Category: 6 SPL Case&Testing

We are naturally interested in order-related operations which include calculating the rate of last period or YOY. This article is focused on comparing the order-related operations between Python and SPL.

Selecting subset from a set is a very common operation, for example, selecting members who are more than 40 years old from all the members in the company. In this article, we’ll compare the selection operations between Python and SPL.

The functions that calculate every member in the set and traverse the set to get a new result are generally called the loop function. The native loop functions of “list” in Python are too few, and the “for” statement should be used for those slightly complex loops, so instead of introducing them in this article, we’ll focus on comparing the loop functions in Pandas and SPL.

A sequence consists of objects (or events) that are arranged in line, in this way, each element is either in front of or behind another element. Therefore, the order of the elements is quite important.

Python and esProc SPL are both very good programming languages for analyzing and processing data, and some people may be familiar with only one of them. In order to facilitate you to further understand these two languages and choose a more suitable programming language for yourselves, here we provide a series of articles comparing the advantages and disadvantages of these two languages in various aspects.

SQL focuses on structured data computations, yet it lacks procedural control syntax for handling procedure-oriented computations. The SQL-based Stored procedure (SP) is created to make up for this absence by supporting the much-needed syntax. SP also features a series of merits, including code encapsulation, injection prevention and dynamic syntax. In practical use, however, its demerits are unignorable.

If data to be processed is divided to be stored in multiple databases, of different types sometimes, the mixed cross-database computing is needed. This essay compares four methods, DBLink, esProc SPL, Scala and Calcit, for performing cross-database computing in terms of cross-base coding design, deployment and configuration, and computing performance.

The function syntaxes of various types of databases are more or less different from each other. In order to make the SQL query statements of the same functionality be executed successfully in different types of databases, we need to translate these differentiated function syntaxes that are available in each database, and that is SQL migration. This article will explore several technologies for SQL migration and compare them in detail.

Programmers have been trying to use the ORM technique to convert SQL statements between different types of databases. The issue is that the technique is only suitable for translating simple SQL statements in OLTP scenarios. Complicated SQL statements in OLAP cases are still hard to migrate. esProc SPL, however, (Structured Process Language) supports a wealth of functions to be able to describe various algorithms and thus handle a rich variety of computing scenarios.

Dumping data among databases first needs to export the data of the original database to a certain file and then import the file to the target database. There are also some more complicated situations which need to process the exported data firstly and import them to the target database afterward. This article will explore several types of file used for data dumping and compare them in detail.