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Note:
The current performance metrics are based on an earlier version. The latest version has significant
improvements in both performance and …"><meta property="og:title" content="v0.5.6 Cluster(Cassandra)"><meta property="og:description" content="Note:
The current performance metrics are based on an earlier version. The latest version has significant improvements in both performance and functionality. We encourage you to refer to the most recent release featuring autonomous distributed storage and enhanced computational push down capabilities. Alternatively, you may wait for the community to update the data with these enhancements.
1 Test environment Compressed machine information
CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2."><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="2024-04-23T23:55:16+08:00"><meta property="og:site_name" content="HugeGraph"><meta itemprop=name content="v0.5.6 Cluster(Cassandra)"><meta itemprop=description content="Note:
The current performance metrics are based on an earlier version. The latest version has significant improvements in both performance and functionality. We encourage you to refer to the most recent release featuring autonomous distributed storage and enhanced computational push down capabilities. Alternatively, you may wait for the community to update the data with these enhancements.
1 Test environment Compressed machine information
CPU Memory 网卡 磁盘 48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2."><meta itemprop=dateModified content="2024-04-23T23:55:16+08:00"><meta itemprop=wordCount content="605"><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="Note:
The current performance metrics are based on an earlier version. The latest version has significant improvements in both performance and functionality. We encourage you to refer to the most recent release featuring autonomous distributed storage and enhanced computational push down capabilities. Alternatively, you may wait for the community to update the data with these enhancements.
1 Test environment Compressed machine information
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class="td-sidebar-nav__section-title td-sidebar-nav__section with-child" id=m-docslanguage-li><a href=/docs/language/ class="align-left pl-0 td-sidebar-link td-sidebar-link__section" id=m-docslanguage><span>QUERY LANGUAGE</span></a><ul class="ul-2 foldable"><li class="td-sidebar-nav__section-title td-sidebar-nav__section without-child" id=m-docslanguagehugegraph-gremlin-li><a href=/docs/language/hugegraph-gremlin/ title="HugeGraph Gremlin" class="align-left pl-0 td-sidebar-link td-sidebar-link__page" id=m-docslanguagehugegraph-gremlin><span>Gremlin Query Language</span></a></li><li class="td-sidebar-nav__section-title td-sidebar-nav__section without-child" id=m-docslanguagehugegraph-example-li><a href=/docs/language/hugegraph-example/ class="align-left pl-0 td-sidebar-link td-sidebar-link__page" id=m-docslanguagehugegraph-example><span>HugeGraph Examples</span></a></li></ul></li><li class="td-sidebar-nav__section-title td-sidebar-nav__section with-child active-path" 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id=m-docsperformanceapi-preformancehugegraph-api-056-rocksdb-li><a href=/docs/performance/api-preformance/hugegraph-api-0.5.6-rocksdb/ class="align-left pl-0 td-sidebar-link td-sidebar-link__page" id=m-docsperformanceapi-preformancehugegraph-api-056-rocksdb><span>v0.5.6 Stand-alone(RocksDB)</span></a></li><li class="td-sidebar-nav__section-title td-sidebar-nav__section without-child" id=m-docsperformanceapi-preformancehugegraph-api-056-cassandra-li><a href=/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/ class="align-left pl-0 active td-sidebar-link td-sidebar-link__page" id=m-docsperformanceapi-preformancehugegraph-api-056-cassandra><span class=td-sidebar-nav-active-item>v0.5.6 Cluster(Cassandra)</span></a></li></ul></li><li class="td-sidebar-nav__section-title td-sidebar-nav__section without-child" id=m-docsperformancehugegraph-loader-performance-li><a href=/docs/performance/hugegraph-loader-performance/ class="align-left pl-0 td-sidebar-link td-sidebar-link__page" 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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-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></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-item><a href=/docs/performance/>PERFORMANCE</a></li><li class=breadcrumb-item><a href=/docs/performance/api-preformance/>HugeGraph-API Performance</a></li><li class="breadcrumb-item active" aria-current=page><a href=/docs/performance/api-preformance/hugegraph-api-0.5.6-cassandra/>v0.5.6 Cluster(Cassandra)</a></li></ol></nav><div class=td-content><h1>v0.5.6 Cluster(Cassandra)</h1><header class=article-meta></header><blockquote><p><strong>Note:</strong></p><p>The current performance metrics are based on an earlier version. The <strong>latest version</strong> has significant
improvements in both performance and functionality. We encourage you to refer to the most recent release featuring
<strong>autonomous distributed storage</strong> and <strong>enhanced computational push down capabilities</strong>. Alternatively,
you may wait for the community to update the data with these enhancements.</p></blockquote><h3 id=1-test-environment>1 Test environment</h3><p>Compressed machine information</p><table><thead><tr><th>CPU</th><th>Memory</th><th>网卡</th><th>磁盘</th></tr></thead><tbody><tr><td>48 Intel(R) Xeon(R) CPU E5-2650 v4 @ 2.20GHz</td><td>128G</td><td>10000Mbps</td><td>750GB SSD,2.7T HDD</td></tr></tbody></table><ul><li>Starting Pressure Machine Information: Configure the same as the compressed machine.</li><li>Testing tool: Apache JMeter 2.5.1.</li></ul><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; 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-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>The speed of a 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-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><h6 id=conclusion>Conclusion:</h6><ul><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=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><h6 id=conclusion-1>Conclusion:</h6><ul><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-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>Duration: 5 minutes.</li><li>Service exception mark: Error rate greater than 0.00%.</li></ul><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><h6 id=conclusion-2>Conclusion:</h6><ul><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=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><h6 id=conclusion-3>Conclusion:</h6><ul><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-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>Duration: 5 minutes</li><li>Service exception flag: error rate greater than 0.00%</li></ul><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><h6 id=conclusion-4>Conclusion:</h6><ul><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=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><h6 id=conclusion-5>Conclusion:</h6><ul><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 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