Big Data Analytics on Object Stores: A Performance Study
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چکیده
Object stores provide a highly scalable and cheap storage solution due to their key-value store semantics and commodity-hardware based deployment. This makes them an attractive option for archiving large amounts of data that are produced in science and industry. To analyze that data, advanced analytics such as MapReduce can be used. However, copying the data from the object store into the distributed file system that the analytics system requires is complex and time-intensive. Hence, running analytics directly on object stores greatly improves usability and performance. In this work, we study this combination and identify common problems.
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تاریخ انتشار 2014