overview of what the poster reports on. Title: Pipeline architectures in C++: overloaded pipe operator | std::expected and its monadic operations Brief overview: Functional programming in C++ is the overloaded pipe operator. In this poster I show how to implement a custom pipeline framework that employs std::expected, available since C++23. An overloaded custom pipe operator | will be presented my book about C++ [1][3]. One of the topics was to describe the behavior of the overloaded pipe operator | in std::ranges. I came across Ankur's Satle lecture [4] and decided to expand on this topic –

第三届中国Rust开发者大会 使用Rust与ClickHouse构建高 效可靠的日志系统 刘炜 腾讯云（专有云） • 自我介绍 • 系统介绍 • 整体架构 • 系统实现 • 遇到问题 大纲 自我介绍 • 大龄码农 • 做过嵌入式/CDN/数据库开发 • 从C/C++到Rust • 现在在腾讯云（专有云）从事日志系统的开发 自我介绍 PhoTto / image / chart 提供日志的搜索/报警/处理等功能 系统介绍 • 为什么放弃 Loki • 资源占用过大 • 统计/计算能力比较弱 • 组件过多，排查问题比较困难 • 商业使用不友好的开源协议 • 为什么选择Mencius+ClickHouse • 存储计算与业务分离 • 计算/统计能力更强 • 资源占用更小，性能更好 • 更友好的开源协议 系统介绍 • 多种接入方式 • Agent • Client • 查询 • • 写入 • 每天 100G • 磁盘 • 压缩比 1:13 • 内存 • Mencius • 200M左右 • ClickHouse • 2G以下 • 接入端 • API Gateway • 日志服务(Mencius) • 存储(ClickHouse) 整体架构 • 协议层 • 处理层 • 计算层 • 存储层 系统实现 协议层 • 支持协议 • Loki • 写入

*>(dst + size - 16), _mm_loadu_si128(reinterpret_cast(src + size - 16))); Factual Clickhouse implementation as an exampleExample – memcpy: handcrafted 88 void *memcpy_ch(void * __restrict __m128i*>(src) + 6); c7 = _mm_loadu_si128(reinterpret_cast(src) + 7); src += 128; Factual Clickhouse implementation as an exampleExample – memcpy: handcrafted 89 void *memcpy_ch(void * __restrict return ret; } Factual Clickhouse implementation as an exampleExample – memcpy: handcrafted 90 Re-autovectorized, loops unrolled Still predominantly unaligned Factual Clickhouse implementation as an

日志记录 缓存控制 调用鉴权 异常捕获 并发控制 数据统计 监控报警 链路跟踪 自动降载 自动熔断 超时控制 Redis集群 Redis集群 数据库 MySQL集群 MongoDB集群 ClickHouse集群 服务发现 ETCD集群 Redis集群 代码未动，数据先行 ● 定义数据边界 ● 数据库互相隔离，通过RPC访问 ● No join, no pain! 用户 商品 订单

亚秒级OLAP系统 • 实时写⼊入与查询 • 组件⻆角⾊色较多，搭建较为复杂 • Json-QL（有SQL适配器器） • 不不⽀支持外Join、窗⼝口等 其他OLAP选择: Clickhouse • 性能优越： • 10亿+条规模⽐比商业软件快5倍 • ⽐比MySQL快⼏几百倍 • 稳定可靠，⾮非Hadoop体系， • 类SQL功能 • 缺点： • 聚合结果要在⼀一台机器器内存内

that it should make your code easier to unit test. You can instantiate objects by using the new operator without even involving Spring. You can also use mock objects instead of real dependencies. Often auto-configuration is available for hosts that are monitored by the OneAgent or by the Dynatrace Operator for Kubernetes. Local OneAgent: If a OneAgent is running on the host, metrics are automatically Dynatrace Kubernetes Operator: When running in Kubernetes with the Dynatrace Operator installed, the registry will automatically pick up your endpoint URI and API token from the operator instead. This is

that it should make your code easier to unit test. You can instantiate objects by using the new operator without even involving Spring. You can also use mock objects instead of real dependencies. Often auto-configuration is available for hosts that are monitored by the OneAgent or by the Dynatrace Operator for Kubernetes. Local OneAgent: If a OneAgent is running on the host, metrics are automatically Dynatrace Kubernetes Operator: When running in Kubernetes with the Dynatrace Operator installed, the registry will automatically pick up your endpoint URI and API token from the operator instead. This is

that it should make your code easier to unit test. You can instantiate objects by using the new operator without even involving Spring. You can also use mock objects instead of real dependencies. Often auto-configuration is available for hosts that are monitored by the OneAgent or by the Dynatrace Operator for Kubernetes. Local OneAgent: If a OneAgent is running on the host, metrics are automatically Dynatrace Kubernetes Operator: When running in Kubernetes with the Dynatrace Operator installed, the registry will automatically pick up your endpoint URI and API token from the operator instead. This is

that it should make your code easier to unit test. You can instantiate objects by using the new operator without even involving Spring. You can also use mock objects instead of real dependencies. Often auto-configuration is available for hosts that are monitored by the OneAgent or by the Dynatrace Operator for Kubernetes. Local OneAgent: If a OneAgent is running on the host, metrics are automatically Dynatrace Kubernetes Operator: When running in Kubernetes with the Dynatrace Operator installed, the registry will automatically pick up your endpoint URI and API token from the operator instead. This is

that it should make your code easier to unit test. You can instantiate objects by using the new operator without even involving Spring. You can also use mock objects instead of real dependencies. Often auto-configuration is available for hosts that are monitored by the OneAgent or by the Dynatrace Operator for Kubernetes. Local OneAgent: If a OneAgent is running on the host, metrics are automatically Dynatrace Kubernetes Operator: When running in Kubernetes with the Dynatrace Operator installed, the registry will automatically pick up your endpoint URI and API token from the operator instead. This is