Parallel Indexing of Large Multi-dimensional Data

This paper proposes two methods of indexing a large amount of data in order to resolve the issues about time limitation and size limitation. One is the method that an index is created one by one. When the size of an index reaches the limitation, a new index is created. The other is the method that several indexes are created in advance. Data are inserted into the indexes according to the Round-robin scheme. The performance evaluation experiments show that the proposed one-by-one method provides the best insertion performance and that the proposed methods provide better retrieval performance than the conventional method. In addition, parallel processing to indexes divided by the proposed methods could accelerate the retrieval.