transactional processing and real-time data analysis in the same system, which greatly saves cost. • Data aggregation and secondary processing scenarios 41 TiDB is suitable for companies that need to aggregate scattered statements, aggregation by SQL cannot effectively identify issues. Starting from v8.4.0, you can choose to aggregate CPU time By TABLE or By DB. In 50 scenarios with multiple systems, the new aggregation method ing from v8.4.0, Index Join is sup- ported by default when the inner table has Selection �→ , Aggregation �→ , or Projection �→ opera- tors on it. 57 Variable name Change type Description tidb_ �→ opt_

transactional processing and real-time data analysis in the same system, which greatly saves cost. • Data aggregation and secondary processing scenarios 36 TiDB is suitable for companies that need to aggregate scattered statements, aggregation by SQL cannot effectively identify issues. Starting from v8.4.0, you can choose to aggregate CPU time By TABLE or By DB. In 45 scenarios with multiple systems, the new aggregation method ing from v8.4.0, Index Join is sup- ported by default when the inner table has Selection �→ , Aggregation �→ , or Projection �→ opera- tors on it. 52 Variable name Change type Description tidb_ �→ opt_

transactional processing and real-time data analysis in the same system, which greatly saves cost. • Data aggregation and secondary processing scenarios TiDB is suitable for companies that need to aggregate scattered • TiFlash introduces HashAgg aggregation calculation modes to improve the perfor- mance for high NDV data #9196 @guo-shaoge Before v8.3.0, TiFlash has low aggregation calculation efficiency during the HashAgg aggregation when handling data with high NDV (number of distinct values). Starting from v8.3.0, TiFlash introduces multiple HashAgg aggregation calculation 38 modes to improve the aggregation performance

transactional processing and real-time data analysis in the same system, which greatly saves cost. • Data aggregation and secondary processing scenarios TiDB is suitable for companies that need to aggregate scattered parallel HashAgg algorithm �→ of TiDB supports disk spill (GA) HashAgg is a widely used aggregation operator in TiDB for efficiently �→ aggregating rows with the same field values. TiDB v8.0.0 introduces converting a two-level hash table in the HashAgg operator #8956 @gengliqi • Remove redundant aggregation functions for the HashAgg operator to reduce com- putational overhead #8891 @guo-shaoge • Tools

transactional processing and real-time data analysis in the same system, which greatly saves cost. • Data aggregation and secondary processing scenarios 36 TiDB is suitable for companies that need to aggregate scattered Y Y Y Y Y Y Y Y Y Information functions Y Y Y Y Y Y Y Y Y JSON functions Y Y Y Y E E E E E Aggregation functions Y Y Y Y Y Y Y Y Y Window functions Y Y Y Y Y Y Y Y Y Miscellaneous functions Y Y Y analytical processing performance If your application involves complex analytical queries, such as aggregation and join operations, and these queries are performed on a large amount of data (more than 10 million

列表，功能是将每一条输入数据映射成新的输出数据。 Aggregation 对应 SQL 语句中的 Group By 语句或者没有 Group By 语句但是存在聚合函数，例如 count 或 sum 函数等。TiDB 支持两种聚合算法：Hash Aggregation 以及 Stream Aggregation（待补充）。 Hash Aggregation 是基于哈希的聚合算法，如果 Hash Aggregation 紧邻 Table 算法进行连接计算。 值得注意的是，Apply 一般会被查询优化器自动转换为 Join 操作。用户在编写 SQL 的过程中应尽量避免 Apply 算子的出现。 Selection Projection Aggregation Join Apply 理解 TiDB 执行计划 - 63 - 本文档使用 书栈(BookStack.CN) 构建 统计信息 TiDB 优化器会根据统计信息来选择最优的执行计划。统计信息收 表的元信息 列的元信息 统计信息 - 65 - 本文档使用 书栈(BookStack.CN) 构建 column_name 列名 is_index 是否是索引列 update_time 更新时间 distinct_count 不同值数量 null_count NULL 的数量 avg_col_size 列平均长度 你可以通过 SHOW STATS_BUCKETS 来查看直方图每个桶的信息。 语法：

multi_ �→ pattern �→ 修改 默认值 从 OFF 修改为 ON。从 v8.4.0 开 始，当 内表上 有 Selection �→ 、 Projection �→ 或 Aggregation �→ 算子 时，默 认支持 Index Join。 tidb_opt_ �→ prefer �→ _range �→ _scan 修改 默认值 从 OFF 修改为 ON。对 于没有 为日志表mysql.tidb_runaway_queries 增加写入控制，降低大量并发写入引发的开销 #54434 @HuSharp – 当内表上有 Selection、Projection 或 Aggregation 算子时默认支持 Index Join #47233 @winoros – 在某些场景下减少 DELETE 操作从 TiKV 获取的列信息数量，降低 DELETE 操作的资源开销 #38911 比如说，你希望知道哪些年出生的作家比较多，你可以将作家基本信息按照 birth_year 列进行分组，然后分 别统计在当年出生的作家数量： SELECT birth_year, COUNT(DISTINCT id) AS author_count FROM authors GROUP BY birth_year ORDER BY author_count DESC; public class

multi_ �→ pattern �→ 修改 默认值 从 OFF 修改为 ON。从 v8.4.0 开 始，当 内表上 有 Selection �→ 、 Projection �→ 或 Aggregation �→ 算子 时，默 认支持 Index Join。 tidb_opt_ �→ prefer �→ _range �→ _scan 修改 默认值 从 OFF 修改为 ON。对 于没有 为日志表mysql.tidb_runaway_queries 增加写入控制，降低大量并发写入引发的开销 #54434 @HuSharp – 当内表上有 Selection、Projection 或 Aggregation 算子时默认支持 Index Join #47233 @winoros – 在某些场景下减少 DELETE 操作从 TiKV 获取的列信息数量，降低 DELETE 操作的资源开销 #38911 比如说，你希望知道哪些年出生的作家比较多，你可以将作家基本信息按照 birth_year 列进行分组，然后分 别统计在当年出生的作家数量： SELECT birth_year, COUNT(DISTINCT id) AS author_count FROM authors GROUP BY birth_year ORDER BY author_count DESC; public class

#53972 @hi-rustin – 修复查询 TABLESAMPLE 时可能遇到 plan not supported 报错的问题 #54015 @tangenta – 修复执行 SELECT DISTINCT CAST(col AS DECIMAL), CAST(col AS SIGNED)FROM ... 查询时结果出 错的问题 #53726 @hawkingrei – 修复在客户端读取数据超时后查询无法被终止的问题 未定义导致 STATE 显示为空的问题 #53026 @cfzjywxk – 修复关闭 tidb_enable_async_merge_global_stats 时，GlobalStats 中的 Distinct_count 信息可能错 误的问题 #53752 @hawkingrei – 修复使用 Optimizer Hints 时，可能输出错误的 WARNINGS 信息的问题 #53767 @hawkingrei 比如说，你希望知道哪些年出生的作家比较多，你可以将作家基本信息按照 birth_year 列进行分组，然后分 别统计在当年出生的作家数量： SELECT birth_year, COUNT(DISTINCT id) AS author_count FROM authors GROUP BY birth_year ORDER BY author_count DESC; public class

unable to boot with the VirtualBox EFI implementation. 3.12.1 Video modes in EFI EFI provides two distinct video interfaces: GOP (Graphics Output Protocol) and UGA (Universal Graphics Adapter). Mac OS X virtualization performance. 10.5 Details about hardware virtualization With Intel VT-x, there are two distinct modes of CPU operation: VMX root mode and non-root mode. • In root mode, the CPU operates much like control the distribution of derivative or collective works based on the Program. In addition, mere aggregation of another work not based on the Program with the Program (or with a work based on the Program)