The purpose of this article is to introduce MySQL MySQL Cluster-- is Air Max 2011 Womens Purple Black Grey set within memory, real-time, scalable and highly available version. Title in solving mentioned 200 million queries per second capacity problems before, we first MySQL Cluster architecture for some background information and its review, which will help you understand the process to achieve these goals. MySQL Cluster MySQL Cluster is an introduction with scalability, real-time, in-memory requirements and ACID-compliant transactional database, which will be 99.999 percent high availability and low total cost of ownership of open 2015 Nike Free 5.0 source combined. In terms of design ideas, MySQL Cluster uses a distributed multi-master architecture and thereby completely eliminate single points of failure. MySQL Cluster can scale to commercial hardware above, it is possible to carry through the automatic partitioning read and write sensitive workloads, and interface access via SQL and NoSQL. Was originally designed as a set for the embedded telecommunications database for internal network applications to achieve carrier-grade availability and real-time performance solutions, MySQL Cluster has been rapid development and by strengthening the many new feature set, which will extend the scope of use cases Web, mobile and enterprise applications, and deployment in which instances of internal or cloud environments, including: large-scale OLTP (real-time analysis) e-commerce, inventory management, shopping cart, payment processing, order tracking, online gaming, financial transactions and fraud detection, mobile and micro payments, session management and caching, data flow Air Max 2011 Womens Purple Grey supply, analysis and recommendations, content management and delivery, communication and presentation services, subscription / user configuration management and subsidies and so on. MySQL Cluster Architecture Overview of transaction-oriented applications process behind the existence of the three is responsible for service delivery to the node type of application. The figure below shows a simple example of type MySQL Cluster architecture, which consists of 12 sets of nodes are divided into six groups of Data Node constitution. MySQL Cluster Data Node belongs among the main node. They are responsible for providing the following features: in-memory copy of the data is synchronized with the storage and management of data on disk, automation and user-defined table type division (zoning) based on data between different nodes, transaction and data checking, automatic failover and use to achieve self-healing fault automatic resynchronization. Among the various tables will be automatic partitioning multiple data nodes, and each node as a data write operation of the receiving body, which it can easily be written over multiple nodes sensitive commercial workload distribution to, at the same time ensure full transparency in the application. By saving the data and distribute 585388-083 Anti-Nerf Nike KD V Elite Outlet to a shared-nothing architecture - that is, do not use any shared disks - which, at least for the data and synchronized to within a set of copies, MySQL Cluster can ensure that when a single Data Node fails, the user at least also has another store the same information Data Node. As a result, requests and transaction processing will continue to provide non-disruptive manner satisfactory working results. Any malfunction caused due to the Data Node Failover short window (time in seconds) to process the transaction can not be completed correctly will be rolled back and re-execute. We can choose to store data, including all stored in the memory or only part of the data on the disk (only non-indexed data). Internal memory storage for data that needs to be changed regularly (that is New Nike Free Run 3 Shoes Silver 3 active in the working group) in terms of significance. Data stored in the memory will periodically check to a local disk, and coordination with all Data Node, MySQL Cluster can be so when the whole system failure - such as power outages - to be fully restored. Disk-based data can be used to store data on the performance of less demanding, but such data collection is often greater than the available memory space. Just the same as most other database servers, MySQL Cluster will use the disk-based page caching and data access higher frequency in the Data Node cache memory which, thereby increasing its actual performance. Application Node is responsible for providing the connection by the application logic to the data nodes. Applications can use SQL to access the database, in particular by one or multiple sets of MySQL servers to the same set of data is stored within MySQL Cluster execute SQL interface functions. Among the MySQL Server, we can use any kind of standardized MySQL connection mechanism, which means that everyone has a very rich choice of access technology. In addition, a set of high-performance called NDB API (based on C ++) interface can be used Air Jordan Outlet to implement additional control, improved real-time behavior and bring better throughput. NDB API layer enables additional NoSQL interfaces to bypass the SQL layer and direct access to the cluster, this way not only decreased latency, developers have a more ideal level of flexibility. Existing interfaces including Java, JPA, Memcached, JavaScript with Node.js and HTTP / REST (through a realization Apache Module). All Application 597806-400 Nike LeBron X EXT QS Denim-Pink Outlet Node are able to access data from any Data Node, so even if there is a fault, they do not cause any loss of service - because New Nike Free 5.0 V4 Grey Lime Trainers each application can continue to use the other nodes are still capable of normal operation. Management Node configuration responsibilities that the cluster nodes to release them all to achieve the cluster node management. Management Node onset time point when the cluster starts, respectively, for a node joins a cluster and when you want to reconfigure the system. Management Node can not affect the ongoing premise of Data and Application Node perform the operation carried out under the suspension and restart. By default, Management Node ruling also provides services, such as some kind of network failure caused by a 'split-brain (ie split-brain)' or a letter clusters start the network division. Divided by transparent scalability multiple partitions / fragments from any given Air Jordan Heel table row are to be split into transparent manner. In each segment contains a single data node, responsible for maintaining all of the data points to the data content and process all read and write operations. Each data node also has a partner system, which together form a group of nodes; partner node in the preservation of a secondary copy of the data segment, but also have their own primary fragments. MySQL Cluster use the two-step submission protocol data synchronization, ensuring when a transaction is committed, the change will be triggered simultaneously stored in two data among nodes. By default, the primary key of the table will be use as a shard key, and MySQL Cluster will perform MD5 hashed the shard key, you need to save in order to select which fragment / partition. If a transaction or query needs to access data from multiple nodes, then one of the data nodes will act as a transaction coordinator and will assign specific tasks to other relevant data node; the next visit will be to integrate the results and, ultimately, provided to the application. Please note that we can also make multiple transactions or queries to access data from multiple partitions and tables - compared to the use of stored data fragmentation mechanism typical NoSQL, which will undoubtedly become a significant comparative advantage of MySQL Cluster. To achieve the best (linear) size scaling effects, we need to ensure that high-strength query / transaction only run on a single set of data nodes (as this can greatly reduce inter-node communication brought about by the data network delay) ʱ?? To achieve this goal, we can make an application to obtain the distribution of identification - specifically, this means planning defined by the administrator to cover any column fragments key is to be used. For example in terms of the figure shows a set equipped with a user ID and service name a Nike Air Max composite primary key of the table; all rows selected by the 585388-083 Anti-Nerf Nike KD V Elite Outlet user ID for the shard key, in the table associated with a given user always be accommodated In the same segment were. More powerful is that if we use the same user ID column in another table and set it to shard key, then the user will be given all the data in all tables are contained within the same fragment - In other words, pointing to the user's query / transaction will be processed within a single data node. Maximizing the use of NoSQL API data access speeds MySQL Cluster provides a variety of ways to access the stored data; most common way is SQL, New Nike Free 5.0 V4 Grey Blue Running Shoes but as the chart below, we can also use a variety Nike Free Run 3 of native API to help applications directly from the database which read and write data, while by switching to SQL mode MySQL Server to bypass inefficient or pulled to prevent the development of complexity. Existing API for C ++, Java, JPA, JavaScript / Node.js, HTTP and Memcached protocol. Baseline Target: 200 million queries per 586590-300 Nike Kobe 8 System Elite GC Poison Green Superhero Outlet second MySQL Cluster is designed primarily for two working load among type: -OLTP (ie, online transaction processing): memory-optimized to provide sub-millisecond latency table and called the extreme levels of OLTP workloads concurrent capacity, while still ensuring excellent durability performance; in addition, it can also be used to process the data based on the table of the disk. - Temporary search: MySQL Cluster increases the maximum number of parallel, leading to a significant speed boost when on non-indexed data columns within the table scan. It is worth mentioning that, MySQL Cluster performance in dealing with the most prominent OLTP workloads, particularly in a concurrent manner emit massive query / case transaction request. For this reason, we generally use flexAsynch benchmarks to measure after you add more data among nodes to the cluster, the actual performance enhancement effect NoSQL obtained. Each data node for the benchmark tests are run on dedicated 56 thread Intel E5-2697 v3 (Haswell architecture) device. The figure shows the data throughput with the trend growth in the number of data nodes, the specific range from two to 32 nodes final node (Please note, MySQL Cluster currently supports up to 48 data nodes). As set you can see, the entire extended ratio remained almost linear, and in 32 data centers of its overall handling capacity of 200 million times per second NoSQL queries. If you are interested in this Nike Lebron 10(X) test, you can click here for a detailed description associated with the latest results within MySQL Cluster benchmarks page. The 200 million QPS benchmark runs on MySQL Cluster 7.4 version (the latest generic version) - you can click here to learn more and MySQL Cluster 7.4 release relevant information, or click here to view the topic Webinar It will replay video.MySQL Cluster: how to expand to bring 200 million QPS MySQL