While importing the structured text files into the database using Java alone, we need to combine the SQL statements together manually, and to deal with various troublesome situations as well, like if the data in a table has been existed, whether we should update it or insert data into it, if some fields are included in the file, and if the fields in the file are consistent with those in the table.

As esProc participates in Java programming, these problems can be solved…

There is a type of text files that they are too big to be entirely loaded into the memory, yet as the data have been sorted by a certain column and if they are imported in groups according to this column, they can be all put into the memory for computing. These text files include the call detail record of a telecom company, statistics of visitors on a website, information of members of a shopping mall, etc.

A great deal of complicated code, which is difficult to maintain, is…

As Java doesn’t directly support dynamically parsing expressions in the text files, the computation can only be realized by splitting strings manually and then writing a recursive program. The whole process requires writing a great amount of code, is complicated and the code is difficult to maintain. With the assistance of esProc, we can develop program for the computation in Java without writing code manually. Let’s look at how esProc works through an example.

Here is a text…

During developing the database applications, we often need to perform computations on the grouped data in each group. For example, list the names of the students who have published papers in each of the past three years; make statistics of the employees who have taken part in all previous training; select the top three days when each client gets the highest scores in a golf game; and the like. To perform these computations, SQL needs multi-layered nests, which will…

MongoDB can find out elements of a built-in array according to their indexes, but cannot find the indexes through the values of the elements. For example, the elements of an array are names of people stored according to their rankings. In MongoDB, names can be found according to the rankings (indexes of the array), but the values of rankings cannot be determined through names. esProc can help MongoDB in realizing this operation. The following example will teach you how it works in…

esProc can help Java deal with various computations in processing structured texts. But in the case of non-single row records, it is necessary to preprocess the data before esProc can perform computations on it. 

Let’s look at this through an example. The text file Social.txt is the access records of a website, in which every three rows corresponds to a record. The records should be rearranged first before other computations can be performed. They should be imported in the form…

It is common to use R language to group and summarize data of files. Sometimes we may find ourselves processing comparatively big files which have smaller computed result and bigger source data. We cannot load them wholly to the memory when we need to compute them. The only solutions could be batch importing and computing as well as result merging. We’ll use an example in the following to illustrate the way of R language to group and summarize data from big text files.

Here is a file,…

Both esProc and R language are typical data processing and analysis languages with two-dimension…