Avicenna came up with a Cosmological argument that Aquinas u…

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Avicennа cаme up with а Cоsmоlоgical argument that Aquinas used 200 years later.

Internet_Scаle_Cоmputing_2c Mаp Reduce   The cоntext fоr this question is the sаme as the previous question. 2. Consider the following implementation of a MapReduce Application. It operates on a cluster of server nodes with the following execution model: Each worker thread executes its assigned map tasks sequentially (one map task at a time) Intermediate data from each map task is stored on the worker's local disk Data transfer occurs for reducers to collect the intermediate data from the mapper tasks  No network cost for accessing data on the same server node Network transfer cost applies only between different server nodes All inter-server-node data transfers can occur in parallel A reduce task begins processing only after receiving all its required intermediate data. Each worker thread executes its assigned reduce tasks sequentially (one reduce task at a time) Specifications of the MapReduce Application to be run: Input data: 100GB split into 100 shards of 1GB each Number of map tasks: 100 (one per shard) Number of reduce tasks: 10 (the desired number of outputs from the Map-Reduce Application) Each map task produces 100MB of intermediate data Each reduce task gets equal of amount of intermediate data from each of the map tasks to process for generating the final output Simplifying assumptions: Ignore local disk I/O time All network paths between server nodes have same bandwidth. Parallel network transfers don't affect each other (no bandwidth contention). All data transfers occur ONLY after ALL the map tasks have completed execution Perfect load balancing (work distributed evenly to all reduce tasks) All server nodes in a given configuration have identical performance Compare two different cluster configurations: Configuration A (High-Performance Server Nodes): 5 server nodes Processing speed: 1 minute per GB (for either map or reduce task) Network transfer speed: 2GB per minute between server nodes Configuration B (Commodity Nodes): 10 server nodes Processing speed: 1.5 minutes per GB (for either map or reduce task) Network transfer speed: 1GB per minute between server nodes   (c) [1 point] Which configuration is faster in this example – configuration A (smaller number of high-performance nodes) or configuration B (larger number of commodity nodes)?