2024 Best 51 AWS Glue Interview Questions And Answers

If you want an accurate data analysis for your business, AWS Glue is the service for you. If you don’t know anything about AWS Glue Interview Questions will help you to understand Amazon Glue better.

Amazon Web Services has revolutionized the way modern companies do business. They are the ultimate one-stop-shop that allows you to develop, manage, maintain and deploy your business’s web application, website, etc.

They offer many services, and from inception to final deployment, they can help you do it all. So out of all the services provided by AWS today, we are talking about AWS Glue in interview questions format.

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AWS Glue Interview Questions And Answers

Go through these frequently asked questions below. This will help you learn about everything you need to know about AWS Glue from these AWS Glue interview questions.

1. AWS Glue Explained?

AWS Glue is a service that makes classifying our data, cleaning it, and moving it reliably across multiple data storage and data streams, simple and cost-efficient.

It comprises a central metadata store known as AWS Glue Catalog. Amazon Web Services Glue helps with Python and Scale code creation by managing dependencies, task monitoring, and retries.

AWS Glue is a Cloud hosting is a configurable framework that we can utilize for our ETL scripts.

Dynamic Frame is much like Apache Spark data frame or data abstraction, both of which are used to organize the data in rows and columns.

2. What is AWS Glue Primary Job?

The fundamental job of AWS Glue is to manage the platform for managing your ETL operation. You may use AWS Glue to create tasks that execute the script.

These scripts can be used to extract, manipulate, and transmit data. Jobs can be planned and chained, or they can be triggered by events such as the introduction of fresh data.

3. Function AWS Glue Can Perform?

The following are the core functions AWS Glue can perform when you utilize their services:

Developer Endpoints	Aids in the development of unique readers, writers, and transformations.
Automatic Schema Identification	Enables crawlers to be automated in obtaining schema-related information and putting it in a data catalog.
Automatic Code Creation	Aids in the generation of code. The AWS pipeline’s Consolidated Repository contains data from several sources.
Job Scheduler	Multiple tasks can be scheduled simultaneously, and supervisors can set dependencies between them.

4. Where is AWS Glue Best Used?

According to AWS Glue interview questions, the following use cases AWS Glue has:

Data extraction	Assists in the extraction of data in a range of forms.
Data transformation	Aids in data reformatting for storage.
Data integration	Aids in data integration into company data lakes and warehouses.

5. AWS Glue Interview Questions Explains The Limitation of AWS Glue?

The Following are the limitations of AWS Glue

Limited Compatibility	Utilized for dealing with several regularly used data sources and with AWS services.
Lack of data synchronization	For real-time ETL workloads, Glue is not the best fit.
Learning curve	Utilized to support standard relational database queries.

6. Explain AWS Glue Data Catalog?

AWS Glue Data Catalog is mostly a persistent metadata repository utilized for recording structural and functional metadata for any and all data sets.

It also offers common storage where various systems can aid in storing and discovering metadata for data silos. It queries and transforms data using metadata.

It even helps with data gathering and is a drop-in solution for Big Data Applications operating on AWS EMR. AWS Glue Data Catalog also contributes by offering a pre-built interface for Redshirt Spectrum, EMR, and Athena.

7. Explaining Amazon Web Services Glue Crawlers?

AWS Glue Crawlers are used to store data and go through a prioritized list of classifiers to extract the architecture of our data and other information, which are then utilized to create the Glue Data Catalog.

They assist us by running regularly to identify the availability of new data and alter existing information, including table definition modifications.

Crawlers automatically add new tables, partitions to existing tables, and updated models of table definitions.

AWS glue real time interview questions

8. Amazon Glue Schema Registry Explained?

The AWS Glue Schema Registry assists us by validating and regulating the development of streaming data using authorized Apache Avro schemas at no additional cost.

Schema Registry aids in the integration of Java Applications for various streaming platforms.

9. How Does AWS Glue Help Streaming ETL?

AWS Glue facilitates ETL processes on streaming data by utilizing continuously-running tasks.

It may also be built atop the Apache Spark Organized Streaming engine and can consume streams via Fully Managed Broadcasting for Apache Kafka and Kinesis Data Streams.

It can clean and convert streaming data before loading it into AWS S3 and JDBC databases and analyze event data such as IoT stream, click stream, and network records.

10. How Does AWS Glue Architecture Work?

The following are the steps for the basics of utilizing AWS Glue to create a Data Catalog and handle ETL data flow.

Users build tasks in AWS Glue to complete the extraction, transformation, and loading (ETL) of information out of a source of data to an information destination.

Typically, they would perform the following:

You build a crawler targeting data storage assets to add metadata table entries to your AWS Glue Data Catalog. When you point your crawler toward a data repository, the crawler adds table definitions to the Data Catalog. For streaming sources, manually specify Information Catalog tables and metadata properties.
The AWS Glue Data Model includes extra metadata necessary to create ETL processes supplementary to table descriptions. When users take on that role, they utilize this knowledge to change their data.
AWS Glue could provide a data processing script. Users can also provide the script via the AWS Glue interface or API.
Users might finish their job right away or schedule it to begin when another incident happens. A timer might be used as the trigger.

11. AWS Data Crawler Explained

The AWS Glue crawler is often used to load tables into the AWS Glue catalog. It can crawl several data repositories in a single operation.

Once the crawler is finished, one or several tables inside this Data Repository are generated or changed. These Data Directory tables are utilized as resources and destinations in AWS Glue ETL processes.

This ETL operation reads and publishes data to the source and destination Data Catalog tables.

12. Benefits of Using Elastic Views in AWS Glue

The primary benefit of using elastic views in AWS Glue is that Elastic Views on AWS are used to aggregate and constantly replicate data throughout several data repositories in near-real-time.
When building new application functionality which requires data access from one or more current data stores, this is typically the case.
A corporation, for example, could employ a CRM strategy program to maintain customer data and an e-commerce platform to conduct online transactions.
The information would be saved in these applications or in additional data repositories.
The company is now working on a new proprietary application that generates and shows special promotions for proactive web traffic.

13. Is AWS Glue Any Good For Streaming?

AWS Glue can be used to process streaming data. If your use scenarios are largely ETL and you want to perform processes on a cloud platform Apache Spark-based architecture, AWS Glue is recommended.

For ideal result use, use the same cloud services and pay-as-you-go architecture that you are using for batch jobs; AWS Glue’s Stream ETL allows you to do complicated ETL on streaming data.

AWS Glue offers customized ETL algorithms to process your information in flight and includes capabilities to handle semi-structured or evolving schema Streaming data.

Glue’s developed and Spark-native operations can be used to import streams of data to your central database or warehouse.

14. Advantages of Using AWS Glue

The following are the crucial advantages of using AWS Glue according to AWS Glue interview questions.

Fault Tolerance	Logs from AWS Glue may be debugged and accessed.
Filtering	AWS Glue uses filtering to deal with bad data.
Maintenance and Development	Because AWS administers the service, AWS Glue depends on maintenance and deployment.

15. Ideal Situation To Use AWS Glue over Other Similar Services?

Although many applications provide you with similar services to AWS Glue’s functions, AWS itself serves another by AWS Batch.

So we will compare the two of when you should use which and the following are the ideal scenarios.

AWS Batch allows you to easily and efficiently run any batch computing operation on AWS, irrespective of the project mission. AWS Batch is a suitable partner for certain batch-oriented usage cases.

AWS Batch manages and creates computational capabilities in your AWS account, providing comprehensive control and visibility into resources in use.

On the other hand, AWS Glue is a completely managed ETL solution that executes your ETL activities in a cloud hosting Apache Spark environment. For specific ETL use instances, we propose AWS Glue.

16. which engine is supported by AWS glue?

AWS Glue is built on Apache Spark Structured Streaming engine.

17. What kind of data security is provided by AWS glue?

Glue supports only CMKs i.e. symmetric customer master keys.

Also, find below the AWS Interview questions guide.

The Final Word

AWS Glue is the service for you if you are trying to figure out the actual analytical situation of your business. People lie, but analytics does not. They give you an accurate representation of how you are performing.

Hence, AWS Glue is a revolutionary service for people who wish to take command of their business. We have tried to answer as many FAQs as possible through these AWS Glue interview questions to educate you more about them.

Please go through them and let us know if you received clarity regarding the topic and if you have any other questions, feel free to reach us in the comments section.

Happy Clouding!!

Steve

I am an Amazon Web Services Professional, having more than 11 years of experience in AWS and other technologies. Extensively working in various AWS tools like S3, Lambda, API, Kinesis, Load Balancers, EKS, ECS, and many more. Working as a Solution Architect and Technology Lead for Architecting and implementing the same for different clients. He provides expert solutions around the world and especially in countries like the United States, Canada, United Kingdom, Australia, New Zealand, etc. Check out the complete profile on About us.