Mongodb Count Query

MongoDB company formerly known as 10gen, founded in 2007, in 2013 received a sum of 231 million U.S. dollars in financing, the company's market value has been increased to 1 billion U.S. dollar level, this height is well-known open source company Red Hat (founded in 1993) 20 's struggle results. High-performance, easy to expand has been the foothold of the MongoDB, while the specification of documents and interfaces to make it more popular with users, this point from the analysis of the results of Db-engines's score is not difficult to see-just 1 years, MongoDB finished the 7th ...

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 ({...).

With the rise of internet web2.0 websites, the relational database has become a very hot new field, the development of the non relational database products is very rapid. 　　But the traditional relational database in dealing with web2.0 website, especially the super large-scale and high concurrent SNS type web2.0 pure dynamic website already appeared to be powerless, has exposed many insurmountable problems, for example: 1, high configured--to the database higher concurrent reads and writes the demand WEB2.0 website to be based on user personalized information to generate real-time dynamic ...

The scalability of the system is the main reason for promoting the development of NoSQL movement, including distributed system coordination, failover, resource management and many other features. That makes NoSQL sound like a big basket that can be stuffed with anything. Although the NoSQL movement does not bring fundamental technological changes to distributed data processing, it still leads to extensive research and practice on protocols and algorithms. It is through these attempts to gradually summarize some effective database construction methods. In this article, I will focus on the NoSQL database distributed special ...

The scalability of the system is the main reason for promoting the development of NoSQL movement, including distributed system coordination, failover, resource management and many other features. That makes NoSQL sound like a big basket that can be stuffed with anything. Although the NoSQL movement does not bring fundamental technological changes to distributed data processing, it still leads to extensive research and practice on protocols and algorithms. It is through these attempts to gradually summarize some effective database construction methods. In this article, I will focus on the distributed features of the NoSQL database ...

After Facebook abandoned Cassandra, HBase 0.89 was given a lot of stability optimizations to make it truly an industrial-grade, structured data storage retrieval system. Facebook's Puma, Titan, ODS time Series monitoring system uses hbase as a back-end data storage System. 　　HBase is also used in some projects of domestic companies. HBase subordinate to the Hadoop ecosystem, from the beginning of the design of the system is very focused on the expansion of the dynamic expansion of the cluster, load are ...

In today's technology world, big Data is a popular it buzzword. To mitigate the complexity of processing large amounts of data, Apache developed a reliable, scalable, distributed computing framework for hadoop--. Hadoop is especially good for large data processing tasks, and it can leverage its distributed file systems, reliably and cheaply, to replicate data blocks to nodes in the cluster, enabling data to be processed on the local machine. 　　Anoop Kumar explains the techniques needed to handle large data using Hadoop in 10 ways. For the ...

In today's technology world, big Data is a popular it buzzword. To mitigate the complexity of processing large amounts of data, Apache developed a reliable, scalable, distributed computing framework for hadoop--. Hadoop is especially good for large data processing tasks, and it can leverage its distributed file systems, reliably and cheaply, to replicate data blocks to nodes in the cluster, enabling data to be processed on the local machine. Anoop Kumar explains the techniques needed to handle large data using Hadoop in 10 ways. For from HD ...

Using Redis to develop applications is a pleasant process, but as with other technologies, you need to remember a few things as well, based on Redis application design. Before, you might have a chest of the whole pattern of relational database development, and REDIS application development has many similarities, but you have to keep in mind that the following two points--redis is a memory database, and it is single-threaded. Therefore, when using Redis, you need to pay attention to the following points: 1. Master all key databases stored in Redis ...

At present, the global large data enterprises are divided into two major camps. Some of them are just emerging companies with large data technology as their core, hoping to bring innovative solutions to the market and promote technological development. There are a number of original database/data warehousing business vendors, they intend to use their own advantage to impact large data areas, the existing installation base and product line Word-of-mouth to promote a new wave of technology. 　　Let's take a look at today's 15 Big data companies list, of which 10 have long been renowned, and the other five are newcomers. 1, IBM according to Wikibon hair ...