試験SAA-C03 トピック3 問題743 スレッド
Amazon SAA-C03のリアル試験問題集
問題 #: 743
トピック #: 3
問題 #: 743
トピック #: 3
A real-time data analytics application is using AWS Lambda to process data and store results in JSON format to an S3 bucket. To speed up the existing workflow, you have to use a service where you can run sophisticated Big Data analytics on your data without moving them into a separate analytics system.
Which of the following group of services can you use to meet this requirement?
Which of the following group of services can you use to meet this requirement?
おすすめの解答：D 解答を投票する
Amazon S3 allows you to run sophisticated Big Data analytics on your data without moving the data into a separate analytics system. In AWS, there is a suite of tools that make analyzing and processing large amounts of data in the cloud faster, including ways to optimize and integrate existing workflows with Amazon S3:
1. S3 Select
Amazon S3 Select is designed to help analyze and process data within an object in Amazon S3 buckets, faster and cheaper. It works by providing the ability to retrieve a subset of data from an object in Amazon S3 using simple SQL expressions. Your applications no longer have to use compute resources to scan and filter the data from an object, potentially increasing query performance by up to 400%, and reducing query costs as much as 80%. You simply change your application to use SELECT instead of GET to take advantage of S3 Select.
2. Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL expressions. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL expressions. Most results are delivered within seconds.
With Athena, there's no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.
3. Amazon Redshift Spectrum
Amazon Redshift also includes Redshift Spectrum, allowing you to directly run SQL queries against exabytes of unstructured data in Amazon S3. No loading or transformation is required, and you can use open data formats, including Avro, CSV, Grok, ORC, Parquet, RCFile, RegexSerDe, SequenceFile, TextFile, and TSV. Redshift Spectrum automatically scales query compute capacity based on the data being retrieved, so queries against Amazon S3 run fast, regardless of data set size.
Reference:
https://aws.amazon.com/s3/features/#Query_in_Place
Amazon Redshift Overview:
https://youtu.be/jlLERNzhHOg
Check out these AWS Cheat Sheets:
https://tutorialsdojo.com/amazon-s3/
https://tutorialsdojo.com/amazon-athena/
https://tutorialsdojo.com/amazon-redshift/
1. S3 Select
Amazon S3 Select is designed to help analyze and process data within an object in Amazon S3 buckets, faster and cheaper. It works by providing the ability to retrieve a subset of data from an object in Amazon S3 using simple SQL expressions. Your applications no longer have to use compute resources to scan and filter the data from an object, potentially increasing query performance by up to 400%, and reducing query costs as much as 80%. You simply change your application to use SELECT instead of GET to take advantage of S3 Select.
2. Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL expressions. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries you run. Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL expressions. Most results are delivered within seconds.
With Athena, there's no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets.
3. Amazon Redshift Spectrum
Amazon Redshift also includes Redshift Spectrum, allowing you to directly run SQL queries against exabytes of unstructured data in Amazon S3. No loading or transformation is required, and you can use open data formats, including Avro, CSV, Grok, ORC, Parquet, RCFile, RegexSerDe, SequenceFile, TextFile, and TSV. Redshift Spectrum automatically scales query compute capacity based on the data being retrieved, so queries against Amazon S3 run fast, regardless of data set size.
Reference:
https://aws.amazon.com/s3/features/#Query_in_Place
Amazon Redshift Overview:
https://youtu.be/jlLERNzhHOg
Check out these AWS Cheat Sheets:
https://tutorialsdojo.com/amazon-s3/
https://tutorialsdojo.com/amazon-athena/
https://tutorialsdojo.com/amazon-redshift/
Sugita 2025-01-31 01:03:52
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