dosubot[bot]

你的 JVM 堆内存 64GB 已经非常充足，不会是 1.5.0 查询变慢的根本原因。当前 HugeGraph 1.5.0 查询慢，主要还是和 hstore/集群模式的分布式调度、锁、后端通信、索引覆盖、缓存参数、RocksDB 配置等有关。建议重点排查： 1. 检查所有 where/has/filter 条件是否有二级或范围索引覆盖，避免全表扫描，schema 设计要覆盖高频查询路径 [参考](https://github.com/apache/incubator-hugegraph/issues/2836)。 2. 查询语句尽量减少多层 out()/in() 链式遍历，优先用 has() 精准过滤起点，并加 limit、分页，避免一次性拉取过多数据导致 OOM 或超时 [参考](https://github.com/apache/incubator-hugegraph/issues/2836)。 3. cache...

你的 schema 没有任何二级索引（indexlabels），所有 where/has/filter 查询都会全表扫描，这是 1.5.0 查询极慢的核心原因，尤其在 50 亿点/边规模下，链式 outE/inE 查询会导致每层都拉全量数据在内存中过滤，性能会指数级下降。HugeGraph 1.5.0 的 HugeVertexStep、TraversalFilterStep、AndStep 等遍历步骤，底层会先构造后端查询，再用 FilterIterator 在 JVM 内存中做二次过滤，没有索引时会极大拖慢查询，且分布式锁和 session 管理进一步放大了延迟[代码分析](https://github.com/apache/incubator-hugegraph/blob/a53af864b31f803780a1db31cb20d3d94d5d34fc/hugegraph-server/hugegraph-core/src/main/java/org/apache/hugegraph/traversal/algorithm/HugeTraverser.java)。 **必须优化 schema：** - 给所有高频查询属性（如 country_code、status、multi_scene_mark 等）补充二级索引（secondary index），如： ```groovy schema.indexLabel("userByCountryCode").onV("user").by("country_code").secondary().create()...

你的确是主键 id 起点查询，GraphStep(vertex,[id]) 这一步不需要二级索引，性能也不会有瓶颈。但你的 Gremlin 查询后续包含了多层 outE/inE/bothE 遍历和复杂 where/filter 条件（如 country_code、status 等），这些步骤在 HugeGraph 1.5.0（hstore 架构）下如果没有二级索引，依然会导致全表扫描和大量数据在 JVM 内存中过滤，极大拖慢查询。 代码实现上，HugeVertexStep、TraversalFilterStep、AndStep 等遍历步骤会先构造后端查询（GraphTransaction.constructEdgesQuery），再用 FilterIterator 在内存中过滤属性。没有索引时，每层都要拉取大量边/点数据，尤其在 50 亿点/边规模下，性能会指数级下降，硬件再强也无法弥补索引缺失带来的全表扫描和内存压力（详见[代码分析](https://github.com/apache/incubator-hugegraph/blob/a53af864b31f803780a1db31cb20d3d94d5d34fc/hugegraph-server/hugegraph-core/src/main/java/org/apache/hugegraph/traversal/algorithm/HugeTraverser.java)）。 社区和官方 issue 也明确指出，所有 where/has/filter 查询条件都必须有二级或范围索引覆盖，才能避免全表扫描，提升多层遍历和复杂过滤的性能，尤其在 1.5.0 这种分布式后端下更为关键（[参考](https://github.com/apache/incubator-hugegraph/issues/2836)）。...

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Great suggestion—this is a common pain point and your feedback matches what many in the community have raised. The current documentation for [monitoring with the Prometheus Operator](https://cloudnative-pg.io/documentation/1.27/monitoring/#monitoring-with-the-prometheus-operator) does not include...

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