How to Build an ETL App for Amazon Athena Data in Python with CData

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Amazon Athena and the petl framework, you can build Amazon Athena-connected applications and pipelines for extracting, transforming, and loading Amazon Athena data. This article shows how to connect to Amazon Athena with the CData Python Connector and use petl and pandas to extract, transform, and load Amazon Athena data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Amazon Athena data in Python. When you issue complex SQL queries from Amazon Athena, the driver pushes supported SQL operations, like filters and aggregations, directly to Amazon Athena and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Amazon Athena Data

Connecting to Amazon Athena data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Authenticating to Amazon Athena

To authorize Amazon Athena requests, provide the credentials for an administrator account or for an IAM user with custom permissions: Set AccessKey to the access key Id. Set SecretKey to the secret access key.

Note: Though you can connect as the AWS account administrator, it is recommended to use IAM user credentials to access AWS services.

Obtaining the Access Key

To obtain the credentials for an IAM user, follow the steps below:

1. Sign into the IAM console.
2. In the navigation pane, select Users.
3. To create or manage the access keys for a user, select the user and then select the Security Credentials tab.

To obtain the credentials for your AWS root account, follow the steps below:

1. Sign into the AWS Management console with the credentials for your root account.
2. Select your account name or number and select My Security Credentials in the menu that is displayed.
3. Click Continue to Security Credentials and expand the Access Keys section to manage or create root account access keys.

Authenticating from an EC2 Instance

If you are using the CData Data Provider for Amazon Athena 2018 from an EC2 Instance and have an IAM Role assigned to the instance, you can use the IAM Role to authenticate. To do so, set UseEC2Roles to true and leave AccessKey and SecretKey empty. The CData Data Provider for Amazon Athena 2018 will automatically obtain your IAM Role credentials and authenticate with them.

Authenticating as an AWS Role

In many situations it may be preferable to use an IAM role for authentication instead of the direct security credentials of an AWS root user. An AWS role may be used instead by specifying the RoleARN. This will cause the CData Data Provider for Amazon Athena 2018 to attempt to retrieve credentials for the specified role. If you are connecting to AWS (instead of already being connected such as on an EC2 instance), you must additionally specify the AccessKey and SecretKey of an IAM user to assume the role for. Roles may not be used when specifying the AccessKey and SecretKey of an AWS root user.

Authenticating with MFA

For users and roles that require Multi-factor Authentication, specify the MFASerialNumber and MFAToken connection properties. This will cause the CData Data Provider for Amazon Athena 2018 to submit the MFA credentials in a request to retrieve temporary authentication credentials. Note that the duration of the temporary credentials may be controlled via the TemporaryTokenDuration (default 3600 seconds).

Connecting to Amazon Athena

In addition to the AccessKey and SecretKey properties, specify Database, S3StagingDirectory and Region. Set Region to the region where your Amazon Athena data is hosted. Set S3StagingDirectory to a folder in S3 where you would like to store the results of queries.

If Database is not set in the connection, the data provider connects to the default database set in Amazon Athena.

After installing the CData Amazon Athena Connector, follow the procedure below to install the other required modules and start accessing Amazon Athena through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for Amazon Athena Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.amazonathena as mod

You can now connect with a connection string. Use the connect function for the CData Amazon Athena Connector to create a connection for working with Amazon Athena data.

cnxn = mod.connect("AccessKey='a123';SecretKey='s123';Region='IRELAND';Database='sampledb';S3StagingDirectory='s3://bucket/staging/';")

Create a SQL Statement to Query Amazon Athena

Use SQL to create a statement for querying Amazon Athena. In this article, we read data from the Customers entity.

sql = "SELECT Name, TotalDue FROM Customers WHERE CustomerId = '12345'"

Extract, Transform, and Load the Amazon Athena Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Amazon Athena data. In this example, we extract Amazon Athena data, sort the data by the TotalDue column, and load the data into a CSV file.

Loading Amazon Athena Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'TotalDue')

etl.tocsv(table2,'customers_data.csv')

In the following example, we add new rows to the Customers table.

Adding New Rows to Amazon Athena

table1 = [ ['Name','TotalDue'], ['NewName1','NewTotalDue1'], ['NewName2','NewTotalDue2'], ['NewName3','NewTotalDue3'] ]

etl.appenddb(table1, cnxn, 'Customers')

With the CData Python Connector for Amazon Athena, you can work with Amazon Athena data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for Amazon Athena to start building Python apps and scripts with connectivity to Amazon Athena data. Reach out to our Support Team if you have any questions.

Full Source Code

import petl as etl
import pandas as pd
import cdata.amazonathena as mod

cnxn = mod.connect("AccessKey='a123';SecretKey='s123';Region='IRELAND';Database='sampledb';S3StagingDirectory='s3://bucket/staging/';")

sql = "SELECT Name, TotalDue FROM Customers WHERE CustomerId = '12345'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'TotalDue')

etl.tocsv(table2,'customers_data.csv')

table3 = [ ['Name','TotalDue'], ['NewName1','NewTotalDue1'], ['NewName2','NewTotalDue2'], ['NewName3','NewTotalDue3'] ]

etl.appenddb(table3, cnxn, 'Customers')