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href="#序列分区槽">序列分区槽</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level3" href="#时间分区槽">时间分区槽</a></li><!----><!--]--></ul></li><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level2" href="#元数据分区">元数据分区</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level2" href="#数据分区">数据分区</a></li><!----><!--]--><!--[--><li class="vp-toc-item"><a class="route-link vp-toc-link level2" href="#负载均衡">负载均衡</a></li><!----><!--]--></ul><div class="vp-toc-marker" style="top:-1.7rem;"></div></div><!--[--><!----><!--]--></aside></div><!--[--><!----><!--]--><div class="theme-hope-content"><h1 id="集群数据分区与负载均衡" tabindex="-1"><a class="header-anchor" href="#集群数据分区与负载均衡"><span>集群数据分区与负载均衡</span></a></h1><p>IoTDB 以数据分区（DataRegion）为单位对元数据和数据进行管理，从序列和时间两个维度进行数据划分。</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/分区槽与数据分区.png?raw=true"><h2 id="分区槽" tabindex="-1"><a class="header-anchor" href="#分区槽"><span>分区槽</span></a></h2><p>一个序列分区槽和一个时间分区槽可以组合产生一个数据分区(当该序列分区槽在该时间分区槽下有对应数据时)。</p><h3 id="序列分区槽" tabindex="-1"><a class="header-anchor" href="#序列分区槽"><span>序列分区槽</span></a></h3><p>每个数据库持有固定数量的序列分区槽，默认为1000个。该数据库管理的每个时间序列都将通过序列分区算法（通常为某种哈希算法）被分配给唯一的序列分区槽管理。</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/SeriesPartitionSlot.png?raw=true"><h3 id="时间分区槽" tabindex="-1"><a class="header-anchor" href="#时间分区槽"><span>时间分区槽</span></a></h3><p>每个时间序列都将持续产生数据，如果一个时间序列产生的全部数据持续存储于一个节点，那么集群新增的 DataNode 可能无法得到有效利用。</p><p>时间分区槽从时间维度对时序数据进行分片（默认为每 7 天一个时间分区），使得集群时序数据的存储易于规划。</p><h2 id="元数据分区" tabindex="-1"><a class="header-anchor" href="#元数据分区"><span>元数据分区</span></a></h2><p>单个数据库的元数据分区管理，会按照一定的负载均衡策略，将所有序列槽分配到相应的 SchemaRegionGroup 中，进而在集群中横向扩展。</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/SchemaRegion.png?raw=true"><h2 id="数据分区" tabindex="-1"><a class="header-anchor" href="#数据分区"><span>数据分区</span></a></h2><p>会按照一定的负载均衡策略，进行时间分区槽和序列分区槽的划分，并分配到相应的 DataRegionGroup 中，进而在集群中横向扩展。</p><img style="width:100%;max-width:800px;max-height:600px;margin-left:auto;margin-right:auto;display:block;" src="https://alioss.timecho.com/docs/img/DataRegion.png?raw=true"><h2 id="负载均衡" tabindex="-1"><a class="header-anchor" href="#负载均衡"><span>负载均衡</span></a></h2><p>当集群容量保持不变时，数据会被均匀分配到各个节点，以实现存储和计算资源的均衡利用。</p><p>同时，在进行集群扩容时，系统会自动增加区域（region）的数量，以充分利用所有节点的计算资源，无需人工干预。这种动态扩展能够提高集群的性能和可扩展性，使整个系统更加灵活和高效。</p></div><!--[--><!----><!--]--><footer class="vp-page-meta"><div class="vp-meta-item edit-link"><a href="https://github.com/apache/iotdb-docs/edit/main/src/zh/UserGuide/latest/Basic-Concept/Cluster-data-partitioning.md" rel="noopener noreferrer" 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