Category: 1 SPL&Code

To achieve the business logic focused on database in Java, three key elements are required: the objectification of the database table, the ability to calculate the structured data, and the ability to process the flow. Hibernate is an old and well-established technology, and has long since provided the three elements, and achieved a large number of data business logics in many projects. SPL is a new data computing language. Likewise, SPL has the said elements, which can also be used to achieve data business logic. This article will compare them in many aspects so as to find out the one

SPL, as a technology specifically used for processing structured data and semi-structured data, is often faster than SQL by several to hundreds of times in practice, much shorter in code length, and has obvious advantages, especially when dealing with complex calculations. These advantages attract strong attention from users. However, they worry about the difficulty of mastering SPL. After all, the concept and syntax of SPL are quite different from SQL, and they need to re-understand some concepts and learn new syntax, which makes them hesitant. So, how difficult is it to get started with SPL? Let’s begin with SQL to

Many open-source technologies can implement the business logic focused on database in Java. Among them, JOOQ is more powerful than Hibernate in computing power, and more powerful than MyBatis in migratability, thereby getting increasing attention. Likewise, esProc SPL, as a new data computing language, is also outstanding in terms of computing power and migratability. This article will compare them in many aspects so as to find out the one that is more efficient in developing data business logic. JOOQ commercial edition mainly supports commercial database and stored procedure, which will not be discussed in this article. Language features Programming style

Many free open-source data processing engines can be embedded in Java application, among which, SQLite has been used for a long time, and used by many users, and esProc SPL, as a rising star, is also strong in functionality. This article will compare them in many aspects. Basic features Language style SQLite uses the traditional SQL code (the two are equivalent in this article). SQL is popular in this industry, so there is no need to give a more introduction to it. SPL is a modern data computing language, whose style belongs to the simplified object-oriented language. SPL has the

As the most commonly used data processing language, SQL is widely used in many scenarios, such as query and batch operating. When the amount of data is large, SQL (and stored procedure) often leads to very slow running. In this case, it needs to optimize SQL. To optimize SQL, there are some specific systemized ways. Normally, we need to check the execution plan first to find out the reason, and then recode in a targeted manner to achieve the purpose of optimization. For example, for the judgment of continuous numbers, we can use between to replace in, use the select

The open-source data processing languages based on JVM mainly include Kotlin, Scala and SPL. This article will compare them in many aspects to find out the one with the highest development efficiency. The applicable scenarios of this article are limited to common data processing and business logic in practice, placing emphasis on the structured data, not focusing on big data and high performance, nor involving special scenarios such as message flow and scientific computing. Basic features Applicability Kotlin was originally designed to develop more efficient Java, and is applicable to any application scenario involved in Java. In addition to common

It is common for us to write SQL code to process data in our daily work. Whether the data processing in an application or the ad hoc query analysis, both can be done with SQL. Compared with other technologies (high-level languages such as Java), SQL is simpler. However, the simplicity of SQL is limited to dealing with simple requirements. For some complex computing scenarios, it is very difficult to write in SQL, which requires nesting multiple levels, up to hundreds and thousands of lines. When it comes to the length of SQL code, it is usually not measured by lines

It is common to process data files of open formats like txt, csv, json, xml and xls in Java applications. Hardcoding in Java is extremely complicated, so we often turn to certain ready-for-use open-source packages. But each package has their weaknesses. Parsing library. This type of class libraries enables to read an external file in Java as the latter’s internal object through a simpler coding process than hardcoded data retrieval. Common products include OpenCSV for parsing txt and csv files, SJ.json, Gson and JsonPath for parsing json files, XOM, Xerces-J, Jdom, Dom4J intended to parse xml files, and POI, which

Though a lot of embedded data engines for Java are available, the competent and effective ones are rare. Redis has poor computing ability and can only handle simple query scenarios. Spark has complex and heavy framework and is inconvenient to deploy and maintain. Embedded databases like H2\HSQLDB\Derby have lightweight frameworks but they lack sufficient computing abilities – they even do not support the basic window functions. SQLite achieves the best balance between a good framework and satisfactory computing ability. It is now a widely-used Java embedded data engine. SQLite suits regular basic computing scenarios SQLite has lightweight framework. The library

WebService/Restful is widely used for communication between applications represented by microservices, data exchange and public/proprietary data services. Its popularity stems from the use of hierarchical structured data, like XML and JSON, for data communication. XML and JSON allows data to be stored not only in a text format but in a hierarchical structure at the same time. This enables them to carry more general and richer information. The problem is that hierarchical data, compared with traditional two-dimensional data, is complicated and hard to process after it is retrieved. In the days when there were no specialized JSON/XML processing technologies, JAVA