As HBase and Hadoop continue to become routine across enterprises, these enterprises inevitably shift priorities from effective deployments to cost-efficient operations. Consolidation of infrastructure, the sum of hardware, software, and system-administrator effort, is the most common strategy to reduce costs. As a company grows, the number of business organizations, development teams, and individuals accessing HBase grows commensurately, creating a not-so-simple requirement: HBase must effectively service many users, each with a variety of use-cases. This is problem is known as multi-tenancy. While multi-tenancy isn’t a new problem, it also isn’t a solved one, in HBase or otherwise. This talk will present a high-level view of the common issues organizations face when multiple users and teams share a single HBase instance and how certain HBase features were designed specifically to mitigate the issues created by the sharing of finite resources.

1. Democratizing HBase
Josh Elser
HBaseCon West
June 2017

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Engineer at Hortonworks, Member of the Apache Software Foundation
Various roles and involvement in…
Top-Level Projects
• Accumulo
• Calcite
• HBase
• Phoenix
ASF Incubator
• Fluo
• Gossip
• Rya
• Slider
These Apache project names are trademarks or registered
trademarks of the Apache Software Foundation.

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Scope
Apps
Middleware
HBase
HDFS
Hypervisor
Linux
Hardware

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A Retrospective on Adoption
Proof of Concept
Single Org Sim-Prod
Multi-Org Transition
Single Org Transition
Multi-Org Sim-Prod
Company-Wide Shift
1 User
2+ Users

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Optimal Utilization
à Tight Budgets
à Expensive Hardware Acquisition
à Easily Accessible to Clients
Bad BadGood

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Multi-tenancy
à Out of many workloads, one system.
• Low Latency (ms)
• Always Up
• Guarantees of Multiple 9’s
• High Latency (min-hr)
• Scheduled/Regular
• High Throughput

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Our Goals
à User isolation
à Sharing of resources
à Flexibility in resource partitioning
à Willful developer ignorance
Image: Me, South Philadelphia Graffiti

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Security side-step
à Strong authentication
à No unauthenticated users
ÃNo impersonation

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Execution Throttles
User-Driven Tasks
à RPC Quotas
à RPC Priorities
à Space Quotas
HBase Internals
à MemStore Flushes
à Compactions
Image: 3DOM Graffiti

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Workload Partitioning
à RegionServer Groups
– Benefits workload per table
à Anti-pattern with present value
à Beware external systems
à Signal for required improvements
Image: Me, South Philadelphia Graffiti

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Insight and Metrics
à Categorize system metrics
à Validate configured limits
à Understand HBase/HDFS limitations
à Verify application use
Image: Me, South Philadelphia Graffiti

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Takeaways
à Quantify application needs
à Calculate system ability
à Meet needs with throttling and partitioning
à Understand non-HBase/HDFS processes
à Monitor, Interpret, Act

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Thanks!
Email: elserj@apache.org
Twitter: @joshelser