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Azure MapReduce

Agenda. Recap of Azure Cloud ServicesRecap of MapReduceAzure MapReduce ArchitecturePairwise distance alignment implementationNext steps. Cloud Computing. On demand computational services over webBacked by massive commercial infrastructures giving economies of scaleSpiky compute needs of the sc

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Azure MapReduce

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    1. Azure MapReduce Thilina Gunarathne Salsa group, Indiana University

    2. Agenda Recap of Azure Cloud Services Recap of MapReduce Azure MapReduce Architecture Pairwise distance alignment implementation Next steps AzureMapReduce is a distributed decentralized MapReduce runtime for Windows Azure developed using Azure cloud infrastructure services. AzureMapReduce is a distributed decentralized MapReduce runtime for Windows Azure developed using Azure cloud infrastructure services.

    3. Cloud Computing On demand computational services over web Backed by massive commercial infrastructures giving economies of scale Spiky compute needs of the scientists Horizontal scaling with no additional cost Increased throughput Cloud infrastructure services Storage, messaging, tabular storage Cloud oriented services guarantees Virtually unlimited scalability Future seems to be CLOUDY!!! Horizontal scaling increase throughput – 100 hours in 10 nodes == 10 hours in 100 nodes Virtually Unlimited resource availability Horizontal scaling increase throughput – 100 hours in 10 nodes == 10 hours in 100 nodes Virtually Unlimited resource availability

    4. Azure Platform Windows Azure Compute .net platform as a service Worker roles & web roles Azure Storage Blobs Queues Table Development SDK, fabric and storage .net and REST interfaces. Blob containers and blobs.. Page vs block. Queus ? Provides loose synchronization, Any number of messages, one week of persistence, Maximum size 8KB, Visibility timeout Table -> structured storage, tables and entities (set of properties).. .net and REST interfaces. Blob containers and blobs.. Page vs block. Queus ? Provides loose synchronization, Any number of messages, one week of persistence, Maximum size 8KB, Visibility timeout Table -> structured storage, tables and entities (set of properties)..

    5. MapReduce Automatic parallelization & distribution Fault-tolerant Provides status and monitoring tools Clean abstraction for programmers map (in_key, in_value) -> (out_key, intermediate_value) list reduce (out_key, intermediate_value list) -> out_value list

    6. Motivation Currently no parallel programming framework on Azure No MPI, No Dryad Well known, easy to use programming model Cloud nodes are not as reliable as conventional cluster nodes Need for a framework which handles the reliability issues.Need for a framework which handles the reliability issues.

    7. Azure MapReduce Concepts Take advantage of the cloud services Distributed services, Unlimited scalability Backed by industrial strength data centers and technologies Decentralized control Dynamically scale up/down Eventual consistency Large latencies Coarser grained map tasks Global queue based scheduling

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