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esProc Simplifies SQL-style Computations – Arrange Multilayered Data in One Column

We are often confronted with complicated SQL-style computations during developing data base applications. For instance, arrange grouped data into one column in certain order, making marks for different types of groups and detail data, as shown in the following: This kind of operation is commonly seen in organizing report data. As SQL lacks the mechanism […]

esPro Helps Process Structured Texts in Java – Data Import

Java provides only the most basic data import functions like specifying separators. But other common functions, such as importing specified columns by column names, specifying the order of columns and data types and that no separator should be used, need to be realized manually. Though they are not difficult to realize, the code is complicated […]

esProc Helps Process Heterogeneous Data Sources in Java –Cross-Database Relating

JoinRowSet and FilteredRowSet provided by RowSet– Java’s class library for data computing – can perform cross-database related computing, but they have a lot of weaknesses. First, JoinRowSet only supports inner join, it doesn’t support outer join. Second, test shows that db2, mysql and hsql can work with JoinRowSet, yet the result set of joinoracle 11g […]

esProc Helps Process Heterogeneous Data Sources in Java – Excel

Generally, Java programmers use poi or other open source packages to read and compute Excel data. These open source packages support low-level programming, which increases the overall learning cost and complicates the operation. But with the help of esProc, Java can avoid these problems. An example will make the point clearly understood. Read the information […]

esProc Helps Process Heterogeneous Data Sources in Java – HDFS

It is not difficult for Java to access HDFS through API provided by Hadoop. But to realize computations, like grouping, filtering and sorting, on files in HDFS in Java is troublesome. esProc is a good helper in Java’s dealing with these computations. It can execute the access to HDFS too. With the help of esProc, […]

esCalc Solves Spreadsheet Problems – Sort Detailed Data

Sometimes you are required to sort the detailed data in a spreadsheet. However, the sorting is difficult to realize due to the inflexible operation in Excel. You have to sort the data by groups, which requires quite a lot of work. But you can perform the operation more easily in esCalc. Let’s look at an […]

esProc Helps Process Heterogeneous Data Sources in Java – JSON

Java’s JSON open source package can only parse JSON data and hasn’t the computational function. It is troublesome for programmers to develop a general program for performing computations, such as grouping, sorting, filtering and joining, by themselves. For example, during developing program for performing conditional filtering in JSON files using Java, the code has to […]

esProc Helps Process Heterogeneous Data Sources in Java – Hive

It is easy for Java to connect to Hive using JDBC. But the computational ability of Hive is less than that of SQL in other databases. So to deal with uncommon computations, data should be retrieved before further operation is performed using Java. Thus the code for will be complicated. But if esProc is used to […]

Programming Languages for Desktop Data Analysis

For a programming language for desktop data analysis, the most important is that it must be user-friendly and have great computing power. We can judge whether a language is suitable for analyzing data on desktop from six aspects: application environment, file processing, text and string processing, structured data processing, predictive modeling algorithms and other less […]

esProc Helps Process Heterogeneous DataSources in Java – MongoDB

MongoDB does not support join directly.The unity JDBC recommended by the official website can perform the join operation after retrieving data out. But the advanced functions, like join, group, functions and expressions, are only provided by the paid version of unity JDBC. Even the paid version does not support the complicated SQL operations, such as […]

Parallelism of esProc enhances Oracle Data Import Speed

Recently, we skillfully handled an industry project to import a great amount of data from file to Oracle in comparatively short time. At the beginning, we tried to import the data with the sqlldr of Oracle, only to find it is surprisingly time-consuming to load a great amount of data: Too slow if 2.5 hours […]

Structured Data Computing: the Focus of Routine Data Analysis

Essentially, the main content of various data analyses in our routine business is the structured data computing. For example: A. Compute the link relative ratio and year-on-year comparison of each business branch’s monthly sales during a specified period of time. Implementation approach: filter the sales data by time range, then group and summarize data by […]

esProc’s Participation in Java Structured Text Processing– Grouping and Summarizing

Following problems will arise if you perform conditional filtering on text files in Java alone: 1. The text file is not a database, so it cannot be accessed by SQL. The code needs to be modified if the expression of grouping and summarizing is changed. Besides, if you want a flexible expression, you have to […]

Functions of esProc/R/Python/Perl in Structured Data Process by Comparison:Chapter 12.Appending Records

esProc     tbl.insert(5,value1:col1,value2:col2,……)        //Insert a record preceding Row 5 Perl In Perl, to insert an element into an array, it may be easy if this is at the beginning, where shift and unshift functions are available, for example:     @array = (“one”,”two”,”three”);     $m = shift (@array);            #$m Get “one”, now @array is (“two”, “three”)     shift @array; […]

Comparison of Loop Function in esProc and R Language

Loop function can traverse every member of an array or a set, express complicated loop statements with simple functions, as well as reduce the amount of code and increase readability. Both esProc and R language support the loop function. The following will compare their similarities and differences in usage. 1. Generating data Generate odd numbers […]

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