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- - + + \ No newline at end of file diff --git a/assets/js/1c14429f.443c96ad.js b/assets/js/1c14429f.1aadb6b1.js similarity index 99% rename from assets/js/1c14429f.443c96ad.js rename to assets/js/1c14429f.1aadb6b1.js index 150778ea3..f120fe1da 100644 --- a/assets/js/1c14429f.443c96ad.js +++ b/assets/js/1c14429f.1aadb6b1.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[2702],{3905:(e,t,n)=>{n.d(t,{Zo:()=>c,kt:()=>m});var o=n(7294);function a(e,t,n){return t in e?Object.defineProperty(e,t,{value:n,enumerable:!0,configurable:!0,writable:!0}):e[t]=n,e}function r(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var o=Object.getOwnPropertySymbols(e);t&&(o=o.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,o)}return n}function i(e){for(var t=1;t=0||(a[n]=e[n]);return a}(e,t);if(Object.getOwnPropertySymbols){var 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quick Fleek Network TL;DR?",id:"need-a-quick-fleek-network-tldr",level:2},{value:"Why is Fleek Network needed?",id:"why-is-fleek-network-needed",level:2},{value:"How Does Fleek Network Work?",id:"how-does-fleek-network-work",level:2},{value:"Running a Node",id:"running-a-node",level:2},{value:"Clone the source code",id:"clone-the-source-code",level:3},{value:"Dependencies",id:"dependencies",level:3},{value:"Build",id:"build",level:3},{value:"Node Launch",id:"node-launch",level:3},{value:"Health check",id:"health-check",level:3},{value:"Next steps",id:"next-steps",level:2},{value:"Conclusion",id:"conclusion",level:2}],p={toc:u},h="wrapper";function m(e){let{components:t,...n}=e;return(0,a.kt)(h,(0,o.Z)({},p,n,{components:t,mdxType:"MDXLayout"}),(0,a.kt)("h2",{id:"introduction"},"Introduction"),(0,a.kt)("p",null,"For this guide, we\u2019ll have a simple look into how Fleek Network works in its current development phase and briefly share some of the core concepts like spinning up a node and making a request to a service to put and retrieve a .car files from the network."),(0,a.kt)("p",null,"For those seeking advanced knowledge:"),(0,a.kt)("ul",null,(0,a.kt)("li",{parentName:"ul"},"Read our ",(0,a.kt)("a",{parentName:"li",href:"/docs/whitepaper"},"whitepaper"),"."),(0,a.kt)("li",{parentName:"ul"},"Check out ",(0,a.kt)("a",{parentName:"li",href:"https://github.com/fleek-network/lightning"},"our open-source code"),".")),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"If you find any typos in our documentation, feel free to ",(0,a.kt)("a",{parentName:"p",href:"https://discord.gg/fleekxyz"},"provide us feedback")," or contribute by opening a PR in our repository ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/fleek-network-docs/"},"here"),".")),(0,a.kt)("h2",{id:"pre-requisites"},"Pre-requisites"),(0,a.kt)("p",null,"To follow the guide, you will need the following:"),(0,a.kt)("ul",null,(0,a.kt)("li",{parentName:"ul"},"Familiarity with the command-line interface"),(0,a.kt)("li",{parentName:"ul"},"Git")),(0,a.kt)("h2",{id:"need-a-quick-fleek-network-tldr"},"Need a quick Fleek Network TL;DR?"),(0,a.kt)("p",null,"Fleek Network is an open-source edge computing platform to accelerate the development and execution of the next generation of web services."),(0,a.kt)("p",null,"The system is built on a distributed network of nodes, where services run within a fair and incentivized ecosystem constituted by an open community of developers and operators. It relies on blockchain technology at its core, allowing governance and token rewards as incentives for participation in serving the network."),(0,a.kt)("p",null,"Made by an open community that's free to operate nodes or build services without the need for approvals, permissions, or intermediaries. Or simply, consume Fleek Network resources on demand, from anywhere, provided by services running on the edge."),(0,a.kt)("p",null,"Applications, platforms and protocols build and utilize decentralized services on the Fleek Network to optimize performance and reduce dependency on typical centralized cloud providers and corporate infrastructure."),(0,a.kt)("p",null,"Developers can build faster and launch better products by offloading parts of the development stack to the edge to focus on core features for the value proposition of the services being developed."),(0,a.kt)("p",null,"To get started, install a Network Node in a ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/requirements"},"supported")," Linux server, such as Debian or Ubuntu (latest) by utilizing our simple ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#assisted-installer"},"assisted installer")," to help onboard as quickly as possible."),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"Our network is open to everyone, so you're more than welcome to join us anytime without any restrictions, permission or formalities. We'd be happy to have you as part of our community!")),(0,a.kt)("p",null,"Once connected to the server, open a terminal window and execute the following command:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"curl https://get.fleek.network | bash\n")),(0,a.kt)("p",null,"Follow the install assistant recommendations to have the node ready without hassle and as quickly as possible."),(0,a.kt)("h2",{id:"why-is-fleek-network-needed"},"Why is Fleek Network needed?"),(0,a.kt)("p",null,"Web3 products typically rely on centralized cloud infrastructure, which is vulnerable to attacks as computation and data can be easily manipulated to suit business goals. However, blockchain technology has paved the way for a new era of decentralized cloud computing and data storage. The Fleek Network offers a sustainable alternative to traditional centralized architectures, providing a secure, transparent, and accessible decentralized edge computing future for everyone."),(0,a.kt)("h2",{id:"how-does-fleek-network-work"},"How Does Fleek Network Work?"),(0,a.kt)("p",null,"When a client requests a service, the protocol determines the best route to the nodes where the service replicas and workload are allocated."),(0,a.kt)("p",null,"Once the computation is successful, the data streaming routes to the client. On-client request fulfillment, a proof of delivery is generated containing cryptographically secured metadata about the original request, any parts involved and the resources consumed."),(0,a.kt)("p",null,"The Delivery Acknowledgements are stored locally in the participating node memory pools, rolled up to the protocol consensus consistently throughout the Epoch. This agreement is formed by a random committee of any healthy Nodes that use the information provided to reward the Nodes fairly."),(0,a.kt)("h2",{id:"running-a-node"},"Running a Node"),(0,a.kt)("p",null,"A Fleek Network node can be built and run on your machine. It\u2019s an ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"open-source project")," and is open for contributions."),(0,a.kt)("p",null,"The project is written with Rust, a general-purpose programming language that you need to have installed in advance to be able to follow the current guide."),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"To set up Rust, packages and library dependencies can be tricky. The quickest is to visit the ",(0,a.kt)("a",{parentName:"p",href:"https://rustup.rs/"},"rustup.rs"),". Alternatively, if you haven't already, the build section has a ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#manual-installation"},"manual installation")," document to help.")),(0,a.kt)("h3",{id:"clone-the-source-code"},"Clone the source code"),(0,a.kt)("p",null,"We\u2019ll clone the repository locally, build it and interact with the node through the binary or the HTTP JSON-RPC API with a client like cURL, but you can use a GUI (Postman, Insomnia, amongst others) if you prefer."),(0,a.kt)("admonition",{type:"note"},(0,a.kt)("p",{parentName:"admonition"},"The ~/fleek-network/lightning or $HOME/fleek-network/lightning directory is the default or recommended location to store the repository. If you like to follow conventions, then is best to stick with the recommendation, to avoid confusion and make it easier to follow our documentation.")),(0,a.kt)("p",null,"Start by cloning the repository located at ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"https://github.com/fleek-network/lightning")),(0,a.kt)(i.ZP,{mdxType:"GitCloneOptions"}),(0,a.kt)("p",null,"Once the git clone completes, you\u2019ll have the latest version at the time of cloning. You should use git to fetch or pull the latest versions consequently."),(0,a.kt)("h3",{id:"dependencies"},"Dependencies"),(0,a.kt)("p",null,"Install the required dependencies necessary for compiling general software and for our use-case Lightning CLI."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"sudo apt-get install \\\n build-essential \\\n clang \\\n pkg-config \\\n libssl-dev \\\n gcc-multilib \\\n protobuf-compiler\n")),(0,a.kt)("h3",{id:"build"},"Build"),(0,a.kt)("p",null,"Start by changing the directory to the project directory where the source code is stored. If you have followed the recommended location that'll be ",(0,a.kt)("inlineCode",{parentName:"p"},"~/fleek-network/lightning"),", as follows:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"cd ~/fleek-network/lightning\n")),(0,a.kt)("p",null,"Run the Rust package manager clean and update commands."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"cargo clean\ncargo update\n")),(0,a.kt)("p",null,"Execute the install command to build and install the Fleek Network CLI."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"cargo build\n")),(0,a.kt)("p",null,"The install command uses the Rust compiler to build; It might take a while depending on how speedy is your machine."),(0,a.kt)("p",null,"Once the Rust compiler completes, the generated binary will be available in the source code project directory. If you stick with the default, that'll look like ",(0,a.kt)("inlineCode",{parentName:"p"},"~/fleek-network/lightning/target/debug/lightning-node"),"."),(0,a.kt)("p",null,"To avoid having to specify the pathname everytime, create a symbolic link to keep it short. Here we'll name the process as the global ",(0,a.kt)("inlineCode",{parentName:"p"},"lgtn"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'sudo ln -s "~/fleek-network/lightning/target/debug/lightning-node" /usr/local/bin/lgtn\n')),(0,a.kt)("p",null,"Run the CLI with the flag ",(0,a.kt)("inlineCode",{parentName:"p"},"version")," to confirm it's available globally."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"lgtn --version\n")),(0,a.kt)("p",null,"The output should look like:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"Usage: lgtn [OPTIONS] \n\nCommands:\n run Start the node\n keys Handle keys\n print-config Print the loaded configuration\n dev-init-only Initialize the node without starting it\n dev-dump-graph Dump the infusion graph of the node instance\n help Print this message or the help of the given subcommand(s)\n\nOptions:\n -c, --config Path to the toml configuration file [default: ~/.lightning/config.toml]\n --with-mock-consensus Determines that we should be using the mock consensus backend\n -v... Increases the level of verbosity (the max level is -vvv)\n --log-location Print code location on console logs\n -h, --help Print help\n -V, --version Print version\n")),(0,a.kt)("h3",{id:"node-launch"},"Node Launch"),(0,a.kt)("p",null,"After ",(0,a.kt)("a",{parentName:"p",href:"#build"},"building"),", the node can be launched by running the subcommand ",(0,a.kt)("inlineCode",{parentName:"p"},"run"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"lgtn run\n")),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"It's highly recommend to use systemd to manage the Fleek Network service for node operators. Systemd is a system and service manager for Linux operating systems that provides a consistent way to manage system services across various distributions.")),(0,a.kt)("p",null,"Learn how to create a new Systemd service in the ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#manual-installation"},"manual installation")," document."),(0,a.kt)("h3",{id:"health-check"},"Health check"),(0,a.kt)("p",null,"It's important for Node operators to regularly check on the health of their resources to make sure everything is running smoothly. By doing this, they can get helpful feedback and know for sure if their Node is up and running. Some experienced node operators even automate this process using cronjobs and get reports sent to them via email or other custom methods."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'curl -w "\\n" localhost:4069/health\n')),(0,a.kt)("p",null,"If everything goes well, the response should be:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"OK\n")),(0,a.kt)("p",null,"Alternatively, use the JSON-RPC method ",(0,a.kt)("inlineCode",{parentName:"p"},"flk_ping"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'curl -s \\\n -X POST \\\n -H "Content-Type: application/json" \\\n -d \'{\n "jsonrpc": "2.0",\n "method": "flk_ping",\n "params": [],\n "id": 1\n }\' \\\n localhost:4069/rpc/v0\n')),(0,a.kt)("p",null,"Which response should return the key ",(0,a.kt)("inlineCode",{parentName:"p"},"result")," with value ",(0,a.kt)("inlineCode",{parentName:"p"},"pong"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'{\n "jsonrpc": "2.0",\n "result": "pong",\n "id": 1\n}\n')),(0,a.kt)("h2",{id:"next-steps"},"Next steps"),(0,a.kt)("p",null,"While you can run the Network Node as described here, it's required to set up the Network Node correctly and securely! It requires some degree of patience, knowledge and time to go through our guides but we'll provide some guides and references to help you manage your network node server!"),(0,a.kt)("p",null,"To avoid having to go through all the steps manually, we recommend reading our ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#assisted-installer"},"assisted installer")," document for quick onboarding."),(0,a.kt)("h2",{id:"conclusion"},"Conclusion"),(0,a.kt)("p",null,"We introduced Fleek Network as an open-source edge computing platform to help us accelerate the development and execution of the next generation of web services."),(0,a.kt)("p",null,"We have learned a bit about the importance of a decentralized edge computing network to reach and fulfill the future of computation and how the Fleek Network protocol works succinctly."),(0,a.kt)("p",null,"We guide you through a step-by-step installation of the network node process, where we pull the source code, build the binary and launch the service."),(0,a.kt)("p",null,"Finally, we do a quick health check to confirm the status of our node."),(0,a.kt)("p",null,"Discover more about the project by ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"watching/contributing on GitHub"),", following us on ",(0,a.kt)("a",{parentName:"p",href:"https://twitter.com/fleek_net"},"Twitter"),", and joining ",(0,a.kt)("a",{parentName:"p",href:"https://discord.gg/fleekxyz"},"our community Discord")," for any updates."),(0,a.kt)(r.Z,{name:"Helder Oliveira",image:"https://github.com/heldrida.png",title:"Software Developer + DX",url:"https://github.com/heldrida",mdxType:"Author"}))}m.isMDXComponent=!0},2915:(e,t,n)=>{n.d(t,{ZP:()=>l});var o=n(7462),a=(n(7294),n(3905));const r={toc:[]},i="wrapper";function l(e){let{components:t,...n}=e;return(0,a.kt)(i,(0,o.Z)({},r,n,{components:t,mdxType:"MDXLayout"}),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"You have several ways of doing this:"),(0,a.kt)("ul",{parentName:"admonition"},(0,a.kt)("li",{parentName:"ul"},"Clone via HTTPS"),(0,a.kt)("li",{parentName:"ul"},"Clone via SSH"),(0,a.kt)("li",{parentName:"ul"},"Download via Github CLI"),(0,a.kt)("li",{parentName:"ul"},"Download the ",(0,a.kt)("a",{parentName:"li",href:"https://github.com/fleek-network/lightning/archive/refs/heads/main.zip"},"zip package")," from the repository")),(0,a.kt)("p",{parentName:"admonition"},"We recommend HTTPS because it is the easiest to set up in the wild, and by users who are new to all this.\nAlthough, we strongly recommend using an SSH connection when interacting with GitHub. If you are to this and are interested read more about it ",(0,a.kt)("a",{parentName:"p",href:"https://docs.github.com/en/authentication/connecting-to-github-with-ssh"},"here"),"."),(0,a.kt)("pre",{parentName:"admonition"},(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"git clone -b testnet-alpha-0 https://github.com/fleek-network/lightning.git \n")),(0,a.kt)("p",{parentName:"admonition"},"Here's an example of what it'd look like when sticking to the recommended path location:"),(0,a.kt)("pre",{parentName:"admonition"},(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"git clone -b testnet-alpha-0 https://github.com/fleek-network/lightning.git ~/fleek-network/lightning\n"))))}l.isMDXComponent=!0},3872:(e,t,n)=>{n.d(t,{Z:()=>a});var o=n(7294);const a=e=>{let{image:t,name:n,title:a,url:r}=e;return o.createElement("section",{className:"author_card"},o.createElement("div",null,o.createElement("span",{className:"avatar"},o.createElement("a",{href:r,target:"_blank",alt:n},o.createElement("img",{src:t,alt:n}))),o.createElement("div",null,o.createElement("span",{className:"name"},o.createElement("a",{href:r,target:"_blank",alt:n},n)),o.createElement("span",{className:"title"},a),o.createElement("span",{className:"discord"},"Got questions? 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Network Work?",id:"how-does-fleek-network-work",level:2},{value:"Running a Node",id:"running-a-node",level:2},{value:"Clone the source code",id:"clone-the-source-code",level:3},{value:"Dependencies",id:"dependencies",level:3},{value:"Build",id:"build",level:3},{value:"Node Launch",id:"node-launch",level:3},{value:"Health check",id:"health-check",level:3},{value:"Next steps",id:"next-steps",level:2},{value:"Conclusion",id:"conclusion",level:2}],p={toc:u},h="wrapper";function m(e){let{components:t,...n}=e;return(0,a.kt)(h,(0,o.Z)({},p,n,{components:t,mdxType:"MDXLayout"}),(0,a.kt)("h2",{id:"introduction"},"Introduction"),(0,a.kt)("p",null,"For this guide, we\u2019ll have a simple look into how Fleek Network works in its current development phase and briefly share some of the core concepts like spinning up a node and making a request to a service to put and retrieve a .car files from the network."),(0,a.kt)("p",null,"For those seeking advanced knowledge:"),(0,a.kt)("ul",null,(0,a.kt)("li",{parentName:"ul"},"Read our ",(0,a.kt)("a",{parentName:"li",href:"/docs/whitepaper"},"whitepaper"),"."),(0,a.kt)("li",{parentName:"ul"},"Check out ",(0,a.kt)("a",{parentName:"li",href:"https://github.com/fleek-network/lightning"},"our open-source code"),".")),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"If you find any typos in our documentation, feel free to ",(0,a.kt)("a",{parentName:"p",href:"https://discord.gg/fleekxyz"},"provide us feedback")," or contribute by opening a PR in our repository ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/fleek-network-docs/"},"here"),".")),(0,a.kt)("h2",{id:"pre-requisites"},"Pre-requisites"),(0,a.kt)("p",null,"To follow the guide, you will need the following:"),(0,a.kt)("ul",null,(0,a.kt)("li",{parentName:"ul"},"Familiarity with the command-line interface"),(0,a.kt)("li",{parentName:"ul"},"Git")),(0,a.kt)("h2",{id:"need-a-quick-fleek-network-tldr"},"Need a quick Fleek Network TL;DR?"),(0,a.kt)("p",null,"Fleek Network is an open-source edge computing platform to accelerate the development and execution of the next generation of web services."),(0,a.kt)("p",null,"The system is built on a distributed network of nodes, where services run within a fair and incentivized ecosystem constituted by an open community of developers and operators. It relies on blockchain technology at its core, allowing governance and token rewards as incentives for participation in serving the network."),(0,a.kt)("p",null,"Made by an open community that's free to operate nodes or build services without the need for approvals, permissions, or intermediaries. Or simply, consume Fleek Network resources on demand, from anywhere, provided by services running on the edge."),(0,a.kt)("p",null,"Applications, platforms and protocols build and utilize decentralized services on the Fleek Network to optimize performance and reduce dependency on typical centralized cloud providers and corporate infrastructure."),(0,a.kt)("p",null,"Developers can build faster and launch better products by offloading parts of the development stack to the edge to focus on core features for the value proposition of the services being developed."),(0,a.kt)("p",null,"To get started, install a Network Node in a ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/requirements"},"supported")," Linux server, such as Debian or Ubuntu (latest) by utilizing our simple ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#assisted-installer"},"assisted installer")," to help onboard as quickly as possible."),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"Our network is open to everyone, so you're more than welcome to join us anytime without any restrictions, permission or formalities. We'd be happy to have you as part of our community!")),(0,a.kt)("p",null,"Once connected to the server, open a terminal window and execute the following command:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"curl https://get.fleek.network | bash\n")),(0,a.kt)("p",null,"Follow the install assistant recommendations to have the node ready without hassle and as quickly as possible."),(0,a.kt)("h2",{id:"why-is-fleek-network-needed"},"Why is Fleek Network needed?"),(0,a.kt)("p",null,"Web3 products typically rely on centralized cloud infrastructure, which is vulnerable to attacks as computation and data can be easily manipulated to suit business goals. However, blockchain technology has paved the way for a new era of decentralized cloud computing and data storage. The Fleek Network offers a sustainable alternative to traditional centralized architectures, providing a secure, transparent, and accessible decentralized edge computing future for everyone."),(0,a.kt)("h2",{id:"how-does-fleek-network-work"},"How Does Fleek Network Work?"),(0,a.kt)("p",null,"When a client requests a service, the protocol determines the best route to the nodes where the service replicas and workload are allocated."),(0,a.kt)("p",null,"Once the computation is successful, the data streaming routes to the client. On-client request fulfillment, a proof of delivery is generated containing cryptographically secured metadata about the original request, any parts involved and the resources consumed."),(0,a.kt)("p",null,"The Delivery Acknowledgements are stored locally in the participating node memory pools, rolled up to the protocol consensus consistently throughout the Epoch. This agreement is formed by a random committee of any healthy Nodes that use the information provided to reward the Nodes fairly."),(0,a.kt)("h2",{id:"running-a-node"},"Running a Node"),(0,a.kt)("p",null,"A Fleek Network node can be built and run on your machine. It\u2019s an ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"open-source project")," and is open for contributions."),(0,a.kt)("p",null,"The project is written with Rust, a general-purpose programming language that you need to have installed in advance to be able to follow the current guide."),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"To set up Rust, packages and library dependencies can be tricky. The quickest is to visit the ",(0,a.kt)("a",{parentName:"p",href:"https://rustup.rs/"},"rustup.rs"),". Alternatively, if you haven't already, the build section has a ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#manual-installation"},"manual installation")," document to help.")),(0,a.kt)("h3",{id:"clone-the-source-code"},"Clone the source code"),(0,a.kt)("p",null,"We\u2019ll clone the repository locally, build it and interact with the node through the binary or the HTTP JSON-RPC API with a client like cURL, but you can use a GUI (Postman, Insomnia, amongst others) if you prefer."),(0,a.kt)("admonition",{type:"note"},(0,a.kt)("p",{parentName:"admonition"},"The ~/fleek-network/lightning or $HOME/fleek-network/lightning directory is the default or recommended location to store the repository. If you like to follow conventions, then is best to stick with the recommendation, to avoid confusion and make it easier to follow our documentation.")),(0,a.kt)("p",null,"Start by cloning the repository located at ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"https://github.com/fleek-network/lightning")),(0,a.kt)(i.ZP,{mdxType:"GitCloneOptions"}),(0,a.kt)("p",null,"Once the git clone completes, you\u2019ll have the latest version at the time of cloning. You should use git to fetch or pull the latest versions consequently."),(0,a.kt)("h3",{id:"dependencies"},"Dependencies"),(0,a.kt)("p",null,"Install the required dependencies necessary for compiling general software and for our use-case Lightning CLI."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"sudo apt-get install \\\n build-essential \\\n clang \\\n pkg-config \\\n libssl-dev \\\n gcc-multilib \\\n protobuf-compiler\n")),(0,a.kt)("h3",{id:"build"},"Build"),(0,a.kt)("p",null,"Start by changing the directory to the project directory where the source code is stored. If you have followed the recommended location that'll be ",(0,a.kt)("inlineCode",{parentName:"p"},"~/fleek-network/lightning"),", as follows:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"cd ~/fleek-network/lightning\n")),(0,a.kt)("p",null,"Run the Rust package manager clean and update commands."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"cargo clean\ncargo update\n")),(0,a.kt)("p",null,"Execute the install command to build and install the Fleek Network CLI."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"cargo build\n")),(0,a.kt)("p",null,"The install command uses the Rust compiler to build; It might take a while depending on how speedy is your machine."),(0,a.kt)("p",null,"Once the Rust compiler completes, the generated binary will be available in the source code project directory. If you stick with the default, that'll look like ",(0,a.kt)("inlineCode",{parentName:"p"},"~/fleek-network/lightning/target/debug/lightning-node"),"."),(0,a.kt)("p",null,"To avoid having to specify the pathname everytime, create a symbolic link to keep it short. Here we'll name the process as the global ",(0,a.kt)("inlineCode",{parentName:"p"},"lgtn"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'sudo ln -s "~/fleek-network/lightning/target/debug/lightning-node" /usr/local/bin/lgtn\n')),(0,a.kt)("p",null,"Run the CLI with the flag ",(0,a.kt)("inlineCode",{parentName:"p"},"version")," to confirm it's available globally."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"lgtn --version\n")),(0,a.kt)("p",null,"The output should look like:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"Usage: lgtn [OPTIONS] \n\nCommands:\n run Start the node\n keys Handle keys\n print-config Print the loaded configuration\n dev-init-only Initialize the node without starting it\n dev-dump-graph Dump the infusion graph of the node instance\n help Print this message or the help of the given subcommand(s)\n\nOptions:\n -c, --config Path to the toml configuration file [default: ~/.lightning/config.toml]\n --with-mock-consensus Determines that we should be using the mock consensus backend\n -v... Increases the level of verbosity (the max level is -vvv)\n --log-location Print code location on console logs\n -h, --help Print help\n -V, --version Print version\n")),(0,a.kt)("h3",{id:"node-launch"},"Node Launch"),(0,a.kt)("p",null,"After ",(0,a.kt)("a",{parentName:"p",href:"#build"},"building"),", the node can be launched by running the subcommand ",(0,a.kt)("inlineCode",{parentName:"p"},"run"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"lgtn run\n")),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"It's highly recommend to use systemd to manage the Fleek Network service for node operators. Systemd is a system and service manager for Linux operating systems that provides a consistent way to manage system services across various distributions.")),(0,a.kt)("p",null,"Learn how to create a new Systemd service in the ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#manual-installation"},"manual installation")," document."),(0,a.kt)("h3",{id:"health-check"},"Health check"),(0,a.kt)("p",null,"It's important for Node operators to regularly check on the health of their resources to make sure everything is running smoothly. By doing this, they can get helpful feedback and know for sure if their Node is up and running. Some experienced node operators even automate this process using cronjobs and get reports sent to them via email or other custom methods."),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'curl -w "\\n" localhost:4069/health\n')),(0,a.kt)("p",null,"If everything goes well, the response should be:"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"OK\n")),(0,a.kt)("p",null,"Alternatively, use the JSON-RPC method ",(0,a.kt)("inlineCode",{parentName:"p"},"flk_ping"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'curl -s \\\n -X POST \\\n -H "Content-Type: application/json" \\\n -d \'{\n "jsonrpc": "2.0",\n "method": "flk_ping",\n "params": [],\n "id": 1\n }\' \\\n localhost:4069/rpc/v0\n')),(0,a.kt)("p",null,"Which response should return the key ",(0,a.kt)("inlineCode",{parentName:"p"},"result")," with value ",(0,a.kt)("inlineCode",{parentName:"p"},"pong"),":"),(0,a.kt)("pre",null,(0,a.kt)("code",{parentName:"pre",className:"language-sh"},'{\n "jsonrpc": "2.0",\n "result": "pong",\n "id": 1\n}\n')),(0,a.kt)("h2",{id:"next-steps"},"Next steps"),(0,a.kt)("p",null,"While you can run the Network Node as described here, it's required to set up the Network Node correctly and securely! It requires some degree of patience, knowledge and time to go through our guides but we'll provide some guides and references to help you manage your network node server!"),(0,a.kt)("p",null,"To avoid having to go through all the steps manually, we recommend reading our ",(0,a.kt)("a",{parentName:"p",href:"/docs/node/install#assisted-installer"},"assisted installer")," document for quick onboarding."),(0,a.kt)("h2",{id:"conclusion"},"Conclusion"),(0,a.kt)("p",null,"We introduced Fleek Network as an open-source edge computing platform to help us accelerate the development and execution of the next generation of web services."),(0,a.kt)("p",null,"We have learned a bit about the importance of a decentralized edge computing network to reach and fulfill the future of computation and how the Fleek Network protocol works succinctly."),(0,a.kt)("p",null,"We guide you through a step-by-step installation of the network node process, where we pull the source code, build the binary and launch the service."),(0,a.kt)("p",null,"Finally, we do a quick health check to confirm the status of our node."),(0,a.kt)("p",null,"Discover more about the project by ",(0,a.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"watching/contributing on GitHub"),", following us on ",(0,a.kt)("a",{parentName:"p",href:"https://twitter.com/fleek_net"},"Twitter"),", and joining ",(0,a.kt)("a",{parentName:"p",href:"https://discord.gg/fleekxyz"},"our community Discord")," for any updates."),(0,a.kt)(r.Z,{name:"Helder Oliveira",image:"https://github.com/heldrida.png",title:"Software Developer + DX",url:"https://github.com/heldrida",mdxType:"Author"}))}m.isMDXComponent=!0},2915:(e,t,n)=>{n.d(t,{ZP:()=>l});var o=n(7462),a=(n(7294),n(3905));const r={toc:[]},i="wrapper";function l(e){let{components:t,...n}=e;return(0,a.kt)(i,(0,o.Z)({},r,n,{components:t,mdxType:"MDXLayout"}),(0,a.kt)("admonition",{type:"tip"},(0,a.kt)("p",{parentName:"admonition"},"You have several ways of doing this:"),(0,a.kt)("ul",{parentName:"admonition"},(0,a.kt)("li",{parentName:"ul"},"Clone via HTTPS"),(0,a.kt)("li",{parentName:"ul"},"Clone via SSH"),(0,a.kt)("li",{parentName:"ul"},"Download via Github CLI"),(0,a.kt)("li",{parentName:"ul"},"Download the ",(0,a.kt)("a",{parentName:"li",href:"https://github.com/fleek-network/lightning/archive/refs/heads/main.zip"},"zip package")," from the repository")),(0,a.kt)("p",{parentName:"admonition"},"We recommend HTTPS because it is the easiest to set up in the wild, and by users who are new to all this.\nAlthough, we strongly recommend using an SSH connection when interacting with GitHub. If you are to this and are interested read more about it ",(0,a.kt)("a",{parentName:"p",href:"https://docs.github.com/en/authentication/connecting-to-github-with-ssh"},"here"),"."),(0,a.kt)("pre",{parentName:"admonition"},(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"git clone -b testnet-alpha-0 https://github.com/fleek-network/lightning.git \n")),(0,a.kt)("p",{parentName:"admonition"},"Here's an example of what it'd look like when sticking to the recommended path location:"),(0,a.kt)("pre",{parentName:"admonition"},(0,a.kt)("code",{parentName:"pre",className:"language-sh"},"git clone -b testnet-alpha-0 https://github.com/fleek-network/lightning.git ~/fleek-network/lightning\n"))))}l.isMDXComponent=!0},3872:(e,t,n)=>{n.d(t,{Z:()=>a});var o=n(7294);const a=e=>{let{image:t,name:n,title:a,url:r}=e;return o.createElement("section",{className:"author_card"},o.createElement("div",null,o.createElement("span",{className:"avatar"},o.createElement("a",{href:r,target:"_blank",alt:n},o.createElement("img",{src:t,alt:n}))),o.createElement("div",null,o.createElement("span",{className:"name"},o.createElement("a",{href:r,target:"_blank",alt:n},n)),o.createElement("span",{className:"title"},a),o.createElement("span",{className:"discord"},"Got questions? 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I decided to take a look at the file permissions of /tmp on the default DO Ubuntu 22.x which is drwxr-xr-x. According to what's documented, it should be 1777. This is because writing to /tmp regardless of the comment on standards, should be widely accessible. For this reason, I've introduced a step in the installer as a test to change /tmp to what's supposed to be default (we shouldn't mess with user choice, though)."),(0,i.kt)("p",null,"During testnet the Lightning binary process is required to write to ",(0,i.kt)("inlineCode",{parentName:"p"},"/tmp"),". The ",(0,i.kt)("inlineCode",{parentName:"p"},"/tmp")," directory is used to store temporary DB checkpoints when synch state. For the users who're following the recommended Systemd unit service, to control the Fleek Network service via systemctl, it should not be mistaken with the stdout/stderr ",(0,i.kt)("inlineCode",{parentName:"p"},"/var/log/lightning/output.log")," and ",(0,i.kt)("inlineCode",{parentName:"p"},"/var/log/lightning/diagnostic.log")," log files declared in the service file."),(0,i.kt)("p",null,"Users are recommended to use systemctl to manage the service as a non-admin user. The use of ",(0,i.kt)("strong",{parentName:"p"},"sudo")," or ",(0,i.kt)("strong",{parentName:"p"},"root")," causes permissions issues, as we see in the output below:"),(0,i.kt)("pre",null,(0,i.kt)("code",{parentName:"pre"},'[00007fcbe168e764] openat(AT_FDCWD, "/tmp/lightning.log", O_WRONLY|O_CREAT|O_APPEND|O_CLOEXEC, 0666) = -1 EACCES (Permission denied)\n[00007fcbe168ea6f] write(2, "thread \'", 8thread \') = 8\n[00007fcbe168ea6f] write(2, "main", 4main) = 4\n[00007fcbe168ea6f] write(2, "\' panicked at \'", 15\' panicked at \') = 15\n[00007fcbe168ea6f] write(2, "called `Result::unwrap()` on an "..., 114called `Result::unwrap()` on an `Err` value: Os { code: 13, kind: PermissionDenied, message: "Permission denied" }) = 114\n[00007fcbe168ea6f] write(2, "\', ", 3\', ) = 3\n')),(0,i.kt)("p",null,"The ",(0,i.kt)("inlineCode",{parentName:"p"},"/tmp")," directory should have wide permissions for all applications, but to mitigate any permission issues the user can override the system environment ",(0,i.kt)("inlineCode",{parentName:"p"},"TMPDIR"),". For example, the ",(0,i.kt)("inlineCode",{parentName:"p"},"installer")," and ",(0,i.kt)("inlineCode",{parentName:"p"},"update")," scripts override ",(0,i.kt)("inlineCode",{parentName:"p"},"TMPDIR")," environment variable to ",(0,i.kt)("inlineCode",{parentName:"p"},"/var/tmp")," setting it in the service unit ",(0,i.kt)("inlineCode",{parentName:"p"},"Environment="),"."),(0,i.kt)(o.Z,{name:"Helder Oliveira",image:"https://github.com/heldrida.png",title:"Software Developer + DX",url:"https://github.com/heldrida",mdxType:"Author"}))}u.isMDXComponent=!0},3872:(e,t,n)=>{n.d(t,{Z:()=>i});var r=n(7294);const i=e=>{let{image:t,name:n,title:i,url:o}=e;return r.createElement("section",{className:"author_card"},r.createElement("div",null,r.createElement("span",{className:"avatar"},r.createElement("a",{href:o,target:"_blank",alt:n},r.createElement("img",{src:t,alt:n}))),r.createElement("div",null,r.createElement("span",{className:"name"},r.createElement("a",{href:o,target:"_blank",alt:n},n)),r.createElement("span",{className:"title"},i),r.createElement("span",{className:"discord"},"Got questions? Find us on ",r.createElement("a",{href:"https://discord.gg/fleekxyz",target:"_blank"},"Discord!")))))}}}]); \ No newline at end of file diff --git a/assets/js/29b62a39.6839f49e.js b/assets/js/29b62a39.ad607ffe.js similarity index 98% rename from assets/js/29b62a39.6839f49e.js rename to assets/js/29b62a39.ad607ffe.js index 2be061e6c..b68d04499 100644 --- a/assets/js/29b62a39.6839f49e.js +++ b/assets/js/29b62a39.ad607ffe.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[1498],{3905:(e,t,r)=>{r.d(t,{Zo:()=>l,kt:()=>m});var n=r(7294);function o(e,t,r){return t in e?Object.defineProperty(e,t,{value:r,enumerable:!0,configurable:!0,writable:!0}):e[t]=r,e}function a(e,t){var r=Object.keys(e);if(Object.getOwnPropertySymbols){var n=Object.getOwnPropertySymbols(e);t&&(n=n.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),r.push.apply(r,n)}return r}function i(e){for(var t=1;t=0||(o[r]=e[r]);return o}(e,t);if(Object.getOwnPropertySymbols){var a=Object.getOwnPropertySymbols(e);for(n=0;n=0||Object.prototype.propertyIsEnumerable.call(e,r)&&(o[r]=e[r])}return o}var c=n.createContext({}),d=function(e){var t=n.useContext(c),r=t;return e&&(r="function"==typeof e?e(t):i(i({},t),e)),r},l=function(e){var t=d(e.components);return n.createElement(c.Provider,{value:t},e.children)},u="mdxType",p={inlineCode:"code",wrapper:function(e){var t=e.children;return n.createElement(n.Fragment,{},t)}},f=n.forwardRef((function(e,t){var r=e.components,o=e.mdxType,a=e.originalType,c=e.parentName,l=s(e,["components","mdxType","originalType","parentName"]),u=d(r),f=o,m=u["".concat(c,".").concat(f)]||u[f]||p[f]||a;return r?n.createElement(m,i(i({ref:t},l),{},{components:r})):n.createElement(m,i({ref:t},l))}));function m(e,t){var r=arguments,o=t&&t.mdxType;if("string"==typeof e||o){var a=r.length,i=new Array(a);i[0]=f;var s={};for(var c in t)hasOwnProperty.call(t,c)&&(s[c]=t[c]);s.originalType=e,s[u]="string"==typeof e?e:o,i[1]=s;for(var d=2;d{r.r(t),r.d(t,{assets:()=>d,contentTitle:()=>s,default:()=>f,frontMatter:()=>i,metadata:()=>c,toc:()=>l});var n=r(7462),o=(r(7294),r(3905));const a=r.p+"assets/images/banner-guides-cd76f6e8aac3594bb5d072a564e0e277.png",i={title:"About guides",hide_title:!0,sidebar_position:1,tags:["Guides","Help","Fleek Network"]},s=void 0,c={unversionedId:"index",id:"index",title:"About guides",description:"The guides provide step-by-step instructions and descriptions to help understand how and why you'd have to do or execute certain commands or processes.",source:"@site/guides/index.md",sourceDirName:".",slug:"/",permalink:"/guides/",draft:!1,editUrl:"https://github.com/fleek-network/fleek-network-docs/edit/main/guides/index.md",tags:[{label:"Guides",permalink:"/guides/tags/guides"},{label:"Help",permalink:"/guides/tags/help"},{label:"Fleek Network",permalink:"/guides/tags/fleek-network"}],version:"current",lastUpdatedAt:1694447033,formattedLastUpdatedAt:"Sep 11, 2023",sidebarPosition:1,frontMatter:{title:"About guides",hide_title:!0,sidebar_position:1,tags:["Guides","Help","Fleek Network"]},sidebar:"defaultSidebar",next:{title:"Getting Started",permalink:"/guides/Node Operators/getting-started"}},d={},l=[],u={toc:l},p="wrapper";function f(e){let{components:t,...r}=e;return(0,o.kt)(p,(0,n.Z)({},u,r,{components:t,mdxType:"MDXLayout"}),(0,o.kt)("img",{className:"banner",src:a}),(0,o.kt)("p",null,"The guides provide step-by-step instructions and descriptions to help understand how and why you'd have to do or execute certain commands or processes."),(0,o.kt)("p",null,"It differs from the ",(0,o.kt)("a",{parentName:"p",href:"/references"},"references")," documentation which serves as a quick direct breakdown of commands and processes without much explanation, as the name implies."),(0,o.kt)("p",null,"To start, find guides by consulting the available categories to locate the content on the sidebar. 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This is to avoid the path being determined dynamically (given path base ~ or $HOME), as users might control the systemctl service as a ",(0,r.kt)("strong",{parentName:"p"},"user")," or ",(0,r.kt)("strong",{parentName:"p"},"sudoer"),". For example, a ",(0,r.kt)("strong",{parentName:"p"},"sudoer")," would have the ",(0,r.kt)("strong",{parentName:"p"},"configuration")," set to ",(0,r.kt)("inlineCode",{parentName:"p"},"/root/.lightning/config.toml")," or ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/username/.lightning/config.toml")," depending on using ",(0,r.kt)("strong",{parentName:"p"},"sudo")," which might cause some confusion to some users.")))}i.isMDXComponent=!0},2300:(e,t,n)=>{n.d(t,{ZP:()=>i});var a=n(7462),r=(n(7294),n(3905));const o={toc:[]},l="wrapper";function i(e){let{components:t,...n}=e;return(0,r.kt)(l,(0,a.Z)({},o,n,{components:t,mdxType:"MDXLayout"}),(0,r.kt)("p",null,"You should be following the ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/install#create-a-user-1"},"create a user")," recommendation. For our example, we have the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn"),"."),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"If you have chosen a different username, replace ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn")," by the correct username you have selected.")),(0,r.kt)("p",null,"In the ",(0,r.kt)("inlineCode",{parentName:"p"},"config.toml")," you'll find some and more of the following:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-toml"},'[BLANK]\n\n[application]\ndb_path = "~/.lightning/data/app_db"\n\n[consensus]\nstore_path = "~/.lightning/data/narwhal_store"\n\n[fsstore]\nroot = "~/.lightning/blockstore"\n\n[resolver]\nstore_path = "~/.lightning/data/resolver_store"\n\n[signer]\nconsensus_key_path = "~/.lightning/keystore/consensus.pem"\nnode_key_path = "~/.lightning/keystore/node.pem"\n')),(0,r.kt)("p",null,"Find and replace all instances of ",(0,r.kt)("inlineCode",{parentName:"p"},"~")," in the config file ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/lgtn/.lightning/config.toml"),". 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To use it execute the following command in your server terminal and follow the instructions:"),(0,r.kt)("pre",{parentName:"admonition"},(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"curl -sS https://get.fleek.network/update | bash\n"))),(0,r.kt)("h2",{id:"switch-to-the-installation-user"},"Switch to the installation user"),(0,r.kt)("p",null,"Switch to the username you've used throughout the installation process."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"su \n")),(0,r.kt)("p",null,"For example, if you used the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn")," it'll look like the following command:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"su lgtn\n")),(0,r.kt)("h2",{id:"change-directory-to-the-source-code"},"Change directory to the source code"),(0,r.kt)("p",null,"If you have installed it via the recommended process or instructions, then the default location where the ",(0,r.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"source code")," is stored is ",(0,r.kt)("inlineCode",{parentName:"p"},"~/fleek-network/lightning"),"."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"cd ~/fleek-network/lightning\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"Notice that we use ",(0,r.kt)("inlineCode",{parentName:"p"},"~"),", which refers to ",(0,r.kt)("inlineCode",{parentName:"p"},"$HOME"),". You must use the username used for the installation process. For example, on ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/requirements#server"},"Ubuntu")," if you use the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn"),", the pathname for ",(0,r.kt)("inlineCode",{parentName:"p"},"$HOME")," is ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/lgtn"),".")),(0,r.kt)("h2",{id:"checkout-to-branch"},"Checkout to branch"),(0,r.kt)("p",null,"Make sure that you are checked in to the correct branch. For the current testnet phase that'd be ",(0,r.kt)("inlineCode",{parentName:"p"},"testnet-alpha-0"),". If you use any other branch name, your node will not function correctly. Use the branch name ",(0,r.kt)("inlineCode",{parentName:"p"},"testnet-alpha-0"),"."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git checkout testnet-alpha-0\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"We try to update our documentation promptly but sometimes are a bit behind on any changes we might make in real-time. If you find any typos, such as the wrong branch name, help us by letting us know! Find us in Fleek Network section of our ",(0,r.kt)("a",{parentName:"p",href:"https://discord.gg/fleekxyz"},"Discord"),".")),(0,r.kt)("h2",{id:"pull-the-latest-changes"},"Pull the latest changes"),(0,r.kt)("p",null,"Before make sure that you stash or clear any changes you may have in the working directory, as otherwise, ",(0,r.kt)("inlineCode",{parentName:"p"},"git")," will let you know about local changes\u2013if you'd like to learn more about it read the ",(0,r.kt)("a",{parentName:"p",href:"https://git-scm.com/docs/git-stash"},"git stash document"),"."),(0,r.kt)("p",null,"A quick way to clean is to ",(0,r.kt)("inlineCode",{parentName:"p"},"stash")," the changes, for example:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git stash \n")),(0,r.kt)("p",null,"To pull the latest changes use the ",(0,r.kt)("inlineCode",{parentName:"p"},"git pull")," command, as follows:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git pull origin testnet-alpha-0\n")),(0,r.kt)("p",null,"Alternatively, to have to stash and pull, you can reset the repository to the origin."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git fetch origin testnet-alpha-0\ngit reset --hard origin/testnet-alpha-0\ngit clean -f\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"We are using the branch named ",(0,r.kt)("inlineCode",{parentName:"p"},"testnet-alpha-0"),", which is specific to the early testnet launch. Change to the correct branch name according to needs. For example, in the future the mainnet version will go on branch name ",(0,r.kt)("inlineCode",{parentName:"p"},"main"),".")),(0,r.kt)("h2",{id:"build-binary-from-the-source"},"Build binary from the source"),(0,r.kt)("p",null,"To build the binary from the source code, we execute the cargo build command:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"cargo +stable build --release\n")),(0,r.kt)("h2",{id:"update-the-symlink"},"Update the symlink"),(0,r.kt)("p",null,"Start by removing the existing one:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},'sudo rm -f "/usr/local/bin/lgtn"\n')),(0,r.kt)("p",null,"Create a new symlink that links the new build binary to ",(0,r.kt)("inlineCode",{parentName:"p"},"/usr/local/bin/lgtn"),", as follows:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"sudo ln -s ~/fleek-network/lightning/target/release/lightning-node /usr/local/bin/lgtn\n")),(0,r.kt)("h2",{id:"set-user-path-in-configtoml"},"Set user path in config.toml"),(0,r.kt)(l.ZP,{mdxType:"SetUserPathInConfigToml"}),(0,r.kt)("h2",{id:"update-the-systemd-service-unit"},"Update the systemd service unit"),(0,r.kt)("p",null,"Open and edit the ",(0,r.kt)("inlineCode",{parentName:"p"},"/etc/systemd/system/lightning.service")," file."),(0,r.kt)("p",null,"1) Replace ",(0,r.kt)("inlineCode",{parentName:"p"},"")," with the username. For example, in the ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/install#create-a-user"},"documentation")," we use the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn"),"."),(0,r.kt)("p",null,"2) Make sure that the ",(0,r.kt)("inlineCode",{parentName:"p"},"ExecStart")," is set correctly"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"[Unit]\nDescription=Fleek Network Node lightning service\n\n[Service]\nUser=\nType=simple\nMemoryHigh=32G\nRestartSec=15s\nRestart=always\nExecStart=lgtn -c /home/lgtn/.lightning/config.toml run\nStandardOutput=append:/var/log/lightning/output.log\nStandardError=append:/var/log/lightning/diagnostic.log\nEnvironment=/var/tmp\n\n[Install]\nWantedBy=multi-user.target\n")),(0,r.kt)(i.ZP,{mdxType:"NoteExecStartFlagCConfigPath"}),(0,r.kt)("p",null,"When complete make sure the file is saved. Followed by a systemctl daemon reload:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"sudo systemctl daemon-reload\n")),(0,r.kt)("h2",{id:"clear-the-data"},"Clear the data"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"rm -rf ~/.lightning/data\n")),(0,r.kt)("h2",{id:"restart-the-service"},"Restart the service"),(0,r.kt)("p",null,"Once the cargo build process is completed, you have to restart the service. We're assuming you are using non-root user as ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/install#create-a-user"},"recommended"),", you won't use ",(0,r.kt)("strong",{parentName:"p"},"sudo")," to start the service. The command will look as follows:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"sudo systemctl restart lightning\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"If you have installed the Fleek Network lightning manually, the ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/install#systemd-service-setup"},"installation instructions")," recommended setting up a systemd service for the Fleek Network process. If you haven't, you're advised to check the instructions provided.")),(0,r.kt)("h2",{id:"health-checkup"},"Health checkup"),(0,r.kt)("p",null,"Do a quick health check by running:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},'curl -w "\\p" localhost:4069/health\n')),(0,r.kt)("p",null,"If successful, you should get the response ",(0,r.kt)("inlineCode",{parentName:"p"},"OK"),", as follows:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"OK\n")),(0,r.kt)(o.Z,{name:"Helder Oliveira",image:"https://github.com/heldrida.png",title:"Software Developer + DX",url:"https://github.com/heldrida",mdxType:"Author"}))}g.isMDXComponent=!0},3872:(e,t,n)=>{n.d(t,{Z:()=>r});var a=n(7294);const r=e=>{let{image:t,name:n,title:r,url:o}=e;return a.createElement("section",{className:"author_card"},a.createElement("div",null,a.createElement("span",{className:"avatar"},a.createElement("a",{href:o,target:"_blank",alt:n},a.createElement("img",{src:t,alt:n}))),a.createElement("div",null,a.createElement("span",{className:"name"},a.createElement("a",{href:o,target:"_blank",alt:n},n)),a.createElement("span",{className:"title"},r),a.createElement("span",{className:"discord"},"Got questions? Find us on ",a.createElement("a",{href:"https://discord.gg/fleekxyz",target:"_blank"},"Discord!")))))}}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[4402],{3905:(e,t,n)=>{n.d(t,{Zo:()=>c,kt:()=>m});var a=n(7294);function r(e,t,n){return t in e?Object.defineProperty(e,t,{value:n,enumerable:!0,configurable:!0,writable:!0}):e[t]=n,e}function o(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var a=Object.getOwnPropertySymbols(e);t&&(a=a.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),n.push.apply(n,a)}return n}function l(e){for(var t=1;t=0||(r[n]=e[n]);return r}(e,t);if(Object.getOwnPropertySymbols){var o=Object.getOwnPropertySymbols(e);for(a=0;a=0||Object.prototype.propertyIsEnumerable.call(e,n)&&(r[n]=e[n])}return r}var s=a.createContext({}),p=function(e){var t=a.useContext(s),n=t;return e&&(n="function"==typeof e?e(t):l(l({},t),e)),n},c=function(e){var t=p(e.components);return a.createElement(s.Provider,{value:t},e.children)},u="mdxType",h={inlineCode:"code",wrapper:function(e){var t=e.children;return a.createElement(a.Fragment,{},t)}},d=a.forwardRef((function(e,t){var n=e.components,r=e.mdxType,o=e.originalType,s=e.parentName,c=i(e,["components","mdxType","originalType","parentName"]),u=p(n),d=r,m=u["".concat(s,".").concat(d)]||u[d]||h[d]||o;return n?a.createElement(m,l(l({ref:t},c),{},{components:n})):a.createElement(m,l({ref:t},c))}));function m(e,t){var n=arguments,r=t&&t.mdxType;if("string"==typeof e||r){var o=n.length,l=new Array(o);l[0]=d;var i={};for(var s in t)hasOwnProperty.call(t,s)&&(i[s]=t[s]);i.originalType=e,i[u]="string"==typeof e?e:r,l[1]=i;for(var p=2;p{n.d(t,{ZP:()=>i});var a=n(7462),r=(n(7294),n(3905));const o={toc:[]},l="wrapper";function i(e){let{components:t,...n}=e;return(0,r.kt)(l,(0,a.Z)({},o,n,{components:t,mdxType:"MDXLayout"}),(0,r.kt)("admonition",{type:"note"},(0,r.kt)("p",{parentName:"admonition"},"The flag ",(0,r.kt)("inlineCode",{parentName:"p"},"-c")," in the ",(0,r.kt)("inlineCode",{parentName:"p"},"lightning.service")," ",(0,r.kt)("strong",{parentName:"p"},"ExecStart"),", is to provide the toml configuration file path e.g. defaults to ",(0,r.kt)("inlineCode",{parentName:"p"},"~/.lightning/config.toml"),". This is to avoid the path being determined dynamically (given path base ~ or $HOME), as users might control the systemctl service as a ",(0,r.kt)("strong",{parentName:"p"},"user")," or ",(0,r.kt)("strong",{parentName:"p"},"sudoer"),". For example, a ",(0,r.kt)("strong",{parentName:"p"},"sudoer")," would have the ",(0,r.kt)("strong",{parentName:"p"},"configuration")," set to ",(0,r.kt)("inlineCode",{parentName:"p"},"/root/.lightning/config.toml")," or ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/username/.lightning/config.toml")," depending on using ",(0,r.kt)("strong",{parentName:"p"},"sudo")," which might cause some confusion to some users.")))}i.isMDXComponent=!0},2300:(e,t,n)=>{n.d(t,{ZP:()=>i});var a=n(7462),r=(n(7294),n(3905));const o={toc:[]},l="wrapper";function i(e){let{components:t,...n}=e;return(0,r.kt)(l,(0,a.Z)({},o,n,{components:t,mdxType:"MDXLayout"}),(0,r.kt)("p",null,"You should be following the ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/install#create-a-user-1"},"create a user")," recommendation. For our example, we have the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn"),"."),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"If you have chosen a different username, replace ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn")," by the correct username you have selected.")),(0,r.kt)("p",null,"In the ",(0,r.kt)("inlineCode",{parentName:"p"},"config.toml")," you'll find some and more of the following:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-toml"},'[BLANK]\n\n[application]\ndb_path = "~/.lightning/data/app_db"\n\n[consensus]\nstore_path = "~/.lightning/data/narwhal_store"\n\n[fsstore]\nroot = "~/.lightning/blockstore"\n\n[resolver]\nstore_path = "~/.lightning/data/resolver_store"\n\n[signer]\nconsensus_key_path = "~/.lightning/keystore/consensus.pem"\nnode_key_path = "~/.lightning/keystore/node.pem"\n')),(0,r.kt)("p",null,"Find and replace all instances of ",(0,r.kt)("inlineCode",{parentName:"p"},"~")," in the config file ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/lgtn/.lightning/config.toml"),". Here's an example using ",(0,r.kt)("inlineCode",{parentName:"p"},"sed"),":"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},'sed -i "s|~/.lightning|/home/lgtn/.lightning|g" "/home/lgtn/.lightning/config.toml"\n')),(0,r.kt)("admonition",{type:"caution"},(0,r.kt)("p",{parentName:"admonition"},"The ",(0,r.kt)("inlineCode",{parentName:"p"},"config.toml")," example below is a shorter version of what you'll encounter, yours might look different. We do this to keep the guide simple to read. Do not copy and replace with the version demonstrated here.")),(0,r.kt)("p",null,"Once changed, all the instances of ",(0,r.kt)("inlineCode",{parentName:"p"},"~/")," should be replaced by your user path e.g. ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/lgtn/"),". 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To use it execute the following command in your server terminal and follow the instructions:"),(0,r.kt)("pre",{parentName:"admonition"},(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"curl -sS https://get.fleek.network/update | bash\n"))),(0,r.kt)("h2",{id:"switch-to-the-installation-user"},"Switch to the installation user"),(0,r.kt)("p",null,"Switch to the username you've used throughout the installation process."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"su \n")),(0,r.kt)("p",null,"For example, if you used the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn")," it'll look like the following command:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"su lgtn\n")),(0,r.kt)("h2",{id:"change-directory-to-the-source-code"},"Change directory to the source code"),(0,r.kt)("p",null,"If you have installed it via the recommended process or instructions, then the default location where the ",(0,r.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/lightning"},"source code")," is stored is ",(0,r.kt)("inlineCode",{parentName:"p"},"~/fleek-network/lightning"),"."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"cd ~/fleek-network/lightning\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"Notice that we use ",(0,r.kt)("inlineCode",{parentName:"p"},"~"),", which refers to ",(0,r.kt)("inlineCode",{parentName:"p"},"$HOME"),". You must use the username used for the installation process. For example, on ",(0,r.kt)("a",{parentName:"p",href:"/docs/node/requirements#server"},"Ubuntu")," if you use the username ",(0,r.kt)("inlineCode",{parentName:"p"},"lgtn"),", the pathname for ",(0,r.kt)("inlineCode",{parentName:"p"},"$HOME")," is ",(0,r.kt)("inlineCode",{parentName:"p"},"/home/lgtn"),".")),(0,r.kt)("h2",{id:"checkout-to-branch"},"Checkout to branch"),(0,r.kt)("p",null,"Make sure that you are checked in to the correct branch. For the current testnet phase that'd be ",(0,r.kt)("inlineCode",{parentName:"p"},"testnet-alpha-0"),". If you use any other branch name, your node will not function correctly. Use the branch name ",(0,r.kt)("inlineCode",{parentName:"p"},"testnet-alpha-0"),"."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git checkout testnet-alpha-0\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"We try to update our documentation promptly but sometimes are a bit behind on any changes we might make in real-time. If you find any typos, such as the wrong branch name, help us by letting us know! Find us in Fleek Network section of our ",(0,r.kt)("a",{parentName:"p",href:"https://discord.gg/fleekxyz"},"Discord"),".")),(0,r.kt)("h2",{id:"pull-the-latest-changes"},"Pull the latest changes"),(0,r.kt)("p",null,"Before make sure that you stash or clear any changes you may have in the working directory, as otherwise, ",(0,r.kt)("inlineCode",{parentName:"p"},"git")," will let you know about local changes\u2013if you'd like to learn more about it read the ",(0,r.kt)("a",{parentName:"p",href:"https://git-scm.com/docs/git-stash"},"git stash document"),"."),(0,r.kt)("p",null,"A quick way to clean is to ",(0,r.kt)("inlineCode",{parentName:"p"},"stash")," the changes, for example:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git stash \n")),(0,r.kt)("p",null,"To pull the latest changes use the ",(0,r.kt)("inlineCode",{parentName:"p"},"git pull")," command, as follows:"),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git pull origin testnet-alpha-0\n")),(0,r.kt)("p",null,"Alternatively, to have to stash and pull, you can reset the repository to the origin."),(0,r.kt)("pre",null,(0,r.kt)("code",{parentName:"pre",className:"language-sh"},"git fetch origin testnet-alpha-0\ngit reset --hard origin/testnet-alpha-0\ngit clean -f\n")),(0,r.kt)("admonition",{type:"tip"},(0,r.kt)("p",{parentName:"admonition"},"We are using the branch named ",(0,r.kt)("inlineCode",{parentName:"p"},"testnet-alpha-0"),", which is specific to the early testnet launch. 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Filters",id:"other-filters",level:2},{value:"Conclusion",id:"conclusion",level:2},{value:"References",id:"references",level:3}],h={toc:c},p="wrapper";function m(e){let{components:t,...r}=e;return(0,n.kt)(p,(0,o.Z)({},h,r,{components:t,mdxType:"MDXLayout"}),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(4221).Z,width:"1200",height:"628"})),(0,n.kt)("p",null,"Disclaimer: This is not a general comparison between Bloom filters and Cuckoo filters. 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"),(0,n.kt)("p",null,"One of the convenient features of Bloom filters is that they can be configured to have a specific false positive rate.\nOf course, there is a tradeoff here; the lower the false positive rate, the larger the memory footprint. Bloom filters support two operations: ",(0,n.kt)("inlineCode",{parentName:"p"},"insert")," and ",(0,n.kt)("inlineCode",{parentName:"p"},"contains.")," "),(0,n.kt)("p",null,"A Bloom filter is represented by an array of m bits together with k independent hash functions. To insert an element into the filter, it is hashed with each of the k hash functions.\nThe resulting hashes are interpreted as integers (modulo m) to obtain k array positions. The bits at these positions are then set to 1 (if there aren't already 1).",(0,n.kt)("br",{parentName:"p"}),"\n","To check whether or not an element is contained in the filter, the element is hashed k times with the different hash functions."),(0,n.kt)("p",null,"If all bits at the resulting array positions are 1, the element is assumed to be present. If any of the k bits are zero, we can be certain that the queried element is not present in the set."),(0,n.kt)("p",null,"However, even if all bits are 1, it might still be the case that the bits were set by a combination of other elements. This is where the aforementioned false positive rate comes into play. "),(0,n.kt)("p",null,"Since we also need a ",(0,n.kt)("inlineCode",{parentName:"p"},"remove")," operation for our use case, we have been using Counting Bloom filters, a variant of Bloom filters.\nCounting Bloom filters retain most of the properties that regular Bloom filters have. The ",(0,n.kt)("inlineCode",{parentName:"p"},"remove")," operation comes at the cost of an increased memory footprint."),(0,n.kt)("p",null,"Each position in the array is no longer a single bit but a group of bits representing a counter.\nWhenever an element is inserted into the filter, the counters for all k positions are incremented by 1. To remove an element, we decrement the counters."),(0,n.kt)("h2",{id:"cuckoo-filters"},"Cuckoo Filters"),(0,n.kt)("p",null,"Bloom filters are the most known members of a class of data structures called Approximate Membership Query Filters (AMQ Filters).\nA relatively recent addition to this class is the Cuckoo filter ","[1]",". Cuckoo filters share many similarities with Bloom filters, especially Counting Bloom filters."),(0,n.kt)("p",null,"They are space-efficient and can be used for approximate set membership queries. Cuckoo filters also support the operations ",(0,n.kt)("inlineCode",{parentName:"p"},"insert,")," ",(0,n.kt)("inlineCode",{parentName:"p"},"contains,")," and ",(0,n.kt)("inlineCode",{parentName:"p"},"remove,")," and have configurable false positive rates. "),(0,n.kt)("p",null,"Cuckoo filters are based on Cuckoo hash tables ","[2]"," and leverage an optimization called partial-key cuckoo hashing. A basic Cuckoo hash table consists of an array of buckets.\nWe determine two candidate buckets for each element using two different hash functions, h1 and h2. "),(0,n.kt)("p",null,"The ",(0,n.kt)("inlineCode",{parentName:"p"},"contains")," operation will check if either bucket contains the element.\nFor insertion, if either bucket is empty, the element will be inserted into the empty bucket."),(0,n.kt)("p",null,"If neither bucket is empty, one of the buckets is selected, and the existing element is removed and inserted into its alternate location.\nThis may trigger another relocation if the alternate location is not empty. "),(0,n.kt)("p",null,"Although the insertion operation may perform a sequence of relocations, the amortized runtime is O(1). "),(0,n.kt)("p",null,"Most implementations of Cuckoo hash tables and, consequently, Cuckoo filters will use buckets that can hold multiple elements, as proposed in ","[3]","."),(0,n.kt)("p",null,"For Cuckoo filters, the hash table size is reduced by only storing fingerprints - a bit string calculated from an element's hash - rather than key-value pairs."),(0,n.kt)("p",null,"The fingerprint size is derived from the desired false positive rate.",(0,n.kt)("br",{parentName:"p"}),"\n","A problem that arises is that, to relocate existing fingerprints using the Cuckoo hashing approach described above, we need the original hash from which the fingerprint was derived."),(0,n.kt)("p",null,"Of course, we could store this hash somewhere, but the whole point of using fingerprints is to reduce the memory footprint of the filter."),(0,n.kt)("p",null,"The solution to this predicament is the aforementioned partial-key cuckoo hashing, a technique for determining an element's alternate location using only its fingerprint.",(0,n.kt)("br",{parentName:"p"}),"\n","For a given element x, the two candidate buckets are computed as follows: "),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(9440).Z,width:"1324",height:"194"})),(0,n.kt)("p",null,"An important property of this technique is that h1(x) can also be computed from h2(x) and the fingerprint."),(0,n.kt)("h2",{id:"benchmarking"},"Benchmarking"),(0,n.kt)("p",null,"As this post mentioned, we are not aiming for a general comparison of Counting Bloom and Cuckoo filters."),(0,n.kt)("p",null,"Instead, we want to determine which filter suits our specific use case better. The two main properties we are looking for are space efficiency and lookup performance. "),(0,n.kt)("p",null,"Space efficiency is important because nodes frequently update their cache and have to communicate these changes with their peers. These messages should take up as little bandwidth as possible."),(0,n.kt)("p",null,"Lookup speed is also important because Fleek Network aims to serve user requests as quickly as possible. Checking whether a peer has some content stored in their cache summary should not be a bottleneck. "),(0,n.kt)("h2",{id:"experimental-setup"},"Experimental Setup"),(0,n.kt)("p",null,"We are using our own Counting Bloom filter ",(0,n.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/ursa/blob/483f4d56cbaa5e83182454d2c1db6f6af7c54912/crates/ursa-network/src/utils/bloom_filter.rs#L11"},"implementation")," and\n",(0,n.kt)("a",{parentName:"p",href:"https://github.com/sile/scalable_cuckoo_filter"},"this")," Cuckoo filter implementation in Rust (the ",(0,n.kt)("a",{parentName:"p",href:"https://github.com/efficient/cuckoofilter"},"original")," implementation is in C++). All experiments\nwere performed on a Linux machine with 16 GB RAM and an Intel Core i7 (10th Gen). Whenever the experiment is probabilistic, we repeat the experiment 20 times and report the mean and standard deviation."),(0,n.kt)("h2",{id:"memory-footprint"},"Memory Footprint"),(0,n.kt)("p",null,"For both Counting Bloom filters and Cuckoo filters, the memory footprint is determined by two factors: the filter's capacity and the desired false positive rate. In the first experiment, we examine the impact that\nthese factors have on the memory footprint. "),(0,n.kt)("p",null,"To this end, we fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The result is shown in Fig. 1.\nThe size of Bloom filters scales linearly with the capacity. Cuckoo filters are more space-efficient. This result is consistent with the experiments reported in ","[1]","."),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(5441).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 1: We fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The y-axis shows the size of the filters in Megabytes.")),(0,n.kt)("p",null,"Next, we fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. Fig. 2 shows that Cuckoo filters are more space-efficient."),(0,n.kt)("p",null,"The gap between Counting Bloom filters and Cuckoo filters grows as the false positive rate decreases. This is also consistent with experiments in ","[1]","."),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(9844).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 2: We fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. The y-axis shows the size of the filters in Megabytes.")),(0,n.kt)("h2",{id:"lookup-performance"},"Lookup Performance"),(0,n.kt)("p",null,"We first add elements to both filters until the capacity is reached. We then measure the lookup performance for different ratios of positive and negative lookups."),(0,n.kt)("p",null,"A positive lookup is for an existing element, and a negative lookup is for an element not contained in the filter. We perform 100K lookups for each ratio and report the average lookup duration and standard deviation. "),(0,n.kt)("p",null,"Fig. 3 shows the results. Bloom filters perform slightly better on average than Cuckoo filters. This result is inconsistent with ","[1]",",\nwhere Cuckoo filters were reported to have a better lookup performance than Bloom filters. It should be noted here that the authors in ","[1]"," use the original C++ Cuckoo filter implementation and their own unreleased Bloom filter implementation. In contrast, we use a Rust Cuckoo filter implementation and our Bloom filter implementation. We cannot easily determine the reason for this discrepancy."),(0,n.kt)("p",null,"However, the performance difference is negligible."),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(8915).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 3: Lookup performance for different ratios of positive and negative lookups. For example, ratio 0.25 indicates that 25% of lookups are positive and 75% are negative.\nThe shaded region indicates the standard deviation.")),(0,n.kt)("h2",{id:"insertion-performance"},"Insertion Performance"),(0,n.kt)("p",null,"Less critical than lookup performance but still important for our purposes is insertion performance. We measure how the insertion performance varies for different occupancy levels.\nFig. 4 shows the results. The insertion performance is constant across all levels of occupancy for Bloom filters."),(0,n.kt)("p",null,"For Cuckoo filters, the performance decreases as the filter becomes fuller because more relocations are required. In Fig. 4, the performance for Bloom filters is not constant. It quickly increases and then remains constant. This can be explained by CPU caching. "),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(989).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 4: Insertion performance for different occupancy levels. The shaded region indicates the standard deviation.")),(0,n.kt)("h2",{id:"capacity-and-scaling"},"Capacity and Scaling"),(0,n.kt)("p",null,"We have mentioned the capacity of a filter several times now. An interesting case is what happens when a filter's capacity is exceeded.\nBloom filters and Cuckoo filters behave differently in this scenario."),(0,n.kt)("p",null,"For Bloom filters, the ",(0,n.kt)("inlineCode",{parentName:"p"},"insertion")," operation always succeeds. However, the false positive rate will rapidly increase as we exceed the filter's capacity. While Bloom filters fail silently, Cuckoo filters are more explicit. Most implementations have a maximum number of\nrelocations that will be performed for an insertion. The ",(0,n.kt)("inlineCode",{parentName:"p"},"insertion")," operation will return an error if more relocations are required. "),(0,n.kt)("p",null,"For both filters, we can avoid this problem by simply initializing the filter with a sufficiently large capacity. However, this will increase the memory footprint of the filter."),(0,n.kt)("p",null,"Furthermore, it is difficult to predict how many elements a node on Fleek Network will cache. It is also likely that the number of cached elements will greatly vary for different nodes. "),(0,n.kt)("p",null,"Fortunately, a variant of Bloom filters called Scalable Bloom Filters ","[4]"," can adapt dynamically to the number of elements stored while guaranteeing a maximum false positive rate."),(0,n.kt)("p",null,"The proposed technique is also applicable to Cuckoo filters."),(0,n.kt)("h2",{id:"other-filters"},"Other Filters"),(0,n.kt)("p",null,"While we only looked at Bloom filters and Cuckoo filters, there are other AMQ filters that we want to mention here briefly:"),(0,n.kt)("ul",null,(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},"Quotient filters ","[5, 6]",": Compact hash tables that support insertion, lookup, and deletion. Less space-efficient than Bloom filters and Cuckoo filters. ")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},"XOR filters ","[7]",": More space-efficient than Bloom filters and Cuckoo filters. However, they are static, meaning the filter has to be rebuilt if additional elements are added. "))),(0,n.kt)("h2",{id:"conclusion"},"Conclusion"),(0,n.kt)("p",null,"We examined whether Counting Bloom filters or Cuckoo filters are more suitable for summarizing caches on Fleek Network. Cuckoo filters are more space-efficient, especially for lower false positive rates. Bloom filters have a slightly better insertion and lookup performance for the implementations we tested."),(0,n.kt)("p",null,"Both filters can be adapted to grow and shrink in size dynamically. Since the difference in insertion and lookup performance is negligible while Cuckoo filters are significantly more space-efficient, we favor Cuckoo filters for our use case. "),(0,n.kt)("h3",{id:"references"},"References"),(0,n.kt)("p",null,"[1]"," Bin Fan, Dave G. Andersen, Michael Kaminsky, and Michael D. Mitzenmacher. Cuckoo Filter: Practically Better Than Bloom.\nIn Proceedings of the 10th ACM International Conference on emerging Networking Experiments and Technologies (CoNEXT 14). Association for Computing Machinery, New York, NY, USA, pp. 75-88, 2014. "),(0,n.kt)("p",null,"[2]"," Rasmus Pagha and Flemming Friche Rodler. Cuckoo hashing. Journal of Algorithms, 51(2), pp. 122-144, 2004. "),(0,n.kt)("p",null,"[3]"," Martin Dietzfelbinger and Christoph Weidling. Balanced Allocation and Dictionaries with Tightly Packed Constant Size Bins. Theoretical Computer Science, 380(1), pp. 47-68, 2007. "),(0,n.kt)("p",null,"[4]"," Paulo S. Almeida, Carlos Baquero, Nuno Pregui\xe7a, and David Hutchison. Scalable Bloom Filters. Information Processing Letters, 101(6), pp. 255-261, 2007. "),(0,n.kt)("p",null,"[5]"," John G. Cleary. Compact hash tables using bidirectional linear probing. IEEE Transactions on Computers. 33(9), pp. 828-834, 1984. "),(0,n.kt)("p",null,"[6]"," Anna Pagh, Rasmus Pagh, and S. Srinivasa Rao. An optimal Bloom filter replacement. Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 823-829, 2005. "),(0,n.kt)("p",null,"[7]"," Thomas Mueller Graf and Daniel Lemire. Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters. ACM Journal of Experimental Algorithmics. 25, pp. 1-16, 2020."))}m.isMDXComponent=!0},4221:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/bloom-79da0db687b4fb2060758838b9c44513.png"},5441:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/capacity-size-5c2576bd69db0e5b510781e7cc1c5257.png"},9844:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/fp-rate-size-fbb54b2450b4a91e28c97d8adf0253e8.png"},989:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/insert-3ff48d4c63724adcf399f81b29607691.png"},8915:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/lookup-e36011237d8602b5f6c36fe5dd145bf5.png"},9440:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/math-formul-a247d4df475b26b1e7cbb2acfc0ab8c2.png"}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[3396],{3905:(e,t,i)=>{i.d(t,{Zo:()=>h,kt:()=>f});var o=i(7294);function n(e,t,i){return t in 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filters.",slug:"bloom-and-cuckoo-filters-for-cache-summarization",image:"./assets/bloom-cuckoo/bloom.png?202301181528",authors:{name:"Matthias Wright",title:"Software Engineer",url:"https://github.com/matthias-wright",image_url:"https://github.com/matthias-wright.png"},tags:["fleek network","blog","engineering","content routing"]},a=void 0,l={permalink:"/blog/bloom-and-cuckoo-filters-for-cache-summarization",source:"@site/blog/bloom-and-cuckoo-filters-for-cache-summarization.md",title:"Bloom Filters and Cuckoo Filters for Cache Summarization",description:"Summary of our experiment informing whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters.",date:"2023-09-11T15:51:51.000Z",formattedDate:"September 11, 2023",tags:[{label:"fleek network",permalink:"/blog/tags/fleek-network"},{label:"blog",permalink:"/blog/tags/blog"},{label:"engineering",permalink:"/blog/tags/engineering"},{label:"content routing",permalink:"/blog/tags/content-routing"}],readingTime:10.36,hasTruncateMarker:!0,authors:[{name:"Matthias Wright",title:"Software Engineer",url:"https://github.com/matthias-wright",image_url:"https://github.com/matthias-wright.png",imageURL:"https://github.com/matthias-wright.png"}],frontMatter:{title:"Bloom Filters and Cuckoo Filters for Cache Summarization",description:"Summary of our experiment informing whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters.",slug:"bloom-and-cuckoo-filters-for-cache-summarization",image:"./assets/bloom-cuckoo/bloom.png?202301181528",authors:{name:"Matthias Wright",title:"Software Engineer",url:"https://github.com/matthias-wright",image_url:"https://github.com/matthias-wright.png",imageURL:"https://github.com/matthias-wright.png"},tags:["fleek network","blog","engineering","content routing"]}},s={image:i(4221).Z,authorsImageUrls:[void 0]},c=[{value:"Background",id:"background",level:2},{value:"Bloom Filters",id:"bloom-filters",level:2},{value:"Cuckoo Filters",id:"cuckoo-filters",level:2},{value:"Benchmarking",id:"benchmarking",level:2},{value:"Experimental Setup",id:"experimental-setup",level:2},{value:"Memory Footprint",id:"memory-footprint",level:2},{value:"Lookup Performance",id:"lookup-performance",level:2},{value:"Insertion Performance",id:"insertion-performance",level:2},{value:"Capacity and Scaling",id:"capacity-and-scaling",level:2},{value:"Other Filters",id:"other-filters",level:2},{value:"Conclusion",id:"conclusion",level:2},{value:"References",id:"references",level:3}],h={toc:c},p="wrapper";function m(e){let{components:t,...r}=e;return(0,n.kt)(p,(0,o.Z)({},h,r,{components:t,mdxType:"MDXLayout"}),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(4221).Z,width:"1200",height:"628"})),(0,n.kt)("p",null,"Disclaimer: This is not a general comparison between Bloom filters and Cuckoo filters. This blog post summarizes some of the experiments we conducted to decide whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters, for a specific use case."),(0,n.kt)("h2",{id:"background"},"Background"),(0,n.kt)("p",null,"Nodes on Fleek Network currently use Counting Bloom filters to summarize their cached content. These cache summaries are exchanged with other nodes in order to facilitate content routing."),(0,n.kt)("p",null,"If a particular node does not store a requested piece of content, it can use the Bloom filters that it received from its peers to check if a peer stores the requested content."),(0,n.kt)("p",null,"We are using Counting Bloom filters rather than regular Bloom filters because we need to be able to remove elements from the filter to support cache eviction."),(0,n.kt)("h2",{id:"bloom-filters"},"Bloom Filters"),(0,n.kt)("p",null,"A Bloom filter is a space-efficient probabilistic data structure that can be used to perform approximate set membership queries.\nThe answer to an approximate set membership query is not ",(0,n.kt)("inlineCode",{parentName:"p"},"no")," or ",(0,n.kt)("inlineCode",{parentName:"p"},"yes,")," but rather ",(0,n.kt)("inlineCode",{parentName:"p"},"no")," or ",(0,n.kt)("inlineCode",{parentName:"p"},"probably.")," This ",(0,n.kt)("inlineCode",{parentName:"p"},"probably")," is quantified with the false positive rate. "),(0,n.kt)("p",null,"One of the convenient features of Bloom filters is that they can be configured to have a specific false positive rate.\nOf course, there is a tradeoff here; the lower the false positive rate, the larger the memory footprint. Bloom filters support two operations: ",(0,n.kt)("inlineCode",{parentName:"p"},"insert")," and ",(0,n.kt)("inlineCode",{parentName:"p"},"contains.")," "),(0,n.kt)("p",null,"A Bloom filter is represented by an array of m bits together with k independent hash functions. To insert an element into the filter, it is hashed with each of the k hash functions.\nThe resulting hashes are interpreted as integers (modulo m) to obtain k array positions. The bits at these positions are then set to 1 (if there aren't already 1).",(0,n.kt)("br",{parentName:"p"}),"\n","To check whether or not an element is contained in the filter, the element is hashed k times with the different hash functions."),(0,n.kt)("p",null,"If all bits at the resulting array positions are 1, the element is assumed to be present. If any of the k bits are zero, we can be certain that the queried element is not present in the set."),(0,n.kt)("p",null,"However, even if all bits are 1, it might still be the case that the bits were set by a combination of other elements. This is where the aforementioned false positive rate comes into play. "),(0,n.kt)("p",null,"Since we also need a ",(0,n.kt)("inlineCode",{parentName:"p"},"remove")," operation for our use case, we have been using Counting Bloom filters, a variant of Bloom filters.\nCounting Bloom filters retain most of the properties that regular Bloom filters have. The ",(0,n.kt)("inlineCode",{parentName:"p"},"remove")," operation comes at the cost of an increased memory footprint."),(0,n.kt)("p",null,"Each position in the array is no longer a single bit but a group of bits representing a counter.\nWhenever an element is inserted into the filter, the counters for all k positions are incremented by 1. To remove an element, we decrement the counters."),(0,n.kt)("h2",{id:"cuckoo-filters"},"Cuckoo Filters"),(0,n.kt)("p",null,"Bloom filters are the most known members of a class of data structures called Approximate Membership Query Filters (AMQ Filters).\nA relatively recent addition to this class is the Cuckoo filter ","[1]",". Cuckoo filters share many similarities with Bloom filters, especially Counting Bloom filters."),(0,n.kt)("p",null,"They are space-efficient and can be used for approximate set membership queries. Cuckoo filters also support the operations ",(0,n.kt)("inlineCode",{parentName:"p"},"insert,")," ",(0,n.kt)("inlineCode",{parentName:"p"},"contains,")," and ",(0,n.kt)("inlineCode",{parentName:"p"},"remove,")," and have configurable false positive rates. "),(0,n.kt)("p",null,"Cuckoo filters are based on Cuckoo hash tables ","[2]"," and leverage an optimization called partial-key cuckoo hashing. A basic Cuckoo hash table consists of an array of buckets.\nWe determine two candidate buckets for each element using two different hash functions, h1 and h2. "),(0,n.kt)("p",null,"The ",(0,n.kt)("inlineCode",{parentName:"p"},"contains")," operation will check if either bucket contains the element.\nFor insertion, if either bucket is empty, the element will be inserted into the empty bucket."),(0,n.kt)("p",null,"If neither bucket is empty, one of the buckets is selected, and the existing element is removed and inserted into its alternate location.\nThis may trigger another relocation if the alternate location is not empty. "),(0,n.kt)("p",null,"Although the insertion operation may perform a sequence of relocations, the amortized runtime is O(1). "),(0,n.kt)("p",null,"Most implementations of Cuckoo hash tables and, consequently, Cuckoo filters will use buckets that can hold multiple elements, as proposed in ","[3]","."),(0,n.kt)("p",null,"For Cuckoo filters, the hash table size is reduced by only storing fingerprints - a bit string calculated from an element's hash - rather than key-value pairs."),(0,n.kt)("p",null,"The fingerprint size is derived from the desired false positive rate.",(0,n.kt)("br",{parentName:"p"}),"\n","A problem that arises is that, to relocate existing fingerprints using the Cuckoo hashing approach described above, we need the original hash from which the fingerprint was derived."),(0,n.kt)("p",null,"Of course, we could store this hash somewhere, but the whole point of using fingerprints is to reduce the memory footprint of the filter."),(0,n.kt)("p",null,"The solution to this predicament is the aforementioned partial-key cuckoo hashing, a technique for determining an element's alternate location using only its fingerprint.",(0,n.kt)("br",{parentName:"p"}),"\n","For a given element x, the two candidate buckets are computed as follows: "),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(9440).Z,width:"1324",height:"194"})),(0,n.kt)("p",null,"An important property of this technique is that h1(x) can also be computed from h2(x) and the fingerprint."),(0,n.kt)("h2",{id:"benchmarking"},"Benchmarking"),(0,n.kt)("p",null,"As this post mentioned, we are not aiming for a general comparison of Counting Bloom and Cuckoo filters."),(0,n.kt)("p",null,"Instead, we want to determine which filter suits our specific use case better. The two main properties we are looking for are space efficiency and lookup performance. "),(0,n.kt)("p",null,"Space efficiency is important because nodes frequently update their cache and have to communicate these changes with their peers. These messages should take up as little bandwidth as possible."),(0,n.kt)("p",null,"Lookup speed is also important because Fleek Network aims to serve user requests as quickly as possible. Checking whether a peer has some content stored in their cache summary should not be a bottleneck. "),(0,n.kt)("h2",{id:"experimental-setup"},"Experimental Setup"),(0,n.kt)("p",null,"We are using our own Counting Bloom filter ",(0,n.kt)("a",{parentName:"p",href:"https://github.com/fleek-network/ursa/blob/483f4d56cbaa5e83182454d2c1db6f6af7c54912/crates/ursa-network/src/utils/bloom_filter.rs#L11"},"implementation")," and\n",(0,n.kt)("a",{parentName:"p",href:"https://github.com/sile/scalable_cuckoo_filter"},"this")," Cuckoo filter implementation in Rust (the ",(0,n.kt)("a",{parentName:"p",href:"https://github.com/efficient/cuckoofilter"},"original")," implementation is in C++). All experiments\nwere performed on a Linux machine with 16 GB RAM and an Intel Core i7 (10th Gen). Whenever the experiment is probabilistic, we repeat the experiment 20 times and report the mean and standard deviation."),(0,n.kt)("h2",{id:"memory-footprint"},"Memory Footprint"),(0,n.kt)("p",null,"For both Counting Bloom filters and Cuckoo filters, the memory footprint is determined by two factors: the filter's capacity and the desired false positive rate. In the first experiment, we examine the impact that\nthese factors have on the memory footprint. "),(0,n.kt)("p",null,"To this end, we fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The result is shown in Fig. 1.\nThe size of Bloom filters scales linearly with the capacity. Cuckoo filters are more space-efficient. This result is consistent with the experiments reported in ","[1]","."),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(5441).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 1: We fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The y-axis shows the size of the filters in Megabytes.")),(0,n.kt)("p",null,"Next, we fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. Fig. 2 shows that Cuckoo filters are more space-efficient."),(0,n.kt)("p",null,"The gap between Counting Bloom filters and Cuckoo filters grows as the false positive rate decreases. This is also consistent with experiments in ","[1]","."),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(9844).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 2: We fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. The y-axis shows the size of the filters in Megabytes.")),(0,n.kt)("h2",{id:"lookup-performance"},"Lookup Performance"),(0,n.kt)("p",null,"We first add elements to both filters until the capacity is reached. We then measure the lookup performance for different ratios of positive and negative lookups."),(0,n.kt)("p",null,"A positive lookup is for an existing element, and a negative lookup is for an element not contained in the filter. We perform 100K lookups for each ratio and report the average lookup duration and standard deviation. "),(0,n.kt)("p",null,"Fig. 3 shows the results. Bloom filters perform slightly better on average than Cuckoo filters. This result is inconsistent with ","[1]",",\nwhere Cuckoo filters were reported to have a better lookup performance than Bloom filters. It should be noted here that the authors in ","[1]"," use the original C++ Cuckoo filter implementation and their own unreleased Bloom filter implementation. In contrast, we use a Rust Cuckoo filter implementation and our Bloom filter implementation. We cannot easily determine the reason for this discrepancy."),(0,n.kt)("p",null,"However, the performance difference is negligible."),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(8915).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 3: Lookup performance for different ratios of positive and negative lookups. For example, ratio 0.25 indicates that 25% of lookups are positive and 75% are negative.\nThe shaded region indicates the standard deviation.")),(0,n.kt)("h2",{id:"insertion-performance"},"Insertion Performance"),(0,n.kt)("p",null,"Less critical than lookup performance but still important for our purposes is insertion performance. We measure how the insertion performance varies for different occupancy levels.\nFig. 4 shows the results. The insertion performance is constant across all levels of occupancy for Bloom filters."),(0,n.kt)("p",null,"For Cuckoo filters, the performance decreases as the filter becomes fuller because more relocations are required. In Fig. 4, the performance for Bloom filters is not constant. It quickly increases and then remains constant. This can be explained by CPU caching. "),(0,n.kt)("p",null,(0,n.kt)("img",{src:i(989).Z,width:"640",height:"480"})),(0,n.kt)("blockquote",null,(0,n.kt)("p",{parentName:"blockquote"},"Figure 4: Insertion performance for different occupancy levels. The shaded region indicates the standard deviation.")),(0,n.kt)("h2",{id:"capacity-and-scaling"},"Capacity and Scaling"),(0,n.kt)("p",null,"We have mentioned the capacity of a filter several times now. An interesting case is what happens when a filter's capacity is exceeded.\nBloom filters and Cuckoo filters behave differently in this scenario."),(0,n.kt)("p",null,"For Bloom filters, the ",(0,n.kt)("inlineCode",{parentName:"p"},"insertion")," operation always succeeds. However, the false positive rate will rapidly increase as we exceed the filter's capacity. While Bloom filters fail silently, Cuckoo filters are more explicit. Most implementations have a maximum number of\nrelocations that will be performed for an insertion. The ",(0,n.kt)("inlineCode",{parentName:"p"},"insertion")," operation will return an error if more relocations are required. "),(0,n.kt)("p",null,"For both filters, we can avoid this problem by simply initializing the filter with a sufficiently large capacity. However, this will increase the memory footprint of the filter."),(0,n.kt)("p",null,"Furthermore, it is difficult to predict how many elements a node on Fleek Network will cache. It is also likely that the number of cached elements will greatly vary for different nodes. "),(0,n.kt)("p",null,"Fortunately, a variant of Bloom filters called Scalable Bloom Filters ","[4]"," can adapt dynamically to the number of elements stored while guaranteeing a maximum false positive rate."),(0,n.kt)("p",null,"The proposed technique is also applicable to Cuckoo filters."),(0,n.kt)("h2",{id:"other-filters"},"Other Filters"),(0,n.kt)("p",null,"While we only looked at Bloom filters and Cuckoo filters, there are other AMQ filters that we want to mention here briefly:"),(0,n.kt)("ul",null,(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},"Quotient filters ","[5, 6]",": Compact hash tables that support insertion, lookup, and deletion. Less space-efficient than Bloom filters and Cuckoo filters. ")),(0,n.kt)("li",{parentName:"ul"},(0,n.kt)("p",{parentName:"li"},"XOR filters ","[7]",": More space-efficient than Bloom filters and Cuckoo filters. However, they are static, meaning the filter has to be rebuilt if additional elements are added. "))),(0,n.kt)("h2",{id:"conclusion"},"Conclusion"),(0,n.kt)("p",null,"We examined whether Counting Bloom filters or Cuckoo filters are more suitable for summarizing caches on Fleek Network. Cuckoo filters are more space-efficient, especially for lower false positive rates. Bloom filters have a slightly better insertion and lookup performance for the implementations we tested."),(0,n.kt)("p",null,"Both filters can be adapted to grow and shrink in size dynamically. Since the difference in insertion and lookup performance is negligible while Cuckoo filters are significantly more space-efficient, we favor Cuckoo filters for our use case. "),(0,n.kt)("h3",{id:"references"},"References"),(0,n.kt)("p",null,"[1]"," Bin Fan, Dave G. Andersen, Michael Kaminsky, and Michael D. Mitzenmacher. Cuckoo Filter: Practically Better Than Bloom.\nIn Proceedings of the 10th ACM International Conference on emerging Networking Experiments and Technologies (CoNEXT 14). Association for Computing Machinery, New York, NY, USA, pp. 75-88, 2014. "),(0,n.kt)("p",null,"[2]"," Rasmus Pagha and Flemming Friche Rodler. Cuckoo hashing. Journal of Algorithms, 51(2), pp. 122-144, 2004. "),(0,n.kt)("p",null,"[3]"," Martin Dietzfelbinger and Christoph Weidling. Balanced Allocation and Dictionaries with Tightly Packed Constant Size Bins. Theoretical Computer Science, 380(1), pp. 47-68, 2007. "),(0,n.kt)("p",null,"[4]"," Paulo S. Almeida, Carlos Baquero, Nuno Pregui\xe7a, and David Hutchison. Scalable Bloom Filters. Information Processing Letters, 101(6), pp. 255-261, 2007. "),(0,n.kt)("p",null,"[5]"," John G. Cleary. Compact hash tables using bidirectional linear probing. IEEE Transactions on Computers. 33(9), pp. 828-834, 1984. "),(0,n.kt)("p",null,"[6]"," Anna Pagh, Rasmus Pagh, and S. Srinivasa Rao. An optimal Bloom filter replacement. Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 823-829, 2005. "),(0,n.kt)("p",null,"[7]"," Thomas Mueller Graf and Daniel Lemire. Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters. ACM Journal of Experimental Algorithmics. 25, pp. 1-16, 2020."))}m.isMDXComponent=!0},4221:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/bloom-79da0db687b4fb2060758838b9c44513.png"},5441:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/capacity-size-5c2576bd69db0e5b510781e7cc1c5257.png"},9844:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/fp-rate-size-fbb54b2450b4a91e28c97d8adf0253e8.png"},989:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/insert-3ff48d4c63724adcf399f81b29607691.png"},8915:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/lookup-e36011237d8602b5f6c36fe5dd145bf5.png"},9440:(e,t,i)=>{i.d(t,{Z:()=>o});const o=i.p+"assets/images/math-formul-a247d4df475b26b1e7cbb2acfc0ab8c2.png"}}]); \ No newline at end of file diff --git a/assets/js/719c0fd7.ee1a772c.js b/assets/js/719c0fd7.ee1a772c.js new file mode 100644 index 000000000..65207e236 --- /dev/null +++ b/assets/js/719c0fd7.ee1a772c.js @@ -0,0 +1 @@ +"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[706],{6419:e=>{e.exports=JSON.parse('{"label":"permissions","permalink":"/references/tags/permissions","allTagsPath":"/references/tags","count":1,"items":[{"id":"Lightning CLI/permission-denied-os-error-13","title":"Permission denied (os error 13)","description":"\x3c!--","permalink":"/references/Lightning CLI/permission-denied-os-error-13"}]}')}}]); \ No newline at end of file diff --git a/assets/js/b2f554cd.a7386739.js b/assets/js/b2f554cd.b42ab275.js similarity index 99% rename from assets/js/b2f554cd.a7386739.js rename to assets/js/b2f554cd.b42ab275.js index 70edb3f54..8bc207384 100644 --- a/assets/js/b2f554cd.a7386739.js +++ b/assets/js/b2f554cd.b42ab275.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[1477],{10:e=>{e.exports=JSON.parse('{"blogPosts":[{"id":"bloom-and-cuckoo-filters-for-cache-summarization","metadata":{"permalink":"/blog/bloom-and-cuckoo-filters-for-cache-summarization","source":"@site/blog/bloom-and-cuckoo-filters-for-cache-summarization.md","title":"Bloom Filters and Cuckoo Filters for Cache Summarization","description":"Summary of our experiment informing whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters.","date":"2023-09-11T15:43:53.000Z","formattedDate":"September 11, 2023","tags":[{"label":"fleek network","permalink":"/blog/tags/fleek-network"},{"label":"blog","permalink":"/blog/tags/blog"},{"label":"engineering","permalink":"/blog/tags/engineering"},{"label":"content routing","permalink":"/blog/tags/content-routing"}],"readingTime":10.36,"hasTruncateMarker":true,"authors":[{"name":"Matthias Wright","title":"Software Engineer","url":"https://github.com/matthias-wright","image_url":"https://github.com/matthias-wright.png","imageURL":"https://github.com/matthias-wright.png"}],"frontMatter":{"title":"Bloom Filters and Cuckoo Filters for Cache Summarization","description":"Summary of our experiment informing whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters.","slug":"bloom-and-cuckoo-filters-for-cache-summarization","image":"./assets/bloom-cuckoo/bloom.png?202301181528","authors":{"name":"Matthias Wright","title":"Software Engineer","url":"https://github.com/matthias-wright","image_url":"https://github.com/matthias-wright.png","imageURL":"https://github.com/matthias-wright.png"},"tags":["fleek network","blog","engineering","content routing"]}},"content":"![](./assets/bloom-cuckoo/bloom.png?202301181528)\\n\\nDisclaimer: This is not a general comparison between Bloom filters and Cuckoo filters. This blog post summarizes some of the experiments we conducted to decide whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters, for a specific use case.\\n\\n\x3c!--truncate--\x3e\\n\\n## Background\\n\\nNodes on Fleek Network currently use Counting Bloom filters to summarize their cached content. These cache summaries are exchanged with other nodes in order to facilitate content routing.\\n\\nIf a particular node does not store a requested piece of content, it can use the Bloom filters that it received from its peers to check if a peer stores the requested content.\\n\\nWe are using Counting Bloom filters rather than regular Bloom filters because we need to be able to remove elements from the filter to support cache eviction.\\n\\n## Bloom Filters\\n\\nA Bloom filter is a space-efficient probabilistic data structure that can be used to perform approximate set membership queries.\\nThe answer to an approximate set membership query is not `no` or `yes,` but rather `no` or `probably.` This `probably` is quantified with the false positive rate. \\n\\nOne of the convenient features of Bloom filters is that they can be configured to have a specific false positive rate.\\nOf course, there is a tradeoff here; the lower the false positive rate, the larger the memory footprint. Bloom filters support two operations: `insert` and `contains.` \\n\\nA Bloom filter is represented by an array of m bits together with k independent hash functions. To insert an element into the filter, it is hashed with each of the k hash functions.\\nThe resulting hashes are interpreted as integers (modulo m) to obtain k array positions. The bits at these positions are then set to 1 (if there aren\'t already 1). \\nTo check whether or not an element is contained in the filter, the element is hashed k times with the different hash functions.\\n\\nIf all bits at the resulting array positions are 1, the element is assumed to be present. If any of the k bits are zero, we can be certain that the queried element is not present in the set.\\n\\nHowever, even if all bits are 1, it might still be the case that the bits were set by a combination of other elements. This is where the aforementioned false positive rate comes into play. \\n\\nSince we also need a `remove` operation for our use case, we have been using Counting Bloom filters, a variant of Bloom filters.\\nCounting Bloom filters retain most of the properties that regular Bloom filters have. The `remove` operation comes at the cost of an increased memory footprint.\\n\\nEach position in the array is no longer a single bit but a group of bits representing a counter.\\nWhenever an element is inserted into the filter, the counters for all k positions are incremented by 1. To remove an element, we decrement the counters.\\n\\n## Cuckoo Filters\\n\\nBloom filters are the most known members of a class of data structures called Approximate Membership Query Filters (AMQ Filters).\\nA relatively recent addition to this class is the Cuckoo filter [1]. Cuckoo filters share many similarities with Bloom filters, especially Counting Bloom filters.\\n\\nThey are space-efficient and can be used for approximate set membership queries. Cuckoo filters also support the operations `insert,` `contains,` and `remove,` and have configurable false positive rates. \\n\\nCuckoo filters are based on Cuckoo hash tables [2] and leverage an optimization called partial-key cuckoo hashing. A basic Cuckoo hash table consists of an array of buckets.\\nWe determine two candidate buckets for each element using two different hash functions, h1 and h2. \\n\\nThe `contains` operation will check if either bucket contains the element.\\nFor insertion, if either bucket is empty, the element will be inserted into the empty bucket.\\n\\nIf neither bucket is empty, one of the buckets is selected, and the existing element is removed and inserted into its alternate location.\\nThis may trigger another relocation if the alternate location is not empty. \\n\\nAlthough the insertion operation may perform a sequence of relocations, the amortized runtime is O(1). \\n\\nMost implementations of Cuckoo hash tables and, consequently, Cuckoo filters will use buckets that can hold multiple elements, as proposed in [3].\\n\\nFor Cuckoo filters, the hash table size is reduced by only storing fingerprints - a bit string calculated from an element\'s hash - rather than key-value pairs.\\n\\nThe fingerprint size is derived from the desired false positive rate. \\nA problem that arises is that, to relocate existing fingerprints using the Cuckoo hashing approach described above, we need the original hash from which the fingerprint was derived.\\n\\nOf course, we could store this hash somewhere, but the whole point of using fingerprints is to reduce the memory footprint of the filter.\\n\\nThe solution to this predicament is the aforementioned partial-key cuckoo hashing, a technique for determining an element\'s alternate location using only its fingerprint. \\nFor a given element x, the two candidate buckets are computed as follows: \\n\\n\\n\x3c!-- \\nTODO: Install math forms renderer, till then use img\\n\\n$h_1(x) = \\\\text{hash}(x)$\\n\\n$h_2(x) = h_1(x) \\\\oplus \\\\text{hash}(\\\\text{fingerprint}(x))$\\n--\x3e\\n\\n![](./assets/bloom-cuckoo/math-formul.png?202301181528)\\n\\nAn important property of this technique is that h1(x) can also be computed from h2(x) and the fingerprint.\\n\\n## Benchmarking\\n\\nAs this post mentioned, we are not aiming for a general comparison of Counting Bloom and Cuckoo filters.\\n\\nInstead, we want to determine which filter suits our specific use case better. The two main properties we are looking for are space efficiency and lookup performance. \\n\\nSpace efficiency is important because nodes frequently update their cache and have to communicate these changes with their peers. These messages should take up as little bandwidth as possible.\\n\\nLookup speed is also important because Fleek Network aims to serve user requests as quickly as possible. Checking whether a peer has some content stored in their cache summary should not be a bottleneck. \\n\\n## Experimental Setup\\n\\nWe are using our own Counting Bloom filter [implementation](https://github.com/fleek-network/ursa/blob/483f4d56cbaa5e83182454d2c1db6f6af7c54912/crates/ursa-network/src/utils/bloom_filter.rs#L11) and \\n[this](https://github.com/sile/scalable_cuckoo_filter) Cuckoo filter implementation in Rust (the [original](https://github.com/efficient/cuckoofilter) implementation is in C++). All experiments\\nwere performed on a Linux machine with 16 GB RAM and an Intel Core i7 (10th Gen). Whenever the experiment is probabilistic, we repeat the experiment 20 times and report the mean and standard deviation.\\n\\n## Memory Footprint\\n\\nFor both Counting Bloom filters and Cuckoo filters, the memory footprint is determined by two factors: the filter\'s capacity and the desired false positive rate. In the first experiment, we examine the impact that\\nthese factors have on the memory footprint. \\n\\nTo this end, we fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The result is shown in Fig. 1. \\nThe size of Bloom filters scales linearly with the capacity. Cuckoo filters are more space-efficient. This result is consistent with the experiments reported in [1].\\n\\n![](./assets/bloom-cuckoo/capacity-size.png?202301121718)\\n\\n> Figure 1: We fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The y-axis shows the size of the filters in Megabytes.\\n\\nNext, we fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. Fig. 2 shows that Cuckoo filters are more space-efficient.\\n\\nThe gap between Counting Bloom filters and Cuckoo filters grows as the false positive rate decreases. This is also consistent with experiments in [1].\\n\\n![](./assets/bloom-cuckoo/fp-rate-size.png?202301121718)\\n\\n> Figure 2: We fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. The y-axis shows the size of the filters in Megabytes.\\n\\n## Lookup Performance\\n\\nWe first add elements to both filters until the capacity is reached. We then measure the lookup performance for different ratios of positive and negative lookups.\\n\\nA positive lookup is for an existing element, and a negative lookup is for an element not contained in the filter. We perform 100K lookups for each ratio and report the average lookup duration and standard deviation. \\n\\nFig. 3 shows the results. Bloom filters perform slightly better on average than Cuckoo filters. This result is inconsistent with [1],\\nwhere Cuckoo filters were reported to have a better lookup performance than Bloom filters. It should be noted here that the authors in [1] use the original C++ Cuckoo filter implementation and their own unreleased Bloom filter implementation. In contrast, we use a Rust Cuckoo filter implementation and our Bloom filter implementation. We cannot easily determine the reason for this discrepancy.\\n\\nHowever, the performance difference is negligible.\\n\\n![](./assets/bloom-cuckoo/lookup.png?202301121718)\\n\\n> Figure 3: Lookup performance for different ratios of positive and negative lookups. For example, ratio 0.25 indicates that 25% of lookups are positive and 75% are negative.\\nThe shaded region indicates the standard deviation.\\n\\n## Insertion Performance\\n\\nLess critical than lookup performance but still important for our purposes is insertion performance. We measure how the insertion performance varies for different occupancy levels.\\nFig. 4 shows the results. The insertion performance is constant across all levels of occupancy for Bloom filters.\\n\\nFor Cuckoo filters, the performance decreases as the filter becomes fuller because more relocations are required. In Fig. 4, the performance for Bloom filters is not constant. It quickly increases and then remains constant. This can be explained by CPU caching. \\n\\n![](./assets/bloom-cuckoo/insert.png?202301121718)\\n\\n> Figure 4: Insertion performance for different occupancy levels. The shaded region indicates the standard deviation.\\n\\n## Capacity and Scaling\\n\\nWe have mentioned the capacity of a filter several times now. An interesting case is what happens when a filter\'s capacity is exceeded.\\nBloom filters and Cuckoo filters behave differently in this scenario.\\n\\nFor Bloom filters, the `insertion` operation always succeeds. However, the false positive rate will rapidly increase as we exceed the filter\'s capacity. While Bloom filters fail silently, Cuckoo filters are more explicit. Most implementations have a maximum number of\\nrelocations that will be performed for an insertion. The `insertion` operation will return an error if more relocations are required. \\n\\nFor both filters, we can avoid this problem by simply initializing the filter with a sufficiently large capacity. However, this will increase the memory footprint of the filter.\\n\\nFurthermore, it is difficult to predict how many elements a node on Fleek Network will cache. It is also likely that the number of cached elements will greatly vary for different nodes. \\n\\nFortunately, a variant of Bloom filters called Scalable Bloom Filters [4] can adapt dynamically to the number of elements stored while guaranteeing a maximum false positive rate.\\n\\nThe proposed technique is also applicable to Cuckoo filters.\\n\\n## Other Filters\\n\\nWhile we only looked at Bloom filters and Cuckoo filters, there are other AMQ filters that we want to mention here briefly:\\n\\n* Quotient filters [5, 6]: Compact hash tables that support insertion, lookup, and deletion. Less space-efficient than Bloom filters and Cuckoo filters. \\n\\n* XOR filters [7]: More space-efficient than Bloom filters and Cuckoo filters. However, they are static, meaning the filter has to be rebuilt if additional elements are added. \\n\\n## Conclusion\\n\\nWe examined whether Counting Bloom filters or Cuckoo filters are more suitable for summarizing caches on Fleek Network. Cuckoo filters are more space-efficient, especially for lower false positive rates. Bloom filters have a slightly better insertion and lookup performance for the implementations we tested.\\n\\nBoth filters can be adapted to grow and shrink in size dynamically. Since the difference in insertion and lookup performance is negligible while Cuckoo filters are significantly more space-efficient, we favor Cuckoo filters for our use case. \\n\\n### References\\n\\n[1] Bin Fan, Dave G. Andersen, Michael Kaminsky, and Michael D. Mitzenmacher. Cuckoo Filter: Practically Better Than Bloom.\\nIn Proceedings of the 10th ACM International Conference on emerging Networking Experiments and Technologies (CoNEXT 14). Association for Computing Machinery, New York, NY, USA, pp. 75-88, 2014. \\n\\n[2] Rasmus Pagha and Flemming Friche Rodler. Cuckoo hashing. Journal of Algorithms, 51(2), pp. 122-144, 2004. \\n\\n[3] Martin Dietzfelbinger and Christoph Weidling. Balanced Allocation and Dictionaries with Tightly Packed Constant Size Bins. Theoretical Computer Science, 380(1), pp. 47-68, 2007. \\n\\n[4] Paulo S. Almeida, Carlos Baquero, Nuno Pregui\xe7a, and David Hutchison. Scalable Bloom Filters. Information Processing Letters, 101(6), pp. 255-261, 2007. \\n\\n[5] John G. Cleary. Compact hash tables using bidirectional linear probing. IEEE Transactions on Computers. 33(9), pp. 828-834, 1984. \\n\\n[6] Anna Pagh, Rasmus Pagh, and S. Srinivasa Rao. An optimal Bloom filter replacement. Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 823-829, 2005. \\n \\n[7] Thomas Mueller Graf and Daniel Lemire. Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters. ACM Journal of Experimental Algorithmics. 25, pp. 1-16, 2020."}]}')}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[1477],{10:e=>{e.exports=JSON.parse('{"blogPosts":[{"id":"bloom-and-cuckoo-filters-for-cache-summarization","metadata":{"permalink":"/blog/bloom-and-cuckoo-filters-for-cache-summarization","source":"@site/blog/bloom-and-cuckoo-filters-for-cache-summarization.md","title":"Bloom Filters and Cuckoo Filters for Cache Summarization","description":"Summary of our experiment informing whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters.","date":"2023-09-11T15:51:51.000Z","formattedDate":"September 11, 2023","tags":[{"label":"fleek network","permalink":"/blog/tags/fleek-network"},{"label":"blog","permalink":"/blog/tags/blog"},{"label":"engineering","permalink":"/blog/tags/engineering"},{"label":"content routing","permalink":"/blog/tags/content-routing"}],"readingTime":10.36,"hasTruncateMarker":true,"authors":[{"name":"Matthias Wright","title":"Software Engineer","url":"https://github.com/matthias-wright","image_url":"https://github.com/matthias-wright.png","imageURL":"https://github.com/matthias-wright.png"}],"frontMatter":{"title":"Bloom Filters and Cuckoo Filters for Cache Summarization","description":"Summary of our experiment informing whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters.","slug":"bloom-and-cuckoo-filters-for-cache-summarization","image":"./assets/bloom-cuckoo/bloom.png?202301181528","authors":{"name":"Matthias Wright","title":"Software Engineer","url":"https://github.com/matthias-wright","image_url":"https://github.com/matthias-wright.png","imageURL":"https://github.com/matthias-wright.png"},"tags":["fleek network","blog","engineering","content routing"]}},"content":"![](./assets/bloom-cuckoo/bloom.png?202301181528)\\n\\nDisclaimer: This is not a general comparison between Bloom filters and Cuckoo filters. This blog post summarizes some of the experiments we conducted to decide whether or not we should replace our implementation of Counting Bloom filters with Cuckoo filters, for a specific use case.\\n\\n\x3c!--truncate--\x3e\\n\\n## Background\\n\\nNodes on Fleek Network currently use Counting Bloom filters to summarize their cached content. These cache summaries are exchanged with other nodes in order to facilitate content routing.\\n\\nIf a particular node does not store a requested piece of content, it can use the Bloom filters that it received from its peers to check if a peer stores the requested content.\\n\\nWe are using Counting Bloom filters rather than regular Bloom filters because we need to be able to remove elements from the filter to support cache eviction.\\n\\n## Bloom Filters\\n\\nA Bloom filter is a space-efficient probabilistic data structure that can be used to perform approximate set membership queries.\\nThe answer to an approximate set membership query is not `no` or `yes,` but rather `no` or `probably.` This `probably` is quantified with the false positive rate. \\n\\nOne of the convenient features of Bloom filters is that they can be configured to have a specific false positive rate.\\nOf course, there is a tradeoff here; the lower the false positive rate, the larger the memory footprint. Bloom filters support two operations: `insert` and `contains.` \\n\\nA Bloom filter is represented by an array of m bits together with k independent hash functions. To insert an element into the filter, it is hashed with each of the k hash functions.\\nThe resulting hashes are interpreted as integers (modulo m) to obtain k array positions. The bits at these positions are then set to 1 (if there aren\'t already 1). \\nTo check whether or not an element is contained in the filter, the element is hashed k times with the different hash functions.\\n\\nIf all bits at the resulting array positions are 1, the element is assumed to be present. If any of the k bits are zero, we can be certain that the queried element is not present in the set.\\n\\nHowever, even if all bits are 1, it might still be the case that the bits were set by a combination of other elements. This is where the aforementioned false positive rate comes into play. \\n\\nSince we also need a `remove` operation for our use case, we have been using Counting Bloom filters, a variant of Bloom filters.\\nCounting Bloom filters retain most of the properties that regular Bloom filters have. The `remove` operation comes at the cost of an increased memory footprint.\\n\\nEach position in the array is no longer a single bit but a group of bits representing a counter.\\nWhenever an element is inserted into the filter, the counters for all k positions are incremented by 1. To remove an element, we decrement the counters.\\n\\n## Cuckoo Filters\\n\\nBloom filters are the most known members of a class of data structures called Approximate Membership Query Filters (AMQ Filters).\\nA relatively recent addition to this class is the Cuckoo filter [1]. Cuckoo filters share many similarities with Bloom filters, especially Counting Bloom filters.\\n\\nThey are space-efficient and can be used for approximate set membership queries. Cuckoo filters also support the operations `insert,` `contains,` and `remove,` and have configurable false positive rates. \\n\\nCuckoo filters are based on Cuckoo hash tables [2] and leverage an optimization called partial-key cuckoo hashing. A basic Cuckoo hash table consists of an array of buckets.\\nWe determine two candidate buckets for each element using two different hash functions, h1 and h2. \\n\\nThe `contains` operation will check if either bucket contains the element.\\nFor insertion, if either bucket is empty, the element will be inserted into the empty bucket.\\n\\nIf neither bucket is empty, one of the buckets is selected, and the existing element is removed and inserted into its alternate location.\\nThis may trigger another relocation if the alternate location is not empty. \\n\\nAlthough the insertion operation may perform a sequence of relocations, the amortized runtime is O(1). \\n\\nMost implementations of Cuckoo hash tables and, consequently, Cuckoo filters will use buckets that can hold multiple elements, as proposed in [3].\\n\\nFor Cuckoo filters, the hash table size is reduced by only storing fingerprints - a bit string calculated from an element\'s hash - rather than key-value pairs.\\n\\nThe fingerprint size is derived from the desired false positive rate. \\nA problem that arises is that, to relocate existing fingerprints using the Cuckoo hashing approach described above, we need the original hash from which the fingerprint was derived.\\n\\nOf course, we could store this hash somewhere, but the whole point of using fingerprints is to reduce the memory footprint of the filter.\\n\\nThe solution to this predicament is the aforementioned partial-key cuckoo hashing, a technique for determining an element\'s alternate location using only its fingerprint. \\nFor a given element x, the two candidate buckets are computed as follows: \\n\\n\\n\x3c!-- \\nTODO: Install math forms renderer, till then use img\\n\\n$h_1(x) = \\\\text{hash}(x)$\\n\\n$h_2(x) = h_1(x) \\\\oplus \\\\text{hash}(\\\\text{fingerprint}(x))$\\n--\x3e\\n\\n![](./assets/bloom-cuckoo/math-formul.png?202301181528)\\n\\nAn important property of this technique is that h1(x) can also be computed from h2(x) and the fingerprint.\\n\\n## Benchmarking\\n\\nAs this post mentioned, we are not aiming for a general comparison of Counting Bloom and Cuckoo filters.\\n\\nInstead, we want to determine which filter suits our specific use case better. The two main properties we are looking for are space efficiency and lookup performance. \\n\\nSpace efficiency is important because nodes frequently update their cache and have to communicate these changes with their peers. These messages should take up as little bandwidth as possible.\\n\\nLookup speed is also important because Fleek Network aims to serve user requests as quickly as possible. Checking whether a peer has some content stored in their cache summary should not be a bottleneck. \\n\\n## Experimental Setup\\n\\nWe are using our own Counting Bloom filter [implementation](https://github.com/fleek-network/ursa/blob/483f4d56cbaa5e83182454d2c1db6f6af7c54912/crates/ursa-network/src/utils/bloom_filter.rs#L11) and \\n[this](https://github.com/sile/scalable_cuckoo_filter) Cuckoo filter implementation in Rust (the [original](https://github.com/efficient/cuckoofilter) implementation is in C++). All experiments\\nwere performed on a Linux machine with 16 GB RAM and an Intel Core i7 (10th Gen). Whenever the experiment is probabilistic, we repeat the experiment 20 times and report the mean and standard deviation.\\n\\n## Memory Footprint\\n\\nFor both Counting Bloom filters and Cuckoo filters, the memory footprint is determined by two factors: the filter\'s capacity and the desired false positive rate. In the first experiment, we examine the impact that\\nthese factors have on the memory footprint. \\n\\nTo this end, we fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The result is shown in Fig. 1. \\nThe size of Bloom filters scales linearly with the capacity. Cuckoo filters are more space-efficient. This result is consistent with the experiments reported in [1].\\n\\n![](./assets/bloom-cuckoo/capacity-size.png?202301121718)\\n\\n> Figure 1: We fix the false positive rate and initialize the filters with capacities ranging from 100K to 1M. The y-axis shows the size of the filters in Megabytes.\\n\\nNext, we fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. Fig. 2 shows that Cuckoo filters are more space-efficient.\\n\\nThe gap between Counting Bloom filters and Cuckoo filters grows as the false positive rate decreases. This is also consistent with experiments in [1].\\n\\n![](./assets/bloom-cuckoo/fp-rate-size.png?202301121718)\\n\\n> Figure 2: We fix the capacity and initialize the filters with false positive rates ranging from 0.0001 to 0.5. The y-axis shows the size of the filters in Megabytes.\\n\\n## Lookup Performance\\n\\nWe first add elements to both filters until the capacity is reached. We then measure the lookup performance for different ratios of positive and negative lookups.\\n\\nA positive lookup is for an existing element, and a negative lookup is for an element not contained in the filter. We perform 100K lookups for each ratio and report the average lookup duration and standard deviation. \\n\\nFig. 3 shows the results. Bloom filters perform slightly better on average than Cuckoo filters. This result is inconsistent with [1],\\nwhere Cuckoo filters were reported to have a better lookup performance than Bloom filters. It should be noted here that the authors in [1] use the original C++ Cuckoo filter implementation and their own unreleased Bloom filter implementation. In contrast, we use a Rust Cuckoo filter implementation and our Bloom filter implementation. We cannot easily determine the reason for this discrepancy.\\n\\nHowever, the performance difference is negligible.\\n\\n![](./assets/bloom-cuckoo/lookup.png?202301121718)\\n\\n> Figure 3: Lookup performance for different ratios of positive and negative lookups. For example, ratio 0.25 indicates that 25% of lookups are positive and 75% are negative.\\nThe shaded region indicates the standard deviation.\\n\\n## Insertion Performance\\n\\nLess critical than lookup performance but still important for our purposes is insertion performance. We measure how the insertion performance varies for different occupancy levels.\\nFig. 4 shows the results. The insertion performance is constant across all levels of occupancy for Bloom filters.\\n\\nFor Cuckoo filters, the performance decreases as the filter becomes fuller because more relocations are required. In Fig. 4, the performance for Bloom filters is not constant. It quickly increases and then remains constant. This can be explained by CPU caching. \\n\\n![](./assets/bloom-cuckoo/insert.png?202301121718)\\n\\n> Figure 4: Insertion performance for different occupancy levels. The shaded region indicates the standard deviation.\\n\\n## Capacity and Scaling\\n\\nWe have mentioned the capacity of a filter several times now. An interesting case is what happens when a filter\'s capacity is exceeded.\\nBloom filters and Cuckoo filters behave differently in this scenario.\\n\\nFor Bloom filters, the `insertion` operation always succeeds. However, the false positive rate will rapidly increase as we exceed the filter\'s capacity. While Bloom filters fail silently, Cuckoo filters are more explicit. Most implementations have a maximum number of\\nrelocations that will be performed for an insertion. The `insertion` operation will return an error if more relocations are required. \\n\\nFor both filters, we can avoid this problem by simply initializing the filter with a sufficiently large capacity. However, this will increase the memory footprint of the filter.\\n\\nFurthermore, it is difficult to predict how many elements a node on Fleek Network will cache. It is also likely that the number of cached elements will greatly vary for different nodes. \\n\\nFortunately, a variant of Bloom filters called Scalable Bloom Filters [4] can adapt dynamically to the number of elements stored while guaranteeing a maximum false positive rate.\\n\\nThe proposed technique is also applicable to Cuckoo filters.\\n\\n## Other Filters\\n\\nWhile we only looked at Bloom filters and Cuckoo filters, there are other AMQ filters that we want to mention here briefly:\\n\\n* Quotient filters [5, 6]: Compact hash tables that support insertion, lookup, and deletion. Less space-efficient than Bloom filters and Cuckoo filters. \\n\\n* XOR filters [7]: More space-efficient than Bloom filters and Cuckoo filters. However, they are static, meaning the filter has to be rebuilt if additional elements are added. \\n\\n## Conclusion\\n\\nWe examined whether Counting Bloom filters or Cuckoo filters are more suitable for summarizing caches on Fleek Network. Cuckoo filters are more space-efficient, especially for lower false positive rates. Bloom filters have a slightly better insertion and lookup performance for the implementations we tested.\\n\\nBoth filters can be adapted to grow and shrink in size dynamically. Since the difference in insertion and lookup performance is negligible while Cuckoo filters are significantly more space-efficient, we favor Cuckoo filters for our use case. \\n\\n### References\\n\\n[1] Bin Fan, Dave G. Andersen, Michael Kaminsky, and Michael D. Mitzenmacher. Cuckoo Filter: Practically Better Than Bloom.\\nIn Proceedings of the 10th ACM International Conference on emerging Networking Experiments and Technologies (CoNEXT 14). Association for Computing Machinery, New York, NY, USA, pp. 75-88, 2014. \\n\\n[2] Rasmus Pagha and Flemming Friche Rodler. Cuckoo hashing. Journal of Algorithms, 51(2), pp. 122-144, 2004. \\n\\n[3] Martin Dietzfelbinger and Christoph Weidling. Balanced Allocation and Dictionaries with Tightly Packed Constant Size Bins. Theoretical Computer Science, 380(1), pp. 47-68, 2007. \\n\\n[4] Paulo S. Almeida, Carlos Baquero, Nuno Pregui\xe7a, and David Hutchison. Scalable Bloom Filters. Information Processing Letters, 101(6), pp. 255-261, 2007. \\n\\n[5] John G. Cleary. Compact hash tables using bidirectional linear probing. IEEE Transactions on Computers. 33(9), pp. 828-834, 1984. \\n\\n[6] Anna Pagh, Rasmus Pagh, and S. Srinivasa Rao. An optimal Bloom filter replacement. Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 823-829, 2005. \\n \\n[7] Thomas Mueller Graf and Daniel Lemire. Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters. ACM Journal of Experimental Algorithmics. 25, pp. 1-16, 2020."}]}')}}]); \ No newline at end of file diff --git a/assets/js/b35f1b7f.9ecb4e0c.js b/assets/js/b35f1b7f.ad119aa2.js similarity index 99% rename from assets/js/b35f1b7f.9ecb4e0c.js rename to assets/js/b35f1b7f.ad119aa2.js index 4e8d51f45..cb91ebdca 100644 --- a/assets/js/b35f1b7f.9ecb4e0c.js +++ b/assets/js/b35f1b7f.ad119aa2.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[7706],{3905:(e,t,r)=>{r.d(t,{Zo:()=>c,kt:()=>h});var s=r(7294);function n(e,t,r){return t in e?Object.defineProperty(e,t,{value:r,enumerable:!0,configurable:!0,writable:!0}):e[t]=r,e}function a(e,t){var r=Object.keys(e);if(Object.getOwnPropertySymbols){var s=Object.getOwnPropertySymbols(e);t&&(s=s.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),r.push.apply(r,s)}return r}function l(e){for(var t=1;t=0||(n[r]=e[r]);return n}(e,t);if(Object.getOwnPropertySymbols){var 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",(0,n.kt)("inlineCode",{parentName:"p"},"--user"),". When the commands were executed as ",(0,n.kt)("inlineCode",{parentName:"p"},"--user")," it failed with:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"Failed to connect to bus: Operation not permitted (consider using --machine=@.host --user to connect to bus of other user)\n")),(0,n.kt)("p",null,"The user should be able to operate as user, it shouldn't be required to connect on behalf of other users. This means that even for a simple command, such as to retrieve the list of unit files:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user list-unit-files\n")),(0,n.kt)("p",null,"We'd get the error:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"Failed to connect to bus: Operation not permitted (consider using --machine=@.host --user to connect to bus of other user)\n")),(0,n.kt)("p",null,"For any of the supported user unit locations e.g. $HOME/.config/systemd/user as documented in ",(0,n.kt)("a",{parentName:"p",href:"https://www.freedesktop.org/software/systemd/man/systemd.unit.html"},"Systemd unit documentation"),", the result is the error above."),(0,n.kt)("p",null,"This is related to the load paths when running in user mode (--user), as described in the discussion ",(0,n.kt)("a",{parentName:"p",href:"https://unix.stackexchange.com/questions/224992/where-do-i-put-my-systemd-unit-file/367237#367237"},"here"),"."),(0,n.kt)("p",null,(0,n.kt)("strong",{parentName:"p"},"User-dependent")),(0,n.kt)("p",null,(0,n.kt)("strong",{parentName:"p"},"$XDG_CONFIG_HOME/systemd/user")," User configuration (only used when $XDG_CONFIG_HOME is set)"),(0,n.kt)("p",null,(0,n.kt)("strong",{parentName:"p"},"$HOME/.config/systemd/user")," User configuration (only used when $XDG_CONFIG_HOME is not set)"),(0,n.kt)("p",null,(0,n.kt)("strong",{parentName:"p"},"$XDG_RUNTIME_DIR/systemd/user")," Runtime units (only used when $XDG_RUNTIME_DIR is set)"),(0,n.kt)("p",null,(0,n.kt)("strong",{parentName:"p"},"$XDG_DATA_HOME/systemd/user")," Units of packages that have been installed in the home directory (only used when $XDG_DATA_HOME is set)"),(0,n.kt)("p",null,(0,n.kt)("strong",{parentName:"p"},"$HOME/.local/share/systemd/user")," Units of packages that have been installed in the home directory (only used when $XDG_DATA_HOME is not set)"),(0,n.kt)("p",null,"For example, if we check the ",(0,n.kt)("inlineCode",{parentName:"p"},"$XDG_RUNTIME_DIR")," in a DigitalOcean box, we get the following output:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"/run/user/0\n")),(0,n.kt)("p",null,"For this reason and to provide support for a wider audience of users and systems, we've stuck to sudo to execute the service, but this should not be a requirement and is not recommended."),(0,n.kt)(a.Z,{name:"Helder Oliveira",image:"https://github.com/heldrida.png",title:"Software Developer + DX",url:"https://github.com/heldrida",mdxType:"Author"}))}d.isMDXComponent=!0},3872:(e,t,r)=>{r.d(t,{Z:()=>n});var s=r(7294);const n=e=>{let{image:t,name:r,title:n,url:a}=e;return s.createElement("section",{className:"author_card"},s.createElement("div",null,s.createElement("span",{className:"avatar"},s.createElement("a",{href:a,target:"_blank",alt:r},s.createElement("img",{src:t,alt:r}))),s.createElement("div",null,s.createElement("span",{className:"name"},s.createElement("a",{href:a,target:"_blank",alt:r},r)),s.createElement("span",{className:"title"},n),s.createElement("span",{className:"discord"},"Got questions? Find us on ",s.createElement("a",{href:"https://discord.gg/fleekxyz",target:"_blank"},"Discord!")))))}}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocta=self.webpackChunkdocta||[]).push([[7706],{3905:(e,t,r)=>{r.d(t,{Zo:()=>c,kt:()=>h});var s=r(7294);function n(e,t,r){return t in e?Object.defineProperty(e,t,{value:r,enumerable:!0,configurable:!0,writable:!0}):e[t]=r,e}function a(e,t){var r=Object.keys(e);if(Object.getOwnPropertySymbols){var s=Object.getOwnPropertySymbols(e);t&&(s=s.filter((function(t){return Object.getOwnPropertyDescriptor(e,t).enumerable}))),r.push.apply(r,s)}return r}function l(e){for(var t=1;t=0||(n[r]=e[r]);return n}(e,t);if(Object.getOwnPropertySymbols){var a=Object.getOwnPropertySymbols(e);for(s=0;s=0||Object.prototype.propertyIsEnumerable.call(e,r)&&(n[r]=e[r])}return n}var i=s.createContext({}),u=function(e){var t=s.useContext(i),r=t;return e&&(r="function"==typeof e?e(t):l(l({},t),e)),r},c=function(e){var t=u(e.components);return 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0,i={unversionedId:"Systemd/user-service",id:"Systemd/user-service",title:"User service",description:"\x3c!--",source:"@site/references/Systemd/user-service.md",sourceDirName:"Systemd",slug:"/Systemd/user-service",permalink:"/references/Systemd/user-service",draft:!1,editUrl:"https://github.com/fleek-network/fleek-network-docs/edit/main/references/Systemd/user-service.md",tags:[{label:"references",permalink:"/references/tags/references"},{label:"help",permalink:"/references/tags/help"},{label:"user service",permalink:"/references/tags/user-service"},{label:"unit",permalink:"/references/tags/unit"},{label:"systemctl",permalink:"/references/tags/systemctl"},{label:"systemd",permalink:"/references/tags/systemd"}],version:"current",lastUpdatedAt:1694447511,formattedLastUpdatedAt:"Sep 11, 2023",frontMatter:{title:"User service",slug:"user-service",hide_title:!0,tags:["references","help","user service","unit","systemctl","systemd"]},sidebar:"defaultSidebar",previous:{title:"Update CLI from source code",permalink:"/references/Lightning CLI/update-cli-from-source-code"}},u={},c=[{value:"Check --user support",id:"check---user-support",level:2},{value:"Systemd service control as --user",id:"systemd-service-control-as---user",level:2},{value:"Problem statement",id:"problem-statement",level:2}],p={toc:c},m="wrapper";function d(e){let{components:t,...r}=e;return(0,n.kt)(m,(0,s.Z)({},p,r,{components:t,mdxType:"MDXLayout"}),(0,n.kt)("p",null,"A user should have the ability to run a Systemd user service unit without having to use ",(0,n.kt)("inlineCode",{parentName:"p"},"sudo")," to control it."),(0,n.kt)("h2",{id:"check---user-support"},"Check ",(0,n.kt)("inlineCode",{parentName:"h2"},"--user")," support"),(0,n.kt)("p",null,"Use the ",(0,n.kt)("inlineCode",{parentName:"p"},"--user")," flag when getting the list of unit files."),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user list-unit-files\n")),(0,n.kt)("p",null,"It should return a list of unit files."),(0,n.kt)("p",null,"##\xa0Put the service unit in the user service"),(0,n.kt)("p",null,"Create the Systemd user units directory:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"sudo mkdir -p /etc/systemd/system/user\n")),(0,n.kt)("p",null,"Move the ",(0,n.kt)("inlineCode",{parentName:"p"},"lightning.service")," to the system user unit service directory:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"mv /etc/systemd/system/lightning.service /etc/systemd/system/user/lightning.service\n")),(0,n.kt)("p",null,"Check the ",(0,n.kt)("strong",{parentName:"p"},"Load path when running in user mode (--user)")," in ",(0,n.kt)("a",{parentName:"p",href:"https://www.freedesktop.org/software/systemd/man/systemd.unit.html"},"Systemd unit")," for other alternative user paths, or to understand how it works to customize your server accordingly."),(0,n.kt)("p",null,"##\xa0Reload daemon"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"sudo systemctl daemon-reload\n")),(0,n.kt)("h2",{id:"systemd-service-control-as---user"},"Systemd service control as ",(0,n.kt)("inlineCode",{parentName:"h2"},"--user")),(0,n.kt)("p",null,"Reload the Systemctl daemon by executing the command:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user daemon-reload\n")),(0,n.kt)("p",null,"Enable the service for starting up on system boot:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user enable lightning.service\n")),(0,n.kt)("p",null,"Start the service by:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user start lightning\n")),(0,n.kt)("p",null,"Stop the service by:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user stop lightning\n")),(0,n.kt)("p",null,"Restart the service by:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user restart lightning\n")),(0,n.kt)("p",null,"Check the service status by:"),(0,n.kt)("pre",null,(0,n.kt)("code",{parentName:"pre",className:"language-sh"},"systemctl --user status lightning.service\n")),(0,n.kt)("h2",{id:"problem-statement"},"Problem statement"),(0,n.kt)("p",null,"On tests done in a DigitalOcean Ubuntu 22.x, we had setup user-level services which were operated with ",(0,n.kt)("inlineCode",{parentName:"p"},"--user"),". 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