颁/颁++与尝耻补混合编程
Download as ppt, pdf3 likes1,785 views
最近一直在考虑在高效c++上层，用一个动态语言封装一个可以动态解析输入，并传递给c++的层。 之前的PHP有一些缺陷，考虑用Python或lua做。 这篇ppt来自云风
1 of 14
Downloaded 31 times
Ad
Recommended
Bài t?p m?u C và C++ có gi?i
Bài t?p m?u C và C++ có gi?iTrung Thanh Nguyen
?
Download ebook mi?n phí t?i link : http://www.share99.net/2014/12/bai-tap-mau-c-va-c-plus-plus-co-giai.htmlGiao an trinh_pascal_bai_tap_co_dap_an_huong_dan
Giao an trinh_pascal_bai_tap_co_dap_an_huong_danV? T?m Long
?
Giao an trinh_pascal_bai_tap_co_dap_an_huong_danWhat does it take to make google work at scale 
What does it take to make google work at scale xlight
?
The document discusses the software stacks used by companies like Google and Facebook to run services at massive scale. It describes key components of their infrastructure like MapReduce for distributed processing, BigTable for storage, and Borg for cluster management. The stacks are optimized for data-intensive workloads across thousands of machines through replication, load balancing, and fault tolerance. Current research aims to improve utilization, stream processing, and distributed algorithms to enable real-time insights from huge datasets.
New zealand bloom filter
New zealand bloom filterxlight
?
Bloom filters provide a space-efficient probabilistic data structure for representing a set in order to support membership queries. They allow false positives but no false negatives. The structure uses k hash functions to map elements to bit positions in a bit array. Querying whether an element is in the set checks if the corresponding bit positions are all set to 1. Modern applications include distributed caching, peer-to-peer networks, routing, and measurement infrastructure where Bloom filters trade off exact representation for speed and space efficiency.
Optimizing Drupal Performance Zend Acquia Whitepaper Feb2010
Optimizing Drupal Performance Zend Acquia Whitepaper Feb2010xlight
?
The document summarizes the results of performance benchmarks testing various PHP runtime environments and configurations for optimizing Drupal performance. Key findings include:
- Zend Server with full page caching provided the best performance with 988 requests per second on Linux and 624 requests per second on Windows.
- Bytecode caching (APC, WinCache, Zend Server Optimizer+) improved performance by over 300% compared to plain PHP. Additional caching like shared memory provided further gains.
- On Linux with aggressive Drupal caching, Zend Server with shared memory caching achieved the highest requests per second at 891. On Windows, Zend Server with shared memory achieved 584 requests per second.Google: The Chubby Lock Service for Loosely-Coupled Distributed Systems
Google: The Chubby Lock Service for Loosely-Coupled Distributed Systemsxlight
?
The document describes the Chubby lock service, which provides coarse-grained locking and reliable storage for loosely-coupled distributed systems. Chubby uses Paxos consensus to elect a master from replicas to handle read/write requests. It provides locks and storage of small files to help systems elect leaders and coordinate activities. Chubby has been used successfully by several Google systems for tasks like master election and metadata storage.Google: The Chubby Lock Service for Loosely-Coupled Distributed Systems
Google: The Chubby Lock Service for Loosely-Coupled Distributed Systemsxlight
?
This document summarizes the Chubby lock service, which was designed to provide coarse-grained locking and reliable storage for distributed systems. Chubby uses the Paxos consensus protocol to elect leaders and synchronize data. It has been used successfully by several Google systems for tasks like master election and metadata storage. The initial design focused on availability over performance. While it has worked well overall, some aspects had to be modified based on unexpected usage patterns.High Availability MySQL with DRBD and Heartbeat MTV Japan Mobile Service
High Availability MySQL with DRBD and Heartbeat MTV Japan Mobile Servicexlight
?
MTV Networks Japan implemented a high availability MySQL database with DRBD and Heartbeat to provide redundancy for their MTV Flux and MTV Mobile services. They migrated the databases from a multiple master architecture to a active-passive setup with a virtual IP and DRBD synchronous replication between primary and secondary nodes. The migration took around 2 hours with little application downtime. Lessons learned included the need for extensive testing of the complex Heartbeat and DRBD configuration and being careful not to run both database nodes simultaneously.PgSQL vs MySQL
PgSQL vs MySQLxlight
?
PostgreSQL is very differently architected and presents none
of these problems. All PostgreSQL operations are multi-versioned using
Multi-Version Concurrency Control (MVCC). As a result, common
operations such as re-indexing, adding or dropping columns, and
recreating views can be performed online and without excessive locking,SpeedGeeks
SpeedGeeksxlight
?
The document discusses the importance of frontend website performance. It provides examples showing that speeding up websites by even small amounts, such as 0.4 seconds, can significantly increase metrics like search traffic, revenue, and reduce bandwidth usage. The document recommends techniques for improving performance like concatenating files, minifying files, using content delivery networks, browser caching, and reducing redundant content. It also discusses tools for analyzing website performance.GOOGLE: Designs, Lessons and Advice from Building Large Distributed Systems 
GOOGLE: Designs, Lessons and Advice from Building Large Distributed Systems xlight
?
Designs, Lessons and Advice from Building Large
Distributed Systems
Jeff Dean
Google Fellow
jeff@google.comUDT
UDTxlight
?
The document summarizes the UDT protocol, which is a high performance transport protocol designed for data-intensive applications over high-speed networks. It discusses the limitations of TCP for these applications and high bandwidth-delay product networks. It then provides an overview of the design and implementation of the UDT protocol, including its congestion control algorithm, APIs, and composable framework. It evaluates UDT's performance in terms of efficiency, fairness, and stability compared to TCP. The goal of UDT is to enable efficient, fair, and friendly transport of data for distributed applications over high-speed networks.sector-sphere
sector-spherexlight
?
Sector is a distributed file system that stores files on local disks of nodes without splitting files. Sphere is a parallel data processing engine that processes data locally using user-defined functions like MapReduce. Sector/Sphere is open source, written in C++, and provides high performance distributed storage and processing for large datasets across wide areas using techniques like UDT for fast data transfer. Experimental results show it outperforms Hadoop for certain applications by exploiting data locality.Fixing Twitter Improving The Performance And Scalability Of The Worlds Most ...
Fixing Twitter Improving The Performance And Scalability Of The Worlds Most ...xlight
?
Fixing Twitter and Finding your own Fail Whale document discusses Twitter operations. The operations team manages software performance, availability, capacity planning, and configuration management using metrics, logs, and data-driven analysis to find weak points and take corrective action. They use managed services for infrastructure to focus on computer science problems. The document outlines Twitter's rapid growth and challenges in maintaining performance as traffic increases. It provides recommendations around caching, databases, asynchronous processing, and other techniques Twitter uses to optimize performance under heavy load.Gfarm Fs Tatebe Tip2004
Gfarm Fs Tatebe Tip2004xlight
?
1. The Trans-Pacific Grid Datafarm testbed provides 70 terabytes of disk capacity and 13 gigabytes per second of disk I/O performance across clusters in Japan, the US, and Thailand.
2. Using the GNET-1 network testbed device, the Trans-Pacific Grid Datafarm achieved stable transfer rates of up to 3.79 gigabits per second during a file replication experiment between Japan and the US, near the theoretical maximum of 3.9 gigabits per second.
3. Precise pacing of network traffic flows using inter-frame gap controls on the GNET-1 device allowed for high-speed, lossless utilization of long-haul trans-Pacific network links.Make Your web Work
Make Your web Workxlight
?
The document provides tips for improving website conversions by addressing common frustrations of online shoppers. It discusses 10 tips across various areas, including landing visitors on the right page, making the homepage useful, helping with navigation, improving site search, clearly displaying products, including necessary product details, making registration optional, simplifying forms, reassuring visitors, and getting feedback. Testing changes using tools like Google Analytics and Website Optimiser is recommended to identify areas for improvement and measure the impact of tests.Capacity Management from Flickr
Capacity Management from Flickrxlight
?
The document discusses various strategies and techniques for capacity management of web operations, including forecasting future capacity needs, identifying ceilings for system resources, implementing safety factors, and performing diagonal scaling. It also provides examples of metrics used at Flickr for monitoring capacity and some "stupid capacity tricks" that can be employed in emergencies.More Related Content
More from xlight (20)
What does it take to make google work at scale
What does it take to make google work at scale xlight
?
The document discusses the software stacks used by companies like Google and Facebook to run services at massive scale. It describes key components of their infrastructure like MapReduce for distributed processing, BigTable for storage, and Borg for cluster management. The stacks are optimized for data-intensive workloads across thousands of machines through replication, load balancing, and fault tolerance. Current research aims to improve utilization, stream processing, and distributed algorithms to enable real-time insights from huge datasets.New zealand bloom filter
New zealand bloom filterxlight
?
Bloom filters provide a space-efficient probabilistic data structure for representing a set in order to support membership queries. They allow false positives but no false negatives. The structure uses k hash functions to map elements to bit positions in a bit array. Querying whether an element is in the set checks if the corresponding bit positions are all set to 1. Modern applications include distributed caching, peer-to-peer networks, routing, and measurement infrastructure where Bloom filters trade off exact representation for speed and space efficiency.Optimizing Drupal Performance Zend Acquia Whitepaper Feb2010
Optimizing Drupal Performance Zend Acquia Whitepaper Feb2010xlight
?
The document summarizes the results of performance benchmarks testing various PHP runtime environments and configurations for optimizing Drupal performance. Key findings include:
- Zend Server with full page caching provided the best performance with 988 requests per second on Linux and 624 requests per second on Windows.
- Bytecode caching (APC, WinCache, Zend Server Optimizer+) improved performance by over 300% compared to plain PHP. Additional caching like shared memory provided further gains.
- On Linux with aggressive Drupal caching, Zend Server with shared memory caching achieved the highest requests per second at 891. On Windows, Zend Server with shared memory achieved 584 requests per second.Google: The Chubby Lock Service for Loosely-Coupled Distributed Systems
Google: The Chubby Lock Service for Loosely-Coupled Distributed Systemsxlight
?
The document describes the Chubby lock service, which provides coarse-grained locking and reliable storage for loosely-coupled distributed systems. Chubby uses Paxos consensus to elect a master from replicas to handle read/write requests. It provides locks and storage of small files to help systems elect leaders and coordinate activities. Chubby has been used successfully by several Google systems for tasks like master election and metadata storage.Google: The Chubby Lock Service for Loosely-Coupled Distributed Systems
Google: The Chubby Lock Service for Loosely-Coupled Distributed Systemsxlight
?
This document summarizes the Chubby lock service, which was designed to provide coarse-grained locking and reliable storage for distributed systems. Chubby uses the Paxos consensus protocol to elect leaders and synchronize data. It has been used successfully by several Google systems for tasks like master election and metadata storage. The initial design focused on availability over performance. While it has worked well overall, some aspects had to be modified based on unexpected usage patterns.High Availability MySQL with DRBD and Heartbeat MTV Japan Mobile Service
High Availability MySQL with DRBD and Heartbeat MTV Japan Mobile Servicexlight
?
MTV Networks Japan implemented a high availability MySQL database with DRBD and Heartbeat to provide redundancy for their MTV Flux and MTV Mobile services. They migrated the databases from a multiple master architecture to a active-passive setup with a virtual IP and DRBD synchronous replication between primary and secondary nodes. The migration took around 2 hours with little application downtime. Lessons learned included the need for extensive testing of the complex Heartbeat and DRBD configuration and being careful not to run both database nodes simultaneously.PgSQL vs MySQL
PgSQL vs MySQLxlight
?
PostgreSQL is very differently architected and presents none
of these problems. All PostgreSQL operations are multi-versioned using
Multi-Version Concurrency Control (MVCC). As a result, common
operations such as re-indexing, adding or dropping columns, and
recreating views can be performed online and without excessive locking,SpeedGeeks
SpeedGeeksxlight
?
The document discusses the importance of frontend website performance. It provides examples showing that speeding up websites by even small amounts, such as 0.4 seconds, can significantly increase metrics like search traffic, revenue, and reduce bandwidth usage. The document recommends techniques for improving performance like concatenating files, minifying files, using content delivery networks, browser caching, and reducing redundant content. It also discusses tools for analyzing website performance.GOOGLE: Designs, Lessons and Advice from Building Large Distributed Systems
GOOGLE: Designs, Lessons and Advice from Building Large Distributed Systems xlight
?
Designs, Lessons and Advice from Building Large
Distributed Systems
Jeff Dean
Google Fellow
jeff@google.comUDT
UDTxlight
?
The document summarizes the UDT protocol, which is a high performance transport protocol designed for data-intensive applications over high-speed networks. It discusses the limitations of TCP for these applications and high bandwidth-delay product networks. It then provides an overview of the design and implementation of the UDT protocol, including its congestion control algorithm, APIs, and composable framework. It evaluates UDT's performance in terms of efficiency, fairness, and stability compared to TCP. The goal of UDT is to enable efficient, fair, and friendly transport of data for distributed applications over high-speed networks.sector-sphere
sector-spherexlight
?
Sector is a distributed file system that stores files on local disks of nodes without splitting files. Sphere is a parallel data processing engine that processes data locally using user-defined functions like MapReduce. Sector/Sphere is open source, written in C++, and provides high performance distributed storage and processing for large datasets across wide areas using techniques like UDT for fast data transfer. Experimental results show it outperforms Hadoop for certain applications by exploiting data locality.Fixing Twitter Improving The Performance And Scalability Of The Worlds Most ...
Fixing Twitter Improving The Performance And Scalability Of The Worlds Most ...xlight
?
Fixing Twitter and Finding your own Fail Whale document discusses Twitter operations. The operations team manages software performance, availability, capacity planning, and configuration management using metrics, logs, and data-driven analysis to find weak points and take corrective action. They use managed services for infrastructure to focus on computer science problems. The document outlines Twitter's rapid growth and challenges in maintaining performance as traffic increases. It provides recommendations around caching, databases, asynchronous processing, and other techniques Twitter uses to optimize performance under heavy load.Gfarm Fs Tatebe Tip2004
Gfarm Fs Tatebe Tip2004xlight
?
1. The Trans-Pacific Grid Datafarm testbed provides 70 terabytes of disk capacity and 13 gigabytes per second of disk I/O performance across clusters in Japan, the US, and Thailand.
2. Using the GNET-1 network testbed device, the Trans-Pacific Grid Datafarm achieved stable transfer rates of up to 3.79 gigabits per second during a file replication experiment between Japan and the US, near the theoretical maximum of 3.9 gigabits per second.
3. Precise pacing of network traffic flows using inter-frame gap controls on the GNET-1 device allowed for high-speed, lossless utilization of long-haul trans-Pacific network links.Make Your web Work
Make Your web Workxlight
?
The document provides tips for improving website conversions by addressing common frustrations of online shoppers. It discusses 10 tips across various areas, including landing visitors on the right page, making the homepage useful, helping with navigation, improving site search, clearly displaying products, including necessary product details, making registration optional, simplifying forms, reassuring visitors, and getting feedback. Testing changes using tools like Google Analytics and Website Optimiser is recommended to identify areas for improvement and measure the impact of tests.Capacity Management from Flickr
Capacity Management from Flickrxlight
?
The document discusses various strategies and techniques for capacity management of web operations, including forecasting future capacity needs, identifying ceilings for system resources, implementing safety factors, and performing diagonal scaling. It also provides examples of metrics used at Flickr for monitoring capacity and some "stupid capacity tricks" that can be employed in emergencies.颁/颁++与尝耻补混合编程
- 1. C/C++ 与 Lua 的混合编程
- 3. 为什么是 C ? 为底层开发人员最熟悉 大部分操作系统层面和通用库均提供 C API 性能可以得到保证 C++ 亦可，但不推荐
- 4. 为什么是 Lua ? 容易嵌入 轻量 语言特性补充了 C 的不足 还有其它的选择 Python Javascript 自定义语言
- 5. 获得的好处 隔离底层，让系统更健壮 降低开发成本 应付多变的需求 热更新系统 数据描述更方便 能做到单一语言难以做到的
- 6. 易出现的问题 多语言构建的系统更为复杂 层次划分不清，职责混乱 把 Lua 当成 C/C++ 来用 定义不恰当的 DSL
- 7. 嵌入还是扩展，这是一个问题 选择 1: 以 C 语言为主体，将 Lua 嵌入 选择 2: 以标准 Lua 解释器为主体，编写 C 扩展
- 8. Lua 作为数据描述语言 配置管理 处理结构化数据 XML (LuaExpat/LOM)
- 9. 为 Lua 编写 C/C++ 模块 luabind (boost.python?) tolua? lua native C API
- 10. 面向对象 C++ 层的对象粒度 userdata/lightuserdata/handle ? 对象生命期管理问题 lua metatable 带来的动态性 C/Lua 交互的性能
- 11. 调试 lua debug 库 阅读 lua source code debug API IDE
- 12. 系统性能优化 重写内存分配器 保持 C 层次的简洁 理解 Lua ，它是一门独立语言 LuaJIT LuaCOM
- 13. 参考资料 http://www.lua.org lua mailling list 书 Programming In Lua (Pil) Lua 手册 Lua Programming Gems http://blog.codingnow.com
- 14. 谢谢