'''Originally Posted By: avinash anantharamu'''

Practice Final Solutions ,Post your answers here

'''Originally Posted By: avinash anantharamu'''

Distinguish intra-query and inter-query parallelism as far as information retrieval. <br><br>What bottlenecks exists to intra-query parallelism if partition-by-document is used.<br><br>[] Document partitioning works best when the index data on the individual nodes can be stored in main memory or on SSD.<br>[]To see what happens when data is stored on disk, suppose queries were on average 3 words and we want the search engine to handle 100 queries per second.<br>[]Due to queueing effects, we cannot achieve a utilization of more than 50% typically, without experiencing latency jumps.<br>[]So a query load of 100qps translates to a require service rate of at least 200 qps. For 3 word queries, this translates to at least 600 random access operations per second.<br>[]Assuming an average disk latency of 10ms, a single hard disk drive cannot perform more than 100 random access operations per second, one sixth of what we need on each of our nodes.<br>[]Adding more machines doesn't affect the minimum of what each machine must do, so this is a bottleneck for the document partitioning approach.<br>[]Term partitioning addresses this problem by splitting the collection into sets of terms and assigning nodes to each of these sets.<br>[]This resolves the problem above because, each node won't be responsible for handling every query.<br><br>Team Members<br>[]Avinash Anantharamu<br>[]Chetan Sharma<br>[*]Lok Kei Leong