阿里云Elasticsearch（简称ES）新增8.13版本，支持硬件加速并提供开源向量检索等场景的新特性和优化点，较上一个版本有明显的性能优势。本文通过实际测试数据，展示ES 8.13版本和8.9版本的性能对比。
压测配置
ES集群配置
ES实例版本：8.13版本、8.9版本
数据节点规格：16核32 GiB
数据节点存储类型：ESSD云盘
数据节点存储性能级别：PL1
数据单节点存储空间：500 GiB
数据节点数量：1个
说明本压测场景因需要控制变量并突出单节点性能表现，特提供单节点实例的性能对比数据。阿里云ES暂不支持创建单节点实例，集群性能表现和节点个数正相关。
测试集索引的主分片数为1，副本分片数为0。
测试集索引的配置（mapping和setting）如下：
{ "vectors_so": { "aliases": {}, "mappings": { "properties": { "acceptedAnswerId": { "type": "keyword" }, "body": { "type": "text" }, "creationDate": { "type": "date" }, "questionId": { "type": "keyword" }, "tags": { "type": "keyword" }, "title": { "type": "text" }, "titleVector": { "type": "dense_vector", "dims": 768, "index": true, "similarity": "dot_product" }, "type": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "user": { "type": "text", "fields": { "keyword": { "type": "keyword", "ignore_above": 256 } } }, "userId": { "type": "keyword" } } }, "settings": { "index": { "number_of_shards": "1", "number_of_replicas": "0" } } } }
测试数据集
本测试使用StackOverflow 200w 768维的向量数据。获取测集，请参见Elastic_vector。
测试集的数据示例：
{"user":"209706","tags":["java","svn","git"],"questionId":"3329041","creationDate":"2010-07-25T11:43:57.960","title":"Best practice to store .jar files in VCS (SVN, Git, 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know, in the time of Maven it is not recommended to store libraries in VCS, but sometimes it makes sense, though. My question is how to best store them - compressed or uncompressed? Uncompressed they are larger, but if they are replaced a couple of times with newer ones, then maybe the stored difference between two uncompressed .jar files might be much smaller than the difference of compressed ones. Did someone make some tests? "}测试集的查询示例：
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测试结果
测试结果仅供参考，无法代表实际生产中写入查询情况，建议您结合业务生产数据进行压测。
当前测试结果仅提供数据写入后直接查询的结果，如果通过forcemerge成一个segment的方式进行优化，实际查询效果还有数倍提升空间。
查询性能
说明
KNN查询case说明：
knn-search-100-100：k=100，num_candidates=100。
knn-search-1000-1000：k=1000，num_candidates=1000。
20并发测试结果
ES版本 | 查询case | QPS（次/秒） | 50分位查询耗时（ms） | 99分位查询耗时（ms） | CPU使用率（%） |
8.13版本 | knn-search-100-100 | 813.16 | 22.2122 | 45.159 | 92% |
knn-search-1000-1000 | 157.58 | 123.515 | 205.025 | 100% | |
8.9版本 | knn-search-100-100 | 191.32 | 97.4562 | 159.974 | 99% |
knn-search-1000-1000 | 32.97 | 588.647 | 839.913 | 100% |
单并发测试结果
ES版本 | 查询case | QPS（次/秒） | 50分位查询耗时（ms） | 99分位查询耗时（ms） | CPU使用率（%） |
8.13版本 | knn-search-100-100 | 168.79 | 4.47948 | 6.00996 | 22% |
knn-search-1000-1000 | 69.18 | 13.2466 | 15.2825 | 42% | |
8.9版本 | knn-search-100-100 | 16.48 | 59.4866 | 65.296 | 7% |
knn-search-1000-1000 | 2.98 | 336.262 | 363.806 | 8% |
写入性能
ES版本 | 写入TPS（docs/s） | 写入耗时（ms） （bulk size=1000） | CPU使用率（%） |
8.13版本 | 8201.66 | 1105.91 | 100 |
8.9版本 | 4711.86 | 2263.13 | 100 |
存储表现
引擎版本 | 存储容量 |
8.13版本 | 30.8 GB |
8.9版本 | 30.8 GB |
测试结果总结
查询性能：ES 8.13版本的查询性能是ES 8.9版本的4-5倍，单并发可以到8.9版本的10倍。
写入性能：ES 8.13版本的写入性能是ES 8.9版本的1.74倍。
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