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...

5 Top features of Sqoop in the age of Big data

The ‘Sqoop’ is a command-line user interface program for conveying information amid relational databases and Hadoop.

The SQOOP

It aids increasing stacks of a sole table either a gratis shape SQL request as well like preserved appointments that may be run numerous periods to ingress upgrades produced to a database ever since the final ingress.

Imports may as well be applied to inhabit boards in Apache Hive|Hive either HBase. Exports may be applied to put information as of Hadoop into a relational database.

Apache Foundation

Sqoop grew to be a top-level Apache Software Foundation, Apache program in March 2012. Microsoft utilizes a Sqoop-based connector to aid transference information as of Microsoft SQL Server databases to Hadoop.

Couchbase, Inc. As well delivers a Couchbase Server-Hadoop connector by intents of Sqoop.

Comments

Popular posts from this blog

SQL Query: 3 Methods for Calculating Cumulative SUM

5 SQL Queries That Popularly Used in Data Analysis

A Beginner's Guide to Pandas Project for Immediate Practice