AWS Tutorials - Amazon Athena Query Cost Optimization

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Amazon Athena is a Serverless and interactive query service to query and analyze data in Amazon S3 using standard SQL. Amazon Athena cost depends on amount of data scanned to bring the query result. The amount of data scanned can be optimized using data partitioning and parquet format based storage. The video explain these two methods and then does a live demo to show the result of the optimization.

[@RoryDavidWatts]

Great tutorial, thank you

[@victorfeight9644]

great summary

[@venkatasubbareddy9184]

Can you share me the data which you used in this tutorial ?

[@mkalicharan]

Excellent video, loved it. So going by this what will be the cost of the athena query? if the sum of all data scanned on multiple attemps across days is 1tb then we are charged 5$ isnt it?

[@AWSTutorialsOnline]

You are right. It is simple amount of data scan.

[@kingzao9046]

What happens if you do a JOIN ? How is the cost computed ?

[@AWSTutorialsOnline]

It will scan files of both data sets and sum of both scans will determine the cost.

[@ivenk1976]

If there are multiple partition like 'State' and other as 'likeSports' Then will my data storage size will double?

[@AWSTutorialsOnline]

partition is like hierarchy so the first partition on "state" and then on "likesports". So first it will create multiple folders for "state" and then within "state" folder; create multiple folders for "likesports". So the storage size is not doubled.