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Jessica Qiu

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Top Stories by Jessica Qiu

In Java development, we may encounter the complex set operations. Java alone is not powerful enough to save programmers' efforts in implementing the computation details, which is time-consuming and poor in code reuse. In view of this, programmers usually resort to dynamic calculation script for set operation. SQL is surely the first kind of script that comes into most programmers' mind. However, to their disappointments, SQL does not support the explicit set, and is unable to represent the sets of a set, ordered set, generic set, and only the result set can be recognized as a set. Therefore, it is only the subset of the true set. Many operations on sets are hard to implement through SQL. Moreover, the computation is not limited on database, such as the data from Excel and even there is no database in the application environment. In this case, the usage of SQL databa... (more)

Which Tool Will You Choose for Java: Hibernate, esProc, SQL, iBATIS or R?

The data computation layer in between the data persistent layer and the application layer is responsible for computing the data from data persistence layer, and returning the result to the application layer. The data computation layer of Java aims to reduce the coupling between these two layers and shift the computational workload from them. The typical computation layer is characterized with below features: Ability to compute on the data from arbitrary data persistence layers, not only databases, but also the non-database Excel, Txt, or XML files. Of all these computations, the... (more)

Database to Implement Big Data Real-Time Application

The Big Data Real-time Application is a scenario to return the computation and analysis results in real time even if there are huge amounts of data. This is an emerging demand on database applications in recent years. In the past, because there wasn't a lot of data, the computation was simple, and few parallelisms, the pressure on the database wasn't great. A high-end or middle-range database server or cluster could allocate enough resources to meet the demand. Moreover, in order to rapidly and parallel access to the current business data and the historic data, users also tended t... (more)

Realize Memory Computation in Hadoop

The low efficiency of Hadoop computation is an undeniable truth. We believe, one of the major reasons is that the underlying computational structure of MapReduce for Hadoop is basically of the external memory computation. The external memory computation implements the data exchange through the frequent external memory read/write. Because the efficiency of file I/O is two orders of magnitude lower than that of memory, the computational performance of Hadoop is unlikely high. While for the normal users, they usually have a small size of cluster with only tens or scores of nodes. T... (more)

An Example to Illustrate Hadoop Code Reuse

The MapReduce of Hadoop is a widely-used parallel computing framework. However, its code reuse mechanism is inconvenient, and it is quite cumbersome to pass parameters. Far different from our usual experience of calling the library function easily, I found both the coder and the caller must bear a sizable amount of precautions in mind when writing even a short pieces of program for calling by others. However, we finally find that esProc could easily realize code reuse in hadoop. Still a simple and understandable example of grouping and summarizing, let's check out a solution with... (more)