Posts

Showing posts with the label data processing

Featured Post

Step-by-Step Guide to Reading Different Files in Python

Image
 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...

SAP HANA: Top Data Processing Interview Questions

1. How parallel processing is achieved in SAP HANA? The phrase "divide and conquer" (derived from the Latin saying divide et impera) typically is used when a large problem is divided into a number of smaller, easier-to-solve problems. Regarding performance, processing huge amounts of data is a problem that can be solved by splitting the data into smaller chunks of data, which can be processed in parallel. 2.How data portioning will happen in SAP HANA? Although servers that are available today can hold terabytes of data in memory and provide up to eight processors per server with up to 10 cores per processor, the amount of data that is stored in an in-memory database or the computing power that is needed to process such quantities of data might exceed the capacity of a single server. To accommodate the memory and computing power requirements that go beyond the limits of a single server, data can be divided into subsets and placed across a cluster of servers, which forms a d...