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How to Read a CSV File from Amazon S3 Using Python (With Headers and Rows Displayed)

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  Introduction If you’re working with cloud data, especially on AWS, chances are you’ll encounter data stored in CSV files inside an Amazon S3 bucket . Whether you're building a data pipeline or a quick analysis tool, reading data directly from S3 in Python is a fast, reliable, and scalable way to get started. In this blog post, we’ll walk through: Setting up access to S3 Reading a CSV file using Python and Boto3 Displaying headers and rows Tips to handle larger datasets Let’s jump in! What You’ll Need An AWS account An S3 bucket with a CSV file uploaded AWS credentials (access key and secret key) Python 3.x installed boto3 and pandas libraries installed (you can install them via pip) pip install boto3 pandas Step-by-Step: Read CSV from S3 Let’s say your S3 bucket is named my-data-bucket , and your CSV file is sample-data/employees.csv . ✅ Step 1: Import Required Libraries import boto3 import pandas as pd from io import StringIO boto3 is...
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2 Scaling-Up And Scaling-out QlikView's Ideas! That You Can Never Miss

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In scale-up architecture

A single server is used to serve the QlikView applications. In this case, as more throughput is required, bigger and/or faster hardware (e.g. with more RAM and/or CPU capacity) are added to the same server.

Scale-up
The Scale-up architecture


In scale-out architecture

More servers are added when more throughput is needed to achieve the performance necessary. It is common to see the use of commodity servers in these types of architectures. 

As more throughput is required new servers are added, creating a clustered QlikView environment. In these environments, QlikView Server supports load sharing of QlikView applications across multiple physical or logical computers. 

QlikView load balancing refers to the ability to distribute the load (i.e. end-user sessions) across the cluster in accordance with a predefined algorithm for selecting which node should take care of a certain session. QlikView Server version 11 supports three different load balancing algorithms.

Below is a brief definition of each scheme. Please refer to the QlikView Scalability Overview Technology white paper for further details. 

Scale-out
The scale-out Architecture
 
Random: The default load-balancing scheme. The user is sent to a random server, no matter if the QlikView application the user is looking for is loaded or not on a QlikView Server. 
 
Loaded Document: If only one QlikView Server has the particular QlikView application loaded, the user is sent to that QlikView Server. If more than one QlikView Server or none of the QlikView Servers have the application loaded, the user is sent to the QlikView Server with the largest amount of free RAM. 

CPU with RAM Overload: The user is sent to the least busy QlikView Server. Please note that this report does not go into detail on when to use and how to tune different load balancing algorithms for best performance. 

Cluster test executions presented in this report has been run in an environment configured with a better performing scheme for certain conditions of a particular test.

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