You Need This Technique Skill in Java Development

In Java programing, how to debug data calculation scripts conveniently? How to compute on the mass amount of structured data from Excel sheet or Txt file? How to solve the complex computational problems more easily? All in all, how to improve the data computing efficiency of Java?

For most computations, Java is powerful enough and also quite convenient in debugging. However, Java has not directly realized the common data computational algorithms yet. So, Java programmers still have to spend great time and efforts to implement the details like aggregating, filtering, grouping, sorting, and ranking. In the respect of data storage and access, programmers have to use List and other objects to assemble every 2D table and every piece of data, and go through the nested multi-level loops. In addition, such computation involves set and relation operations on massive data, or relative position between object and object properties. The underlying logics for these computations demand great efforts, not to mention the Excel or Text data, data from set, and the complex computational goal.

So, Java alone cannot improve the efficiency for data computation.

SQL database is another option. SQL implements lots of data computational algorithms and alleviates the workload to some extent. But, the shortcomings shown as below are unavoidable:

First, SQL takes a long query as a basic computation unit. Programmers are only allowed to view the final result but not the details of running. It is awkward to prepare the stored procedure and a great many of temporary tables just to debug barely. Writing special script for debugging? Not good idea indeed! A lengthy SQL statement will bring about exponential increase in the difficulty of reading or writing.

Second, to address the Excel, text, or heterogeneous data computation with SQL, programmers have to establish the data mart or global view with ETL or Linked Server at great cost. In addition, SQL does not support the step-by-step computations for decomposing the complex computation goal. Its incomplete support for the set makes programmers still feel tough to solve some complex problems. So, we can conclude that SQL has limited impact on improving the computational efficiency for Java.  

In this case, esProc is highly recommended – a database computation development tool ideal for simplifying the complex computations and tailored for cross-database computation and explicit sets with convenient debugging, and direct support for JDBC to integrate with Java apps easily.

Take this typical set operations for example: Retrieve the contracts on conditions that: 1. All valid contracts; 2. Contracts are Signed in 2012; 3. Quantities ordered are higher than 40 (great volume); 4. Unit prices are above 2000 dollars (great unit price); 5. Contracts meet the conditions 2, 3, and 4; 6. All except for those meet the condition 5.

esProc script:

esProc allows for the direct retrieving and computing across multiple databases, text file, or Excel sheets. It is especially designed with grid-like style and agile syntax for the massive structural data computation. With the native support for the external parameters, cross-database computation, and code reuse, esProc boost the data computation and development efficiency for Java greatly.