open architecture design. It uses a unified job API for each project. Developers only need code one time and can deploy at will. ElasticJob became an Apache ShardingSphere Sub project on May 28 2020. Welcome requirements such as jobs scale out, so that they can focus more on business coding; At the same time, it can release operators too, so that they do not have to worry about jobs high availability and throughput and efficiency improvement – Job processing capacity is flexible and scalable with the allocation of resources • Resource Assign – Execute job on suitable time and assigned resources – Aggregation

. . . . . . . . . . . . . . . . . . . . . . . 489 xii 1 Overview Stargazers Over Time Contributors Over Time Apache ShardingSphere is positioned as a Database Plus, and aims at building a standard Apache ShardingSphere document, v5.1.2 1.3 Roadmap 1.3. Roadmap 6 2 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. Example Codes: Data is increasing explosively, the data storage and computing method are facing innovation all the time. Transaction, big data, association analysis, Internet of things and other scenarios subdivided quickly

. . . . . . . . . . . . . . . . . . . . . . . 301 viii 1 Overview Stargazers over time Contributor over time Apache ShardingSphere is an open‐source ecosystem consisted of a set of distributed database Tracing & Observability Supported • Data Encryption 1.2. Features 4 2 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. 2.1 ShardingSphere-JDBC will increase the disk IO access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the

. . . . . . . . . . . . . . . . . . . . . . . . 391 x 1 Overview Stargazers Over Time Contributors Over Time Apache ShardingSphere is positioned as a Database Plus, and aims at building a new criterion Apache ShardingSphere document, v5.0.0 1.3 Roadmap 1.3. Roadmap 6 2 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. 2.1 ShardingSphere-JDBC Data is increasing explosively, the data storage and computing method are facing innovation all the time. Transaction, big data, association analysis, Internet of things and other scenarios subdivided quickly

Mass data high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 19 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 20 3.1.5 Related References . . provides access to high‐availability computing services based on stateless ser‐ vices. At the same time, it can sense and use the underlying database’s HA solution to achieve its overall high availability suggest using cluster mode in production environment. 1.3. Deployment 10 2 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. Example Codes:

Mass data high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 18 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 19 3.1.5 Related References . . to check out the mailing list and discuss via mail. 1.5. Roadmap 9 2 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. Example Codes: will increase the disk IO access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the

. . . . . . . . . . . . . . . . . . . . . . . 444 xii 1 Overview Stargazers Over Time Contributors Over Time Apache ShardingSphere is positioned as a Database Plus, and aims at building a standard Apache ShardingSphere document, v5.1.1 1.3 Roadmap 1.3. Roadmap 6 2 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. 2.1 ShardingSphere-JDBC Data is increasing explosively, the data storage and computing method are facing innovation all the time. Transaction, big data, association analysis, Internet of things and other scenarios subdivided quickly

Mass data high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 22 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 23 8.1.5 Related References . . are welcome to check out the mailing list and discuss via mail. 13 7 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. Example Codes: will increase the disk IO access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the

Mass data high concurrency in OLTP scenarios . . . . . . . . . . . . . . . . . . . 22 Mass data real‐time analysis in OLAP scenarios . . . . . . . . . . . . . . . . . . . 23 8.1.5 Related References . . are welcome to check out the mailing list and discuss via mail. 13 7 Quick Start In shortest time, this chapter provides users with a simplest quick start with Apache ShardingSphere. Example Codes: will increase the disk IO access number, and thereby, weaken the performance of query. In the same time, high concurrency requests also make the centralized database to be the greatest limitation of the

the pool after the completion of the operation. It reduces the initial connection and authentication time that required to create a new connection. JNDI − For the dataSource type JNDI, MyBatis will get the tutorials_point.com.mybatis_examples.Student. Instead of using this name to address the class every time, you can declare an alias to that class as shown below − time on generating SQL. It is flexible, offers faster development time. It is highly scalable, provides a much more advanced cache. It