atomic operations only when necessary • Distinct non-conflicting and conflicting parts • Layout compatibility; works with T within C structs • Near-identical interface • Encapsulates platform/architecture-specific Developer Community, Azure Boards, todos • GH-713 boyer_moore_searcher • vNext issues affect binary compatibility • Will start vNext after finishing C++2031 cxx20 Issues32 Pull Requests • GH-724 Fix boyer_moore_searcher evolving • Careful code review avoids regressions, new bugs • Especially important for binary compatibility • Codebase consistency is important, especially now • Ideally, looks like the work of a single

currently provides only the bare essentials for writing async code. Rust has very strict backward compatibility requirements, , and they haven't chosen to lock- in a specific runtime. Why need Tokio? Rust

Scalability to 100s of nodes High Performance © 2018 Percona. 8 MySQL Wire Protocol Compatibility with ProxySQL Extra Bonus © 2018 Percona. 9 Logs to ClickHouse © 2018 Percona. 10 Several

Kata-container BareMetal Only Heavy control logic Application kernel based Sandbox gVisor Compatibility problem, Bottleneck in sentry mVMd + QEMU + eklet is what we need to implement Elastic Kubernetes

directly from Visual Studio 2022 Step #3: Compile your code with the latest compiler 💡 Binary compatibility between the VS2022 and previous C++ runtimes (VS 2019, VS 2017, VS 2015) Step #4: Compile your

Reclamation Beyond Concurrency TS2 – Maged Michael // Extend hazard_pointer_obj_base (subject to ABI-compatibility) class hazard_pointer_obj_base { public: void set_cohort(hazard_pointer_cohort* cohort) noexcept;

Can’t update/delete table frequently in Clickhouse Possible Solutions 2. MySQL Engine Not suitable for big tables Not suitable for MongoDB Possible Solutions 3. Reinit whole table every day…… Possible PTS Key Features ● Only one config file needed for a new Clickhouse table ● Init and keep syncing data in one app for a table ● Sync multiple data source to Clickhouse in minutes PTS Provider Transform Listen: binlog, // binlog, kafka DataSource: user:pass@tcp(example.com:3306)/user, Table: user, QueryKeys: [ // usually primary key id ], Pairs:

不支持一些数据库特性，比如 事务、外键约束等 不支持一些数据库特性，比如 事务、外键约束等 • Table level lock Table level lock ，性能稍差，更适合读取多的操作 ，性能稍差，更适合读取多的操作 InnoDB InnoDB 特点 特点 •使用 使用 Table Space Table Space 的方式来进行数据存储 的方式来进行数据存储 (ibdata1, ib_logfile0) order by ， group by 起作用 record_buffer 128K 64M 每个进行一个顺序扫描的线程为其扫描的每 张表分配这个大小的一个缓冲区，可以设置 为 2M 以上 table_cache 64 1024 为所有线程打开表的数量。增加该值能增加 mysqld 要求的文件描述符的数量。 MySQL 对每个唯一打开的表需要 2 个文件描述符。 服务优化 服务优化 MyISAM 、 、 SHOW SHOW STATUS STATUS 、 、 SHOW ENGINES SHOW ENGINES  使用 使用 DESC TABLE xxx DESC TABLE xxx 来查看表结构，使用 来查看表结构，使用 SHOW SHOW INDEX INDEX FROM xxx FROM xxx 来查看表索引 来查看表索引

Обработка графов • Batch jobs • Data Hub Support For Semistructured Data 27 JSO data type: CREATE TABLE games (data JSON) ENGINE = MergeTree; • You can insert arbitrary nested JSONs • Types are automatically games dataset CREATE TABLE games (data String) ENGINE = MergeTree ORDER BY tuple(); SELECT JSONExtractString(data, 'teams', 1, 'name') FROM games; — 0.520 sec. CREATE TABLE games (data JSON) ENGINE teams.name[1] FROM games; — 0.015 sec. Support For Semistructured Data <-- inferred type DESCRIBE TABLE games SETTINGS describe_extend_object_types = 1 name: data type: Tuple( `_id.$oid` String, `date

60, 00. This is the only type of leap second that has occurred so far (note the +1’s in the table). Negative leap seconds: A second is removed, so the seconds on a UTC clock might read 57, 58 SYSTEM\CurrentControlSet\Control\LeapSecondInformation • For pre-2018 leap seconds, we maintain a static constexpr table to pull data from. • Note that we don’t currently have a way to detect upcoming leap seconds October update). • However, because leap seconds happen infrequently, we plan to update this static table periodically so older OSes can still detect more recent leap seconds (they will just need to update