Java Blob

Windows Azure provides a highly scalable storage mechanism for storing structured and unstructured data, known as Windows Azure Storage. Windows Azure Storage provides a development interface for the REST-based Web Service. This means that any programming language under any platform can access Windows Azure Storage by this development interface as long as it supports HTTP communication protocols. Of course...

We have released a storage client Java version that supports Windows http://www.aliyun.com/zixun/aggregation/13357.html ">azure blobs, queue, and table." Our goal is to continue to improve the development experience when writing cloud computing applications that use Windows Azure storage. This is the release of Microsoft's supported Community Technology Preview (CTP). Therefore, we combine the customer ...

To use Hadoop, data consolidation is critical and hbase is widely used. In general, you need to transfer data from existing types of databases or data files to HBase for different scenario patterns. The common approach is to use the Put method in the HBase API, to use the HBase Bulk Load tool, and to use a custom mapreduce job. The book "HBase Administration Cookbook" has a detailed description of these three ways, by Imp ...

In large data technology, Apache Hadoop and MapReduce are the most user-focused. But it's not easy to manage a Hadoop Distributed file system, or to write MapReduce tasks in Java. 　　 　　Then Apache hive may help you solve the problem. The Hive Data Warehouse tool is also a project of the Apache Foundation, one of the key components of the Hadoop ecosystem, which provides contextual query statements, i.e. hive queries ...

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 ...

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, Micros ...

Today, we are ushered in a new era of hybrid clouds, bringing together the best not cloud and cloud computing. Virtual machines, virtual networks, and Web sites are now available as new preview services for Windows Azure. SQL reports are now typically available to customers, and a local redundant storage option has been added to provide additional customer choices, and several enhancements to Windows Azure's existing services are now available. These updates help customers build and use their own unique ways to publish their applications in the cloud. In addition, some price and metering updates add to the overall value. These ...

Windows Azurehdinsight provides the ability to run a dynamic provisioning cluster of Apache Hadoop to handle large data. You can find more information in the first blog in this series, or click here to start using it in the Windows Azure Portal. This article enumerates several different ways for developers to interact with Hdinsight, first by discussing different scenarios, and then delving into the various features of Hdinsight. Because I...

Improve Network Service resource quality, save IT cost, realize multi-point disaster prevention backup "server +IDC" is the basic mode of enterprise building IT system, but now, the pattern is changing. The disadvantages of traditional server model are obvious, the application workload is constantly changing, the single application server is often unable to meet the demand, and the rapid increase in the number of servers, will cause the enterprise capital and operating costs rise. At the same time, increasingly complex IT systems and data centers can be difficult to quickly configure and efficiently manage to meet changing needs. In every it encounter bottleneck ...

Well, I admit it's cool to use Hadoop to handle big data. But sometimes I get frustrated when I do marshalling project. Many times we use a join in a map-reduce task, so the entire job's input may be more than two files (in other words: Mapper to process more than two files). How to handle multiple input with mapper: Multiple mapper: Each mapper process the corresponding input file Https://gi ...