Tag: serverless spark

AWS Glue @ Freshers.in

Schema Evolution in AWS Glue: Best Practices and Implementation Strategies

Schema evolution, the process of managing changes to the structure of data over time, poses significant challenges in data integration…

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AWS Glue @ Freshers.in

Data Discovery in AWS Glue

Data discovery is a crucial first step in any data integration or analytics project. It involves identifying, profiling, and cataloging…

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AWS Glue @ Freshers.in

Understanding the Limitations of AWS Glue

AWS Glue is a fully managed extract, transform, and load (ETL) service provided by Amazon Web Services (AWS), designed to…

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Data Serialization and Deserialization in PySpark with AWS Glue

Introduction to Data Serialization and Deserialization in PySpark Data serialization and deserialization are essential processes in PySpark, especially when working…

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Optimizing data queries with AWS Glue and Amazon Athena

AWS Glue, a serverless data integration service, and Amazon Athena, an interactive query service, together offer a seamless solution for…

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AWS Glue @ Freshers.in

Mastering data partitioning in AWS Glue

This article explores how AWS Glue handles data partitioning during processing, supplemented by a real-world example. Understanding data partitioning in…

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AWS Glue @ Freshers.in

Ensuring data integrity with AWS Glue: A practical guide to data validation

In the world of big data, ensuring the accuracy and integrity of data during ingestion is paramount. AWS Glue, a…

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AWS Glue @ Freshers.in

Navigating job dependencies in AWS glue – Managing ETL workflows

AWS Glue manages dependencies between jobs using triggers. Triggers can start jobs based on the completion status of other jobs,…

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AWS Glue @ Freshers.in

AWS Glue : Handling Errors and Retries in AWS Glue

AWS Glue is a fully managed ETL service that simplifies and automates data processing tasks. While AWS Glue is designed…

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