Mongodb Aggregate

While technology like http://www.aliyun.com/zixun/aggregation/13461.html ">mongodb,mapreduce" is seen as a hallmark of innovation, companies rely on sophisticated technologies such as SQL. 　　Mining important business models from these data becomes very difficult when the enterprise needs to collect more data formats, especially when new formats are not supported by SQL. When faced with such a problem, the market ...

1.count Count returns the number of documents in the collection &http://www.aliyun.com/zixun/aggregation/37954.html ">nbsp;db.refactor.count () No matter how large the collection is, the number of documents can be returned quickly. You can pass the query, MongoDB calculates the number of query results Db.refactor.count ({...).

MongoDB in the latest version of the 2.4 User Rights Management made a new adjustment, the permissions are refined, enhanced security, more and more like the permissions of MySQL management. 2.4 Before the version of User Management 1, the creation of a database management user 1.1, access to the WEIW database: >use weiw; 1.2, add users (Read and write permissions, Readonly-->false): >db.adduser ("java", "Ja ...)

Type selection and design of bigtable NoSQL database release time: 2012.04.16 14:20 Source: Blog Author: Blog This paper introduces the selection strategy and schema design principle of Bigtable/hbase type NoSQL database system. Data scale BigTable Class database system (Hbase,cassandra, etc.) is to solve ...

As global corporate and personal data explode, data itself is replacing software and hardware as the next big "oil field" driving the information technology industry and the global economy. Compared with the fault-type information technology revolution such as PC and Web, the biggest difference of large data is that it is a revolution driven by "open source software". From giants such as IBM and Oracle to big data start-ups, the combination of open source software and big data has produced astonishing industrial subversion, and even VMware's past reliance on proprietary software has embraced big Open-source data ...

Today, the concept of big data has flooded the entire IT community, with a variety of products with large data technologies, and a variety of bamboo seen for processing large data tools like rain. At the same time, if a product does not hold the big data of the thigh, if an organization has not yet worked on Hadoop, Spark, Impala, Storm and other tall tools, will be the evaluation of obsolete yellow flowers. However, do you really need to use Hadoop as a tool for your data? 　　Do you really need large data technology to support the data type of your business processing? Since it is ...

Today, some of the most successful companies gain a strong business advantage by capturing, analyzing, and leveraging a large variety of "big data" that is fast moving. This article describes three usage models that can help you implement a flexible, efficient, large data infrastructure to gain a competitive advantage in your business. This article also describes Intel's many innovations in chips, systems, and software to help you deploy these and other large data solutions with optimal performance, cost, and energy efficiency. Big Data opportunities People often compare big data to tsunamis. Currently, the global 5 billion mobile phone users and nearly 1 billion of Facebo ...

The biggest difference between cloud-based applications and applications running in private data centers is scalability. The cloud provides the ability to scale on demand, extending and shrinking applications based on fluctuations in load. But the traditional application to give full play to the advantages of the cloud, not simply to deploy the application to the cloud is all right, but need to be based on the characteristics of the cloud around scalability to redesign the architecture, Recently AppDynamics's development preacher Dustin.whittle wrote about the application architecture suitable for cloud deployment, which has great inspiration for our traditional application to cloud deployment.