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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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Top Key Architecture Components in HIVE

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5 architectural components present in Hadoop Hive: Shell: allows interactive queries like MySQL shell connected to a database – Also supports web and JDBC clients Driver: session handles, fetch, execute Compiler: parse, plan, optimize Execution engine: DAG of stages (M/R, HDFS, or metadata) Metastore: schema, location in HDFS, SerDe

 Data Mode of Hive:
  • Tables
– Typed columns (int, float, string, date, boolean)
– Also, list: map (for JSON-like data)
  • Partitions
– e.g., to range-partition tables by date
  • Buckets
– Hash partitions within ranges (useful for sampling, join optimization)

HIVE Meta Store
  • Database: namespace containing a set of tables
  • Holds table definitions (column types, physical layout)
  • Partition data 
  • Uses JPOX ORM for implementation; can be stored in Derby, MySQL, many other relational databases
Physical Layout of HIVE
  • Warehouse directory in HDFS
– e.g., /home/hive/warehouse
  • Tables stored in subdirectories of warehouse
– Partitions, buckets form subdirectories of tables
  • Actual data stored in flat files
– Control char-delimited text, or SequenceFiles
– With custom SerDe, can use arbitrary format

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