In my case, I wanted to change the location of the S3 bucket to point to a directory within the bucket.
This example is taken from this AWS knowledge center doc import time
Athena aws json code#
In the example below, the code instructs the Lambda to import boto3 (the AWS SDK for Python) and use it to run a query against a database/table, then output the results of that query in CSV format and upload to a selected S3 bucket. If storage (AWS S3) and data querying (AWS Athena) are both serverless, then why not use AWS lambda to run the job? Lambda 1: Query Athena and load the results into S3 (Python) The permissions are set within AWS and it is locked by default down to the AWS console if all the defaults are kept. I don't need to worry about maintaining and paying for a database. I like using Athena as I can use SQL which I'm comfortable using while benefiting from having unlimited storage in S3. You can use Athena to run ad-hoc queries using ANSI SQL, without the need to aggregate or load the data into Athena. Examples include CSV, JSON, or columnar data formats such as Apache Parquet and Apache ORC. Instead you could have your data dropped off in an S3 bucket in CSV format and you could use Athena to query those files the same way you'd query a regular SQL database.Īthena helps you analyze unstructured, semi-structured, and structured data stored in Amazon S3. This is especially true if you are running large queries on large datasets. For example, if you need to process some data every day, you likely don't need a production server running all day. It will store your data in S3 at S3 prices and only charge you for the queries you execute (time + size of data queried). If you don't need high availablity and speed for your database, you should consider storing your data in a storage solution like Amazon Athena. Why Amazon Athena?ĭatabases cost a lot to run in both time and cash. Serverless services such as AWS Lambda promise to take away that pain and provide you a way to focus on the real thing you care about, the execution of the code you write.
However, as great and easy as it is to get rolling, when you're running production services, worrying about the infrastructure and dev ops side of things can catch you off-guard and ruin your day if there is a problem. When I use Amazon Athena to query AWS Config files, I get the following error: 'Error: HIVECURSORERROR: Row is not a valid JSON Object - JSONException: Duplicate key. Simple, readable and readily available across the web ecosystem. I've used PHP since my Wordpress days back in 2007 and I've enjoyed using it. PHP specifically has been my main tool over the years. Traditionally I've used servers to run ETL jobs.
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