Towards Economic Fairness for Big Data Processing in Pay-as-you-go Cloud Computing Nanyang Technological University Shanjiang Tang, Bu-Sung Lee, Bingsheng He School of Computer Engineering Nanyang Technological University 5/12/2015

Pay-as-You-Go Cloud Computing is Pervasive and Popular Charge users based on the amount of resources used over time (e.g., Hourly). Advantages – Elasticity – Flexibility – Cost efficiency Big data processing on the cloud – E.g., product recommendation, user’s behavior analysis, log analysis – Processing Frameworks: MapReduce, Spark. 2Nanyang Technological University5/12/2015

Twitter’s Cluster One week data from Twitter production cluster [Delimitrou et. Al. ASPLOS’14] Resource Utilization = User resource demands are heterogeneous. – Users have different demands. – A user’s demand is changing over time.  Static provisioning/partitioning causes underutilization. Resource utilization is a critical problem in such pay-as-you-use environments. – Providers waste resources (  waste investment and lose profit). – Users waste money. 3Nanyang Technological University5/12/2015

Resource Sharing can improve resource utilization. – Allow underloaded users to release resources to other users. – Allow overloaded users to temporarily use more resources (from others).  Reduce the idle resources at runtime. What about fairness? – If the fairness is not solved, resource sharing is unlikely to achieve in pay-as-you-use environments. To Share or Not To Share? 4Nanyang Technological University5/12/2015

Pay-as-you-go Fairness: Resource-as-you-pay The total resources a user gained should be proportional to her payment. This is a Service-Level Agreement (SLA). 60 $ 40 $ A: B: 60% 40% Resource Service A A B B Resource Service = Resources-per-time X service time 5Nanyang Technological University5/12/2015

Fair Policy in Existing Systems State-of-the-art: Max-min fairness – Select the user with the minimum allocation/share ratio every time. – Consider the present requirement only (memoryless). Memoryless fairness has severe problems in pay-as-you-use environments, violating the following properties: – Resource-as-you-pay fairness guarantee. – Cost-efficient workload incentive. (Users should be better not to submit dirty workload) – Truthfulness (Users should not get benefits by cheating). 6Nanyang Technological University5/12/2015

Problems with MemoryLess Fairness Resource-as-you-pay Fairness Problem – E.g., A, B equally pay for total resource of 100 units. Time New Demand AB t A A B B Accumulate Resource Usage: Accumulate Resource Usage: Unsatisfied Demand A A B B Current Allocation at t1: Nanyang Technological University5/12/2015

Problems with MemoryLess Fairness Resource-as-you-pay Fairness Problem – E.g., A, B equally pay for total resource of 100 units. Time New Demand AB t t A A B B Accumulate Resource Usage: Accumulate Resource Usage: A A B B Unsatisfied Demand Current Allocation at t2: Nanyang Technological University5/12/2015

Problems with MemoryLess Fairness Resource-as-you-pay Fairness Problem – E.g., A, B equally pay for total resource of 100 units. Time New Demand AB t t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Current Allocation at t3: Nanyang Technological University5/12/2015

Problems with MemoryLess Fairness Resource-as-you-pay Fairness Problem – E.g., A, B equally pay for total resource of 100 units. Time New Demand AB t t t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Existing Fair Policy fails to satisfy Resource-as-you-pay fairness!!! 10 Current Allocation at t4: Nanyang Technological University5/12/2015

Other Problems for MemoryLess Fairness Cost-inefficient workload incentive Problem – Selfish users might possess unneeded resources by submitting dirty workloads. Untruthfulness Problem – Cheating users can get benefit under memoryless policy. 11Nanyang Technological University5/12/2015 Proof sketches are in the paper.

Our Work Challenges: can we find a fair sharing policy that satisfies the following properties? – Resource-as-you-pay fairness – Cost-efficient workload incentives – Truthfulness Our Solution: Long-Term Resource Fairness – Ensure resource fairness over a period of time. – With historical information considered. 12Nanyang Technological University5/12/2015

Long-Term Resource Fairness Basic Concept: Loan agreement (Lending w/o interests) – When resources are not needed, users can lend the resources to others. – When more resources are needed, others should give back.  Benefit others and user herself. 13Nanyang Technological University5/12/2015

Long-Term Resource Fairness Satisfy Pay-as-you-use Fairness Time New Demand AB t A A B B Accumulated resource usage: Unsatisfied Demand A A B B Current Allocation at t1: A A B B Lend Resources: Nanyang Technological University5/12/2015

Long-Term Resource Fairness Satisfy Pay-as-you-use Fairness Time New Demand AB t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Current Allocation at t2: A A B B Lend Resources: Nanyang Technological University5/12/2015

Long-Term Resource Fairness Satisfy Pay-as-you-use Fairness Time New Demand AB t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Current Allocation at t2: A A B B Lend Resources: t Nanyang Technological University5/12/2015

Long-Term Resource Fairness Satisfy Pay-as-you-use Fairness Time New Demand AB t t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Current Allocation at t3: A A B B Lend Resources: Nanyang Technological University5/12/2015

Long-Term Resource Fairness Satisfy Pay-as-you-use Fairness Time New Demand AB t t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Current Allocation at t3: A A B B Lend Resources: t Nanyang Technological University5/12/2015

Long-Term Resource Fairness Satisfy Pay-as-you-use Fairness Time New Demand AB t t t t A A B B Accumulated resource usage: A A B B Unsatisfied Demand Long-Term Resource Fairness satisfy Resource-as-you-pay fairness. 19 Current Allocation at t4: A A B B Lend Resources: Nanyang Technological University5/12/2015

Properties of Long-Term Resource Fairness Satisfy resource-as-you-pay fairness Satisfy cost-efficient workload incentives – Running dirty/cost-inefficient workload can waste money. Users cannot get benefits by lying (strategy- proof). – A robust policy should avoid cheating users get benefit. Otherwise, nobody is willing to share resources. 20 Proof sketches are in the paper. Nanyang Technological University5/12/2015

LTYARN Implement Long-Term Resource Fairness in YARN – Extend memoryless max-min fairness to long-term max- min fairness. – Add a few components into resource manager Support full long-term and time window-based requirements. Currently support a single resource type (main memory). The experimental Results demonstrates the effectiveness of our approach. 21Nanyang Technological University5/12/2015 Detailed design and experimental results are in the paper.

Future Work Plan Consider Multi-resource fairness – Different types of resources, e.g.,. Move to Heterogeneous pricing plans and instance types – On-demand price plan, reserved price plan – t2.micro, t2.small, t2.medium, and m3.large 22Nanyang Technological University5/12/2015

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