Do you know what AWS Athena is? What are the pros and cons it carries? If you don’t, then go through these AWS Athena Interview Questions to learn about it.
Amazon is the biggest and most recognized brand in this world, and one of the reasons why we believe they are is because they changed how the world operates when they introduced Amazon Web Services.
With AWS, they introduced hundreds of services that, till today, help you create, manage, maintain and run your business. However, today, among all of them, we will focus on a single service of AWS.
We will educate you about AWS Athena by informing you what the service is and why it is rated highly. So without any further ado, the following are the AWS Athena Interview Questions.
Frequently Asked AWS Athena Interview Questions
There are at least hundreds if not thousands of questions that we can answer to inform you about AWS Athena and the wonder this service is. What features, benefits, and attributes does it have?
Since we want to make comprehension of this service easier for you, we have answered their FAQs below. Please go through them and learn everything you need to know about AWS Athena.
Explaining AWS Athena Through AWS Athena Interview Questions
The most frequently asked AWS Athena question is, without a doubt, an explanation of what it is, and we believe Amazon Athena is a query application that allows you to examine data on AWS S3 with conventional SQL easily.
Because AWS Athena is platform-independent, there is no architecture to establish or operate, and you can begin analyzing data right away.
You don’t even need to import your data into Athena; it works with S3 data immediately. Simply login inside the Athena Admin Console, specify your structure and begin querying.
AWS Athena deals with several common data types and leverages, Presto, with complete basic SQL support.
AWS Athena is suitable for interactive analytics and connects with AWS’s other services for simple visualization. It can also perform advanced analysis.
Core Features AWS Athena Serve You
The following are the core features of AWS Athena
| Simple implementation | AWS Athena could be managed straight from the AWS Console and the AWS CLI. |
| Cloud computing | AWS Athena can handle anything on its own. |
| Pay per inquiry | Using AWS Athena, we could compress the data collection. |
| Fast | Athena speeds up the execution of complicated queries by splitting them down into simpler ones that can be processed simultaneously. |
| Secure | All information could be stored in S3 buckets, and IAM policies can assist manage user control. |
| Unrivaled Accessibility & Availability | It is extremely accessible and can run queries 24 hours, seven days a week. |
| Seamless Integration | Amazon Athena assists us in producing better data versions, tables, views, and so on. |
Ways To Get The Best Performance Out of AWS Athena?
The following are the ways you can ensure the best performance out of AWS Athena
| Data Partitioning | It is used to divide the table into simple sections and keep relevant data together depending on different column values such as date, nation, region, and so on. |
| Bucketing Data | It is a method for partitioning information in a centralized partition. |
| Compression of the Files | One such strategy is used to improve query speed by ensuring that the documents are of appropriate size and splittable. |
| Refinement of Large Files | Utilized for enabling splittable file types is beneficial to parallelism regardless of file size. |
| Optimization of Central Data Production | This is utilized for capabilities such as effective data storage via column-wise compression, various encoding, and data-type-specific compression. |
| ORDER optimization | Used to return the query results in sorted order. |
How Does AWS Athena Catalog, Compress & Comprehend Your Data?
Amazon Athena aids in the data analysis hosted on Amazon S3.
You can execute interactive analytics in Athena using ANSI SQL without combining or transferring the information into Athena.
Structured, unstructured, and semi-structured data sources can all be processed by AWS Athena.
Benefits of Attaching AWS Glue Services To The Services of AWS Athena?
There are three major benefits of attaching AWS Glue services to the services of AWS Athena, and the following are them.
| Metadata Unified Repository | AWS Glue is a unified metadata repository integrated across several AWS services. It can access data stored in a variety of Amazon Web Services. This service also integrates with various AWS resources and any other compatible application out of the box. |
| Automatic partition and schema recognition | AWS Glue scans your data sources, recognizes data formats, and recommends schemas and transformations. Crawlers can aid in the automation of table generation and partition loading. |
| Easy To Create Workflow Pipeline | AWS Glue creates customized Python code, making pipeline creation simple. AWS Glue is fairly flexible; it manages resource provisioning, setup, and scalability for your ETL operations. |
How is AWS Athena The Correct Big Data Service?
AWS offers you many big data services. Their big data services include but are not limited to Amazon Athena, Redshift, and EMR.
Query services such as Amazon Athena, information repositories such as Amazon Redshift, and complex data processing frameworks such as Amazon EMR all serve distinct demands and use cases.
To decide which the correct big data service is, you need to know the scope of the job and then need to select the appropriate equipment for the job.
However, we feel Amazon Athena is the best big data solution served by AWS on an overall arch, since it provides the simplest approach to conduct interactive searches on S3 data.
It does them without the need to establish or administer any servers. Its quickness and versatility make it ideal for us.
Explain AWS Athena Reliability Through This AWS Athena Interview Questions
Amazon Web Services Athena is reliable because Athena works with several common file formats and leverages AWS Athena Presto with complete standard SQL support.
Athena is capable of handling complicated analyses, and it is highly accessible and durable because it leverages Amazon S3 as the fundamental data storage, with data redundantly saved across many locations and numerous machines in each facility.
Is Amazon Athena The Best Query Running AWS Service?
Many queries running AWS services like AWS EMR can perform much more than just performing SQL queries.
You can use EMR to conduct a wide range of magnitude data processing activities.
Their activities for apps include learning algorithms, graphing analysis, the transformation of data, streaming data, and nearly anything else you can think of.
However, we believe AWS Athena is still the fastest, most competent, and most useful AWS service for simple query running.
Can You Count on AWS Athena For Remarkable Performance?
Yes. You can count on AWS Athena for remarkable performance because it is easily accessible and runs queries across several facilities using computational resources, intelligently routing requests accordingly.
If a specific facility is unavailable, Athena’s underlying data store is Amazon S3, making your data extremely accessible and durable.
Amazon S3 provides long-term infrastructure for storing critical data and is meant to last 99.999999999 percent of the time. Your data is stored redundantly across many facilities and devices inside each site.
Tips to Save Money on Your AWS Athena Service Bill?
By compressing, dividing, and turning your data into column forms, you can reduce your query costs by 30% to 90% while simultaneously improving speed.
These actions decrease the quantity of data that Amazon Athena must scan to run a query. And the less it will scan, the less your bill will be.
ORC and Apache Parquet are two of the biggest open-source column formats supported by Amazon Athena. So use them to convert your data and reduce your operational cost.
AWS Athena Pricing Explained
Amazon Athena is charged per query, and the quantity of data processed by the query. Amazon S3 allows users to share data in several formats.
You save money by compressing, partitioning, or converting your data to columnar storage types. By converting data to columnar format, Athena can access only the columns required to perform the query.
How Does AWS Athena Billing Process Work?
Amazon Athena retrieves data from Amazon S3. Thus, the source data is charged at S3 pricing. When you perform a query using Amazon Athena, the results are stored inside a Cloud server of your choice.
Therefore, you will be billed at regular S3 charges for such result sets. To regulate how much data is retained, we recommend that you audit these buckets and employ lifespan policies.
What Are The Attributes That Make AWS Athena Successful?
According to AWS Athena Interview Questions, the following are the attributes that make AWS Athena successful.
| Affordability |
| Rapid Speed |
| Integration With Other AWS Services |
| Reliability |
| Security |
AWS Athena vs Redshift
AWS Athena query examples
Also, Find Below The AWS Interview Questions Guide.
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- AWS S3 Interview Questions And Answers
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Wrapping It Up!
When it comes to accurate and authentic data visualization, there are very few services that can match the might of AWS Athena.
However, not many people know how it can help you achieve your business’s full potential.
Therefore, in this article, we have answered all the frequently asked AWS Athena Interview Questions to ensure you understand this service adequately.
What do you think about this service? Let us know in the comments section. We hope you find this AWS Athena Tutorial help full.
Happy Clouding!!
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.
