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Data-intensive applications are increasingly designed to execute on large computing clusters. Our previous observation on Tencent production systems has indicated that join query is one of the most important queries in large-scale data processing. When running a join query on Hive system, the job of the join query is divided into map phase and reduce phase, and requires transferring large amounts...
As organizations start to use data intensive cluster computing systems like Hadoop MapReduce to handle large-scale data, scheduling of jobs become very important in order to achieve efficiency. In the default implementations of Hadoop MapReduce, jobs are scheduled in FIFO order. It easily causes the starvation of small jobs in the event of resources being utilized by large jobs, while Fair Scheduler...
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