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[incubator-hugegraph-doc] branch asf-site updated: Update hugegraph-api-0.5.6-RocksDB.md (#228)
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new 3a3b4dad Update hugegraph-api-0.5.6-RocksDB.md (#228)
3a3b4dad is described below
commit 3a3b4dad50bc8779361fb2b54b45f6f11e622dc9
Author: imbajin <im...@users.noreply.github.com>
AuthorDate: Tue May 16 03:48:24 2023 +0000
Update hugegraph-api-0.5.6-RocksDB.md (#228)
Completed the conversion to English. ae0f8f9af2a2cf4157e70f41b47e9787261e80b9
---
docs/_print/index.html | 2 +-
docs/index.xml | 128 ++++++++++-----------
docs/performance/_print/index.html | 2 +-
docs/performance/api-preformance/_print/index.html | 2 +-
.../hugegraph-api-0.5.6-rocksdb/index.html | 29 ++---
docs/performance/api-preformance/index.xml | 128 ++++++++++-----------
en/sitemap.xml | 2 +-
sitemap.xml | 2 +-
8 files changed, 143 insertions(+), 152 deletions(-)
diff --git a/docs/_print/index.html b/docs/_print/index.html
index 7bcf0d3e..f01f5afe 100644
--- a/docs/_print/index.html
+++ b/docs/_print/index.html
@@ -6583,7 +6583,7 @@ 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><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
diff --git a/docs/index.xml b/docs/index.xml
index bc728bdb..61ea3a18 100644
--- a/docs/index.xml
+++ b/docs/index.xml
@@ -2161,8 +2161,8 @@ HugeGraph supports multi-user parallel operations. Users can enter Gremlin query
</span></span><span style="display:flex;"><span> <span style="color:#000;font-weight:bold">]</span>
</span></span><span style="display:flex;"><span><span style="color:#000;font-weight:bold">}</span>
</span></span></code></pre></div></description></item><item><title>Docs: v0.5.6 Stand-alone(RocksDB)</title><link>/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/</guid><description>
-<h3 id="1-测试环境">1 测试环境</h3>
-<p>被压机器信息</p>
+<h3 id="1-test-environment">1 Test environment</h3>
+<p>Compressed machine information:</p>
<table>
<thead>
<tr>
@@ -2182,103 +2182,103 @@ HugeGraph supports multi-user parallel operations. Users can enter Gremlin query
</tbody>
</table>
<ul>
-<li>起压力机器信息：与被压机器同配置</li>
-<li>测试工具：apache-Jmeter-2.5.1</li>
-</ul>
-<p>注：起压机器和被压机器在同一机房</p>
-<h3 id="2-测试说明">2 测试说明</h3>
-<h4 id="21-名词定义时间的单位均为ms">2.1 名词定义（时间的单位均为ms）</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>Throughput &ndash; 吞吐量</li>
-<li>KB/sec &ndash; 以流量做衡量的吞吐量</li>
-</ul>
-<h4 id="22-底层存储">2.2 底层存储</h4>
-<p>后端存储使用RocksDB，HugeGraph与RocksDB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。</p>
-<h3 id="3-性能结果总结">3 性能结果总结</h3>
+<li>Information about the machine used to generate load: configured the same as the machine that is being tested under load.</li>
+<li>Testing tool: Apache JMeter 2.5.1</li>
+</ul>
+<p>Note: The load-generating machine and the machine under test are located in the same local network.</p>
+<h3 id="2-test-description">2 Test description</h3>
+<h4 id="21-definition-of-terms-the-unit-of-time-is-ms">2.1 Definition of terms (the unit of time is ms)</h4>
+<ul>
+<li>Samples: The total number of threads completed in the current scenario.</li>
+<li>Average: The average response time.</li>
+<li>Median: The statistical median of the response time.</li>
+<li>90% Line: The response time below which 90% of all threads fall.</li>
+<li>Min: The minimum response time.</li>
+<li>Max: The maximum response time.</li>
+<li>Error: The error rate.</li>
+<li>Throughput: The number of requests processed per unit of time.</li>
+<li>KB/sec: Throughput measured in terms of data transferred per second.</li>
+</ul>
+<h4 id="22-underlying-storage">2.2 Underlying storage</h4>
+<p>RocksDB is used for backend storage, HugeGraph and RocksDB are both started on the same machine, and the configuration files related to the server remain as default except for the modification of the host and port.</p>
+<h3 id="3-summary-of-performance-results">3 Summary of performance results</h3>
<ol>
-<li>HugeGraph单条插入顶点和边的速度在每秒1w左右</li>
-<li>顶点和边的批量插入速度远大于单条插入速度</li>
-<li>按id查询顶点和边的并发度可达到13000以上，且请求的平均延时小于50ms</li>
+<li>The speed of inserting a single vertex and edge in HugeGraph is about 1w per second</li>
+<li>The batch insertion speed of vertices and edges is much faster than the single insertion speed</li>
+<li>The concurrency of querying vertices and edges by id can reach more than 13000, and the average delay of requests is less than 50ms</li>
</ol>
-<h3 id="4-测试结果及分析">4 测试结果及分析</h3>
-<h4 id="41-batch插入">4.1 batch插入</h4>
-<h5 id="411-压力上限测试">4.1.1 压力上限测试</h5>
-<h6 id="测试方法">测试方法</h6>
-<p>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">压力参数</h6>
-<p>持续时间：5min</p>
-<h6 id="顶点的最大插入速度">顶点的最大插入速度：</h6>
+<h3 id="4-test-results-and-analysis">4 Test results and analysis</h3>
+<h4 id="41-batch-insertion">4.1 batch insertion</h4>
+<h5 id="411-upper-limit-stress-testing">4.1.1 Upper limit stress testing</h5>
+<h6 id="test-methods">Test methods</h6>
+<p>The upper limit of stress testing is to continuously increase the concurrency and test whether the server can still provide services normally.</p>
+<h6 id="stress-parameters">Stress Parameters</h6>
+<p>Duration: 5 minutes</p>
+<h6 id="maximum-insertion-speed-for-vertices">Maximum insertion speed for vertices:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/vertex_batch.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### in conclusion:</p>
<ul>
-<li>并发2200，顶点的吞吐量是2026.8，每秒可处理的数据：2026.8*200=405360/s</li>
+<li>With a concurrency of 2200, the throughput for vertices is 2026.8. This means that the system can process data at a rate of 405360 per second (2026.8 * 200).</li>
</ul>
-<h6 id="边的最大插入速度">边的最大插入速度</h6>
+<h6 id="maximum-insertion-speed-for-edges">Maximum insertion speed for edges</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/edge_batch.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion:</p>
<ul>
-<li>并发900，边的吞吐量是776.9，每秒可处理的数据：776.9*500=388450/s</li>
+<li>With a concurrency of 900, the throughput for edges is 776.9. This means that the system can process data at a rate of 388450 per second (776.9 * 500).</li>
</ul>
-<h4 id="42-single插入">4.2 single插入</h4>
-<h5 id="421-压力上限测试">4.2.1 压力上限测试</h5>
-<h6 id="测试方法-1">测试方法</h6>
-<p>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>
+<h4 id="42-single-insertion">4.2 Single insertion</h4>
+<h5 id="421-stress-limit-testing">4.2.1 Stress limit testing</h5>
+<h6 id="test-methods-1">Test Methods</h6>
+<p>Stress limit testing is a process of continuously increasing the concurrency level to test the upper limit of the server&rsquo;s ability to provide normal service.</p>
+<h6 id="stress-parameters-1">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 indicator: Error rate greater than 0.00%.</li>
</ul>
-<h6 id="顶点的单条插入">顶点的单条插入</h6>
+<h6 id="single-vertex-insertion">Single vertex insertion</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/vertex_single.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion:</p>
<ul>
-<li>并发11500，吞吐量为10730，顶点的单条插入并发能力为11500</li>
+<li>With a concurrency of 11500, the throughput is 10730. This means that the system can handle a single concurrent insertion of vertices at a concurrency level of 11500.</li>
</ul>
-<h6 id="边的单条插入">边的单条插入</h6>
+<h6 id="single-edge-insertion">Single edge insertion</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/edge_single.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion:</p>
<ul>
-<li>并发9000，吞吐量是8418，边的单条插入并发能力为9000</li>
+<li>With a concurrency of 9000, the throughput is 8418. This means that the system can handle a single concurrent insertion of edges at a concurrency level of 9000.</li>
</ul>
-<h4 id="43-按id查询">4.3 按id查询</h4>
-<h5 id="431-压力上限测试">4.3.1 压力上限测试</h5>
-<h6 id="测试方法-2">测试方法</h6>
-<p>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-2">压力参数</h6>
+<h4 id="43-search-by-id">4.3 Search by ID</h4>
+<h5 id="431-stress-test-upper-limit">4.3.1 Stress test upper limit</h5>
+<h6 id="testing-method">Testing method</h6>
+<p>Continuously increasing the concurrency level to test the upper limit of the server&rsquo;s ability to provide service under normal conditions.</p>
+<h6 id="stress-parameters-2">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 abnormality indicator: error rate greater than 0.00%</li>
</ul>
-<h6 id="顶点的按id查询">顶点的按id查询</h6>
+<h6 id="querying-vertices-by-id">Querying vertices by ID</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/vertex_id_query.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion：</p>
<ul>
-<li>并发14000，吞吐量是12663，顶点的按id查询的并发能力为14000，平均延时为44ms</li>
+<li>Concurrency is 14,000, throughput is 12,663. The concurrency capacity for querying vertices by ID is 14,000, with an average delay of 44ms.</li>
</ul>
-<h6 id="边的按id查询">边的按id查询</h6>
+<h6 id="querying-edges-by-id">Querying edges by ID</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/edge_id_query.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion：</p>
<ul>
-<li>并发13000，吞吐量是12225，边的按id查询的并发能力为13000，平均延时为12ms</li>
+<li>Concurrency is 13,000, throughput is 12,225. The concurrency capacity for querying edges by ID is 13,000, with an average delay of 12ms.</li>
</ul></description></item><item><title>Docs: HugeGraph Config Options</title><link>/docs/config/config-option/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>/docs/config/config-option/</guid><description>
<h3 id="gremlin-server-config-options">Gremlin Server Config Options</h3>
<p>Corresponding configuration file <code>gremlin-server.yaml</code></p>
diff --git a/docs/performance/_print/index.html b/docs/performance/_print/index.html
index 5a912e07..a17a3de8 100644
--- a/docs/performance/_print/index.html
+++ b/docs/performance/_print/index.html
@@ -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"><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 [...]
<script src=https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/js/bootstrap.min.js integrity="sha512-UR25UO94eTnCVwjbXozyeVd6ZqpaAE9naiEUBK/A+QDbfSTQFhPGj5lOR6d8tsgbBk84Ggb5A3EkjsOgPRPcKA==" crossorigin=anonymous></script>
diff --git a/docs/performance/api-preformance/_print/index.html b/docs/performance/api-preformance/_print/index.html
index d7f70979..c182078a 100644
--- a/docs/performance/api-preformance/_print/index.html
+++ b/docs/performance/api-preformance/_print/index.html
@@ -2,7 +2,7 @@
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 [...]
<script src=https://cdn.jsdelivr.net/npm/bootstrap@4.6.1/dist/js/bootstrap.min.js integrity="sha512-UR25UO94eTnCVwjbXozyeVd6ZqpaAE9naiEUBK/A+QDbfSTQFhPGj5lOR6d8tsgbBk84Ggb5A3EkjsOgPRPcKA==" crossorigin=anonymous></script>
diff --git a/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/index.html b/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/index.html
index 9f03918f..a9930f32 100644
--- a/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/index.html
+++ b/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/index.html
@@ -1,5 +1,5 @@
-<!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 [...]
-被压机器信息
+<!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 [...]
+Compressed machine information:
@@ -14,28 +14,19 @@ Memory
48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz
128G
10000Mbps
-750GB SSD,2.7T HDD
-
-
-
-
-起压力机器信息：与被压机器同配置
-测试工 …"><meta property="og:title" content="v0.5.6 Stand-alone(RocksDB)"><meta property="og:description" content="1 测试环境 被压机器信息
-CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps 750GB SSD,2.7T HDD 起压力机器信息：与被压机器同配置 测试工具：apache-Jmeter-2.5.1 注：起压机器和被压机器在同一机房
-2 测试说明 2.1 名词定义（时间的单位均为ms） 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 Throughput – 吞吐量 KB/sec – 以流量做衡量的吞吐量 2.2 底层存储 后端存储使用RocksDB，HugeGraph与RocksDB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。
-3 性能结果总结 HugeGraph单条插入顶点和边的速度在每秒1w左右 顶点和边的批量插入速度远大于单条插入速度 按id查询顶点和边的并发度可达到13000以上，且请求的平均延时小于50ms 4 测试结果及分析 4.1 batch插入 4.1.1 压力上限测试 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"><meta property="og:type" content="article"><meta property="og:url" content="/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/"><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 itemp [...]
-CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps 750GB SSD,2.7T HDD 起压力机器信息：与被压机器同配置 测试工具：apache-Jmeter-2.5.1 注：起压机器和被压机器在同一机房
-2 测试说明 2.1 名词定义（时间的单位均为ms） 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 Throughput – 吞吐量 KB/sec – 以流量做衡量的吞吐量 2.2 底层存储 后端存储使用RocksDB，HugeGraph与RocksDB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。
-3 性能结果总结 HugeGraph单条插入顶点和边的速度在每秒1w左右 顶点和边的批量插入速度远大于单条插入速度 按id查询顶点和边的并发度可达到13000以上，且请求的平均延时小于50ms 4 测试结果及分析 4.1 batch插入 4.1.1 压力上限测试 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"><meta itemprop=dateModified content="2022-04-17T11:36:55+08:00"><meta itemprop=wordCount content="115"><meta itemprop=keywords content><meta name=twitter:card content="summary"><meta name=twitter:title content="v0.5.6 Stand-alone(RocksDB)"><meta name=twitter:description content="1 测试环境 被压机器信息
-CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps 750GB SSD,2.7T HDD 起压力机器信息：与被压机器同配置 测试工具：apache-Jmeter-2.5.1 注：起压机器和被压机器在同一机房
-2 测试说明 2.1 名词定义（时间的单位均为ms） 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 Throughput – 吞吐量 KB/sec – 以流量做衡量的吞吐量 2.2 底层存储 后端存储使用RocksDB，HugeGraph与RocksDB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。
-3 性能结果总结 HugeGraph单条插入顶点和边的速度在每秒1w左右 顶点和边的批量插入速度远大于单条插入速度 按id查询顶点和边的并发度可达到13000以上，且请求的平均延时小于50ms 4 测试结果及分析 4.1 batch插入 4.1.1 压力上限测试 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"><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/aliU8dGd2tb6 [...]
+750GB SSD,2.7T …"><meta property="og:title" content="v0.5.6 Stand-alone(RocksDB)"><meta property="og:description" content="1 Test environment Compressed machine information:
+CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps 750GB SSD,2.7T HDD Information about the machine used to generate load: configured the same as the machine that is being tested under load. Testing tool: Apache JMeter 2.5.1 Note: The load-generating machine and the machine under test are located in the same local network.
+2 Test description 2.1 Definition of terms (the unit of time is ms) Samples: The total number of threads completed in the current scenario."><meta property="og:type" content="article"><meta property="og:url" content="/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/"><meta property="article:section" content="docs"><meta property="article:modified_time" content="2023-05-15T22:47:44-05:00"><meta property="og:site_name" content="HugeGraph"><meta itemprop=name content="v0.5.6 St [...]
+CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps 750GB SSD,2.7T HDD Information about the machine used to generate load: configured the same as the machine that is being tested under load. Testing tool: Apache JMeter 2.5.1 Note: The load-generating machine and the machine under test are located in the same local network.
+2 Test description 2.1 Definition of terms (the unit of time is ms) Samples: The total number of threads completed in the current scenario."><meta itemprop=dateModified content="2023-05-15T22:47:44-05:00"><meta itemprop=wordCount content="575"><meta itemprop=keywords content><meta name=twitter:card content="summary"><meta name=twitter:title content="v0.5.6 Stand-alone(RocksDB)"><meta name=twitter:description content="1 Test environment Compressed machine information:
+CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps 750GB SSD,2.7T HDD Information about the machine used to generate load: configured the same as the machine that is being tested under load. Testing tool: Apache JMeter 2.5.1 Note: The load-generating machine and the machine under test are located in the same local network.
+2 Test description 2.1 Definition of terms (the unit of time is ms) Samples: The total number of threads completed in the current scenario."><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/faTqgFtohetphbb [...]
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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-测试说明>2 测试说明</a></li><li><a href=#3-性能结果总结>3 性能结果总结</a></li><li><a href=#4-测试结果及分析>4 测试结果及分析</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 [...]
+<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-description>2 Test description</a></li><li><a href=#3-summary-of-performance-results>3 Summary of performance results</a></li><li><a href=#4-test-results-and-analysis>4 Test results and analysis</a></li></ul></li></ul></nav></div></asid [...]
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diff --git a/docs/performance/api-preformance/index.xml b/docs/performance/api-preformance/index.xml
index b57b6f30..d7c36b6d 100644
--- a/docs/performance/api-preformance/index.xml
+++ b/docs/performance/api-preformance/index.xml
@@ -1,6 +1,6 @@
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>HugeGraph – HugeGraph-API Performance</title><link>/docs/performance/api-preformance/</link><description>Recent content in HugeGraph-API Performance on HugeGraph</description><generator>Hugo -- gohugo.io</generator><atom:link href="/docs/performance/api-preformance/index.xml" rel="self" type="application/rss+xml"/><item><title>Docs: v0.5.6 Stand-alone(RocksDB)</title><link>/docs/performance/api-preformance/hugegr [...]
-<h3 id="1-测试环境">1 测试环境</h3>
-<p>被压机器信息</p>
+<h3 id="1-test-environment">1 Test environment</h3>
+<p>Compressed machine information:</p>
<table>
<thead>
<tr>
@@ -20,103 +20,103 @@
</tbody>
</table>
<ul>
-<li>起压力机器信息：与被压机器同配置</li>
-<li>测试工具：apache-Jmeter-2.5.1</li>
-</ul>
-<p>注：起压机器和被压机器在同一机房</p>
-<h3 id="2-测试说明">2 测试说明</h3>
-<h4 id="21-名词定义时间的单位均为ms">2.1 名词定义（时间的单位均为ms）</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>Throughput &ndash; 吞吐量</li>
-<li>KB/sec &ndash; 以流量做衡量的吞吐量</li>
-</ul>
-<h4 id="22-底层存储">2.2 底层存储</h4>
-<p>后端存储使用RocksDB，HugeGraph与RocksDB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。</p>
-<h3 id="3-性能结果总结">3 性能结果总结</h3>
+<li>Information about the machine used to generate load: configured the same as the machine that is being tested under load.</li>
+<li>Testing tool: Apache JMeter 2.5.1</li>
+</ul>
+<p>Note: The load-generating machine and the machine under test are located in the same local network.</p>
+<h3 id="2-test-description">2 Test description</h3>
+<h4 id="21-definition-of-terms-the-unit-of-time-is-ms">2.1 Definition of terms (the unit of time is ms)</h4>
+<ul>
+<li>Samples: The total number of threads completed in the current scenario.</li>
+<li>Average: The average response time.</li>
+<li>Median: The statistical median of the response time.</li>
+<li>90% Line: The response time below which 90% of all threads fall.</li>
+<li>Min: The minimum response time.</li>
+<li>Max: The maximum response time.</li>
+<li>Error: The error rate.</li>
+<li>Throughput: The number of requests processed per unit of time.</li>
+<li>KB/sec: Throughput measured in terms of data transferred per second.</li>
+</ul>
+<h4 id="22-underlying-storage">2.2 Underlying storage</h4>
+<p>RocksDB is used for backend storage, HugeGraph and RocksDB are both started on the same machine, and the configuration files related to the server remain as default except for the modification of the host and port.</p>
+<h3 id="3-summary-of-performance-results">3 Summary of performance results</h3>
<ol>
-<li>HugeGraph单条插入顶点和边的速度在每秒1w左右</li>
-<li>顶点和边的批量插入速度远大于单条插入速度</li>
-<li>按id查询顶点和边的并发度可达到13000以上，且请求的平均延时小于50ms</li>
+<li>The speed of inserting a single vertex and edge in HugeGraph is about 1w per second</li>
+<li>The batch insertion speed of vertices and edges is much faster than the single insertion speed</li>
+<li>The concurrency of querying vertices and edges by id can reach more than 13000, and the average delay of requests is less than 50ms</li>
</ol>
-<h3 id="4-测试结果及分析">4 测试结果及分析</h3>
-<h4 id="41-batch插入">4.1 batch插入</h4>
-<h5 id="411-压力上限测试">4.1.1 压力上限测试</h5>
-<h6 id="测试方法">测试方法</h6>
-<p>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">压力参数</h6>
-<p>持续时间：5min</p>
-<h6 id="顶点的最大插入速度">顶点的最大插入速度：</h6>
+<h3 id="4-test-results-and-analysis">4 Test results and analysis</h3>
+<h4 id="41-batch-insertion">4.1 batch insertion</h4>
+<h5 id="411-upper-limit-stress-testing">4.1.1 Upper limit stress testing</h5>
+<h6 id="test-methods">Test methods</h6>
+<p>The upper limit of stress testing is to continuously increase the concurrency and test whether the server can still provide services normally.</p>
+<h6 id="stress-parameters">Stress Parameters</h6>
+<p>Duration: 5 minutes</p>
+<h6 id="maximum-insertion-speed-for-vertices">Maximum insertion speed for vertices:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/vertex_batch.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### in conclusion:</p>
<ul>
-<li>并发2200，顶点的吞吐量是2026.8，每秒可处理的数据：2026.8*200=405360/s</li>
+<li>With a concurrency of 2200, the throughput for vertices is 2026.8. This means that the system can process data at a rate of 405360 per second (2026.8 * 200).</li>
</ul>
-<h6 id="边的最大插入速度">边的最大插入速度</h6>
+<h6 id="maximum-insertion-speed-for-edges">Maximum insertion speed for edges</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/edge_batch.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion:</p>
<ul>
-<li>并发900，边的吞吐量是776.9，每秒可处理的数据：776.9*500=388450/s</li>
+<li>With a concurrency of 900, the throughput for edges is 776.9. This means that the system can process data at a rate of 388450 per second (776.9 * 500).</li>
</ul>
-<h4 id="42-single插入">4.2 single插入</h4>
-<h5 id="421-压力上限测试">4.2.1 压力上限测试</h5>
-<h6 id="测试方法-1">测试方法</h6>
-<p>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>
+<h4 id="42-single-insertion">4.2 Single insertion</h4>
+<h5 id="421-stress-limit-testing">4.2.1 Stress limit testing</h5>
+<h6 id="test-methods-1">Test Methods</h6>
+<p>Stress limit testing is a process of continuously increasing the concurrency level to test the upper limit of the server&rsquo;s ability to provide normal service.</p>
+<h6 id="stress-parameters-1">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 indicator: Error rate greater than 0.00%.</li>
</ul>
-<h6 id="顶点的单条插入">顶点的单条插入</h6>
+<h6 id="single-vertex-insertion">Single vertex insertion</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/vertex_single.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion:</p>
<ul>
-<li>并发11500，吞吐量为10730，顶点的单条插入并发能力为11500</li>
+<li>With a concurrency of 11500, the throughput is 10730. This means that the system can handle a single concurrent insertion of vertices at a concurrency level of 11500.</li>
</ul>
-<h6 id="边的单条插入">边的单条插入</h6>
+<h6 id="single-edge-insertion">Single edge insertion</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/edge_single.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion:</p>
<ul>
-<li>并发9000，吞吐量是8418，边的单条插入并发能力为9000</li>
+<li>With a concurrency of 9000, the throughput is 8418. This means that the system can handle a single concurrent insertion of edges at a concurrency level of 9000.</li>
</ul>
-<h4 id="43-按id查询">4.3 按id查询</h4>
-<h5 id="431-压力上限测试">4.3.1 压力上限测试</h5>
-<h6 id="测试方法-2">测试方法</h6>
-<p>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-2">压力参数</h6>
+<h4 id="43-search-by-id">4.3 Search by ID</h4>
+<h5 id="431-stress-test-upper-limit">4.3.1 Stress test upper limit</h5>
+<h6 id="testing-method">Testing method</h6>
+<p>Continuously increasing the concurrency level to test the upper limit of the server&rsquo;s ability to provide service under normal conditions.</p>
+<h6 id="stress-parameters-2">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 abnormality indicator: error rate greater than 0.00%</li>
</ul>
-<h6 id="顶点的按id查询">顶点的按id查询</h6>
+<h6 id="querying-vertices-by-id">Querying vertices by ID</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/vertex_id_query.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion：</p>
<ul>
-<li>并发14000，吞吐量是12663，顶点的按id查询的并发能力为14000，平均延时为44ms</li>
+<li>Concurrency is 14,000, throughput is 12,663. The concurrency capacity for querying vertices by ID is 14,000, with an average delay of 44ms.</li>
</ul>
-<h6 id="边的按id查询">边的按id查询</h6>
+<h6 id="querying-edges-by-id">Querying edges by ID</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/rocksdb/edge_id_query.png" alt="image">
</center>
-<p>####### 结论：</p>
+<p>####### Conclusion：</p>
<ul>
-<li>并发13000，吞吐量是12225，边的按id查询的并发能力为13000，平均延时为12ms</li>
+<li>Concurrency is 13,000, throughput is 12,225. The concurrency capacity for querying edges by ID is 13,000, with an average delay of 12ms.</li>
</ul></description></item><item><title>Docs: v0.5.6 Cluster(Cassandra)</title><link>/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/</guid><description>
<h3 id="1-测试环境">1 测试环境</h3>
<p>被压机器信息</p>
diff --git a/en/sitemap.xml b/en/sitemap.xml
index 8da9671a..f3418fe9 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 207652ff..e7277da2 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>2023-05-14T22:31:02-05:00</lastmod></sitemap><sitemap><loc>/cn/sitemap.xml</loc><lastmod>2023-05-14T22:39:27+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>2023-05-15T22:47:44-05:00</lastmod></sitemap><sitemap><loc>/cn/sitemap.xml</loc><lastmod>2023-05-14T22:39:27+08:00</lastmod></sitemap></sitemapindex>
\ No newline at end of file