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The operating language of the data is SQL, so many tools are developed with the goal of being able to use SQL on Hadoop. Some of these tools are simply packaged on top of the MapReduce, while others implement a complete data warehouse on top of the HDFs, while others are somewhere between the two. There are a lot of such tools, Matthew Rathbone, a software development engineer from Shoutlet, recently published an article outlining some common tools and scenarios for each tool and not ...

March 13, 2014, CSDN online training in the first phase of the "use of Sql-on-hadoop to build Internet Data Warehouse and Business intelligence System" successfully concluded, the trainer is from the United States network of Liang, 　　In the training, Liang shares the current business needs and solutions of data warehousing and business intelligence systems in the Internet domain, Sql-on-hadoop product principles, usage scenarios, architectures, advantages and disadvantages, and performance optimization. CSDN Online training is designed for the vast number of technical practitioners ready online real-time interactive technology training, inviting ...

With Facebook opening up the recently released Presto, the already overcrowded SQL in Hadoop market has become more complex. Some open-source tools are trying to get the attention of developers: Hortonworks around the hive created Stinger, Apache Drill, Apache Tajo, Cloudera Impala, Salesforce's Phoenix (for HBase) and now Facebook Presto. ...

The REST service can help developers to provide services to end users with a simple and unified interface. However, in the application scenario of data analysis, some mature data analysis tools (such as Tableau, Excel, etc.) require the user to provide an ODBC data source, in which case the REST service does not meet the user's need for data usage. This article provides a detailed overview of how to develop a custom ODBC driver based on the existing rest service from an implementation perspective. The article focuses on the introduction of ODBC ...

Naresh Kumar is a software engineer and enthusiastic blogger, passionate and interested in programming and new things. 　　Recently, Naresh wrote a blog, the open source world's two most common database MySQL and PostgreSQL characteristics of the detailed analysis and comparison. If you're going to choose a free, open source database for your project, you may be hesitant between MySQL and PostgreSQL. MySQL and PostgreSQL are free, open source, powerful, and feature-rich databases ...

As a software developer or DBA, one of the essential tasks is to deal with databases, such as MS SQL Server, MySQL, Oracle, PostgreSQL, MongoDB, and so on. As we all know, MySQL is currently the most widely used and the best free open source database, in addition, there are some you do not know or useless but excellent open source database, such as PostgreSQL, MongoDB, HBase, Cassandra, Couchba ...

Data is the most important asset of an enterprise. The mining of data value has always been the source of innovation of enterprise application, technology, architecture and service. After ten years of technical development, the core data processing of the enterprise is divided into two modules: the relational database (RDBMS), mainly used to solve the transaction transaction problem; Based on analytical Data Warehouse, mainly solves the problem of data integration analysis, and when it is necessary to analyze several TB or more than 10 TB data, Most enterprises use MPP database architecture. This is appropriate in the traditional field of application. But in recent years, with the internet ...

Data is the most important asset of an enterprise. The mining of data value has always been the source of innovation of enterprise application, technology, architecture and service. After ten years of technical development, the core data processing of the enterprise is divided into two modules: the relational database (RDBMS), mainly used to solve the transaction transaction problem; Based on analytical Data Warehouse, mainly solves the problem of data integration analysis, and when it is necessary to analyze several TB or more than 10 TB data, Most enterprises use MPP database architecture. This is appropriate in the traditional field of application. But in recent years, with ...

This time, we share the 13 most commonly used open source tools in the Hadoop ecosystem, including resource scheduling, stream computing, and various business-oriented scenarios. First, we look at resource management.

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Doug cutting is based on Google's published academic paper. Users can easily develop and run applications that process massive amounts of data in Hadoop without knowing the underlying details of the distribution. The features of low cost, high reliability, high scalability, high efficiency and high fault tolerance make Hadoop the most popular large data analysis system, yet its HDFs and mapred ...