The Amazon Athena Query Federation SDK allows you to customize Amazon Athena with your own code. This enables you to integrate with new data sources, proprietary data formats, or build in new user defined functions. Initially these customizations will be limited to the parts of a query that occur during a TableScan operation but will eventually be expanded to include other parts of the query lifecycle using the same easy to understand interface.
Athena Federated Queries are now available where Athena is supported. To use this feature, upgrade your engine version to Athena V2 in your workgroup settings. Check documentation here for more details: https://docs.aws.amazon.com/athena/latest/ug/engine-versions.html.
tldr; Get Started:
- Ensure you have the proper permissions/policies to deploy/use Athena Federated Queries
- Navigate to Servless Application Repository and search for "athena-federation". Be sure to check the box to show entries that require custom IAM roles.
- Look for entries published by the "Amazon Athena Federation" author.
- Deploy the application
- To use Federated Queries, upgrade your engine version to Athena V2 in your workgroup settings. Check documentation here for more details: https://docs.aws.amazon.com/athena/latest/ug/engine-versions.html.
- Run a query "show databases in `lambda:<func_name>`" where <func_name> is the name of the Lambda function you deployed in the previous steps.
For more information please consult:
- Intro Video
- SDK ReadMe
- Quick Start Guide
- Available Connectors
- Federation Features
- How To Build A Connector or UDF
- Gathering diagnostic info for support
- Frequently Asked Questions
- Common Problems
- Installation Pre-requisites
- Known Limitations & Open Issues
- Predicate Pushdown How-To
- Our Github Wiki.
- Java Doc
We've written integrations with more than 20 databases, storage formats, and live APIs in order to refine this interface and balance flexibility with ease of use. We hope that making this SDK and initial set of connectors Open Source will allow us to continue to improve the experience and performance of Athena Query Federation.
Imagine a hypothetical e-commerce company who's architecture uses:
- Payment processing in a secure VPC with transaction records stored in HBase on EMR
- Redis is used to store active orders so that the processing engine can get fast access to them.
- DocumentDB (e.g. a mongodb compatible store) for Customer account data like email address, shipping addresses, etc..
- Their e-commerce site using auto-scaling on Fargate with their product catalog in Amazon Aurora.
- Cloudwatch Logs to house the Order Processor's log events.
- A write-once-read-many datawarehouse on Redshift.
- Shipment tracking data in DynamoDB.
- A fleet of Drivers performing last-mile delivery while utilizing IoT enabled tablets.
- Advertising conversion data from a 3rd party source.
Customer service agents begin receiving calls about orders 'stuck' in a weird state. Some show as pending even though they have delivered, others show as delivered but haven't actually shipped. It would be great if we could quickly run a query across this diverse architecture to understand which orders might be affected and what they have in common.
Using Amazon Athena Query Federation and many of the connectors found in this repository, our hypothetical e-commerce company would be able to run a query that:
- Grabs all active orders from Redis. (see athena-redis)
- Joins against any orders with 'WARN' or 'ERROR' events in Cloudwatch logs by using regex matching and extraction. (see athena-cloudwatch)
- Joins against our EC2 inventory to get the hostname(s) and status of the Order Processor(s) that logged the 'WARN' or 'ERROR'. (see athena-cmdb)
- Joins against DocumentDB to obtain customer contact details for the affected orders. (see athena-docdb)
- Joins against DynamoDB to get shipping status and tracking details. (see athena-dynamodb)
- Joins against HBase to get payment status for the affected orders. (see athena-hbase)
WITH logs
AS (SELECT log_stream,
message AS
order_processor_log,
Regexp_extract(message, '.*orderId=(\d+) .*', 1) AS orderId,
Regexp_extract(message, '(.*):.*', 1) AS log_level
FROM
"lambda:cloudwatch"."/var/ecommerce-engine/order-processor".all_log_streams
WHERE Regexp_extract(message, '(.*):.*', 1) != 'WARN'),
active_orders
AS (SELECT *
FROM redis.redis_db.redis_customer_orders),
order_processors
AS (SELECT instanceid,
publicipaddress,
state.NAME
FROM awscmdb.ec2.ec2_instances),
customer
AS (SELECT id,
email
FROM docdb.customers.customer_info),
addresses
AS (SELECT id,
is_residential,
address.street AS street
FROM docdb.customers.customer_addresses),
shipments
AS ( SELECT order_id,
shipment_id,
from_unixtime(cast(shipped_date as double)) as shipment_time,
carrier
FROM lambda_ddb.default.order_shipments),
payments
AS ( SELECT "summary:order_id",
"summary:status",
"summary:cc_id",
"details:network"
FROM "hbase".hbase_payments.transactions)
SELECT _key_ AS redis_order_id,
customer_id,
customer.email AS cust_email,
"summary:cc_id" AS credit_card,
"details:network" AS CC_type,
"summary:status" AS payment_status,
status AS redis_status,
addresses.street AS street_address,
shipments.shipment_time as shipment_time,
shipments.carrier as shipment_carrier,
publicipaddress AS ec2_order_processor,
NAME AS ec2_state,
log_level,
order_processor_log
FROM active_orders
LEFT JOIN logs
ON logs.orderid = active_orders._key_
LEFT JOIN order_processors
ON logs.log_stream = order_processors.instanceid
LEFT JOIN customer
ON customer.id = customer_id
LEFT JOIN addresses
ON addresses.id = address_id
LEFT JOIN shipments
ON shipments.order_id = active_orders._key_
LEFT JOIN payments
ON payments."summary:order_id" = active_orders._key_
This project is licensed under the Apache-2.0 License.