Athena

Overview

• Amazon Athena is an interactive query service
• makes it easy to analyze data in Amazon S3 using standard SQL.
• Athena is serverless, so there is no infrastructure to manage
• you pay only for the queries that you run.
• Athena is used for analytics and not to prepare data for analytics.
• Athena supports many formats
  • CSV
  • JSON
  • ORC
  • Avro
  • Parquet
  • Possibly others
• Amazon is commonly used with QuickSight for reporting/dashboards

Pricing

• Fixed amount
  • $5.00 per TB of data scanned

Use Cases

• Business intelligence
• Analytics
• report, analyze, & query VPC flow logs
• ELB Logs
• CloudTrail trails
• Ad-hoc queries
• Pretty much query any logs that originate from your

Performance Improvement

Use columnar data for cost-savings (scan less!!!)

• Apache Parquet or ORC is recommended.
• This is going to give you a huge performance improvement
• Use Glue to convert your data to Apache Parquet or ORC

Compress Data for smaller retrievals

• bzip2
• gzip
• lz4
• snappy
• zlip
• zstd

Partition Datasets in S3 for Easier Querying on Virtutal Columns

• basic formatting idea

	s3://yourBucket/pathToTable
		/<PARTITION_COLUMN_NAME>=<VALUE>
		  /<PARTITION_COLUMN_NAME>=<VALUE>
		    /<PARTITION_COLUMN_NAME>=<VALUE>
		      /etc...

• example:

  s3://athena-examples/flight/parquet/year=1991/month=1/day=1/
  

Use Larger Files to Minimize Overhead

• 128 MB or larger

Federated Query

• Allows you to run SQL queries across data stored in relational, nne-relational, object, and custom data sources
  • AWS or on-premises
• Uses Data Source Connectors that run on AWS Lambda to run Federated Queries, for example
  • CloudWatch Logs
  • DynamoDB
  • RDS
• Store the results back in S3

Exam Alerts

• Analyze data in S3 using serverless SQL, you should be thinking Athena