datacatalog-fileset-enricher 1.1.0

A package for enriching the content of a fileset Entry with Datacatalog Tags

datacatalog-fileset-enricher

A Python package to enrich Google Cloud Data Catalog Fileset Entries with Data Catalog Tags. The goal of this library is to provide useful statistics regarding the GCS files that match the file pattern on the provided Data Catalog Fileset Entry.

For instructions on how to create Fileset Entries, please go to the official Google Cloud Docs

1. Created Tags

Tags created by the fileset enricher are composed by the following attributes, and all stats are a snapshot of the execution time:

Field	Description	Mandatory
execution_time	Execution time when all stats were collected.	Y
files	Number of files found, that matches the prefix.	N
min_file_size	Minimum file size found in bytes.	N
max_file_size	Maximum file size found in bytes.	N
avg_file_size	Average file size found in bytes.	N
total_file_size	Total file size found in bytes.	N
first_created_date	First time a file was created in the bucket(s).	N
last_created_date	Last time a file was created in the bucket(s).	N
last_updated_date	Last time a file was updated in the bucket(s).	N
created_files_by_day	Number of files created on the same date.	N
updated_files_by_day	Number of files updated on the same date.	N
prefix	Prefix used to find the files.	N
bucket_prefix	When specified at runtime, buckets without this prefix are ignored.	N
buckets_found	Number of buckets that matched the prefix.	N
files_by_bucket	Number of files found on each bucket.	N
files_by_type	Number of files found by file type.	N

If no fields are specified when running the fileset enricher, all Tag fields will be applied.

To generate file statistics and create the Tags this python package, uses the GCS list_buckets and list_blobs APIs to extract the metadata that matches the file pattern, so their billing policies will apply.

2. Environment setup

2.1. Get the code

git clone https://github.com/mesmacosta/datacatalog-fileset-enricher
cd datacatalog-fileset-enricher

2.2. Auth credentials

2.2.1. Create a service account and grant it below roles

• Data Catalog Tag Editor
• Data Catalog TagTemplate Owner
• Data Catalog Viewer
• Storage Admin or Custom Role with storage.buckets.list acl

2.2.2. Download a JSON key and save it as

• ./credentials/datacatalog-fileset-enricher.json

2.3. Virtualenv

Using virtualenv is optional, but strongly recommended unless you use Docker.

2.3.1. Install Python 3.6+

2.3.2. Create and activate an isolated Python environment

pip install --upgrade virtualenv
python3 -m virtualenv --python python3 env
source ./env/bin/activate

2.3.3. Install the dependencies

pip install --upgrade --editable .

2.3.4. Set environment variables

export GOOGLE_APPLICATION_CREDENTIALS=./credentials/datacatalog-fileset-enricher.json

2.4. Docker

Docker may be used as an alternative to run all the scripts. In this case, please disregard the Virtualenv install instructions.

3. Enrich DataCatalog Fileset Entry with Tags

3.1. python main.py - Enrich all fileset entries

• python

python main.py --project-id my_project \
  enrich-gcs-filesets

• docker

docker build --rm --tag datacatalog-fileset-enricher .
docker run --rm --tty -v your_credentials_folder:/data datacatalog-fileset-enricher \
  --project-id my_project \
  enrich-gcs-filesets

3.2. python main.py -- Enrich all fileset entries using template from a different Project

python main.py --project-id my_project \
  enrich-gcs-filesets \
  --tag-template-name projects/my_different_project/locations/us-central1/tagTemplates/fileset_enricher_findings

3.3. python main.py -- Enrich a single entry

python main.py --project-id my_project \
  enrich-gcs-filesets \
   --entry-group-id my_entry_group \
   --entry-id my_entry

3.4. python main.py -- Enrich a single entry, specifying desired tag fields

Users are able to choose the Tag fields from the list provided at Tags

python main.py --project-id my_project \
  enrich-gcs-filesets \
 --entry-group-id my_entry_group \
 --entry-id my_entry
 --tag-fields files,prefix

3.5. python main.py -- Pass a bucket prefix if you want to avoid scanning too many buckets

When the bucket_prefix is specified, the list_bucket api calls pass this prefix and avoid scanning buckets that don't match the prefix. This only applies when there's a wildcard on the bucket_name, otherwise the get bucket method is called and the bucket_prefix is ignored.

python main.py --project-id my_project \
  enrich-gcs-filesets \
 --bucket-prefix my_bucket

3.6. python create fileset enricher template in a project

Creates the fileset enricher template in a different project.

python main.py --project-id my_different_project \
    create-template

3.6. python clean up template and tags (Reversible)

Cleans up the Template and Tags from the Fileset Entries, running the main command will recreate those.

python main.py --project-id my_project \
  clean-up-templates-and-tags

3.7. python clean up all (Non Reversible, be careful)

Cleans up the Fileset Entries, Template and Tags. You have to re create the Fileset entries if you need to restore the state, which is outside the scope of this script.

python main.py --project-id my_project \
  clean-up-all

Disclaimers

This is not an officially supported Google product.