[Doc] Update 3.3.0 release notes (StarRocks#48428)

zhangheihei · Jul 18, 2024 · 151fde0 · 151fde0
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diff --git a/docs/en/release_notes/release-3.3.md b/docs/en/release_notes/release-3.3.md
@@ -59,7 +59,7 @@ Release date: June 21, 2024
 - **Optimized performance on ARM.**
  - Significantly optimized performance for ARM architecture instruction sets. Performance tests under AWS Graviton instances showed that the ARM architecture was 11% faster than the x86 architecture in the SSB 100G test, 39% faster in the Clickbench test, 13% faster in the TPC-H 100G test, and 35% faster in the TPC-DS 100G test.
 - **Spill to Disk is in GA.** Optimized the memory usage of complex queries and improved spill scheduling, allowing large queries to run stably without OOM.
-- [Preview] Supports [spilling intermediate results to object storage](https://docs.starrocks.io/docs/administration/management/resource_management/spill_to_disk/).
+- [Preview] Supports [spilling intermediate results to object storage](https://docs.starrocks.io/docs/administration/management/resource_management/spill_to_disk/#preview-spill-intermediate-result-to-object-storage).
 - **Supports more indexes.**
  - [Preview] Supports [full-text inverted index](https://docs.starrocks.io/docs/table_design/indexes/inverted_index/) to accelerate full-text searches.
  - [Preview] Supports [N-Gram bloom filter index](https://docs.starrocks.io/docs/table_design/indexes/Ngram_Bloom_Filter_Index/) to speed up `LIKE` queries and the computation speed of `ngram_search` and `ngram_search_case_insensitive` functions.
@@ -77,7 +77,7 @@ Release date: June 21, 2024
 
 - **[Enhanced flexibility of range partitioning](https://docs.starrocks.io/docs/table_design/Data_distribution/#range-partitioning).** Three time functions can be used as partitioning columns. These functions convert timestamps or strings in the partitioning columns into date values and then the data can be partitioned based on the converted date values.
 - **FE memory observability.** Provides detailed memory usage metrics for each module within the FE to better manage resources.
-- **[Optimized metadata locks in FE](https://docs.starrocks.io/docs/administration/management/FE_configuration/#lock_manager_enabled).** Provides Lock manager to achieve centralized management for metadata locks in FE. For example, it can refine the granularity of metadata lock from the database level to the table level, which improves load and query concurrency. In a scenario of 100 concurrent load jobs, the load time can be reduced by 35%.
+- **[Optimized metadata locks in FE](https://docs.starrocks.io/docs/administration/management/FE_configuration/#lock_manager_enabled).** Provides Lock manager to achieve centralized management for metadata locks in FE. For example, it can refine the granularity of metadata lock from the database level to the table level, which improves load and query concurrency. In a scenario of 100 concurrent load jobs on a small dataset, the load time can be reduced by 35%.
 - **[Supports adding labels on BEs](https://docs.starrocks.io/docs/administration/management/resource_management/be_label/).** Supports adding labels on BEs based on information such as the racks and data centers where BEs are located. It ensures even data distribution among racks and data centers, and facilitates disaster recovery in case of power failures in certain racks or faults in data centers.
 - **[Optimized the sort key](https://docs.starrocks.io/docs/table_design/indexes/Prefix_index_sort_key/#usage-notes).** Duplicate Key tables, Aggregate tables, and Unique Key tables all support specifying sort keys through the `ORDER BY` clause.
 - **[Experimental] Optimized the storage efficiency of non-string scalar data.** This type of data supports dictionary encoding, reducing storage space usage by 12%.
@@ -139,6 +139,7 @@ Release date: June 21, 2024
 - By default, Data Cache is enabled to accelerate data lake queries. Users can manually disable it by executing `SET enable_scan_datacache = false`. 
 - If users want to re-use the cached data in Data Cache after downgrading a shared-data cluster from v3.3 to v3.2.8 and earlier, they need to manually rename the Blockfile in the directory **starlet_cache** by changing the file name format from `blockfile_{n}.{version}` to `blockfile_{n}`, that is, to remove the suffix of version information. For more information, refer to the [Data Cache Usage Notes](https://docs.starrocks.io/docs/using_starrocks/block_cache/#usage-notes). v3.2.9 and later versions are compatible with the file name format in v3.3, so users do not need to perform this operation manually.
 - Supports dynamically modifying FE parameter `sys_log_level`. [#45062](https://github.com/StarRocks/starrocks/issues/45062)
+- The default value of the Hive Catalog property `metastore_cache_refresh_interval_sec` is changed from `7200` (two hours) to `60` (one minute). [#46681](https://github.com/StarRocks/starrocks/pull/46681)
 
 ### Bug Fixes
 

diff --git a/docs/zh/release_notes/release-3.3.md b/docs/zh/release_notes/release-3.3.md
@@ -61,7 +61,7 @@ displayed_sidebar: "Chinese"
  针对 ARM 架构指令集大幅优化性能。在使用 AWS Gravinton 机型测试的情况下，在 SSB 100G 测试中，使用 ARM 架构时的性能比 x86 快 11%；在 Clickbench 测试中，使用 ARM 架构时的性能比 x86 快 39%，在 TPC-H 100G 测试中，使用 ARM 架构时的性能比 x86 快 13%，在 TPC-DS 100G 测试中，使用 ARM 架构时的性能比 x86 快 35%。
 
 - **中间结果落盘（Spill to Disk）能力 GA**：优化复杂查询的内存占用，优化 Spill 的调度，保证大查询都能稳定执行，不会 OOM。
-- [Preview] 支持将中间结果 [落盘至对象存储](https://docs.starrocks.io/zh/docs/administration/management/resource_management/spill_to_disk/)。
+- [Preview] 支持将中间结果 [落盘至对象存储](https://docs.starrocks.io/zh/docs/administration/management/resource_management/spill_to_disk/#preview-%E5%B0%86%E4%B8%AD%E9%97%B4%E7%BB%93%E6%9E%9C%E8%90%BD%E7%9B%98%E8%87%B3%E5%AF%B9%E8%B1%A1%E5%AD%98%E5%82%A8)。
 - **支持更多索引**：
  - [Preview] 支持[全文倒排索引](https://docs.starrocks.io/zh/docs/table_design/indexes/inverted_index/)，以加速全文检索。
  - [Preview] 支持 [N-Gram bloom filter 索引](https://docs.starrocks.io/zh/docs/table_design/indexes/Ngram_Bloom_Filter_Index/)，以加速 `LIKE` 查询或 `ngram_search` 和 `ngram_search_case_insensitive` 函数的运算速度。
@@ -79,7 +79,7 @@ displayed_sidebar: "Chinese"
 
 - **[增强 Range 分区的灵活性](https://docs.starrocks.io/zh/docs/table_design/Data_distribution/#range-分区)**：新增支持三个特定时间函数作为分区列，可以将时间戳或字符串的分区列值转成日期，然后按转换后的日期划分分区。
 - **FE 内存可观测性**：提供 FE 内各模块的详细内存使用指标，以便更好地管理资源。
-- **[优化 FE 中的元数据锁](https://docs.starrocks.io/zh/docs/administration/management/FE_configuration/#lock_manager_enabled)**：提供 Lock Manager，可以对 FE 中的元数据锁实现集中管理，例如将元数据锁的粒度从库级别细化为表级别，可以提高导入和查询的并发性能。在 100 并发的导入场景下，导入耗时减少 35%。
+- **[优化 FE 中的元数据锁](https://docs.starrocks.io/zh/docs/administration/management/FE_configuration/#lock_manager_enabled)**：提供 Lock Manager，可以对 FE 中的元数据锁实现集中管理，例如将元数据锁的粒度从库级别细化为表级别，可以提高导入和查询的并发性能。在 100 并发小数据量导入场景下，导入耗时减少 35%。
 - **[使用标签管理 BE](https://docs.starrocks.io/zh/docs/administration/management/resource_management/be_label/)**：支持基于 BE 节点所在机架、数据中心等信息，使用标签对 BE 节点进行分组，以保证数据在机架或数据中心等之间均匀分布，应对某些机架断电或数据中心故障情况下的灾备需求。
 - **[优化排序键](https://docs.starrocks.io/zh/docs/table_design/indexes/Prefix_index_sort_key/)**：明细表、聚合表和更新表均支持通过 `ORDER BY` 子句指定排序键。
 - **[Experimental] 优化非字符串标量类型数据的存储效率**：这类数据支持字典编码，存储空间下降 12%。
@@ -141,6 +141,7 @@ displayed_sidebar: "Chinese"
 - 默认启用 Data Cache 来加速数据湖查询。用户也可通过 `SET enable_scan_datacache = false` 手动关闭 Data Cache。
 - 对于存算分离场景，在降级到 v3.2.8 及其之前版本时，如需复用先前 Data Cache 中的缓存数据，需要手动修改 **starlet_cache** 目录下 Blockfile 文件名，将文件名格式从 `blockfile_{n}.{version}` 改为 `blockfile_{n}`，即去掉版本后缀。具体可参考 [Data Cache 使用说明](https://docs.starrocks.io/zh/docs/using_starrocks/block_cache/#使用说明)。v3.2.9 及以后版本自动兼容 v3.3 文件名，无需手动执行该操作。
 - 支持动态修改 FE 参数 `sys_log_level`。[#45062](https://github.com/StarRocks/starrocks/issues/45062)
+- Hive Catalog 属性 `metastore_cache_refresh_interval_sec` 默认值由 `7200` (两小时) 变为 `60` (一分钟)。 [#46681](https://github.com/StarRocks/starrocks/pull/46681)
 
 ### 问题修复