Java Jdbc Odbc Driver

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 ...

Open standards can be used via Optim http://www.aliyun.com/zixun/aggregation/13722.html ">open Data Manager,optim" (such as ODBC, JDBC, or XML) provides continuous access to archived data. Learn the difference between the available methods for accessing Optim archived data in the linux®/unix® environment, and how to do so in a Linux environment ...

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 ...

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 ...

Hadoop is a large data distributed system infrastructure developed by the Apache Foundation, the earliest version of which was the 2003 original Yahoo! Dougcutting 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 mapreduc ...

As we all know, the big data wave is gradually sweeping all corners of the globe. And Hadoop is the source of the Storm's power. There's been a lot of talk about Hadoop, and the interest in using Hadoop to handle large datasets seems to be growing. Today, Microsoft has put Hadoop at the heart of its big data strategy. The reason for Microsoft's move is to fancy the potential of Hadoop, which has become the standard for distributed data processing in large data areas. By integrating Hadoop technology, Microso ...

Have you ever heard such a statement? An IT senior manager talking about the application infrastructure of the organization. He is optimistic about the "modern" aspects of the Environment: multi-tier client-server systems, WEB-oriented development using languages such as PERL, Python, and Ruby, and service-oriented architectures. If you ask the IT senior manager about the IBM System z Server They are using, the answer may well be dismissive: "Oh, that's our legacy system." The word "Left" listens ...

In order to meet the ever-changing business changes, Jingdong's Jingmai team has adopted a popular open source big data calculation engine such as Hadoop on the basis of Jingdong Big Data Platform to create a decision-making data product for JD operations and products.