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new 2f42710d Update hugegraph-api-0.5.6-Cassandra.md (#229)
2f42710d is described below
commit 2f42710d1e23ca02cab321a65b9237256cd8556c
Author: imbajin <[email protected]>
AuthorDate: Wed May 17 04:31:14 2023 +0000
Update hugegraph-api-0.5.6-Cassandra.md (#229)
Completed translation to English. 44d32009138afbf13d7eef1b29dcd2228ceb43a3
---
docs/_print/index.html | 2 +-
docs/index.xml | 122 ++++++++++-----------
docs/performance/_print/index.html | 2 +-
docs/performance/api-preformance/_print/index.html | 2 +-
.../hugegraph-api-0.5.6-cassandra/index.html | 29 ++---
docs/performance/api-preformance/index.xml | 122 ++++++++++-----------
en/sitemap.xml | 2 +-
sitemap.xml | 2 +-
8 files changed, 137 insertions(+), 146 deletions(-)
diff --git a/docs/_print/index.html b/docs/_print/index.html
index d1ad9954..24d00837 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 ffb57360..61974c0c 100644
--- a/docs/index.xml
+++ b/docs/index.xml
@@ -6131,8 +6131,8 @@ And there is no need to guarantee the order between the
two parameters.</p>
<p>Receive a goodbye email. After completing the above steps, you will
receive a goodbye email with the subject GOODBYE from <a
href="mailto:[email protected]";>[email protected]</a>, and
you have successfully unsubscribed to the Apache HugeGraph mailing list, and
you will not receive emails from <a
href="mailto:[email protected]";>[email protected]</a>.</p>
</li>
</ol></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>
+<h3 id="1-test-environment">1 Test environment</h3>
+<p>Compressed machine information</p>
<table>
<thead>
<tr>
@@ -6152,103 +6152,103 @@ And there is no need to guarantee the order between
the two parameters.</p>
</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>
+<li>Starting Pressure Machine Information: Configured the same as the
compressed machine.</li>
+<li>Testing tool: 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>
+<p>Note: The machine used to initiate the load and the machine being tested
are located in the same data center (or server room)</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 &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>
+<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 median response time in statistical
terms.</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>Throughput &ndash; The number of transactions processed per unit of
time.</li>
+<li>KB/sec &ndash; The throughput measured in terms of data transmitted
per second.</li>
</ul>
-<h4 id="22-底层存储">2.2 底层存储</h4>
-<p>后端存储使用15节点Cassandra集群，HugeGraph与Cassandra集群位于不同的服务器，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>
+<h4 id="22-low-level-storage">2.2 Low-Level Storage</h4>
+<p>A 15-node Cassandra cluster is used for backend storage. HugeGraph and
the Cassandra cluster are located on separate servers. Server-related
configuration files are modified only for host and port settings, while the
rest remain default.</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分别为9000和4500</li>
-<li>顶点和边的批量插入速度分别为5w/s和15w/s，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12000以上，且请求的平均延时小于70ms</li>
+<li>The speed of single vertex and edge insertion in HugeGraph is 9000 and
4500 per second, respectively.</li>
+<li>The speed of bulk vertex and edge insertion is 50,000 and 150,000 per
second, respectively, which is much higher than the single insertion
speed.</li>
+<li>The concurrency for querying vertices and edges by ID can reach more
than 12,000, and the average request delay is less than 70ms.</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-pressure-upper-limit-test">4.1.1 Pressure Upper Limit
Test</h5>
+<h6 id="test-method">Test Method</h6>
+<p>Continuously increase the concurrency level to test the upper limit of
the server&rsquo;s ability to provide services.</p>
+<h6 id="pressure-parameters">Pressure Parameters</h6>
+<p>Duration: 5 minutes.</p>
+<h6 id="maximum-insertion-speed-of-vertices">Maximum Insertion Speed of
Vertices:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/vertex_batch.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion">Conclusion:</h6>
<ul>
-<li>并发3500，顶点的吞吐量是261，每秒可处理的数据：261*200=52200/s</li>
+<li>At a concurrency level of 3500, the throughput of vertices is 261, and
the amount of data processed per second is 52,200 (261 * 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-of-edges">Maximum Insertion Speed of
Edges:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/edge_batch.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-1">Conclusion:</h6>
<ul>
-<li>并发1000，边的吞吐量是323，每秒可处理的数据：323*500=161500/s</li>
+<li>At a concurrency level of 1000, the throughput of edges is 323, and the
amount of data processed per second is 161,500 (323 * 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-pressure-upper-limit-test">4.2.1 Pressure Upper Limit
Test</h5>
+<h6 id="test-method-1">Test Method</h6>
+<p>Continuously increase the concurrency level to test the upper limit of
the server&rsquo;s ability to provide services.</p>
+<h6 id="pressure-parameters-1">Pressure 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 mark: 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-insertion-of-vertices">Single Insertion of Vertices:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/vertex_single.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-2">Conclusion:</h6>
<ul>
-<li>并发9000，吞吐量为8400，顶点的单条插入并发能力为9000</li>
+<li>At a concurrency level of 9000, the throughput is 8400, and the
single-insertion concurrency capability for vertices is 9000.</li>
</ul>
-<h6 id="边的单条插入">边的单条插入</h6>
+<h6 id="single-insertion-of-edges">Single Insertion of Edges:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/edge_single.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-3">Conclusion:</h6>
<ul>
-<li>并发4500，吞吐量是4160，边的单条插入并发能力为4500</li>
+<li>At a concurrency level of 4500, the throughput is 4160, and the
single-insertion concurrency capability for edges is 4500.</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-query-by-id">4.3 Query by ID</h4>
+<h5 id="431-pressure-upper-limit-test">4.3.1 Pressure Upper Limit
Test</h5>
+<h6 id="test-method-2">Test Method</h6>
+<p>Continuously increase the concurrency and test the upper limit of the
pressure that the server can still provide services normally.</p>
+<h6 id="pressure-parameters-2">Pressure 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="顶点的按id查询">顶点的按id查询</h6>
+<h6 id="query-by-id-for-vertices">Query by ID for vertices</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/vertex_id_query.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-4">Conclusion:</h6>
<ul>
-<li>并发14500，吞吐量是13576，顶点的按id查询的并发能力为14500，平均延时为11ms</li>
+<li>The concurrent capacity of the vertex search by ID is 14500, with a
throughput of 13576 and an average delay of 11ms.</li>
</ul>
-<h6 id="边的按id查询">边的按id查询</h6>
+<h6 id="edge-search-by-id">Edge search by ID</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/edge_id_query.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-5">Conclusion:</h6>
<ul>
-<li>并发12000，吞吐量是10688，边的按id查询的并发能力为12000，平均延时为63ms</li>
+<li>For edge ID-based queries, the server&rsquo;s concurrent capacity
is up to 12,000, with a throughput of 10,688 and an average latency of
63ms.</li>
</ul></description></item><item><title>Docs: HugeGraph
内置用户权限与扩展权限配置及使用</title><link>/docs/config/config-authentication/</link><pubDate>Mon,
01 Jan 0001 00:00:00
+0000</pubDate><guid>/docs/config/config-authentication/</guid><description>
<h3 id="概述">概述</h3>
<p>HugeGraph 为了方便不同用户场景下的鉴权使用，目前内置了两套权限模式：</p>
diff --git a/docs/performance/_print/index.html
b/docs/performance/_print/index.html
index 53c3348d..a494b216 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/[email protected]/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 b0af02b0..e3f7cd9e 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 [...]
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src=https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.min.js
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crossorigin=anonymous></script>
diff --git
a/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/index.html
b/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/index.html
index 4b97c864..3a87d5d7 100644
--- a/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/index.html
+++ b/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/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,
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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 Cluster(Cassandra)"><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15节点Cassandra集群，HugeGraph与Cassandra集群位于不同的服务器，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分别为9000和4500 顶点和边的批量插入速度分别为5w/s和15w/s，远大于单条插入速度
按id查询顶点和边的并发度可达到12000以上，且请求的平均延时小于70ms 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-cassandra/"><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="H [...]
-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15节点Cassandra集群，HugeGraph与Cassandra集群位于不同的服务器，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分别为9000和4500 顶点和边的批量插入速度分别为5w/s和15w/s，远大于单条插入速度
按id查询顶点和边的并发度可达到12000以上，且请求的平均延时小于70ms 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
Cluster(Cassandra)"><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15节点Cassandra集群，HugeGraph与Cassandra集群位于不同的服务器，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分别为9000和4500 顶点和边的批量插入速度分别为5w/s和15w/s，远大于单条插入速度
按id查询顶点和边的并发度可达到12000以上，且请求的平均延时小于70ms 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
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+750GB SSD,2.7T …"><meta property="og:title" content="v0.5.6
Cluster(Cassandra)"><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 Starting Pressure Machine Information: Configured the same
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property="og:site_name" content="HugeGraph"><meta itemprop=name content="v0.5.6
[...]
+CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz 128G 10000Mbps
750GB SSD,2.7T HDD Starting Pressure Machine Information: Configured the same
as the compressed machine. Testing tool: Apache JMeter 2.5.1. Note: The machine
used to initiate the load and the machine being tested are located in the same
data center (or server room)
+2 Test Description 2.1 Definition of terms (the unit of time is ms) Samples
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name=twitter:card content="summary"><meta name=twitter:title content="v0.5.6
Cluster(Cassandra)"><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 Starting Pressure Machine Information: Configured the same
as the compressed machine. Testing tool: Apache JMeter 2.5.1. Note: The machine
used to initiate the load and the machine being tested are located in the same
data center (or server room)
+2 Test Description 2.1 Definition of terms (the unit of time is ms) Samples
– The total number of threads completed in this scenario."><link
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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
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class="col-12 col-md-9 col-xl-8 pl-md-5" role=main><nav aria-label=breadcrumb
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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 6529c81e..6cb0623d 100644
--- a/docs/performance/api-preformance/index.xml
+++ b/docs/performance/api-preformance/index.xml
@@ -118,8 +118,8 @@
<ul>
<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>
+<h3 id="1-test-environment">1 Test environment</h3>
+<p>Compressed machine information</p>
<table>
<thead>
<tr>
@@ -139,103 +139,103 @@
</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>
+<li>Starting Pressure Machine Information: Configured the same as the
compressed machine.</li>
+<li>Testing tool: 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>
+<p>Note: The machine used to initiate the load and the machine being tested
are located in the same data center (or server room)</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 &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>
+<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 median response time in statistical
terms.</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>Throughput &ndash; The number of transactions processed per unit of
time.</li>
+<li>KB/sec &ndash; The throughput measured in terms of data transmitted
per second.</li>
</ul>
-<h4 id="22-底层存储">2.2 底层存储</h4>
-<p>后端存储使用15节点Cassandra集群，HugeGraph与Cassandra集群位于不同的服务器，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>
+<h4 id="22-low-level-storage">2.2 Low-Level Storage</h4>
+<p>A 15-node Cassandra cluster is used for backend storage. HugeGraph and
the Cassandra cluster are located on separate servers. Server-related
configuration files are modified only for host and port settings, while the
rest remain default.</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分别为9000和4500</li>
-<li>顶点和边的批量插入速度分别为5w/s和15w/s，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12000以上，且请求的平均延时小于70ms</li>
+<li>The speed of single vertex and edge insertion in HugeGraph is 9000 and
4500 per second, respectively.</li>
+<li>The speed of bulk vertex and edge insertion is 50,000 and 150,000 per
second, respectively, which is much higher than the single insertion
speed.</li>
+<li>The concurrency for querying vertices and edges by ID can reach more
than 12,000, and the average request delay is less than 70ms.</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-pressure-upper-limit-test">4.1.1 Pressure Upper Limit
Test</h5>
+<h6 id="test-method">Test Method</h6>
+<p>Continuously increase the concurrency level to test the upper limit of
the server&rsquo;s ability to provide services.</p>
+<h6 id="pressure-parameters">Pressure Parameters</h6>
+<p>Duration: 5 minutes.</p>
+<h6 id="maximum-insertion-speed-of-vertices">Maximum Insertion Speed of
Vertices:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/vertex_batch.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion">Conclusion:</h6>
<ul>
-<li>并发3500，顶点的吞吐量是261，每秒可处理的数据：261*200=52200/s</li>
+<li>At a concurrency level of 3500, the throughput of vertices is 261, and
the amount of data processed per second is 52,200 (261 * 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-of-edges">Maximum Insertion Speed of
Edges:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/edge_batch.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-1">Conclusion:</h6>
<ul>
-<li>并发1000，边的吞吐量是323，每秒可处理的数据：323*500=161500/s</li>
+<li>At a concurrency level of 1000, the throughput of edges is 323, and the
amount of data processed per second is 161,500 (323 * 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-pressure-upper-limit-test">4.2.1 Pressure Upper Limit
Test</h5>
+<h6 id="test-method-1">Test Method</h6>
+<p>Continuously increase the concurrency level to test the upper limit of
the server&rsquo;s ability to provide services.</p>
+<h6 id="pressure-parameters-1">Pressure 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 mark: 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-insertion-of-vertices">Single Insertion of Vertices:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/vertex_single.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-2">Conclusion:</h6>
<ul>
-<li>并发9000，吞吐量为8400，顶点的单条插入并发能力为9000</li>
+<li>At a concurrency level of 9000, the throughput is 8400, and the
single-insertion concurrency capability for vertices is 9000.</li>
</ul>
-<h6 id="边的单条插入">边的单条插入</h6>
+<h6 id="single-insertion-of-edges">Single Insertion of Edges:</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/edge_single.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-3">Conclusion:</h6>
<ul>
-<li>并发4500，吞吐量是4160，边的单条插入并发能力为4500</li>
+<li>At a concurrency level of 4500, the throughput is 4160, and the
single-insertion concurrency capability for edges is 4500.</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-query-by-id">4.3 Query by ID</h4>
+<h5 id="431-pressure-upper-limit-test">4.3.1 Pressure Upper Limit
Test</h5>
+<h6 id="test-method-2">Test Method</h6>
+<p>Continuously increase the concurrency and test the upper limit of the
pressure that the server can still provide services normally.</p>
+<h6 id="pressure-parameters-2">Pressure 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="顶点的按id查询">顶点的按id查询</h6>
+<h6 id="query-by-id-for-vertices">Query by ID for vertices</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/vertex_id_query.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-4">Conclusion:</h6>
<ul>
-<li>并发14500，吞吐量是13576，顶点的按id查询的并发能力为14500，平均延时为11ms</li>
+<li>The concurrent capacity of the vertex search by ID is 14500, with a
throughput of 13576 and an average delay of 11ms.</li>
</ul>
-<h6 id="边的按id查询">边的按id查询</h6>
+<h6 id="edge-search-by-id">Edge search by ID</h6>
<center>
<img src="/docs/images/API-perf/v0.5.6/cassandra/edge_id_query.png"
alt="image">
</center>
-<p>####### 结论：</p>
+<h6 id="conclusion-5">Conclusion:</h6>
<ul>
-<li>并发12000，吞吐量是10688，边的按id查询的并发能力为12000，平均延时为63ms</li>
+<li>For edge ID-based queries, the server&rsquo;s concurrent capacity
is up to 12,000, with a throughput of 10,688 and an average latency of
63ms.</li>
</ul></description></item><item><title>Docs:
v0.4.4</title><link>/docs/performance/api-preformance/hugegraph-api-0.4.4/</link><pubDate>Mon,
01 Jan 0001 00:00:00
+0000</pubDate><guid>/docs/performance/api-preformance/hugegraph-api-0.4.4/</guid><description>
<h3 id="1-test-environment">1 Test environment</h3>
<p>Target Machine Information</p>
diff --git a/en/sitemap.xml b/en/sitemap.xml
index 7f603f23..197cf871 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 948153c9..b874e5ac 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>2023-05-16T23:29:47-05:00</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>2023-05-16T23:30:00-05:00</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
