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[incubator-hugegraph-doc] branch asf-site updated: Update README.md b19c38f59b35382841b6010841868e3026ee5885
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new 058a0a7c Update README.md b19c38f59b35382841b6010841868e3026ee5885
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commit 058a0a7c178ccace127d7c20dc2e4208c3d312a7
Author: coderzc <co...@users.noreply.github.com>
AuthorDate: Sun Nov 27 13:38:33 2022 +0000
Update README.md b19c38f59b35382841b6010841868e3026ee5885
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<a href=# onclick="return print(),!1">Click here to print</a>.</p><p><a href=/docs/>Return to the regular view of this page</a>.</p></div><h1 class=title>Documentation</h1><ul><li>1: <a href=#pg-7dd24b6126e5b249f96de862bfc51025>Introduction with HugeGraph</a></li><li>2: <a href=#pg-64d47cfe1880443239e7c31f8fd1ac1a>Download HugeGraph</a></li><li>3: <a href=#pg-08b1b69f6319108b0455d24614fdd660>Quick Start</a></li><ul><li>3.1: <a href=#pg-8ec2ee5fd8ff8e48255d55eab65d92b6>HugeGraph-Server Qu [...]
implemented the <a href=https://tinkerpop.apache.org>Apache TinkerPop3</a> framework and is fully compatible with the <a href=https://tinkerpop.apache.org/gremlin.html>Gremlin</a> query language,
With complete toolchain components, it helps users to easily build applications and products based on graph databases. HugeGraph supports fast import of more than 10 billion vertices and edges, and provides millisecond-level relational query capability (OLTP).
-It can be integrated with big data platforms such as Hadoop and Spark for offline analysis (OLAP).</p><p>Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.</p>< [...]
-HugeGraph supports multi-user parallel operations. Users can enter Gremlin query statements and get graph query results in time. They can also call HugeGraph API in user programs for graph analysis or query.</p><p>This system has the following features:</p><ul><li>Ease of use: HugeGraph supports Gremlin graph query language and RESTful API, provides common interfaces for graph retrieval, and has peripheral tools with complete functions to easily implement various graph-based query and an [...]
+It support large-scale distributed graph computing (OLAP).</p><p>Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.</p><p>Typical application scenarios of HugeG [...]
+HugeGraph supports multi-user parallel operations. Users can enter Gremlin query statements and get graph query results in time. They can also call HugeGraph API in user programs for graph analysis or query.</p><p>This system has the following features:</p><ul><li>Ease of use: HugeGraph supports Gremlin graph query language and RESTful API, provides common interfaces for graph retrieval, and has peripheral tools with complete functions to easily implement various graph-based query and an [...]
</span></span></code></pre></div><h4 id=22-install-gcc-430glibcxx_3410-or-update-version-optional>2.2 Install GCC-4.3.0(GLIBCXX_3.4.10) or update version (optional)</h4><p>If you are using the RocksDB backend, be sure to execute the <code>gcc --version</code> command to check the gcc version; if you are using other backends, this is not required.</p><div class=highlight><pre tabindex=0 style=background-color:#f8f8f8;-moz-tab-size:4;-o-tab-size:4;tab-size:4><code class=language-bash data- [...]
</span></span></code></pre></div><h3 id=3-deploy>3 Deploy</h3><p>There are three ways to deploy HugeGraph-Server components:</p><ul><li>Method 1: One-click deployment</li><li>Method 2: Download the tarball</li><li>Method 3: Source code compilation</li></ul><h4 id=31-one-click-deployment>3.1 One-click deployment</h4><p>HugeGraph-Tools provides a command-line tool for one-click deployment, users can use this tool to quickly download、decompress、configure and start HugeGraphServer and HugeGr [...]
of course, you still have to download the tarball of HugeGraph-Tools first.</p><div class=highlight><pre tabindex=0 style=background-color:#f8f8f8;-moz-tab-size:4;-o-tab-size:4;tab-size:4><code class=language-bash data-lang=bash><span style=display:flex><span>wget https://github.com/hugegraph/hugegraph-tools/releases/download/v<span style=color:#4e9a06>${</span><span style=color:#000>version</span><span style=color:#4e9a06>}</span>/hugegraph-tools-<span style=color:#4e9a06>${</span><span [...]
diff --git a/docs/index.xml b/docs/index.xml
index 0e5a8fd0..f31feada 100644
--- a/docs/index.xml
+++ b/docs/index.xml
@@ -1604,7 +1604,7 @@ restserver.url=http://0.0.0.0:8080
<p>HugeGraph is an easy-to-use, efficient, general-purpose open source graph database system(Graph Database, <a href="https://github.com/hugegraph/hugegraph">GitHub project address</a>),
implemented the <a href="https://tinkerpop.apache.org">Apache TinkerPop3</a> framework and is fully compatible with the <a href="https://tinkerpop.apache.org/gremlin.html">Gremlin</a> query language,
With complete toolchain components, it helps users to easily build applications and products based on graph databases. HugeGraph supports fast import of more than 10 billion vertices and edges, and provides millisecond-level relational query capability (OLTP).
-It can be integrated with big data platforms such as Hadoop and Spark for offline analysis (OLAP).</p>
+It support large-scale distributed graph computing (OLAP).</p>
<p>Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.</p>
<p>Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.</p>
<h3 id="features">Features</h3>
@@ -1643,7 +1643,7 @@ HugeGraph supports multi-user parallel operations. Users can enter Gremlin query
</li>
<li><a href="/docs/quickstart/hugegraph-client">HugeGraph-Client</a>: HugeGraph-Client provides a RESTful API client for connecting to HugeGraph-Server. Currently, only Java version is implemented. Users of other languages can implement it by themselves;</li>
<li><a href="/docs/quickstart/hugegraph-loader">HugeGraph-Loader</a>: HugeGraph-Loader is a data import tool based on HugeGraph-Client, which converts ordinary text data into graph vertices and edges and inserts them into graph database;</li>
-<li><a href="/docs/quickstart/hugegraph-computer">HugeGraph-Computer</a>: HugeGraph-Computer is a distributed graph processing system for HugeGraph (OLAP). It is an implementation of [Pregel](<a href="https://kowshik.github">https://kowshik.github</a>. io/JPregel/pregel_paper.pdf). It runs on Kubernetes framework;</li>
+<li><a href="/docs/quickstart/hugegraph-computer">HugeGraph-Computer</a>: HugeGraph-Computer is a distributed graph processing system for HugeGraph (OLAP). It is an implementation of <a href="https://kowshik.github.io/JPregel/pregel_paper.pdf">Pregel</a>. It runs on Kubernetes framework;</li>
<li><a href="/docs/quickstart/hugegraph-hubble">HugeGraph-Hubble</a>: HugeGraph-Hubble is HugeGraph&rsquo;s web visualization management platform, a one-stop visual analysis platform. The platform covers the whole process from data modeling, to rapid data import, to online and offline analysis of data, and unified management of graphs;</li>
<li><a href="/docs/quickstart/hugegraph-tools">HugeGraph-Tools</a>: HugeGraph-Tools is HugeGraph&rsquo;s deployment and management tools, including functions such as managing graphs, backup/restore, Gremlin execution, etc.</li>
</ul>
diff --git a/docs/introduction/readme/index.html b/docs/introduction/readme/index.html
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@@ -1,6 +1,6 @@
<!doctype html><html lang=en class=no-js><head><meta charset=utf-8><meta name=viewport content="width=device-width,initial-scale=1,shrink-to-fit=no"><meta name=generator content="Hugo 0.102.3"><meta name=robots content="index, follow"><link rel="shortcut icon" href=/favicons/favicon.ico><link rel=apple-touch-icon href=/favicons/apple-touch-icon-180x180.png sizes=180x180><link rel=icon type=image/png href=/favicons/favicon-16x16.png sizes=16x16><link rel=icon type=image/png href=/favicons [...]
HugeGraph is an easy-to-use, efficient, general-purpose open source graph database system(Graph Database, GitHub project address),
-implemented …"><meta property="og:title" content="Introduction with HugeGraph"><meta property="og:description" content="Summary HugeGraph is an easy-to-use, efficient, general-purpose open source graph database system(Graph Database, GitHub project address), implemented the Apache TinkerPop3 framework and is fully compatible with the Gremlin query language, With complete toolchain components, it helps users to easily build applications and products based on graph databases. HugeGraph sup [...]
+implemented …"><meta property="og:title" content="Introduction with HugeGraph"><meta property="og:description" content="Summary HugeGraph is an easy-to-use, efficient, general-purpose open source graph database system(Graph Database, GitHub project address), implemented the Apache TinkerPop3 framework and is fully compatible with the Gremlin query language, With complete toolchain components, it helps users to easily build applications and products based on graph databases. HugeGraph sup [...]
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<a href=https://github.com/apache/incubator-hugegraph-doc/edit/master/content/en/docs/introduction/README.md class=td-page-meta--edit target=_blank rel=noopener><i class="fa fa-edit fa-fw"></i> Edit this page</a>
<a href="https://github.com/apache/incubator-hugegraph-doc/new/master/content/en/docs/introduction/README.md?filename=change-me.md&value=---%0Atitle%3A+%22Long+Page+Title%22%0AlinkTitle%3A+%22Short+Nav+Title%22%0Aweight%3A+100%0Adescription%3A+%3E-%0A+++++Page+description+for+heading+and+indexes.%0A---%0A%0A%23%23+Heading%0A%0AEdit+this+template+to+create+your+new+page.%0A%0A%2A+Give+it+a+good+name%2C+ending+in+%60.md%60+-+e.g.+%60getting-started.md%60%0A%2A+Edit+the+%22front+matter%22+s [...]
@@ -9,8 +9,8 @@ implemented …"><meta property="og:title" content="Introduction with HugeGraph"
<a id=print href=/docs/_print/><i class="fa fa-print fa-fw"></i> Print entire section</a></div><div class=td-toc><nav id=TableOfContents><ul><li><ul><li><a href=#summary>Summary</a></li><li><a href=#features>Features</a></li><li><a href=#modules>Modules</a></li><li><a href=#contact-us>Contact Us</a></li></ul></li></ul></nav></div></aside><main class="col-12 col-md-9 col-xl-8 pl-md-5" role=main><nav aria-label=breadcrumb class=td-breadcrumbs><ol class=breadcrumb><li class=breadcrumb-item> [...]
implemented the <a href=https://tinkerpop.apache.org>Apache TinkerPop3</a> framework and is fully compatible with the <a href=https://tinkerpop.apache.org/gremlin.html>Gremlin</a> query language,
With complete toolchain components, it helps users to easily build applications and products based on graph databases. HugeGraph supports fast import of more than 10 billion vertices and edges, and provides millisecond-level relational query capability (OLTP).
-It can be integrated with big data platforms such as Hadoop and Spark for offline analysis (OLAP).</p><p>Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.</p>< [...]
-HugeGraph supports multi-user parallel operations. Users can enter Gremlin query statements and get graph query results in time. They can also call HugeGraph API in user programs for graph analysis or query.</p><p>This system has the following features:</p><ul><li>Ease of use: HugeGraph supports Gremlin graph query language and RESTful API, provides common interfaces for graph retrieval, and has peripheral tools with complete functions to easily implement various graph-based query and an [...]
+It support large-scale distributed graph computing (OLAP).</p><p>Typical application scenarios of HugeGraph include deep relationship exploration, association analysis, path search, feature extraction, data clustering, community detection, knowledge graph, etc., and are applicable to business fields such as network security, telecommunication fraud, financial risk control, advertising recommendation, social network and intelligence Robots etc.</p><p>Typical application scenarios of HugeG [...]
+HugeGraph supports multi-user parallel operations. Users can enter Gremlin query statements and get graph query results in time. They can also call HugeGraph API in user programs for graph analysis or query.</p><p>This system has the following features:</p><ul><li>Ease of use: HugeGraph supports Gremlin graph query language and RESTful API, provides common interfaces for graph retrieval, and has peripheral tools with complete functions to easily implement various graph-based query and an [...]
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