucket. A bucket cannot be deleted if it is not empty. Warning: this will delete all aliases associated with the bucket! -#### UpdateBucket `PUT /v0/bucket?id=` +#### UpdateBucket `PUT /v1/bucket?id=` Updates configuration of the given bucket. @@ -667,7 +667,7 @@ to change only one of the two quotas. ### Operations on permissions for keys on buckets -#### BucketAllowKey `POST /v0/bucket/allow` +#### BucketAllowKey `POST /v1/bucket/allow` Allows a key to do read/write/owner operations on a bucket. @@ -688,7 +688,7 @@ Request body format: Flags in `permissions` which have the value `true` will be activated. Other flags will remain unchanged. -#### BucketDenyKey `POST /v0/bucket/deny` +#### BucketDenyKey `POST /v1/bucket/deny` Denies a key from doing read/write/owner operations on a bucket. @@ -712,19 +712,19 @@ Other flags will remain unchanged. ### Operations on bucket aliases -#### GlobalAliasBucket `PUT /v0/bucket/alias/global?id=&alias=` +#### GlobalAliasBucket `PUT /v1/bucket/alias/global?id=&alias=` Empty body. Creates a global alias for a bucket. -#### GlobalUnaliasBucket `DELETE /v0/bucket/alias/global?id=&alias=` +#### GlobalUnaliasBucket `DELETE /v1/bucket/alias/global?id=&alias=` Removes a global alias for a bucket. -#### LocalAliasBucket `PUT /v0/bucket/alias/local?id=&accessKeyId=&alias=` +#### LocalAliasBucket `PUT /v1/bucket/alias/local?id=&accessKeyId=&alias=` Empty body. Creates a local alias for a bucket in the namespace of a specific access key. -#### LocalUnaliasBucket `DELETE /v0/bucket/alias/local?id=&accessKeyId&alias=` +#### LocalUnaliasBucket `DELETE /v1/bucket/alias/local?id=&accessKeyId&alias=` Removes a local alias for a bucket in the namespace of a specific access key. -- cgit v1.2.3 From 7895f99d3afc6e97f62f52abe06a6ee8d0f0617f Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 16:56:15 +0200 Subject: admin and cli: hide secret keys unless asked --- doc/drafts/admin-api.md | 3 +++ 1 file changed, 3 insertions(+) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index 79ea7e8c..340f4583 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -411,6 +411,9 @@ If `id` is set, the key is looked up using its exact identifier (faster). If `search` is set, the key is looked up using its name or prefix of identifier (slower, all keys are enumerated to do this). +Optionnally, the query parameter `showSecretKey=true` can be set to reveal the +associated secret access key. + Example response: ```json -- cgit v1.2.3 From a83a092c032058728f191119de99f38844aa74f5 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 17:12:37 +0200 Subject: admin: uniformize layout api and improve code --- doc/drafts/admin-api.md | 14 ++++++++++++++ 1 file changed, 14 insertions(+) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index 340f4583..cb491945 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -318,6 +318,9 @@ Contrary to the CLI that may update only a subset of the fields `capacity`, `zone` and `tags`, when calling this API all of these values must be specified. +This returns the new cluster layout with the proposed staged changes, +as returned by GetClusterLayout. + #### ApplyClusterLayout `POST /v1/layout/apply` @@ -336,6 +339,9 @@ Similarly to the CLI, the body must include the version of the new layout that will be created, which MUST be 1 + the value of the currently existing layout in the cluster. +This returns the message describing all the calculations done to compute the new +layout, as well as the description of the layout as returned by GetClusterLayout. + #### RevertClusterLayout `POST /v1/layout/revert` Clears all of the staged layout changes. @@ -354,6 +360,8 @@ Similarly to the CLI, the body must include the incremented version number, which MUST be 1 + the value of the currently existing layout in the cluster. +This returns the new cluster layout with all changes reverted, +as returned by GetClusterLayout. ### Access key operations @@ -388,6 +396,9 @@ Request body format: } ``` +This returns the key info, including the created secret key, +in the same format as the result of GetKeyInfo. + #### ImportKey `POST /v1/key/import` Imports an existing API key. @@ -402,6 +413,8 @@ Request body format: } ``` +This returns the key info in the same format as the result of GetKeyInfo. + #### GetKeyInfo `GET /v1/key?id=` #### GetKeyInfo `GET /v1/key?search=` @@ -501,6 +514,7 @@ All fields (`name`, `allow` and `deny`) are optionnal. If they are present, the corresponding modifications are applied to the key, otherwise nothing is changed. The possible flags in `allow` and `deny` are: `createBucket`. +This returns the key info in the same format as the result of GetKeyInfo. ### Bucket operations -- cgit v1.2.3 From 8ef42c9609bcefc642cc9739acb921dffba49b89 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 14 Jun 2023 17:13:41 +0200 Subject: admin docs: reformatting, key admin: add check --- doc/drafts/admin-api.md | 83 ++++++++++++++++++++++++++----------------------- 1 file changed, 44 insertions(+), 39 deletions(-) (limited to 'doc') diff --git a/doc/drafts/admin-api.md b/doc/drafts/admin-api.md index cb491945..572595db 100644 --- a/doc/drafts/admin-api.md +++ b/doc/drafts/admin-api.md @@ -363,6 +363,7 @@ existing layout in the cluster. This returns the new cluster layout with all changes reverted, as returned by GetClusterLayout. + ### Access key operations #### ListKeys `GET /v1/key` @@ -384,37 +385,6 @@ Example response: ] ``` -#### CreateKey `POST /v1/key` - -Creates a new API access key. - -Request body format: - -```json -{ - "name": "NameOfMyKey" -} -``` - -This returns the key info, including the created secret key, -in the same format as the result of GetKeyInfo. - -#### ImportKey `POST /v1/key/import` - -Imports an existing API key. - -Request body format: - -```json -{ - "accessKeyId": "GK31c2f218a2e44f485b94239e", - "secretAccessKey": "b892c0665f0ada8a4755dae98baa3b133590e11dae3bcc1f9d769d67f16c3835", - "name": "NameOfMyKey" -} -``` - -This returns the key info in the same format as the result of GetKeyInfo. - #### GetKeyInfo `GET /v1/key?id=` #### GetKeyInfo `GET /v1/key?search=` @@ -490,9 +460,38 @@ Example response: } ``` -#### DeleteKey `DELETE /v1/key?id=` +#### CreateKey `POST /v1/key` -Deletes an API access key. +Creates a new API access key. + +Request body format: + +```json +{ + "name": "NameOfMyKey" +} +``` + +This returns the key info, including the created secret key, +in the same format as the result of GetKeyInfo. + +#### ImportKey `POST /v1/key/import` + +Imports an existing API key. +This will check that the imported key is in the valid format, i.e. +is a key that could have been generated by Garage. + +Request body format: + +```json +{ + "accessKeyId": "GK31c2f218a2e44f485b94239e", + "secretAccessKey": "b892c0665f0ada8a4755dae98baa3b133590e11dae3bcc1f9d769d67f16c3835", + "name": "NameOfMyKey" +} +``` + +This returns the key info in the same format as the result of GetKeyInfo. #### UpdateKey `POST /v1/key?id=` @@ -516,6 +515,11 @@ The possible flags in `allow` and `deny` are: `createBucket`. This returns the key info in the same format as the result of GetKeyInfo. +#### DeleteKey `DELETE /v1/key?id=` + +Deletes an API access key. + + ### Bucket operations #### ListBuckets `GET /v1/bucket` @@ -644,12 +648,6 @@ or no alias at all. Technically, you can also specify both `globalAlias` and `localAlias` and that would create two aliases, but I don't see why you would want to do that. -#### DeleteBucket `DELETE /v1/bucket?id=` - -Deletes a storage bucket. A bucket cannot be deleted if it is not empty. - -Warning: this will delete all aliases associated with the bucket! - #### UpdateBucket `PUT /v1/bucket?id=` Updates configuration of the given bucket. @@ -682,6 +680,13 @@ In `quotas`: new values of `maxSize` and `maxObjects` must both be specified, or to remove the quotas. An absent value will be considered the same as a `null`. It is not possible to change only one of the two quotas. +#### DeleteBucket `DELETE /v1/bucket?id=` + +Deletes a storage bucket. A bucket cannot be deleted if it is not empty. + +Warning: this will delete all aliases associated with the bucket! + + ### Operations on permissions for keys on buckets #### BucketAllowKey `POST /v1/bucket/allow` -- cgit v1.2.3 From 5c923d48d732649eef4f51fc9d5cb14fde3d4ca8 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 30 Aug 2023 23:24:28 +0200 Subject: reference manual: document support for lifecycle configuration --- doc/book/reference-manual/s3-compatibility.md | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) (limited to 'doc') diff --git a/doc/book/reference-manual/s3-compatibility.md b/doc/book/reference-manual/s3-compatibility.md index 15b29bd1..ace4dc36 100644 --- a/doc/book/reference-manual/s3-compatibility.md +++ b/doc/book/reference-manual/s3-compatibility.md @@ -127,15 +127,22 @@ If you need this feature, please [share your use case in our dedicated issue](ht | Endpoint | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) | |------------------------------|----------------------------------|-----------------|---------------|---------|-----| -| [DeleteBucketLifecycle](https://docs.aws.amazon.com/AmazonS3/latest/API/API_DeleteBucketLifecycle.html) | ❌ Missing | ❌| ✅| ❌| ✅| -| [GetBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketLifecycleConfiguration.html) | ❌ Missing | ❌| ✅ | ❌| ✅| -| [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketLifecycleConfiguration.html) | ❌ Missing | ❌| ✅ | ❌| ✅| +| [DeleteBucketLifecycle](https://docs.aws.amazon.com/AmazonS3/latest/API/API_DeleteBucketLifecycle.html) | ✅ Implemented | ❌| ✅| ❌| ✅| +| [GetBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketLifecycleConfiguration.html) | ✅ Implemented | ❌| ✅ | ❌| ✅| +| [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketLifecycleConfiguration.html) | ⚠ Partially implemented (see below) | ❌| ✅ | ❌| ✅| | [GetBucketVersioning](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketVersioning.html) | ❌ Stub (see below) | ✅| ✅ | ❌| ✅| | [ListObjectVersions](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListObjectVersions.html) | ❌ Missing | ❌| ✅ | ❌| ✅| | [PutBucketVersioning](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketVersioning.html) | ❌ Missing | ❌| ✅| ❌| ✅| +**PutBucketLifecycleConfiguration:** The only actions supported are +`AbortIncompleteMultipartUpload` and `Expiration` (without the +`ExpiredObjectDeleteMarker` field). All other operations are dependent on +either bucket versionning or storage classes which Garage currently does not +implement. The deprecated `Prefix` member directly in the the `Rule` +structure/XML tag is not supported, specified prefixes must be inside the +`Filter` structure/XML tag. -**GetBucketVersioning:** Stub implementation (Garage does not yet support versionning so this always returns "versionning not enabled"). +**GetBucketVersioning:** Stub implementation which always returns "versionning not enabled", since Garage does not yet support bucket versionning. ### Replication endpoints -- cgit v1.2.3 From d94f1c9178da4c346f35c27e4451d1b115b9acfb Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Wed, 30 Aug 2023 23:27:02 +0200 Subject: reference manual: remove obsolete caveat about multipart uploads --- doc/book/reference-manual/s3-compatibility.md | 17 +++++++---------- 1 file changed, 7 insertions(+), 10 deletions(-) (limited to 'doc') diff --git a/doc/book/reference-manual/s3-compatibility.md b/doc/book/reference-manual/s3-compatibility.md index ace4dc36..1bcfd123 100644 --- a/doc/book/reference-manual/s3-compatibility.md +++ b/doc/book/reference-manual/s3-compatibility.md @@ -75,16 +75,13 @@ but these endpoints are documented in [Red Hat Ceph Storage - Chapter 2. Ceph Ob | Endpoint | Garage | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) | |------------------------------|----------------------------------|-----------------|---------------|---------|-----| -| [AbortMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_AbortMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | -| [CompleteMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CompleteMultipartUpload.html) | ✅ Implemented (see details below) | ✅ | ✅ | ✅ | ✅ | -| [CreateMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CreateMultipartUpload.html) | ✅ Implemented | ✅| ✅ | ✅ | ✅ | -| [ListMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | -| [ListParts](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListParts.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | -| [UploadPart](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPart.html) | ✅ Implemented (see details below) | ✅ | ✅| ✅ | ✅ | -| [UploadPartCopy](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPartCopy.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | - -Our implementation of Multipart Upload is currently a bit more restrictive than Amazon's one in some edge cases. -For more information, please refer to our [issue tracker](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/204). +| [AbortMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_AbortMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | +| [CompleteMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CompleteMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | +| [CreateMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CreateMultipartUpload.html) | ✅ Implemented | ✅| ✅ | ✅ | ✅ | +| [ListMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListMultipartUpload.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | +| [ListParts](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListParts.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | +| [UploadPart](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPart.html) | ✅ Implemented | ✅ | ✅| ✅ | ✅ | +| [UploadPartCopy](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPartCopy.html) | ✅ Implemented | ✅ | ✅ | ✅ | ✅ | ### Website endpoints -- cgit v1.2.3 From bca347a1e8e4bb74e744ec8e020b8144c6cafdf3 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 7 Sep 2023 12:52:44 +0200 Subject: doc: update page on upgradin clusters --- doc/book/operations/upgrading.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'doc') diff --git a/doc/book/operations/upgrading.md b/doc/book/operations/upgrading.md index e8919a19..9a738282 100644 --- a/doc/book/operations/upgrading.md +++ b/doc/book/operations/upgrading.md @@ -80,6 +80,6 @@ The entire procedure would look something like this: 5. If any specific migration procedure is required, it is usually in one of the two cases: - It can be run on online nodes after the new version has started, during regular cluster operation. - - it has to be run offline + - it has to be run offline, in which case you will have to again take all nodes offline one after the other to run the repair For this last step, please refer to the specific documentation pertaining to the version upgrade you are doing. -- cgit v1.2.3 From 6595efd82fc849c97b964969b6ff935738e7d24a Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 7 Sep 2023 13:23:02 +0200 Subject: Document multi-hdd support --- doc/book/cookbook/real-world.md | 11 +--- doc/book/operations/multi-hdd.md | 100 +++++++++++++++++++++++++++++ doc/book/reference-manual/configuration.md | 13 ++++ 3 files changed, 116 insertions(+), 8 deletions(-) create mode 100644 doc/book/operations/multi-hdd.md (limited to 'doc') diff --git a/doc/book/cookbook/real-world.md b/doc/book/cookbook/real-world.md index 7061069f..a8fbb371 100644 --- a/doc/book/cookbook/real-world.md +++ b/doc/book/cookbook/real-world.md @@ -75,16 +75,11 @@ to store 2 TB of data in total. - For the metadata storage, Garage does not do checksumming and integrity verification on its own. If you are afraid of bitrot/data corruption, - put your metadata directory on a BTRFS partition. Otherwise, just use regular + put your metadata directory on a ZFS or BTRFS partition. Otherwise, just use regular EXT4 or XFS. -- Having a single server with several storage drives is currently not very well - supported in Garage ([#218](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/218)). - For an easy setup, just put all your drives in a RAID0 or a ZFS RAIDZ array. - If you're adventurous, you can try to format each of your disk as - a separate XFS partition, and then run one `garage` daemon per disk drive, - or use something like [`mergerfs`](https://github.com/trapexit/mergerfs) to merge - all your disks in a single union filesystem that spreads load over them. +- Servers with multiple HDDs are supported natively by Garage without resorting + to RAID, see [our dedicated documentation page](@/documentation/operations/multi-hdd.md). ## Get a Docker image diff --git a/doc/book/operations/multi-hdd.md b/doc/book/operations/multi-hdd.md new file mode 100644 index 00000000..5f952262 --- /dev/null +++ b/doc/book/operations/multi-hdd.md @@ -0,0 +1,100 @@ ++++ +title = "Multi-HDD support" +weight = 15 ++++ + + +Since v0.9, Garage natively supports nodes that have several storage drives +for storing data blocks (not for metadata storage). + +## Initial setup + +To set up a new Garage storage node with multiple HDDs, +format and mount all your drives in different directories, +and use a Garage configuration as follows: + +```toml +data_dir = [ + { path = "/path/to/hdd1", capacity = "2T" }, + { path = "/path/to/hdd2", capacity = "4T" }, +] +``` + +Garage will automatically balance all blocks stored by the node +among the different specified directories, proportionnally to the +specified capacities. + +## Updating the list of storage locations + +If you add new storage locations to your `data_dir`, +Garage will not rebalance existing data between storage locations. +Newly written blocks will be balanced proportionnally to the specified capacities, +and existing data may be moved between drives to improve balancing, +but only opportunistically when a data block is re-written (e.g. an object +is re-uploaded, or an object with a duplicate block is uploaded). + +To understand precisely what is happening, we need to dive in to how Garage +splits data among the different storage locations. + +First of all, Garage divides the set of all possible block hashes +in a fixed number of slices (currently 1024), and assigns +to each slice a primary storage location among the specified data directories. +The number of slices having their primary location in each data directory +is proportionnal to the capacity specified in the config file. + +When Garage receives a block to write, it will always write it in the primary +directory of the slice that contains its hash. + +Now, to be able to not lose existing data blocks when storage locations +are added, Garage also keeps a list of secondary data directories +for all of the hash slices. Secondary data directories for a slice indicates +storage locations that once were primary directories for that slice, i.e. where +Garage knows that data blocks of that slice might be stored. +When Garage is requested to read a certain data block, +it will first look in the primary storage directory of its slice, +and if it doesn't find it there it goes through all of the secondary storage +locations until it finds it. This allows Garage to continue operating +normally when storage locations are added, without having to shuffle +files between drives to place them in the correct location. + +This relatively simple strategy works well but does not ensure that data +is correctly balanced among drives according to their capacity. +To rebalance data, two strategies can be used: + +- Lazy rebalancing: when a block is re-written (e.g. the object is re-uploaded), + Garage checks whether the existing copy is in the primary directory of the slice + or in a secondary directory. If the current copy is in a secondary directory, + Garage re-writes a copy in the primary directory and deletes the one from the + secondary directory. + +- Active rebalancing: an operator of a Garage node can explicitly launch a repair + procedure that rebalances the data directories, moving all blocks to their + primary location. Once done, all secondary locations for all hash slices are + removed so that they won't be checked anymore when looking for a data block. + +## Read-only storage locations + +If you would like to move all data blocks from an existing data directory to one +or several new data directories, mark the old directory as read-only: + +```toml +data_dir = [ + { path = "/path/to/old_data", read_only = true }, + { path = "/path/to/new_hdd1", capacity = "2T" }, + { path = "/path/to/new_hdd2", capacity = "4T" }, +] +``` + +Garage will be able to read requested blocks from the read-only directory. +Garage will also move data out of the read-only directory either progressively +(lazy rebalancing) or if requested explicitly (active rebalancing). + +Once an active rebalancing has finished, your read-only directory should be empty: +it might still contain subdirectories, but no data files. You can check that +it contains no files using: + +```bash +find -type f /path/to/old_data +``` + +at which point it can be removed from the `data_dir` list in your config file. diff --git a/doc/book/reference-manual/configuration.md b/doc/book/reference-manual/configuration.md index 3f6ec091..df1251c2 100644 --- a/doc/book/reference-manual/configuration.md +++ b/doc/book/reference-manual/configuration.md @@ -91,6 +91,19 @@ This folder can be placed on an HDD. The space available for `data_dir` should be counted to determine a node's capacity when [adding it to the cluster layout](@/documentation/cookbook/real-world.md). +Since `v0.9.0`, Garage supports multiple data directories with the following syntax: + +```toml +data_dir = [ + { path = "/path/to/old_data", read_only = true }, + { path = "/path/to/new_hdd1", capacity = "2T" }, + { path = "/path/to/new_hdd2", capacity = "4T" }, +] +``` + +See [the dedicated documentation page](@/documentation/operations/multi-hdd.md) +on how to operate Garage in such a setup. + ### `db_engine` (since `v0.8.0`) By default, Garage uses the Sled embedded database library -- cgit v1.2.3 From 6a067e30ee51d3ea9874e3ce18670c39edfd665b Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 7 Sep 2023 13:49:12 +0200 Subject: doc: documentation of rebalance repair --- doc/book/operations/durability-repairs.md | 10 ++++++++++ 1 file changed, 10 insertions(+) (limited to 'doc') diff --git a/doc/book/operations/durability-repairs.md b/doc/book/operations/durability-repairs.md index 498c8fda..33130952 100644 --- a/doc/book/operations/durability-repairs.md +++ b/doc/book/operations/durability-repairs.md @@ -91,6 +91,16 @@ is definitely lost, then there is no other choice than to declare your S3 object as unrecoverable, and to delete them properly from the data store. This can be done using the `garage block purge` command. +## Rebalancing data directories + +In [multi-HDD setups](@/documentation/operations/multi-hdd.md), to ensure that +data blocks are well balanced between storage locations, you may run a +rebalance operation using `garage repair rebalance`. This is usefull when +adding storage locations or when capacities of the storage locations have been +changed. Once this is finished, Garage will know for each block of a single +possible location where it can be, which can increase access speed. This +operation will also move out all data from locations marked as read-only. + # Metadata operations -- cgit v1.2.3 From eb972a8422e19e1eaf69281571f4e52f9c7794ff Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 7 Sep 2023 14:48:36 +0200 Subject: doc: update multi-hdd section --- doc/book/operations/durability-repairs.md | 1 - doc/book/operations/multi-hdd.md | 5 +++-- 2 files changed, 3 insertions(+), 3 deletions(-) (limited to 'doc') diff --git a/doc/book/operations/durability-repairs.md b/doc/book/operations/durability-repairs.md index 33130952..b0d2c78a 100644 --- a/doc/book/operations/durability-repairs.md +++ b/doc/book/operations/durability-repairs.md @@ -124,4 +124,3 @@ in your cluster, you can run one of the following repair procedures: - `garage repair versions`: checks that all versions belong to a non-deleted object, and purges any orphan version - `garage repair block_refs`: checks that all block references belong to a non-deleted object version, and purges any orphan block reference (this will then allow the blocks to be garbage-collected) - diff --git a/doc/book/operations/multi-hdd.md b/doc/book/operations/multi-hdd.md index 5f952262..36445b0a 100644 --- a/doc/book/operations/multi-hdd.md +++ b/doc/book/operations/multi-hdd.md @@ -65,7 +65,8 @@ To rebalance data, two strategies can be used: Garage checks whether the existing copy is in the primary directory of the slice or in a secondary directory. If the current copy is in a secondary directory, Garage re-writes a copy in the primary directory and deletes the one from the - secondary directory. + secondary directory. This might never end up rebalancing everything if there + are data blocks that are only read and never written. - Active rebalancing: an operator of a Garage node can explicitly launch a repair procedure that rebalances the data directories, moving all blocks to their @@ -94,7 +95,7 @@ it might still contain subdirectories, but no data files. You can check that it contains no files using: ```bash -find -type f /path/to/old_data +find -type f /path/to/old_data # should not print anything ``` at which point it can be removed from the `data_dir` list in your config file. -- cgit v1.2.3 From b4a0e636d830c7193968aaa1ec894e27596a1963 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Fri, 22 Sep 2023 09:49:07 +0200 Subject: new layout doc: add examples of unexpected layout, to explain --- doc/book/operations/layout.md | 108 ++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 108 insertions(+) (limited to 'doc') diff --git a/doc/book/operations/layout.md b/doc/book/operations/layout.md index 5e314246..39cbcc1c 100644 --- a/doc/book/operations/layout.md +++ b/doc/book/operations/layout.md @@ -75,3 +75,111 @@ If you are using the `garage` CLI to script layout changes, follow the following - **Only call `garage layout apply` once**, and call it **strictly after** all of the `layout assign` and `layout remove` commands have returned. + + +## Understanding unexpected layout calculations + + +### Example 1 + +``` +$ garage layout show +==== CURRENT CLUSTER LAYOUT ==== +ID Tags Zone Capacity Usable capacity +b10c110e4e854e5a node1 dc1 1000.0 MB 1000.0 MB (100.0%) +a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%) +62b218d848e86a64 node3 dc3 1000.0 MB 1000.0 MB (100.0%) + +Zone redundancy: maximum + +Current cluster layout version: 6 + +==== STAGED ROLE CHANGES ==== +ID Tags Zone Capacity +a11c7cf18af29737 node4 dc1 1000.0 MB + + +==== NEW CLUSTER LAYOUT AFTER APPLYING CHANGES ==== +ID Tags Zone Capacity Usable capacity +b10c110e4e854e5a node1 dc1 1000.0 MB 1000.0 MB (100.0%) +a11c7cf18af29737 node4 dc1 1000.0 MB 0 B (0.0%) +a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%) +62b218d848e86a64 node3 dc3 1000.0 MB 1000.0 MB (100.0%) + +Zone redundancy: maximum + +==== COMPUTATION OF A NEW PARTITION ASSIGNATION ==== + +Partitions are replicated 3 times on at least 3 distinct zones. + +Optimal partition size: 3.9 MB (3.9 MB in previous layout) +Usable capacity / total cluster capacity: 3.0 GB / 4.0 GB (75.0 %) +Effective capacity (replication factor 3): 1000.0 MB + +A total of 0 new copies of partitions need to be transferred. + +dc1 Tags Partitions Capacity Usable capacity + b10c110e4e854e5a node1 256 (0 new) 1000.0 MB 1000.0 MB (100.0%) + a11c7cf18af29737 node4 0 (0 new) 1000.0 MB 0 B (0.0%) + TOTAL 256 (256 unique) 2.0 GB 1000.0 MB (50.0%) + +dc2 Tags Partitions Capacity Usable capacity + a235ac7695e0c54d node2 256 (0 new) 1000.0 MB 1000.0 MB (100.0%) + TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%) + +dc3 Tags Partitions Capacity Usable capacity + 62b218d848e86a64 node3 256 (0 new) 1000.0 MB 1000.0 MB (100.0%) + TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%) +``` + +### Example 2 + +``` +==== CURRENT CLUSTER LAYOUT ==== +ID Tags Zone Capacity Usable capacity +b10c110e4e854e5a node1 dc1 1000.0 MB 500.0 MB (50.0%) +a11c7cf18af29737 node4 dc1 1000.0 MB 500.0 MB (50.0%) +a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%) +62b218d848e86a64 node3 dc3 1000.0 MB 1000.0 MB (100.0%) + +Zone redundancy: maximum + +Current cluster layout version: 8 + +==== STAGED ROLE CHANGES ==== +ID Tags Zone Capacity +a11c7cf18af29737 node4 dc3 1000.0 MB + + +==== NEW CLUSTER LAYOUT AFTER APPLYING CHANGES ==== +ID Tags Zone Capacity Usable capacity +b10c110e4e854e5a node1 dc1 1000.0 MB 1000.0 MB (100.0%) +a235ac7695e0c54d node2 dc2 1000.0 MB 1000.0 MB (100.0%) +62b218d848e86a64 node3 dc3 1000.0 MB 753.9 MB (75.4%) +a11c7cf18af29737 node4 dc3 1000.0 MB 246.1 MB (24.6%) + +Zone redundancy: maximum + +==== COMPUTATION OF A NEW PARTITION ASSIGNATION ==== + +Partitions are replicated 3 times on at least 3 distinct zones. + +Optimal partition size: 3.9 MB (3.9 MB in previous layout) +Usable capacity / total cluster capacity: 3.0 GB / 4.0 GB (75.0 %) +Effective capacity (replication factor 3): 1000.0 MB + +A total of 128 new copies of partitions need to be transferred. + +dc1 Tags Partitions Capacity Usable capacity + b10c110e4e854e5a node1 256 (128 new) 1000.0 MB 1000.0 MB (100.0%) + TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%) + +dc2 Tags Partitions Capacity Usable capacity + a235ac7695e0c54d node2 256 (0 new) 1000.0 MB 1000.0 MB (100.0%) + TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%) + +dc3 Tags Partitions Capacity Usable capacity + 62b218d848e86a64 node3 193 (0 new) 1000.0 MB 753.9 MB (75.4%) + a11c7cf18af29737 node4 63 (0 new) 1000.0 MB 246.1 MB (24.6%) + TOTAL 256 (256 unique) 2.0 GB 1000.0 MB (50.0%) +``` -- cgit v1.2.3 From 405aa42b7dae67adbb32fd0384534bb8bad555ad Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Fri, 22 Sep 2023 10:00:01 +0200 Subject: layout doc: update old text --- doc/book/operations/layout.md | 38 ++++++++++++++++++++++++++------------ 1 file changed, 26 insertions(+), 12 deletions(-) (limited to 'doc') diff --git a/doc/book/operations/layout.md b/doc/book/operations/layout.md index 39cbcc1c..93d502a7 100644 --- a/doc/book/operations/layout.md +++ b/doc/book/operations/layout.md @@ -9,18 +9,30 @@ a certain capacity, or a gateway node that does not store data and is only used as an API entry point for faster cluster access. An introduction to building cluster layouts can be found in the [production deployment](@/documentation/cookbook/real-world.md) page. +In Garage, all of the data that can be stored in a given cluster is divided +into slices which we call *partitions*. Each partition is stored by +one or several nodes in the cluster +(see [`replication_mode`](@/documentation/reference-manual/configuration.md#replication-mode)). +The layout determines the correspondence between these partition, +which exist on a logical level, and actual storage nodes. + ## How cluster layouts work in Garage -In Garage, a cluster layout is composed of the following components: +A cluster layout is composed of the following components: -- a table of roles assigned to nodes +- a table of roles assigned to nodes, defined by the user +- an optimal assignation of partitions to nodes, computed by an algorithm that is ran once when calling `garage layout apply` or the ApplyClusterLayout API endpoint - a version number Garage nodes will always use the cluster layout with the highest version number. Garage nodes also maintain and synchronize between them a set of proposed role changes that haven't yet been applied. These changes will be applied (or -canceled) in the next version of the layout +canceled) in the next version of the layout. + +All operations on the layout can be realized using the `garage` CLI or using the +[administration API endpoint](@/documentation/reference-manual/admin-api.md). +We give here a description of CLI commands, the admin API semantics are very similar. The following commands insert modifications to the set of proposed role changes for the next layout version (but they do not create the new layout immediately): @@ -51,7 +63,7 @@ commands will fail otherwise. ## Warnings about Garage cluster layout management -**Warning: never make several calls to `garage layout apply` or `garage layout +**⚠️ Never make several calls to `garage layout apply` or `garage layout revert` with the same value of the `--version` flag. Doing so can lead to the creation of several different layouts with the same version number, in which case your Garage cluster will become inconsistent until fixed.** If a call to @@ -65,16 +77,18 @@ shell, you shouldn't have much issues as long as you run commands one after the other and take care of checking the output of `garage layout show` before applying any changes. -If you are using the `garage` CLI to script layout changes, follow the following recommendations: +If you are using the `garage` CLI or the admin API to script layout changes, +follow the following recommendations: -- Make all of your `garage` CLI calls to the same RPC host. Do not use the - `garage` CLI to connect to individual nodes to send them each a piece of the - layout changes you are making, as the changes propagate asynchronously - between nodes and might not all be taken into account at the time when the - new layout is applied. +- If using the CLI, make all of your `garage` CLI calls to the same RPC host. + If using the admin API, make all of your API calls to the same Garage node. Do + not connect to individual nodes to send them each a piece of the layout changes + you are making, as the changes propagate asynchronously between nodes and might + not all be taken into account at the time when the new layout is applied. -- **Only call `garage layout apply` once**, and call it **strictly after** all - of the `layout assign` and `layout remove` commands have returned. +- **Only call `garage layout apply`/ApplyClusterLayout once**, and call it + **strictly after** all of the `layout assign` and `layout remove` + commands/UpdateClusterLayout API calls have returned. ## Understanding unexpected layout calculations -- cgit v1.2.3 From 8d07888fa2da8f72aa1e7e63bfd9ac9eb3b1e6ab Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Fri, 22 Sep 2023 16:07:46 +0200 Subject: layout doc: write explanations for bizarre scenarios --- doc/book/operations/layout.md | 74 +++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 74 insertions(+) (limited to 'doc') diff --git a/doc/book/operations/layout.md b/doc/book/operations/layout.md index 93d502a7..0eb0e215 100644 --- a/doc/book/operations/layout.md +++ b/doc/book/operations/layout.md @@ -93,9 +93,23 @@ follow the following recommendations: ## Understanding unexpected layout calculations +When adding, removing or modifying nodes in a cluster layout, sometimes +unexpected assigntations of partitions to node can occure. These assignations +are in fact normal and logical, given the objectives of the algorihtm. Indeed, +**the layout algorithm prioritizes moving less data between nodes over the fact +of achieving equal distribution of load**. This section presents two examples +and illustrates how one can control Garage's behavior to obtain the desired +results. ### Example 1 +In this example, a cluster is originally composed of 3 nodes in 3 different +zones (data centers). The three nodes are of equal capacity, therefore they +are all fully exploited and all store a copy of all of the data in the cluster. + +Then, a fourth node of the same size is added in the datacenter `dc1`. +As illustrated by the following, **Garage will by default not store any data on the new node**: + ``` $ garage layout show ==== CURRENT CLUSTER LAYOUT ==== @@ -146,8 +160,37 @@ dc3 Tags Partitions Capacity Usable capacity TOTAL 256 (256 unique) 1000.0 MB 1000.0 MB (100.0%) ``` +While unexpected, this is logical because of the following facts: + +- storing some data on the new node does not help increase the total quantity + of data that can be stored on the cluster, as the two other zones (`dc2` and + `dc3`) still need to store a full copy of everything, and their capacity is + still the same; + +- there is therefore no need to move any data on the new node as this would be pointless; + +- moving data to the new node has a cost which the algorithm decides to not pay if not necessary. + +This distribution of data can however not be what the administrator wanted: if +they added a new node to `dc1`, it might be because the existing node is too +slow, and they wish to divide its load by half. In that case, what they need to +do to force Garage to distribute the data between the two nodes is to attribute +only half of the capacity to each node in `dc1` (in our example, 500M instead of 1G). +In that case, Garage would determine that to be able to store 1G in total, it +would need to store 500M on the old node and 500M on the added one. + + ### Example 2 +The following example is a slightly different scenario, where `dc1` had two +nodes that were used at 50%, and `dc2` and `dc3` each have one node that is +100% used. All node capacities are the same. + +Then, a node from `dc1` is moved into `dc3`. One could expect that the roles of +`dc1` and `dc3` would simply be swapped: the remaining node in `dc1` would be +used at 100%, and the two nodes now in `dc3` would be used at 50%. Instead, +this happens: + ``` ==== CURRENT CLUSTER LAYOUT ==== ID Tags Zone Capacity Usable capacity @@ -197,3 +240,34 @@ dc3 Tags Partitions Capacity Usable capacity a11c7cf18af29737 node4 63 (0 new) 1000.0 MB 246.1 MB (24.6%) TOTAL 256 (256 unique) 2.0 GB 1000.0 MB (50.0%) ``` + +As we can see, the node that was moved to `dc3` (node4) is only used at 25% (approximatively), +whereas the node that was already in `dc3` (node3) is used at 75%. + +This can be explained by the following: + +- node1 will now be the only node remaining in `dc1`, thus it has to store all + of the data in the cluster. Since it was storing only half of it before, it has + to retrieve the other half from other nodes in the cluster. + +- The data which it does not have is entirely stored by the other node that was + in `dc1` and that is now in `dc3` (node4). There is also a copy of it on node2 + and node3 since both these nodes have a copy of everything. + +- node3 and node4 are the two nodes that will now be in a datacenter that is + under-utilized (`dc3`), this means that those are the two candidates from which + data can be removed to be moved to node1. + +- Garage will move data in equal proportions from all possible sources, in this + case it means that it will tranfer 25% of the entire data set from node3 to + node1 and another 25% from node4 to node1. + +This explains why node3 ends with 75% utilization (100% from before minus 25% +that is moved to node1), and node4 ends with 25% (50% from before minus 25% +that is moved to node1). + +This illustrates another principle of the layout computation: **if there is a +choice in moving data out of some nodes, then all links between pairs of nodes +are used in equal proportions** (this is approximately true, there is +randomness in the algorihtm to achieve this so there might be some small +fluctuations, as we see above). -- cgit v1.2.3 From 0e5925fff6d9b3147de4967e1963b4c785d0055f Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Fri, 22 Sep 2023 16:09:17 +0200 Subject: layout doc: reformulate --- doc/book/operations/layout.md | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) (limited to 'doc') diff --git a/doc/book/operations/layout.md b/doc/book/operations/layout.md index 0eb0e215..ece17ddb 100644 --- a/doc/book/operations/layout.md +++ b/doc/book/operations/layout.md @@ -94,12 +94,13 @@ follow the following recommendations: ## Understanding unexpected layout calculations When adding, removing or modifying nodes in a cluster layout, sometimes -unexpected assigntations of partitions to node can occure. These assignations +unexpected assigntations of partitions to node can occur. These assignations are in fact normal and logical, given the objectives of the algorihtm. Indeed, **the layout algorithm prioritizes moving less data between nodes over the fact -of achieving equal distribution of load**. This section presents two examples -and illustrates how one can control Garage's behavior to obtain the desired -results. +of achieving equal distribution of load. It also tries to use all links between +pairs of nodes in equal proportions when moving data.** This section presents +two examples and illustrates how one can control Garage's behavior to obtain +the desired results. ### Example 1 @@ -266,8 +267,8 @@ This explains why node3 ends with 75% utilization (100% from before minus 25% that is moved to node1), and node4 ends with 25% (50% from before minus 25% that is moved to node1). -This illustrates another principle of the layout computation: **if there is a -choice in moving data out of some nodes, then all links between pairs of nodes -are used in equal proportions** (this is approximately true, there is +This illustrates the second principle of the layout computation: **if there is +a choice in moving data out of some nodes, then all links between pairs of +nodes are used in equal proportions** (this is approximately true, there is randomness in the algorihtm to achieve this so there might be some small fluctuations, as we see above). -- cgit v1.2.3 From 6790e24f5a41af121f413eb2c9052d9b2438a4a0 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 5 Oct 2023 15:20:48 +0200 Subject: Add migration to v0.9 guide --- doc/book/working-documents/migration-09.md | 68 ++++++++++++++++++++++++++++++ 1 file changed, 68 insertions(+) create mode 100644 doc/book/working-documents/migration-09.md (limited to 'doc') diff --git a/doc/book/working-documents/migration-09.md b/doc/book/working-documents/migration-09.md new file mode 100644 index 00000000..b277bb9b --- /dev/null +++ b/doc/book/working-documents/migration-09.md @@ -0,0 +1,68 @@ ++++ +title = "Migrating from 0.8 to 0.9" +weight = 14 ++++ + +**This guide explains how to migrate to 0.9 if you have an existing 0.8 cluster. +We don't recommend trying to migrate to 0.9 directly from 0.7 or older.** + +**We make no guarantee that this migration will work perfectly: +back up all your data before attempting it!** + +The following are **breaking changes** in Garage v0.9 that require your attention when migrating: + +- LMDB is now the default metadata db engine and Sled is deprecated. If you were using Sled, make sure to specify `db_engine = "sled"` in your configuration file, or take the time to [convert your database](https://garagehq.deuxfleurs.fr/documentation/reference-manual/configuration/#db-engine-since-v0-8-0). + +- Capacity values are now in actual byte units. The translation from the old layout will assign 1 capacity = 1Gb by default, which might be wrong for your cluster. This does not cause any data to be moved around, but you might want to re-assign correct capacity values post-migration. + +- Multipart uploads that were started in Garage v0.8 will not be visible in Garage v0.9 and will have to be restarted from scratch. + +- Changes to the admin API: some `v0/` endpoints have been replaced by `v1/` counterparts with updated/uniformized syntax. All other endpoints have also moved to `v1/` by default, without syntax changes, but are still available under `v0/` for compatibility. + + +## Simple migration procedure (takes cluster offline for a while) + +The migration steps are as follows: + +1. Disable API and web access. You may do this by stopping your reverse proxy or by commenting out + the `api_bind_addr` values in your `config.toml` file. +2. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`, + check the logs and check that all data seems to be synced correctly between + nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.) +3. Check that the block resync queue and Merkle queue are empty: + run `garage stats -a` to query them or inspect metrics in the Grafana dashboard. +4. Turn off Garage v0.8 +5. **Backup the metadata folder of all your nodes!** For instance, use the following command + if your metadata directory is `/var/lib/garage/meta`: `cd /var/lib/garage ; tar -acf meta-v0.8.tar.zst meta/` +6. Install Garage v0.9 +7. Update your configuration file if necessary. +8. Turn on Garage v0.9 +9. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`. + Wait for a full table sync to run. +10. Your upgraded cluster should be in a working state. Re-enable API and Web + access and check that everything went well. +11. Monitor your cluster in the next hours to see if it works well under your production load, report any issue. +12. You might want to assign correct capacity values to all your nodes. Doing so might cause data to be moved + in your cluster, which should also be monitored carefully. + +## Minimal downtime migration procedure + +The migration to Garage v0.9 can be done with almost no downtime, +by restarting all nodes at once in the new version. + +The migration steps are as follows: + +1. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`, + check the logs and check that all data seems to be synced correctly between + nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.) + +2. Turn off each node individually; back up its metadata folder (see above); turn it back on again. + This will allow you to take a backup of all nodes without impacting global cluster availability. + You can do all nodes of a single zone at once as this does not impact the availability of Garage. + +3. Prepare your binaries and configuration files for Garage v0.9 + +4. Shut down all v087 nodes simultaneously, and restart them all simultaneously in v0.9. + Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to achieve this as fast as possible. + +5. Proceed with steps 9-12 above. -- cgit v1.2.3 From 2448eb771381318c5dd9f5516c606685156a3040 Mon Sep 17 00:00:00 2001 From: Alex Auvolat Date: Thu, 5 Oct 2023 15:29:55 +0200 Subject: upgrade doc: fixes and precisions --- doc/book/working-documents/migration-09.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) (limited to 'doc') diff --git a/doc/book/working-documents/migration-09.md b/doc/book/working-documents/migration-09.md index b277bb9b..8d403580 100644 --- a/doc/book/working-documents/migration-09.md +++ b/doc/book/working-documents/migration-09.md @@ -25,7 +25,7 @@ The following are **breaking changes** in Garage v0.9 that require your attentio The migration steps are as follows: 1. Disable API and web access. You may do this by stopping your reverse proxy or by commenting out - the `api_bind_addr` values in your `config.toml` file. + the `api_bind_addr` values in your `config.toml` file and restarting Garage. 2. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`, check the logs and check that all data seems to be synced correctly between nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.) @@ -62,7 +62,8 @@ The migration steps are as follows: 3. Prepare your binaries and configuration files for Garage v0.9 -4. Shut down all v087 nodes simultaneously, and restart them all simultaneously in v0.9. +4. Shut down all v0.8 nodes simultaneously, and restart them all simultaneously in v0.9. Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to achieve this as fast as possible. + Garage v0.9 should be in a working state as soon as it starts. -5. Proceed with steps 9-12 above. +5. Proceed with repair and monitoring as described in steps 9-12 above. -- cgit v1.2.3