Apache Atlas: Tracking dataset lineage across Hadoop components
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Disclaimer
This document may contain product features and technology directions that are under development, may be under development in the future or may ultimately not be developed.
Project capabilities are based on information that is publicly available within the Apache Software Foundation project websites ("Apache"). Progress of the project capabilities can be tracked from inception to release through Apache, however, technical feasibility, market demand, user feedback and the overarching Apache Software Foundation community development process can all effect timing and final delivery.
This document’s description of these features and technology directions does not represent a contractual commitment, promise or obligation from Hortonworks to deliver these features in any generally available product.
Product features and technology directions are subject to change, and must not be included in contracts, purchase orders, or sales agreements of any kind.
Since this document contains an outline of general product development plans, customers should not rely upon it when making purchasing decisions.
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Speakers
Andrew AhnGovernance Director Product Management
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Agenda
• Atlas Overview• Near term roadmap• Cross Component Lineage• Questions
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Apache Atlas Overview
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STRUCTURED
UN
STRUCTU
RED
Vision - Enterprise Data Governance Across Platfroms
TRADITIONALRDBMS
METADATA
MPP APPLIANCES
Project 1
Project 5
Project 4
Project 3
Metadata
Project 6
DATALAKE
STREAMING
GOAL: Provide a common approach to data governance across all systems and data within the enterprise
TransparentGovernance standards and protocols must be clearly defined and available to allReproducibleRecreate the relevant data landscape at a point in timeAuditableAll relevant events and assets but be traceable with appropriate historical lineageConsistentCompliance practices must be consistent
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Ready for Trusted Governance
OPERATIONS SECURITY
GOVERNANCE
STORAG
ESTO
RAG
E
MachineLearningBatch
StreamingInteractive
Search
GOVERNANCE
YA R ND A T A O P E R A T I N G S Y S T E M
Data Managementalong the entire data lifecycle with integrated provenance and lineage capability
Modeling with Metadataenables comprehensive data lineage through a hybrid approach with enhanced tagging and attribute capabilities
Interoperable Solutionsacross the Hadoop ecosystem, through a common metadata store
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DGI* Community becomes Apache Atlas
May2015
Proto-typeBuilt
Apache AtlasIncubation
DGI groupKickoff
Feb2015
Dec 2014
July2015HDP 2.3 FoundationGA Release
First kickoff to GA in 7 months
Global FinancialCompany
* DGI: Data Governance Initiative
Faster & SaferCo-Development driven by customer use cases
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Apache Atlas: Metadata Services
• Cross- component dataset lineage. Centralized location for all metadata inside HDP
• Single Interface point for Metadata Exchange with platforms outside of HDP
• Business Taxonomy based classification. Conceptual, Logical And Technical
Apache Atlas
Hiv
e
Ran
ger
Falc
on
Sqoo
p
Stor
m
Kaf
ka
Spar
k
NiF
i
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Big Data Management Through Metadata
Management ScalabilityMany traditional tools and patterns do not scale when applied to multi-tenant data lakes. Many enterprise have silo’d data and metadata stores that collide in the data lake. This is compounded by the ability to have very large windows (years). Can traditional EDW tools manage 100 million entities effectively with room to grow ?
Metadata Tools
Scalable, decoupled, de-centralized manage driven through metadata is the only via solution. This allows quick integration with automation and other metamodels
Tags for Management, Discovery and Security
Proper metadata is the foundation for business taxonomy, stewardship, attribute based security and self-service.
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Apache Atlas High Level Architecture
Type System
Repository
Search DSL
Brid
ge
Hive Storm
Falcon Others
REST API
Graph DB
Sear
ch
Kafka
SqoopCo
nnec
tors
Mes
sagi
ng F
ram
ewor
k
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Near Term Roadmap: Summer 2016
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Dynamic Access Policy Driven by metadata
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Business Catalog
Breadcrumbs for taxonomy context path
Contents at taxonomy context
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Hadoop Cross Component Data Lineage
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Sqoop
TeradataConnector
ApacheKafka
Atlas: Tracks Metadata + Lineage in one place
Custom Activity Reporter
MetadataRepository
RDBMS
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Technical and Logical Metadata Exchange
Knowledge Store
AtlasREST API
StructuredUnstructured
Files:XML / JSON
3rd Party Vendors
CustomReporter
Non-Hadoop
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Hive Integration: Model for integration
Apache Atlas
Hive Bridge(Client)
Hive Hook(Post-execution)
REST API
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HDF: Dataflow Governance Solution
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Dataflow Security Use case Requirements
Accelerated Data Collection: An integrated, data source agnostic collection platform
Increased Security and Unprecedented Chain of Custody: Secure from source to storage with high fidelity data provenance
The Internet of Any Thing (IoAT): A Proven Platform for the Internet of Things
http://hortonworks.com/hdf/
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Enterprise Grade Governance Dataflow Solution
Filtered Metadata
• HDP Taxonomy• Centrallized
Metadata Repository
• Downstream HDP Impacts
• Cross component lineage
• 3rd Party integration
• Guaranteed Delivery
• Data Buffering• Prioritized
Queueing• Flow specific QoS• Visual Command
& ControlMonthsLineage
YearsLineage
ReferenceTaxonomy
(Tags)
Event level versus Dataset
level
HDF - NiFI
Operation Control
MaximumFidelity
Event Level
HDP – Atlas
GovernanceManagement
Medium / LowFidelity
Dataset Level
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Demo
• Tutorial• Atlas Tour• Sqoop Lineage• Kafka / Storm Linage
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Availability: - Tech Preview VMs: May 2016 - GA Release: Summer 2016
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Questions ?
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Reference
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Online Resources
VM: https://s3.amazonaws.com/demo-drops.hortonworks.com/HDP-Atlas-Ranger-TP.ova —> Download Public Preview VM
Tutorial: https://github.com/hortonworks/tutorials/tree/atlas-ranger-tp/tutorials/hortonworks/atlas-ranger-preview
Blog: http://hwxjojo.wpengine.com/blog/the-next-generation-of-hadoop-based-security-data-governance/ (this is giving an error, right now)
Learn More: http://hortonworks.com/solutions/atlas-ranger-integration/
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Thank You