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Posted to commits@hugegraph.apache.org by gi...@apache.org on 2023/05/18 05:35:25 UTC
[incubator-hugegraph-doc] branch asf-site updated: Update hugegraph-api-0.2.md (#234)
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new abde0478 Update hugegraph-api-0.2.md (#234)
abde0478 is described below
commit abde047890d170f95a43aa4734faa6e12abcf62f
Author: imbajin <im...@users.noreply.github.com>
AuthorDate: Thu May 18 05:35:20 2023 +0000
Update hugegraph-api-0.2.md (#234)
Completed the conversion to English. ec1ef02167b8bcd85735d805664e99831701a9ae
---
docs/_print/index.html | 4 +-
docs/index.xml | 119 ++++++++++-----------
docs/performance/_print/index.html | 4 +-
docs/performance/api-preformance/_print/index.html | 4 +-
.../api-preformance/hugegraph-api-0.2/index.html | 40 ++-----
docs/performance/api-preformance/index.xml | 119 ++++++++++-----------
en/sitemap.xml | 2 +-
sitemap.xml | 2 +-
8 files changed, 134 insertions(+), 160 deletions(-)
diff --git a/docs/_print/index.html b/docs/_print/index.html
index 07f46ee0..b5f52f4d 100644
--- a/docs/_print/index.html
+++ b/docs/_print/index.html
@@ -6584,9 +6584,9 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
</span></span><span style=display:flex><span>
</span></span><span style=display:flex><span><span style=color:#8f5902;font-style:italic>// what is the name of the brother and the name of the place?
</span></span></span><span style=display:flex><span><span style=color:#8f5902;font-style:italic></span><span style=color:#000>g</span><span style=color:#ce5c00;font-weight:700>.</span><span style=color:#c4a000>V</span><span style=color:#ce5c00;font-weight:700>(</span><span style=color:#000>pluto</span><span style=color:#ce5c00;font-weight:700>).</span><span style=color:#c4a000>out</span><span style=color:#ce5c00;font-weight:700>(</span><span style=color:#4e9a06>'brother'</span><s [...]
-</span></span></code></pre></div><p>推荐使用<a href=/docs/quickstart/hugegraph-studio>HugeGraph-Studio</a> 通过可视化的方式来执行上述代码。另外也可以通过HugeGraph-Client、HugeApi、GremlinConsole和GremlinDriver等多种方式执行上述代码。</p><h4 id=32-总结>3.2 总结</h4><p>HugeGraph 目前支持 <code>Gremlin</code> 的语法，用户可以通过 <code>Gremlin / REST-API</code> 实现各种查询需求。</p></div><div class=td-content style=page-break-before:always><h1 id=pg-f0a22a813c843322c0d360d952e434ce>8 - PERFORMANCE</h1></div><div class=td-content><h1 id=pg-63f6d63db3ee3a5270 [...]
+</span></span></code></pre></div><p>推荐使用<a href=/docs/quickstart/hugegraph-studio>HugeGraph-Studio</a> 通过可视化的方式来执行上述代码。另外也可以通过HugeGraph-Client、HugeApi、GremlinConsole和GremlinDriver等多种方式执行上述代码。</p><h4 id=32-总结>3.2 总结</h4><p>HugeGraph 目前支持 <code>Gremlin</code> 的语法，用户可以通过 <code>Gremlin / REST-API</code> 实现各种查询需求。</p></div><div class=td-content style=page-break-before:always><h1 id=pg-f0a22a813c843322c0d360d952e434ce>8 - PERFORMANCE</h1></div><div class=td-content><h1 id=pg-63f6d63db3ee3a5270 [...]
</span></span><span style=display:flex><span> batch_size_fail_threshold_in_kb: 1000
-</span></span></code></pre></div><ul><li>HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。</li></ul><h4 id=13-名词解释>1.3 名词解释</h4><ul><li>Samples – 本次场景中一共完成了多少个线程</li><li>Average – 平均响应时间</li><li>Median – 统计意义上面的响应时间的中值</li><li>90% Line – 所有线程中90%的线程的响应时间都小于xx</li><li>Min – 最小响应时间</li><li>Max – 最大响应时间</li><li>Error – 出错率</li><li>Troughput – 吞吐量Â</li><li>KB/sec – 以流量做衡量的吞吐量</li></ul><p><em>注：时间的单位 [...]
+</span></span></code></pre></div><ul><li>HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine. Configuration files for the servers are modified only for the host and port settings.</li></ul><h4 id=13-glossary>1.3 Glossary</h4><ul><li>Samples – The total number of threads completed in this scenario.</li><li>Average – The average response time.</li><li>Median – The statistical median of response times.</li><li>90% Line – The response [...]
</span></span><span style=display:flex><span>git clone https://github.com/<span style=color:#4e9a06>${</span><span style=color:#000>GITHUB_USER_NAME</span><span style=color:#4e9a06>}</span>/hugegraph
</span></span></code></pre></div></li><li><p>Configure local HugeGraph repo</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-shell data-lang=shell><span style=display:flex><span><span style=color:#204a87>cd</span> hugegraph
</span></span><span style=display:flex><span>
diff --git a/docs/index.xml b/docs/index.xml
index 8696458e..91915db8 100644
--- a/docs/index.xml
+++ b/docs/index.xml
@@ -8334,9 +8334,9 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
<blockquote>
<p>可以通过<code>GET http://localhost:8080/graphs/hugegraph/tasks/1</code>（其中&quot;1&quot;是task_id）来查询异步任务的执行状态，更多<a href="../task">异步任务RESTful API</a></p>
</blockquote></description></item><item><title>Docs: v0.2</title><link>/docs/performance/api-preformance/hugegraph-api-0.2/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>/docs/performance/api-preformance/hugegraph-api-0.2/</guid><description>
-<h3 id="1-测试环境">1 测试环境</h3>
-<h4 id="11-软硬件信息">1.1 软硬件信息</h4>
-<p>起压和被压机器配置相同，基本参数如下：</p>
+<h3 id="1-test-environment">1 Test environment</h3>
+<h4 id="11-software-and-hardware-information">1.1 Software and hardware information</h4>
+<p>The load testing and target machines have the same configuration, with the following basic parameters:</p>
<table>
<thead>
<tr>
@@ -8353,32 +8353,31 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
</tr>
</tbody>
</table>
-<p>测试工具：apache-Jmeter-2.5.1</p>
-<h4 id="12-服务配置">1.2 服务配置</h4>
+<h4 id="12-service-configuration">1.2 Service Configuration</h4>
<ul>
-<li>HugeGraph版本：0.2</li>
-<li>后端存储：使用服务内嵌的cassandra-3.10，单点部署；</li>
-<li>后端配置修改：修改了cassandra.yaml文件中的以下两个属性，其余选项均保持默认</li>
+<li>HugeGraph Version: 0.2</li>
+<li>Backend Storage: Cassandra 3.10, deployed as a single node in the service.</li>
+<li>Backend Configuration Modification: Modified two properties in the cassandra.yaml file, while keeping the rest of the options default:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="background-color:#f8f8f8;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-fallback" data-lang="fallback"><span style="display:flex;"><span> batch_size_warn_threshold_in_kb: 1000
</span></span><span style="display:flex;"><span> batch_size_fail_threshold_in_kb: 1000
</span></span></code></pre></div><ul>
-<li>HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。</li>
-</ul>
-<h4 id="13-名词解释">1.3 名词解释</h4>
-<ul>
-<li>Samples &ndash; 本次场景中一共完成了多少个线程</li>
-<li>Average &ndash; 平均响应时间</li>
-<li>Median &ndash; 统计意义上面的响应时间的中值</li>
-<li>90% Line &ndash; 所有线程中90%的线程的响应时间都小于xx</li>
-<li>Min &ndash; 最小响应时间</li>
-<li>Max &ndash; 最大响应时间</li>
-<li>Error &ndash; 出错率</li>
-<li>Troughput &ndash; 吞吐量Â</li>
-<li>KB/sec &ndash; 以流量做衡量的吞吐量</li>
-</ul>
-<p><em>注：时间的单位均为ms</em></p>
-<h3 id="2-测试结果">2 测试结果</h3>
+<li>HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine. Configuration files for the servers are modified only for the host and port settings.</li>
+</ul>
+<h4 id="13-glossary">1.3 Glossary</h4>
+<ul>
+<li>Samples &ndash; The total number of threads completed in this scenario.</li>
+<li>Average &ndash; The average response time.</li>
+<li>Median &ndash; The statistical median of response times.</li>
+<li>90% Line &ndash; The response time below which 90% of all threads fall.</li>
+<li>Min &ndash; The minimum response time.</li>
+<li>Max &ndash; The maximum response time.</li>
+<li>Error &ndash; The error rate.</li>
+<li>Troughput &ndash; The number of requests processed per unit of time.</li>
+<li>KB/sec &ndash; The throughput measured in kilobytes per second.</li>
+</ul>
+<p><em>Note: All time units are measured in ms.</em></p>
+<h3 id="2-test-results">2 Test Results</h3>
<h4 id="21-schema">2.1 schema</h4>
<table>
<thead>
@@ -8434,16 +8433,16 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
</tr>
</tbody>
</table>
-<p>结论：schema的接口，在1000并发持续5分钟的压力下，平均响应时间1-2ms，无压力</p>
-<h4 id="22-single-插入">2.2 single 插入</h4>
-<h5 id="221-插入速率测试">2.2.1 插入速率测试</h5>
-<h6 id="压力参数">压力参数</h6>
-<p>测试方法：固定并发量，测试server和后端的处理速率</p>
+<p>Conclusion: Under the pressure of 1000 concurrent requests lasting for 5 minutes, the average response time for the schema interface is 1-2ms, and there is no pressure.</p>
+<h4 id="22-single-insert">2.2 Single Insert</h4>
+<h5 id="221-insertion-rate-test">2.2.1 Insertion Rate Test</h5>
+<h6 id="pressure-parameters">Pressure Parameters</h6>
+<p>Test Method: Fixed concurrency, test server and backend processing speed.</p>
<ul>
-<li>并发量：1000</li>
-<li>持续时间：5min</li>
+<li>Concurrency: 1000</li>
+<li>Duration: 5 minutes</li>
</ul>
-<h6 id="性能指标">性能指标</h6>
+<h6 id="performance-indicators">Performance Indicators</h6>
<table>
<thead>
<tr>
@@ -8486,19 +8485,19 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
</tr>
</tbody>
</table>
-<h6 id="结论">结论</h6>
+<h6 id="conclusion">Conclusion</h6>
<ul>
-<li>顶点：平均响应时间1ms，每个请求插入一条数据，平均每秒处理920个请求，则每秒平均总共处理的数据为1*920约等于920条数据；</li>
-<li>边：平均响应时间1ms，每个请求插入一条数据，平均每秒处理920个请求，则每秒平均总共处理的数据为1*920约等于920条数据；</li>
+<li>For vertices: average response time of 1ms, with each request inserting one piece of data. With an average of 920 requests processed per second, the average total data processed per second is approximately 920 pieces of data.</li>
+<li>For edges: average response time of 1ms, with each request inserting one piece of data. With an average of 920 requests processed per second, the average total data processed per second is approximately 920 pieces of data.</li>
</ul>
-<h5 id="222-压力上限测试">2.2.2 压力上限测试</h5>
-<p>测试方法：不断提升并发量，测试server仍能正常提供服务的压力上限</p>
-<h6 id="压力参数-1">压力参数</h6>
+<h5 id="222-stress-test">2.2.2 Stress Test</h5>
+<p>Test Method: Continuously increase concurrency to test the maximum stress level at which the server can still provide normal services.</p>
+<h6 id="stress-parameters">Stress Parameters</h6>
<ul>
-<li>持续时间：5min</li>
-<li>服务异常标志：错误率大于0.00%</li>
+<li>Duration: 5 minutes</li>
+<li>Service Exception Flag: Error rate greater than 0.00%</li>
</ul>
-<h6 id="性能指标-1">性能指标</h6>
+<h6 id="performance-metrics">Performance Metrics</h6>
<table>
<thead>
<tr>
@@ -8601,32 +8600,32 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
</tr>
</tbody>
</table>
-<h6 id="结论-1">结论</h6>
+<h6 id="conclusion-1">Conclusion</h6>
<ul>
-<li>顶点：
+<li>Vertex:
<ul>
-<li>4000并发：正常，无错误率，平均耗时13ms；</li>
-<li>5000并发：每秒处理5000个数据的插入，就会存在0.06%的错误，应该已经处理不了了，顶峰应该在4000</li>
+<li>4000 concurrency: normal, no error rate, average time 13ms;</li>
+<li>5000 concurrency: if 5000 data insertions are processed per second, there will be an error rate of 0.06%, indicating that it cannot be handled. The peak should be at 4000.</li>
</ul>
</li>
-<li>边：
+<li>Edge:
<ul>
-<li>1000并发：响应时间2ms，跟2000并发的响应时间相差较多，主要是 IO network rec和send以及CPU几乎增加了一倍）；</li>
-<li>2000并发：每秒处理2000个数据的插入，平均耗时953ms，平均每秒处理1750个请求；</li>
-<li>3000并发：每秒处理3000个数据的插入，平均耗时2258ms，平均每秒处理1810个请求；</li>
-<li>4000并发：每秒处理4000个数据的插入，平均每秒处理1812个请求；</li>
+<li>1000 concurrency: response time is 2ms, which is quite different from the response time of 2000 concurrency, mainly because IO network rec and send, as well as CPU, have almost doubled);</li>
+<li>2000 concurrency: if 2000 data insertions are processed per second, the average time is 953ms, and the average number of requests processed per second is 1750;</li>
+<li>3000 concurrency: if 3000 data insertions are processed per second, the average time is 2258ms, and the average number of requests processed per second is 1810;</li>
+<li>4000 concurrency: if 4000 data insertions are processed per second, the average number of requests processed per second is 1812;</li>
</ul>
</li>
</ul>
-<h4 id="23-batch-插入">2.3 batch 插入</h4>
-<h5 id="231-插入速率测试">2.3.1 插入速率测试</h5>
-<h6 id="压力参数-2">压力参数</h6>
-<p>测试方法：固定并发量，测试server和后端的处理速率</p>
+<h4 id="23-batch-insertion">2.3 Batch Insertion</h4>
+<h5 id="231-insertion-rate-test">2.3.1 Insertion Rate Test</h5>
+<h6 id="pressure-parameters-1">Pressure Parameters</h6>
+<p>Test Method: Fix the concurrency and test the processing speed of the server and backend.</p>
<ul>
-<li>并发量：1000</li>
-<li>持续时间：5min</li>
+<li>Concurrency: 1000</li>
+<li>Duration: 5 minutes</li>
</ul>
-<h6 id="性能指标-2">性能指标</h6>
+<h6 id="performance-indicators-1">Performance Indicators</h6>
<table>
<thead>
<tr>
@@ -8669,10 +8668,10 @@ Merging mode as needed, and when the Restore is completed, restore the graph mod
</tr>
</tbody>
</table>
-<h6 id="结论-2">结论</h6>
+<h6 id="conclusion-2">Conclusion</h6>
<ul>
-<li>顶点：平均响应时间为8959ms，处理时间过长。每个请求插入199条数据，平均每秒处理103个请求，则每秒平均总共处理的数据为199*131约等于2w条数据；</li>
-<li>边：平均响应时间31849ms，处理时间过长。每个请求插入499个数据，平均每秒处理28个请求，则每秒平均总共处理的数据为28*499约等于13900条数据；</li>
+<li>Vertex: The average response time is 8959ms, which is too long. Each request inserts 199 data, and the average processing rate is 103 requests per second. Therefore, the average number of data processed per second is about 2w (20,000) data.</li>
+<li>Edge: The average response time is 31849ms, which is too long. Each request inserts 499 data, and the average processing rate is 28 requests per second. Therefore, the average number of data processed per second is about 13900 (13,900) data.</li>
</ul></description></item><item><title>Docs: HugeGraph-Hubble Quick Start</title><link>/docs/quickstart/hugegraph-hubble/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>/docs/quickstart/hugegraph-hubble/</guid><description>
<h3 id="1-hugegraph-hubble-overview">1 HugeGraph-Hubble Overview</h3>
<p>HugeGraph is an analysis-oriented graph database system that supports batch operations, which fully supports <a href="https://tinkerpop.apache.org">Apache TinkerPop3</a> framework and <a href="https://tinkerpop.apache.org/gremlin.html">Gremlin</a> graph query language. It provides a complete tool chain ecology such as export, backup, and recovery, and effectively solve the storage, query and correlation analysis needs of massive graph data. HugeGraph is widely used in t [...]
diff --git a/docs/performance/_print/index.html b/docs/performance/_print/index.html
index a494b216..43bfafe4 100644
--- a/docs/performance/_print/index.html
+++ b/docs/performance/_print/index.html
@@ -1,8 +1,8 @@
<!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"><link rel=canonical type=text/html href=/docs/performance/><link rel=alternate type=application/rss+xml href=/docs/performance/index.xml><meta name=robots content="noindex, nofollow"><link rel="shortcut icon" href=/favicons/favicon.ico><link rel=apple-touch-icon href=/favicons/apple-touch-icon-180x [...]
<link rel=stylesheet href=/css/prism.css><script type=application/javascript>var doNotTrack=!1;doNotTrack||(window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-00000000-0","auto"),ga("send","pageview"))</script><script async src=https://www.google-analytics.com/analytics.js></script></head><body class=td-section><header><nav class="js-navbar-scroll navbar navbar-expand navbar-dark flex-column flex-md-row td-navbar"><a class=navbar-brand href=/> [...]
-<a href=# onclick="return print(),!1">Click here to print</a>.</p><p><a href=/docs/performance/>Return to the regular view of this page</a>.</p></div><h1 class=title>PERFORMANCE</h1><ul><li>1: <a href=#pg-63f6d63db3ee3a5270fc1ca0a0c0e181>HugeGraph BenchMark Performance</a></li><li>2: <a href=#pg-699ebe5daed825049424b7539aad30f9>HugeGraph-API Performance</a></li><ul><li>2.1: <a href=#pg-dbfafc29a5e930415f78f72c47ee67f2>v0.5.6 Stand-alone(RocksDB)</a></li><li>2.2: <a href=#pg-fd5b165e28a07 [...]
+<a href=# onclick="return print(),!1">Click here to print</a>.</p><p><a href=/docs/performance/>Return to the regular view of this page</a>.</p></div><h1 class=title>PERFORMANCE</h1><ul><li>1: <a href=#pg-63f6d63db3ee3a5270fc1ca0a0c0e181>HugeGraph BenchMark Performance</a></li><li>2: <a href=#pg-699ebe5daed825049424b7539aad30f9>HugeGraph-API Performance</a></li><ul><li>2.1: <a href=#pg-dbfafc29a5e930415f78f72c47ee67f2>v0.5.6 Stand-alone(RocksDB)</a></li><li>2.2: <a href=#pg-fd5b165e28a07 [...]
</span></span><span style=display:flex><span> batch_size_fail_threshold_in_kb: 1000
-</span></span></code></pre></div><ul><li>HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。</li></ul><h4 id=13-名词解释>1.3 名词解释</h4><ul><li>Samples – 本次场景中一共完成了多少个线程</li><li>Average – 平均响应时间</li><li>Median – 统计意义上面的响应时间的中值</li><li>90% Line – 所有线程中90%的线程的响应时间都小于xx</li><li>Min – 最小响应时间</li><li>Max – 最大响应时间</li><li>Error – 出错率</li><li>Troughput – 吞吐量Â</li><li>KB/sec – 以流量做衡量的吞吐量</li></ul><p><em>注：时间的单位 [...]
+</span></span></code></pre></div><ul><li>HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine. Configuration files for the servers are modified only for the host and port settings.</li></ul><h4 id=13-glossary>1.3 Glossary</h4><ul><li>Samples – The total number of threads completed in this scenario.</li><li>Average – The average response time.</li><li>Median – The statistical median of response times.</li><li>90% Line – The response [...]
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diff --git a/docs/performance/api-preformance/_print/index.html b/docs/performance/api-preformance/_print/index.html
index e3f7cd9e..0da1eb36 100644
--- a/docs/performance/api-preformance/_print/index.html
+++ b/docs/performance/api-preformance/_print/index.html
@@ -2,9 +2,9 @@
Single …"><meta property="og:title" content="HugeGraph-API Performance"><meta property="og:description" content="Apache HugeGraph site"><meta property="og:type" content="website"><meta property="og:url" content="/docs/performance/api-preformance/"><meta property="og:site_name" content="HugeGraph"><meta itemprop=name content="HugeGraph-API Performance"><meta itemprop=description content="Apache HugeGraph site"><meta name=twitter:card content="summary"><meta name=twitter:title content="Hug [...]
<link rel=stylesheet href=/css/prism.css><script type=application/javascript>var doNotTrack=!1;doNotTrack||(window.ga=window.ga||function(){(ga.q=ga.q||[]).push(arguments)},ga.l=+new Date,ga("create","UA-00000000-0","auto"),ga("send","pageview"))</script><script async src=https://www.google-analytics.com/analytics.js></script></head><body class=td-section><header><nav class="js-navbar-scroll navbar navbar-expand navbar-dark flex-column flex-md-row td-navbar"><a class=navbar-brand href=/> [...]
-<a href=# onclick="return print(),!1">Click here to print</a>.</p><p><a href=/docs/performance/api-preformance/>Return to the regular view of this page</a>.</p></div><h1 class=title>HugeGraph-API Performance</h1><ul><li>1: <a href=#pg-dbfafc29a5e930415f78f72c47ee67f2>v0.5.6 Stand-alone(RocksDB)</a></li><li>2: <a href=#pg-fd5b165e28a07f1c35ab177b10e15dc8>v0.5.6 Cluster(Cassandra)</a></li><li>3: <a href=#pg-0005aca20e30ef2795411939ccbf0fd9>v0.4.4</a></li><li>4: <a href=#pg-d4233a3feb070643 [...]
+<a href=# onclick="return print(),!1">Click here to print</a>.</p><p><a href=/docs/performance/api-preformance/>Return to the regular view of this page</a>.</p></div><h1 class=title>HugeGraph-API Performance</h1><ul><li>1: <a href=#pg-dbfafc29a5e930415f78f72c47ee67f2>v0.5.6 Stand-alone(RocksDB)</a></li><li>2: <a href=#pg-fd5b165e28a07f1c35ab177b10e15dc8>v0.5.6 Cluster(Cassandra)</a></li><li>3: <a href=#pg-0005aca20e30ef2795411939ccbf0fd9>v0.4.4</a></li><li>4: <a href=#pg-d4233a3feb070643 [...]
</span></span><span style=display:flex><span> batch_size_fail_threshold_in_kb: 1000
-</span></span></code></pre></div><ul><li>HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。</li></ul><h4 id=13-名词解释>1.3 名词解释</h4><ul><li>Samples – 本次场景中一共完成了多少个线程</li><li>Average – 平均响应时间</li><li>Median – 统计意义上面的响应时间的中值</li><li>90% Line – 所有线程中90%的线程的响应时间都小于xx</li><li>Min – 最小响应时间</li><li>Max – 最大响应时间</li><li>Error – 出错率</li><li>Troughput – 吞吐量Â</li><li>KB/sec – 以流量做衡量的吞吐量</li></ul><p><em>注：时间的单位 [...]
+</span></span></code></pre></div><ul><li>HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine. Configuration files for the servers are modified only for the host and port settings.</li></ul><h4 id=13-glossary>1.3 Glossary</h4><ul><li>Samples – The total number of threads completed in this scenario.</li><li>Average – The average response time.</li><li>Median – The statistical median of response times.</li><li>90% Line – The response [...]
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diff --git a/docs/performance/api-preformance/hugegraph-api-0.2/index.html b/docs/performance/api-preformance/hugegraph-api-0.2/index.html
index 98e42b45..f194d9b7 100644
--- a/docs/performance/api-preformance/hugegraph-api-0.2/index.html
+++ b/docs/performance/api-preformance/hugegraph-api-0.2/index.html
@@ -1,41 +1,17 @@
-<!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 [...]
-1.1 软硬件信息
-起压和被压机器配置相同，基本参数如下：
-
-
-
-CPU
-Memory
-网卡
-
-
-
-
-24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz
-61G
-1000Mbps
-
-
-
-测试工具：apache-Jmeter-2.5.1
-1.2 服务 …"><meta property="og:title" content="v0.2"><meta property="og:description" content="1 测试环境 1.1 软硬件信息 起压和被压机器配置相同，基本参数如下：
-CPU Memory 网卡 24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz 61G 1000Mbps 测试工具：apache-Jmeter-2.5.1
-1.2 服务配置 HugeGraph版本：0.2 后端存储：使用服务内嵌的cassandra-3.10，单点部署； 后端配置修改：修改了cassandra.yaml文件中的以下两个属性，其余选项均保持默认 batch_size_warn_threshold_in_kb: 1000 batch_size_fail_threshold_in_kb: 1000 HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。 1.3 名词解释 Samples – 本次场景中一共完成了多少个线程 Average – 平均响应时间 Median – 统计意义上面的响应时间的中值 90% Line – 所有线程中90%的线程的响应时间都小于xx Min – 最小响应时间 Max – 最大响应时间 Error – 出错率 Troughput – 吞吐量Â KB/sec &nda [...]
-2 测试结果 2.1 schema Label Samples Average Median 90%Line Min Max Error% Throughput KB/sec property_keys 331000 1 1 2 0 172 0."><meta property="og:type" content="article"><meta property="og:url" content="/docs/performance/api-preformance/hugegraph-api-0.2/"><meta property="article:section" content="docs"><meta property="article:modified_time" content="2022-04-17T11:36:55+08:00"><meta property="og:site_name" content="HugeGraph"><meta itemprop=name content="v0.2"><meta itemprop=description co [...]
-CPU Memory 网卡 24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz 61G 1000Mbps 测试工具：apache-Jmeter-2.5.1
-1.2 服务配置 HugeGraph版本：0.2 后端存储：使用服务内嵌的cassandra-3.10，单点部署； 后端配置修改：修改了cassandra.yaml文件中的以下两个属性，其余选项均保持默认 batch_size_warn_threshold_in_kb: 1000 batch_size_fail_threshold_in_kb: 1000 HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。 1.3 名词解释 Samples – 本次场景中一共完成了多少个线程 Average – 平均响应时间 Median – 统计意义上面的响应时间的中值 90% Line – 所有线程中90%的线程的响应时间都小于xx Min – 最小响应时间 Max – 最大响应时间 Error – 出错率 Troughput – 吞吐量Â KB/sec &nda [...]
-2 测试结果 2.1 schema Label Samples Average Median 90%Line Min Max Error% Throughput KB/sec property_keys 331000 1 1 2 0 172 0."><meta itemprop=dateModified content="2022-04-17T11:36:55+08:00"><meta itemprop=wordCount content="294"><meta itemprop=keywords content><meta name=twitter:card content="summary"><meta name=twitter:title content="v0.2"><meta name=twitter:description content="1 测试环境 1.1 软硬件信息 起压和被压机器配置相同，基本参数如下：
-CPU Memory 网卡 24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz 61G 1000Mbps 测试工具：apache-Jmeter-2.5.1
-1.2 服务配置 HugeGraph版本：0.2 后端存储：使用服务内嵌的cassandra-3.10，单点部署； 后端配置修改：修改了cassandra.yaml文件中的以下两个属性，其余选项均保持默认 batch_size_warn_threshold_in_kb: 1000 batch_size_fail_threshold_in_kb: 1000 HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。 1.3 名词解释 Samples – 本次场景中一共完成了多少个线程 Average – 平均响应时间 Median – 统计意义上面的响应时间的中值 90% Line – 所有线程中90%的线程的响应时间都小于xx Min – 最小响应时间 Max – 最大响应时间 Error – 出错率 Troughput – 吞吐量Â KB/sec &nda [...]
-2 测试结果 2.1 schema Label Samples Average Median 90%Line Min Max Error% Throughput KB/sec property_keys 331000 1 1 2 0 172 0."><link rel=preload href=/scss/main.min.ad1b0560bef9c54394313a5bc50d3313d4e56ea590ddc5cfb84a077dfc6fec5e.css as=style><link href=/scss/main.min.ad1b0560bef9c54394313a5bc50d3313d4e56ea590ddc5cfb84a077dfc6fec5e.css rel=stylesheet integrity><script src=https://code.jquery.com/jquery-3.5.1.min.js integrity="sha256-9/aliU8dGd2tb6OSsuzixeV4y/faTqgFtohetphbbj0=" crossorigin [...]
+<!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 [...]
+1.1 Software and hardware information
+The load testing and target machines have the same configuration, with the following basic …"><meta property="og:title" content="v0.2"><meta property="og:description" content="1 Test environment 1.1 Software and hardware information The load testing and target machines have the same configuration, with the following basic parameters:
+CPU Memory 网卡 24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz 61G 1000Mbps 1.2 Service Configuration HugeGraph Version: 0.2 Backend Storage: Cassandra 3.10, deployed as a single node in the service. Backend Configuration Modification: Modified two properties in the cassandra.yaml file, while keeping the rest of the options default: batch_size_warn_threshold_in_kb: 1000 batch_size_fail_threshold_in_kb: 1000 HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine [...]
+CPU Memory 网卡 24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz 61G 1000Mbps 1.2 Service Configuration HugeGraph Version: 0.2 Backend Storage: Cassandra 3.10, deployed as a single node in the service. Backend Configuration Modification: Modified two properties in the cassandra.yaml file, while keeping the rest of the options default: batch_size_warn_threshold_in_kb: 1000 batch_size_fail_threshold_in_kb: 1000 HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine [...]
+CPU Memory 网卡 24 Intel(R) Xeon(R) CPU E5-2620 v2 @ 2.10GHz 61G 1000Mbps 1.2 Service Configuration HugeGraph Version: 0.2 Backend Storage: Cassandra 3.10, deployed as a single node in the service. Backend Configuration Modification: Modified two properties in the cassandra.yaml file, while keeping the rest of the options default: batch_size_warn_threshold_in_kb: 1000 batch_size_fail_threshold_in_kb: 1000 HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine [...]
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-<a id=print href=/docs/performance/api-preformance/_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=#1-测试环境>1 测试环境</a></li><li><a href=#2-测试结果>2 测试结果</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><a href=/docs/>Documentation</a></li><li class=breadcrumb- [...]
+<a id=print href=/docs/performance/api-preformance/_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=#1-test-environment>1 Test environment</a></li><li><a href=#2-test-results>2 Test Results</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><a href=/docs/>Doc [...]
</span></span><span style=display:flex><span> batch_size_fail_threshold_in_kb: 1000
-</span></span></code></pre></div><ul><li>HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。</li></ul><h4 id=13-名词解释>1.3 名词解释</h4><ul><li>Samples – 本次场景中一共完成了多少个线程</li><li>Average – 平均响应时间</li><li>Median – 统计意义上面的响应时间的中值</li><li>90% Line – 所有线程中90%的线程的响应时间都小于xx</li><li>Min – 最小响应时间</li><li>Max – 最大响应时间</li><li>Error – 出错率</li><li>Troughput – 吞吐量Â</li><li>KB/sec – 以流量做衡量的吞吐量</li></ul><p><em>注：时间的单位 [...]
+</span></span></code></pre></div><ul><li>HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine. Configuration files for the servers are modified only for the host and port settings.</li></ul><h4 id=13-glossary>1.3 Glossary</h4><ul><li>Samples – The total number of threads completed in this scenario.</li><li>Average – The average response time.</li><li>Median – The statistical median of response times.</li><li>90% Line – The response [...]
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diff --git a/docs/performance/api-preformance/index.xml b/docs/performance/api-preformance/index.xml
index 6cb0623d..32ce3945 100644
--- a/docs/performance/api-preformance/index.xml
+++ b/docs/performance/api-preformance/index.xml
@@ -363,9 +363,9 @@
</ul>
</li>
</ul></description></item><item><title>Docs: v0.2</title><link>/docs/performance/api-preformance/hugegraph-api-0.2/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>/docs/performance/api-preformance/hugegraph-api-0.2/</guid><description>
-<h3 id="1-测试环境">1 测试环境</h3>
-<h4 id="11-软硬件信息">1.1 软硬件信息</h4>
-<p>起压和被压机器配置相同，基本参数如下：</p>
+<h3 id="1-test-environment">1 Test environment</h3>
+<h4 id="11-software-and-hardware-information">1.1 Software and hardware information</h4>
+<p>The load testing and target machines have the same configuration, with the following basic parameters:</p>
<table>
<thead>
<tr>
@@ -382,32 +382,31 @@
</tr>
</tbody>
</table>
-<p>测试工具：apache-Jmeter-2.5.1</p>
-<h4 id="12-服务配置">1.2 服务配置</h4>
+<h4 id="12-service-configuration">1.2 Service Configuration</h4>
<ul>
-<li>HugeGraph版本：0.2</li>
-<li>后端存储：使用服务内嵌的cassandra-3.10，单点部署；</li>
-<li>后端配置修改：修改了cassandra.yaml文件中的以下两个属性，其余选项均保持默认</li>
+<li>HugeGraph Version: 0.2</li>
+<li>Backend Storage: Cassandra 3.10, deployed as a single node in the service.</li>
+<li>Backend Configuration Modification: Modified two properties in the cassandra.yaml file, while keeping the rest of the options default:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="background-color:#f8f8f8;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-fallback" data-lang="fallback"><span style="display:flex;"><span> batch_size_warn_threshold_in_kb: 1000
</span></span><span style="display:flex;"><span> batch_size_fail_threshold_in_kb: 1000
</span></span></code></pre></div><ul>
-<li>HugeGraphServer 与 HugeGremlinServer 与cassandra都在同一机器上启动，server 相关的配置文件除主机和端口有修改外，其余均保持默认。</li>
-</ul>
-<h4 id="13-名词解释">1.3 名词解释</h4>
-<ul>
-<li>Samples &ndash; 本次场景中一共完成了多少个线程</li>
-<li>Average &ndash; 平均响应时间</li>
-<li>Median &ndash; 统计意义上面的响应时间的中值</li>
-<li>90% Line &ndash; 所有线程中90%的线程的响应时间都小于xx</li>
-<li>Min &ndash; 最小响应时间</li>
-<li>Max &ndash; 最大响应时间</li>
-<li>Error &ndash; 出错率</li>
-<li>Troughput &ndash; 吞吐量Â</li>
-<li>KB/sec &ndash; 以流量做衡量的吞吐量</li>
-</ul>
-<p><em>注：时间的单位均为ms</em></p>
-<h3 id="2-测试结果">2 测试结果</h3>
+<li>HugeGraphServer, HugeGremlinServer, and Cassandra are all started on the same machine. Configuration files for the servers are modified only for the host and port settings.</li>
+</ul>
+<h4 id="13-glossary">1.3 Glossary</h4>
+<ul>
+<li>Samples &ndash; The total number of threads completed in this scenario.</li>
+<li>Average &ndash; The average response time.</li>
+<li>Median &ndash; The statistical median of response times.</li>
+<li>90% Line &ndash; The response time below which 90% of all threads fall.</li>
+<li>Min &ndash; The minimum response time.</li>
+<li>Max &ndash; The maximum response time.</li>
+<li>Error &ndash; The error rate.</li>
+<li>Troughput &ndash; The number of requests processed per unit of time.</li>
+<li>KB/sec &ndash; The throughput measured in kilobytes per second.</li>
+</ul>
+<p><em>Note: All time units are measured in ms.</em></p>
+<h3 id="2-test-results">2 Test Results</h3>
<h4 id="21-schema">2.1 schema</h4>
<table>
<thead>
@@ -463,16 +462,16 @@
</tr>
</tbody>
</table>
-<p>结论：schema的接口，在1000并发持续5分钟的压力下，平均响应时间1-2ms，无压力</p>
-<h4 id="22-single-插入">2.2 single 插入</h4>
-<h5 id="221-插入速率测试">2.2.1 插入速率测试</h5>
-<h6 id="压力参数">压力参数</h6>
-<p>测试方法：固定并发量，测试server和后端的处理速率</p>
+<p>Conclusion: Under the pressure of 1000 concurrent requests lasting for 5 minutes, the average response time for the schema interface is 1-2ms, and there is no pressure.</p>
+<h4 id="22-single-insert">2.2 Single Insert</h4>
+<h5 id="221-insertion-rate-test">2.2.1 Insertion Rate Test</h5>
+<h6 id="pressure-parameters">Pressure Parameters</h6>
+<p>Test Method: Fixed concurrency, test server and backend processing speed.</p>
<ul>
-<li>并发量：1000</li>
-<li>持续时间：5min</li>
+<li>Concurrency: 1000</li>
+<li>Duration: 5 minutes</li>
</ul>
-<h6 id="性能指标">性能指标</h6>
+<h6 id="performance-indicators">Performance Indicators</h6>
<table>
<thead>
<tr>
@@ -515,19 +514,19 @@
</tr>
</tbody>
</table>
-<h6 id="结论">结论</h6>
+<h6 id="conclusion">Conclusion</h6>
<ul>
-<li>顶点：平均响应时间1ms，每个请求插入一条数据，平均每秒处理920个请求，则每秒平均总共处理的数据为1*920约等于920条数据；</li>
-<li>边：平均响应时间1ms，每个请求插入一条数据，平均每秒处理920个请求，则每秒平均总共处理的数据为1*920约等于920条数据；</li>
+<li>For vertices: average response time of 1ms, with each request inserting one piece of data. With an average of 920 requests processed per second, the average total data processed per second is approximately 920 pieces of data.</li>
+<li>For edges: average response time of 1ms, with each request inserting one piece of data. With an average of 920 requests processed per second, the average total data processed per second is approximately 920 pieces of data.</li>
</ul>
-<h5 id="222-压力上限测试">2.2.2 压力上限测试</h5>
-<p>测试方法：不断提升并发量，测试server仍能正常提供服务的压力上限</p>
-<h6 id="压力参数-1">压力参数</h6>
+<h5 id="222-stress-test">2.2.2 Stress Test</h5>
+<p>Test Method: Continuously increase concurrency to test the maximum stress level at which the server can still provide normal services.</p>
+<h6 id="stress-parameters">Stress Parameters</h6>
<ul>
-<li>持续时间：5min</li>
-<li>服务异常标志：错误率大于0.00%</li>
+<li>Duration: 5 minutes</li>
+<li>Service Exception Flag: Error rate greater than 0.00%</li>
</ul>
-<h6 id="性能指标-1">性能指标</h6>
+<h6 id="performance-metrics">Performance Metrics</h6>
<table>
<thead>
<tr>
@@ -630,32 +629,32 @@
</tr>
</tbody>
</table>
-<h6 id="结论-1">结论</h6>
+<h6 id="conclusion-1">Conclusion</h6>
<ul>
-<li>顶点：
+<li>Vertex:
<ul>
-<li>4000并发：正常，无错误率，平均耗时13ms；</li>
-<li>5000并发：每秒处理5000个数据的插入，就会存在0.06%的错误，应该已经处理不了了，顶峰应该在4000</li>
+<li>4000 concurrency: normal, no error rate, average time 13ms;</li>
+<li>5000 concurrency: if 5000 data insertions are processed per second, there will be an error rate of 0.06%, indicating that it cannot be handled. The peak should be at 4000.</li>
</ul>
</li>
-<li>边：
+<li>Edge:
<ul>
-<li>1000并发：响应时间2ms，跟2000并发的响应时间相差较多，主要是 IO network rec和send以及CPU几乎增加了一倍）；</li>
-<li>2000并发：每秒处理2000个数据的插入，平均耗时953ms，平均每秒处理1750个请求；</li>
-<li>3000并发：每秒处理3000个数据的插入，平均耗时2258ms，平均每秒处理1810个请求；</li>
-<li>4000并发：每秒处理4000个数据的插入，平均每秒处理1812个请求；</li>
+<li>1000 concurrency: response time is 2ms, which is quite different from the response time of 2000 concurrency, mainly because IO network rec and send, as well as CPU, have almost doubled);</li>
+<li>2000 concurrency: if 2000 data insertions are processed per second, the average time is 953ms, and the average number of requests processed per second is 1750;</li>
+<li>3000 concurrency: if 3000 data insertions are processed per second, the average time is 2258ms, and the average number of requests processed per second is 1810;</li>
+<li>4000 concurrency: if 4000 data insertions are processed per second, the average number of requests processed per second is 1812;</li>
</ul>
</li>
</ul>
-<h4 id="23-batch-插入">2.3 batch 插入</h4>
-<h5 id="231-插入速率测试">2.3.1 插入速率测试</h5>
-<h6 id="压力参数-2">压力参数</h6>
-<p>测试方法：固定并发量，测试server和后端的处理速率</p>
+<h4 id="23-batch-insertion">2.3 Batch Insertion</h4>
+<h5 id="231-insertion-rate-test">2.3.1 Insertion Rate Test</h5>
+<h6 id="pressure-parameters-1">Pressure Parameters</h6>
+<p>Test Method: Fix the concurrency and test the processing speed of the server and backend.</p>
<ul>
-<li>并发量：1000</li>
-<li>持续时间：5min</li>
+<li>Concurrency: 1000</li>
+<li>Duration: 5 minutes</li>
</ul>
-<h6 id="性能指标-2">性能指标</h6>
+<h6 id="performance-indicators-1">Performance Indicators</h6>
<table>
<thead>
<tr>
@@ -698,8 +697,8 @@
</tr>
</tbody>
</table>
-<h6 id="结论-2">结论</h6>
+<h6 id="conclusion-2">Conclusion</h6>
<ul>
-<li>顶点：平均响应时间为8959ms，处理时间过长。每个请求插入199条数据，平均每秒处理103个请求，则每秒平均总共处理的数据为199*131约等于2w条数据；</li>
-<li>边：平均响应时间31849ms，处理时间过长。每个请求插入499个数据，平均每秒处理28个请求，则每秒平均总共处理的数据为28*499约等于13900条数据；</li>
+<li>Vertex: The average response time is 8959ms, which is too long. Each request inserts 199 data, and the average processing rate is 103 requests per second. Therefore, the average number of data processed per second is about 2w (20,000) data.</li>
+<li>Edge: The average response time is 31849ms, which is too long. Each request inserts 499 data, and the average processing rate is 28 requests per second. Therefore, the average number of data processed per second is about 13900 (13,900) data.</li>
</ul></description></item></channel></rss>
\ No newline at end of file
diff --git a/en/sitemap.xml b/en/sitemap.xml
index 22b100ff..7bba54aa 100644
--- a/en/sitemap.xml
+++ b/en/sitemap.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8" standalone="yes"?><urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:xhtml="http://www.w3.org/1999/xhtml"><url><loc>/docs/guides/architectural/</loc><lastmod>2023-05-12T23:46:05-05:00</lastmod><xhtml:link rel="alternate" hreflang="cn" href="/cn/docs/guides/architectural/"/><xhtml:link rel="alternate" hreflang="en" href="/docs/guides/architectural/"/></url><url><loc>/docs/config/config-guide/</loc><lastmod>2023-05-10T12:08:15+08:00</last [...]
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8" standalone="yes"?><urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9" xmlns:xhtml="http://www.w3.org/1999/xhtml"><url><loc>/docs/guides/architectural/</loc><lastmod>2023-05-12T23:46:05-05:00</lastmod><xhtml:link rel="alternate" hreflang="cn" href="/cn/docs/guides/architectural/"/><xhtml:link rel="alternate" hreflang="en" href="/docs/guides/architectural/"/></url><url><loc>/docs/config/config-guide/</loc><lastmod>2023-05-10T12:08:15+08:00</last [...]
\ No newline at end of file
diff --git a/sitemap.xml b/sitemap.xml
index 55a13450..4f2fabd6 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8" standalone="yes"?><sitemapindex xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"><sitemap><loc>/en/sitemap.xml</loc><lastmod>2023-05-17T23:12:35+08:00</lastmod></sitemap><sitemap><loc>/cn/sitemap.xml</loc><lastmod>2023-05-18T11:09:55+08:00</lastmod></sitemap></sitemapindex>
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8" standalone="yes"?><sitemapindex xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"><sitemap><loc>/en/sitemap.xml</loc><lastmod>2023-05-18T00:34:40-05:00</lastmod></sitemap><sitemap><loc>/cn/sitemap.xml</loc><lastmod>2023-05-18T11:09:55+08:00</lastmod></sitemap></sitemapindex>
\ No newline at end of file