Tutorial Expert How-To - Command Line Interface (CLI)

Jun 27, 20230 likes48 views

Promote a shared understanding of meaning and context for data structures across business users and technical users, through the synchronization and publication of these data structures to business-facing data catalogs.

Hackolade Tutorial
Tutorial Expert – Command Line Interface (CLI)
Copyright © 2016-2023 Hackolade 1

Metadata-as-Code
• See our article
• Business purpose: promote a shared understanding of meaning and
context for data structures across business users and technical users,
through the synchronization and publication of these data structures
to business-facing data catalogs.
• Technical purpose: ensure that the evolution of data models and their
schema artifacts follow the same lifecycle as application code,
through their co-location in Git repository and branches.
Copyright © 2016-2023 Hackolade 2

Design
Data Model
Generate
Schema
Catalog
Publish
Use
Evaluate
Data
Modeler
Data
Architect
Subject
Matter
Expert
Data
Engineer
Data
Analyst
Business
Analyst
Data models lifecycle unified with DevOps applications
Copyright © 2016-2023 Hackolade
Application
Metadata Dev Ops

Data models
Schema contracts
Application code
Git repository DevOps CI/CD
pipeline
Application
Database
Copyright © 2016-2023 Hackolade 4
Co-locate data models and schemas with application code
Environments:
• Dev
• Test
• Integration
• Production
ALTER scripts

Command line interface (CLI)
• Lets you AUTOMATE repetitive tasks that you otherwise perform
manually in the Hackolade Studio GUI
• Can be run overnight, or based on workflow trigger
• Can be used on standalone machine, or combined with a GIT
repository, or a docker container
• Allows for end-to-end synchronisation of data structures with
business-facing data dictionaries
Copyright © 2016-2023 Hackolade 5

… …
Consumers
Subject area models
Project models
Models
Local
Repo
Local
Repo
Local
Repo
Clone
Push
Pull
Merge …
Copyright © 2016-2022 Hackolade 6
Hackolade Studio to Schema Repo workflow
CLI
Schemas
DDL files
OAS files
JSON Schema files
Avro Schema files
…

Copyright © 2016-2022 Hackolade
Hackolade’s Metadata-as-Code orchestrates Metadata Pipelines to keep in sync
technical data structures with business-facing data dictionaries
Repository
Human-readable
Models
A
c
t
o
r
s
Design
Models
Data
modelers,
architects,
developers
Technical side
Machine-readable
Schemas
Databases
APIs
Registries
Hubs
Code Classes
Technology
Command-Line
Interface Repository
Schemas
DevOps
CI/CD
Business side
Data
citizens
Metadata
management
Reverse-engineering
Wiki

CLI orchestration
• Often scripted
• Example use cases:
• Governance-first:
reverse-engineer >> compare with baseline model >> delta model >> forward
engineer ALTER script >> submit committed ALTER script for review
• Code-first:
reverse engineer >> compare with baseline model >> delta model >> review
of model comparison >> produce merged model >> commit merged model as
new baseline model
• Many other possibilities depending on your needs
Copyright © 2016-2023 Hackolade 8

Governance-first use case
Copyright © 2016-2023 Hackolade 9

Code-first use case
Copyright © 2016-2023 Hackolade 10

Develop / fine-tune the CLI commands
• Start with the GUI to visualize: different steps of the full workflow
• Start small in CLI
• Beware of “path” complexity
• Split script into multiple parts
• With model comparisons: understand what is model1 and what is
model2 – the sequence matters!
• Test, test, and re-test!
Copyright © 2016-2023 Hackolade 11

Reading material
• See Hackolade online documentation
• The Hackolade Blog
• This excellent new book:
MongoDB Data Modeling & Schema Design
• Many of the principles in the book are related to query
driven modeling based on access patterns!
• Hackolade’s on social media: LinkedIn page, Twitter page
• Download Hackolade studio for free
Copyright © 2016-2023 Hackolade 12

Questions?
Answers!
Copyright © 2016-2023 Hackolade 13

Hackolade Studio has native integration with Git repositories to provide state-of-the-art collaboration, versioning, branching, conflict resolution, peer review workflows, change tracking and traceability. Mostly, it allows to co-locate data models and schemas with application code, and further integrate with DevOps CI/CD pipelines as part of our vision for Metadata-as-Code. Co-located application code and data models provide the single source-of-truth for business and technical stakeholders.

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Co-locate data models and their schema artifacts with application code, so they can follow the lifecycle of application changes. Provides a single source-of-truth for business and technical stakeholders as the data model in the Git repo is the source of the technical schemas used by applications, databases, and APIs at the same time as it is the source for the business-facing data dictionaries. This architecture contributes to the shared understanding of the context and meaning of data by all the stakeholders.

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