Overview

Beekeeper is a service that schedules orphaned paths and expired metadata for deletion.

The original inspiration for a data deletion tool came from another of our open source projects called Circus Train. At a high level, Circus Train replicates Hive datasets. The datasets are copied as immutable snapshots to ensure strong consistency and snapshot isolation, only pointing the replicated Hive Metastore to the new snapshot on successful completion. This process leaves behind snapshots of data which are now unreferenced by the Hive Metastore, so Circus Train includes a Housekeeping module to delete these files later.

Beekeeper is based on Circus Train's Housekeeping module, however it is decoupled from Circus Train so it can be used by other applications as well.

Start using

To deploy Beekeeper in AWS, see the terraform repo.

Docker images can be found in Expedia Group's dockerhub.

How does it work?

Beekeeper makes use of Apiary - an open source federated cloud data lake - to detect changes in the Hive Metastore. One of Apiary’s components, the Apiary Metastore Listener, captures Hive events and publishes these as messages to an SNS topic. Beekeeper uses these messages to detect changes to the Hive Metastore, and perform appropriate deletions.

Beekeeper is comprised of three separate Spring-based Java applications:

1. Scheduler Apiary - An application that schedules paths and metadata for deletion in a shared database, with one table for unreferenced paths and another for expired metadata.
2. Path Cleanup - An application that perform deletions of unreferenced paths.
3. Metadata Cleanup - An application that perform deletions of expired metadata.

Beekeeper Architecture

Unreferenced paths

The "unreferenced" property can be added to tables to detect when paths become unreferenced. It will currently only be triggered by these events:

• alter_partition
• alter_table
• drop_partition
• drop_table

By default, alter_partition and alter_table events require no further configuration. However, in order to avoid unexpected data loss, other event types require whitelisting on a per table basis. See Hive table configuration for more details.

End-to-end lifecycle example

1. A Hive table is configured with the parameter beekeeper.remove.unreferenced.data=true (see Hive table configuration for more details.)
2. An operation is executed on the table that orphans some data (alter partition, drop partition, etc.)
3. Hive Metastore events are emitted by the Hive Metastore Listener as a result of the operation.
4. Hive events are picked up from the queue by Beekeeper using the Apiary Receiver.
5. Beekeeper processes these messages and schedules orphaned paths for deletion by adding them to a database.
6. The scheduled paths are deleted by Beekeeper after a configurable delay, the default is 3 days (see Hive table configuration for more details.)

Time To Live, TTL

The "expired" TTL property will delete tables, partitions, and their locations after a configurable delay. If no delay is specified the default is 30 days.

If the table is partitioned the cleanup delay will also apply to each partition that is added to the table. The table will only be dropped when there are no remaining partitions.

End-to-end lifecycle example

1. A Hive table is configured with the TTL parameter beekeeper.remove.expired.data=true (see Hive table configuration for more details).
2. This Hive event is picked up from the queue by Beekeeper using the Apiary Receiver, and the table is scheduled for cleanup with a configurable delay.
3. An operation is executed on the table which alters it in some way, (alter table, add partition, alter partition)
4. These Hive events are once again picked up from the queue by Beekeeper using the Apiary receiver. Depending on the event, Beekeeper will do the following:
   • Alter table - Creates a new entry in the database with the updated table info
   • Add partition - The partition is scheduled to be deleted using the cleanup delay of the table
   • Alter partition - Creates a new entry in the database with the updated partition info
5. The scheduled partitions, tables, and associated paths will be deleted by Beekeeper after the delay has passed.

TTL Caveats

Currently with the first release of Beekeeper TTL there are the following issues:

• If a table or partition is dropped by a user before the expiration time the related paths will become unreferenced and won’t be cleaned up.
  • This can be avoided by also adding the "unreferenced" property to the table, see the unreferenced paths section. However, this property listens to any drop event on that table and we haven’t yet configured Beekeeper to ignore drop events made by itself. So this will mean that any path for a table/partition dropped by Beekeeper during the TTL cleanup will be scheduled for deletion again in the unreferenced cleanup table.
• If a partitioned table with existing partitions is renamed, these partitions will not be dropped until the table has expired.
  • For example: A table is created with a cleanup delay of 2 days and a partition is added. The delay is changed to 10 days and the table is then renamed. With the current release the existing partition won’t be rescheduled to be deleted under the new table. So it will be deleted along with the table in 10 days instead of 2.

Hive table configuration

Beekeeper only actions on events which are marked with specific parameters. These parameters need to be added to the Hive table that you wish to be monitored by Beekeeper. The configuration parameters for Hive tables are as follows:

Usage

Unreferenced Paths

This command can be used to add the parameter to a Hive Table:

ALTER TABLE <table-name> SET TBLPROPERTIES("beekeeper.remove.unreferenced.data"="true");

TTL

You can either add the property when the table is created:

CREATE TABLE <table> (<col_name> <type>, ... ) TBLPROPERTIES("beekeeper.remove.expired.data"="true", "beekeeper.expired.data.retention.period"="PT2M");

Or alter an existing table:

ALTER TABLE <table> SET TBLPROPERTIES("beekeeper.remove.expired.data"="true", "beekeeper.expired.data.retention.period"="PT1H");

NOTE - if you add this property to a partitioned table any existing partitions will not be scheduled for deletion. They will be deleted along with the table when the TTL delay is met.

Running Beekeeper

Beekeeper consists of three Spring Boot applications which run independently of each other:

• beekeeper-path-cleanup periodically queries a database for paths to delete and performs deletions.
• beekeeper-metadata-cleanup periodically queries a database for metadata to delete and performs deletions on hive tables, partitions, and s3 paths.
• beekeeper-scheduler-apiary periodically polls an Apiary SQS queue for Hive Metastore events and inserts S3 paths and Hive tables to be deleted into a database, scheduling them for deletion.

All applications require configuration to be provided, see Application configuration for details.

java -jar <spring-boot-application>.jar --config=<config>.yml

<config>.yml takes this format:

spring.datasource:
  url: jdbc:mysql://<database-url>:3306/beekeeper?useSSL=false
  username: <username>
  password: <password>   
  
# other config

This can be provided via a file or Spring can load properties from the environment (see below).

Using Docker

Three Docker images are created during mvn install - two for cleanup of paths and metadata, and one for scheduling.

Configuration can be provided in one of two ways:

1. Using environment variables.

docker run --env-file <config-env>.env <image-id>

<config-env>.env takes this format:

spring_datasource_url=jdbc:mysql://<database-url>:3306/beekeeper?useSSL=false
spring_datasource_username=<user>
spring_datasource_password=<password>

# other config

Any additional configuration can be added in a similar way as the app will load properties from the docker environment.

2. Using a base64 encoded properties file as an environment variable:

export BEEKEEPER_CONFIG=$(base64 -w 0 -i <config>.yml)
docker run -e BEEKEEPER_CONFIG=$BEEKEEPER_CONFIG <image-id>

<config>.yml takes this format:

spring.datasource:
  url: jdbc:mysql://<database-url>:3306/beekeeper?useSSL=false
  username: <username>
  password: <password>   
  
# other config

Database password

To avoid the problem of a plaintext password, AWS Secrets Manager is supported.

To use Secrets Manager, remove the password from the <config>.yml:

spring.datasource:
  url: jdbc:mysql://<database-url>:3306/beekeeper?useSSL=false
  username: <username>
  
# other config

and provide the password strategy and password key when running the container:

docker run -e BEEKEEPER_CONFIG=$BEEKEEPER_CONFIG -e DB_PASSWORD_STRATEGY=aws-secrets-manager -e DB_PASSWORD_KEY <password-key> <image-id>

Local dockerised database

If you would like to connect a dockerised application to a local MySQL database (e.g. initialised from docker-compose up), the two containers need to be on the same network:

docker run --network beekeeper_default <image-id>

where <database-url> is the name of the running MySQL container.

Endpoints

Being a Spring Boot Application, all standard actuator endpoints are supported.

For example, the healthcheck endpoint at: http://<address>:<port>/actuator/health.

By default, beekeeper-scheduler-apiary listens on port 8080, beekeeper-path-cleanup listens on port 8008, and beekeeper-metadata-cleanup listens on 9008. To access this endpoint when running in a Docker container, the port must be published:

docker run -p <port>:<port> <image-id>

Application configuration

Beekeeper Scheduler Apiary

Beekeeper Path Cleanup

Beekeeper Metadata Cleanup

Metrics

Beekeeper currently supports Graphite and Prometheus metrics.

Prometheus metrics are exposed at /actuator/prometheus.

Graphite metrics require configuration to enable. If Graphite is enabled, both host and prefix are required. If they are not provided, the application will throw an exception and not start.

The following table shows the configuration that can be provided:

External links

Please see the Housekeeping library for more information.

Legal

This project is available under the Apache 2.0 License.

Copyright 2019-2020 Expedia, Inc.