Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at d...Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at decreasing the time consumed on I/O operations, several improved methods are introduced, including a processing flow based on the boundary growing model, which can reduce the database query operations; a concept of the biggest growing block and its determination which can improve the performance of task partition and resolve data-sparse problem; and a fast bitwise algorithm to compute the index numbers of the neighboring blocks, which is a significant efficiency guarantee. Experiments show that the methods can effectively speed up cross-matching on both sparse datasets and high-density datasets.展开更多
We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions： HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union s...We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions： HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union set of the two different sets. We use the ThreadPool technique to speed up the cross-match. In this way improved accuracy can be obtained on the cross-match. Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs. We give some ideas about solving the many-for-one situation occurred in the cross-match.展开更多
基金Supported by National Natural Science Foundation of China (No.10978016)Natural Science Foundation of Tianjin (No. 08JCZDJC19700)Key Technologies Research and Development Program of Tianjin (No.09ZCKFGX00400)
文摘Astronomical cross-matching is a basic method for aggregating the observational data of different wavelengths. By data aggregation, the properties of astronomical objects can be understood comprehensively. Aiming at decreasing the time consumed on I/O operations, several improved methods are introduced, including a processing flow based on the boundary growing model, which can reduce the database query operations; a concept of the biggest growing block and its determination which can improve the performance of task partition and resolve data-sparse problem; and a fast bitwise algorithm to compute the index numbers of the neighboring blocks, which is a significant efficiency guarantee. Experiments show that the methods can effectively speed up cross-matching on both sparse datasets and high-density datasets.
基金supported by the National Natural Science Foundation of China(Grant Nos.10973021,11078013 and 11233004)
文摘We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions： HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union set of the two different sets. We use the ThreadPool technique to speed up the cross-match. In this way improved accuracy can be obtained on the cross-match. Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs. We give some ideas about solving the many-for-one situation occurred in the cross-match.
