You're reading from Serverless ETL and Analytics with AWS Glue

Product typeBook

Published inAug 2022

Reading LevelExpert

PublisherPackt

ISBN-139781800564985

Edition1st Edition

Languages

Python

Tools

AWS Glue

Concepts

Data Analysis

Authors (6):

Vishal Pathak

Subramanya Vajiraya

Noritaka Sekiyama

Tomohiro Tanaka

Albert Quiroga

Ishan Gaur

View More author details

Troubleshooting and debugging common issues in AWS Glue ETL

While AWS Glue makes it easy to implement data integration workloads using different components/microservices, depending on the user configuration and use case we may encounter a number of issues. In this section, we will discuss some common issues we may encounter while working with AWS Glue and different methods to solve those specific issues one by one.

ETL job failures

A Glue ETL job can fail for a number of reasons. Most job failures can be attributed to issues with configuration or resource provisioning, depending on the use case. Let’s explore some common issues we may come across while working with Glue ETL.

OOM errors

When working with a large volume of data, it is not uncommon for us to run into OOM errors. OOM errors can appear in both drivers and executors, depending on the use case. How we approach the issue largely depends on where exactly the issue is occurring, whether in the driver or the...

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Serverless ETL and Analytics with AWS Glue

Published in: Aug 2022Publisher: PacktISBN-13: 9781800564985

Authors (6)

Vishal Pathak

Vishal Pathak is a Data Lab Solutions Architect at AWS. Vishal works with customers on their use cases, architects solutions to solve their business problems, and helps them build scalable prototypes. Prior to his journey in AWS, Vishal helped customers implement business intelligence, data warehouse, and data lake projects in the US and Australia.
Read more about Vishal Pathak

Subramanya Vajiraya

Subramanya Vajiraya is a Big data Cloud Engineer at AWS Sydney specializing in AWS Glue. He obtained his Bachelor of Engineering degree specializing in Information Science & Engineering from NMAM Institute of Technology, Nitte, KA, India (Visvesvaraya Technological University, Belgaum) in 2015 and obtained his Master of Information Technology degree specialized in Internetworking from the University of New South Wales, Sydney, Australia in 2017. He is passionate about helping customers solve challenging technical issues related to their ETL workload and implementing scalable data integration and analytics pipelines on AWS.
Read more about Subramanya Vajiraya

Noritaka Sekiyama

Noritaka Sekiyama is a Senior Big Data Architect on the AWS Glue and AWS Lake Formation team. He has 11 years of experience working in the software industry. Based in Tokyo, Japan, he is responsible for implementing software artifacts, building libraries, troubleshooting complex issues and helping guide customer architectures
Read more about Noritaka Sekiyama

Tomohiro Tanaka

Tomohiro Tanaka is a senior cloud support engineer at AWS. He works to help customers solve their issues and build data lakes across AWS Glue, AWS IoT, and big data technologies such Apache Spark, Hadoop, and Iceberg.
Read more about Tomohiro Tanaka

Albert Quiroga

Albert Quiroga works as a senior solutions architect at Amazon, where he is helping to design and architect one of the largest data lakes in the world. Prior to that, he spent four years working at AWS, where he specialized in big data technologies such as EMR and Athena, and where he became an expert on AWS Glue. Albert has worked with several Fortune 500 companies on some of the largest data lakes in the world and has helped to launch and develop features for several AWS services.
Read more about Albert Quiroga

Ishan Gaur

Ishan Gaur has more than 13 years of IT experience in soft ware development and data engineering, building distributed systems and highly scalable ETL pipelines using Apache Spark, Scala, and various ETL tools such as Ab Initio and Datastage. He currently works at AWS as a senior big data cloud engineer and is an SME of AWS Glue. He is responsible for helping customers to build out large, scalable distributed systems and implement them in AWS cloud environments using various big data services, including EMR, Glue, and Athena, as well as other technologies, such as Apache Spark, Hadoop, and Hive.
Read more about Ishan Gaur

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You're reading from Serverless ETL and Analytics with AWS Glue

Troubleshooting and debugging common issues in AWS Glue ETL

ETL job failures

OOM errors

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