Getting Started With Amazon Athena Tutorial

This tutorial walks you through using Amazon Athena to query data. You’ll create a table based on sample data stored in Amazon Simple Storage Service, query the table, and check the results of the query.

The tutorial is using live resources, so you are charged for the queries that you run. You aren’t charged for the sample datasets that you use, but if you upload your own data files to Amazon S3, charges do apply.

Step 1: Create a Database

Open the Athena console.
If this is your first time visiting the Athena console, you’ll go to a Getting Started page. Choose Get Started to open the Query Editor. If it isn’t your first time, the Athena Query Editor opens.
In the Athena Query Editor, you see a query pane with an example query. Start typing your query anywhere in the query pane.
To create a database named mydatabase, enter the following CREATE DATABASE statement, and then choose Run Query:
```
CREATE DATABASE mydatabase
```
Confirm that the catalog display refreshes and mydatabase appears in the DATABASE list in the Catalog dashboard on the left side.

Step 2: Create a Table

Now that you have a database, you’re ready to create a table that’s based on the sample data file. You define columns that map to the data, specify how the data is delimited, and provide the location in Amazon S3 for the file.

To create a table

Make sure that mydatabase is selected for DATABASE and then choose New Query.

In the query pane, enter the following CREATE TABLE statement, and then choose Run Query:

Note

You can query data in regions other than the region where you run Athena. Standard inter-region data transfer rates for Amazon S3 apply in addition to standard Athena charges. To reduce data transfer charges, replace myregionin s3://athena-examples-myregion/path/to/data/ with the region identifier where you run Athena, for example, s3://athena-examples-us-east-1/path/to/data/.

CREATE EXTERNAL TABLE IF NOT EXISTS cloudfront_logs (
  `Date` DATE,
  Time STRING,
  Location STRING,
  Bytes INT,
  RequestIP STRING,
  Method STRING,
  Host STRING,
  Uri STRING,
  Status INT,
  Referrer STRING,
  os STRING,
  Browser STRING,
  BrowserVersion STRING
  ) ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.RegexSerDe'
  WITH SERDEPROPERTIES (
  "input.regex" = "^(?!#)([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+([^ ]+)\\s+[^\(]+[\(]([^\;]+).*\%20([^\/]+)[\/](.*)$"
  ) LOCATION 's3://athena-examples-myregion/cloudfront/plaintext/';

The table cloudfront_logs is created and appears in the Catalog dashboard for your database.

Step 3: Query Data

Now that you have the cloudfront_logs table created in Athena based on the data in Amazon S3, you can run queries on the table and see the results in Athena.

To run a query

Choose New Query, enter the following statement anywhere in the query pane, and then choose Run Query:
```
SELECT os, COUNT(*) count
FROM cloudfront_logs
WHERE date BETWEEN date '2014-07-05' AND date '2014-08-05'
GROUP BY os;
```
Results are returned that look like the following: