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在 Milvus 1.0 版本发布后的 2 个月，2021 年 5 月 7 日，Milvus 正式发布了 1.1 版本！
Milvus 1.1 版本新增诸多优化改进，修复大量漏洞，进一步丰富和完善了 Milvus 第一个长期支持（LTS）版本[1]。 以下是 Milvus 1.1 发版说明，想了解更多详情，请见 Milvus GitHub： https://github.com/milvus-io/milvus/releases/tag/v1.1.0 。如需做数据迁移的朋友，可使用 Milvus 数据迁移工具 -- Milvusdm。
特别感谢以下社区贡献者，为此版本添砖加瓦：
@BossZou @shengjun1985 @op-hunter @matrixji @yhmo @ericsyh @LocoRichard @del-zhenwu @XuanYang-cn @fishpenguin
发版说明
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New Features
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#4564 Supports specifying partition in a get_entity_by_id() method call.
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#4806 Supports specifying partition in a delete_entity_by_id() method call.
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#4905 Adds the release_collection() method, which unloads a specific collection from cache.
Improvements
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#4756 Improves the performance of the get_entity_by_id() method call.
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#4856 Upgrades hnswlib to v0.5.0.
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#4958 Improves the performance of IVF index training.
Fixed issues
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#4778 Fails to access vector index in Mishards.
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#4797 The system returns false results after merging search requests with different topK parameters.
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#4838 The server does not respond immediately to an index building request on an empty collection.
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#4858 For GPU-enabled Milvus, the system crashes on a search request with a large topK (> 2048).
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#4862 A read-only node merges segments during startup.
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#4894 The capacity of a Bloom filter does not equal to the row count of the segment it belongs to.
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#4908 The GPU cache is not cleaned up after a collection is dropped.
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#4933 It takes a long while for the system to build index for a small segment.
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#4952 Fails to set timezone as "UTC + 5:30".
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#5008 The system crashes randomly during continuous, concurrent delete, insert, and search operations.
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#5010 For GPU-enabled Milvus, query fails on IVF_PQ if nbits ≠ 8.
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#5050 get_collection_stats() returns false index type for segments still in the process of index building.
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#5063 The system crashes when an empty segment is flushed.
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#5078 For GPU-enabled Milvus, the system crashes when creating an IVF index on vectors of 2048, 4096, or 8192 dimensions.
备注
[1] Milvus 长期版本定义：https://milvus.io/cn/docs/v1.1.0/announcement.md
About Zilliz
Zilliz 以重新定义数据科学为愿景，致力于打造一家全球领先的开源技术创新公司，并通过开源和云原生解决方案为企业解锁非结构化数据的隐藏价值。
Zilliz 构建了 Milvus 向量相似度搜索引擎，以加快下一代数据平台的发展。Milvus 目前是 LF AI & Data 基金会的孵化阶段项目，能够管理大量非结构化数据集。我们的技术在新药发现、计算机视觉、推荐引擎、聊天机器人等方面具有广泛的应用。
