Comparative Study Parallel Join Algorithms for MapReduce environment
There are the following techniques that are used to analyze massive amounts of data: MapReduce paradigm, parallel DBMSs, column-wise store, and various combinations of these approaches. We focus in a MapReduce environment. Unfortunately, join algorithms is not directly supported in MapReduce. The ai...
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| Format: | Article |
| Language: | English |
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Ivannikov Institute for System Programming of the Russian Academy of Sciences
2018-10-01
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| Series: | Труды Института системного программирования РАН |
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| Online Access: | https://ispranproceedings.elpub.ru/jour/article/view/986 |
| _version_ | 1818566490634321920 |
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| author | A. Yu. Pigul |
| author_facet | A. Yu. Pigul |
| author_sort | A. Yu. Pigul |
| collection | DOAJ |
| description | There are the following techniques that are used to analyze massive amounts of data: MapReduce paradigm, parallel DBMSs, column-wise store, and various combinations of these approaches. We focus in a MapReduce environment. Unfortunately, join algorithms is not directly supported in MapReduce. The aim of this work is to generalize and compare existing equi-join algorithms with some optimization techniques. |
| first_indexed | 2024-12-14T01:54:21Z |
| format | Article |
| id | doaj.art-ca6fcc80dd134d6fbd69bfe3fcf43701 |
| institution | Directory Open Access Journal |
| issn | 2079-8156 2220-6426 |
| language | English |
| last_indexed | 2024-12-14T01:54:21Z |
| publishDate | 2018-10-01 |
| publisher | Ivannikov Institute for System Programming of the Russian Academy of Sciences |
| record_format | Article |
| series | Труды Института системного программирования РАН |
| spelling | doaj.art-ca6fcc80dd134d6fbd69bfe3fcf437012022-12-21T23:21:16ZengIvannikov Institute for System Programming of the Russian Academy of SciencesТруды Института системного программирования РАН2079-81562220-64262018-10-0123010.15514/ISPRAS-2012-23-17986Comparative Study Parallel Join Algorithms for MapReduce environmentA. Yu. Pigul0Санкт-Петербургский государственный университетThere are the following techniques that are used to analyze massive amounts of data: MapReduce paradigm, parallel DBMSs, column-wise store, and various combinations of these approaches. We focus in a MapReduce environment. Unfortunately, join algorithms is not directly supported in MapReduce. The aim of this work is to generalize and compare existing equi-join algorithms with some optimization techniques.https://ispranproceedings.elpub.ru/jour/article/view/986параллельные алгоритмы соединения, mapreduce, оптимизация |
| spellingShingle | A. Yu. Pigul Comparative Study Parallel Join Algorithms for MapReduce environment Труды Института системного программирования РАН параллельные алгоритмы соединения, mapreduce, оптимизация |
| title | Comparative Study Parallel Join Algorithms for MapReduce environment |
| title_full | Comparative Study Parallel Join Algorithms for MapReduce environment |
| title_fullStr | Comparative Study Parallel Join Algorithms for MapReduce environment |
| title_full_unstemmed | Comparative Study Parallel Join Algorithms for MapReduce environment |
| title_short | Comparative Study Parallel Join Algorithms for MapReduce environment |
| title_sort | comparative study parallel join algorithms for mapreduce environment |
| topic | параллельные алгоритмы соединения, mapreduce, оптимизация |
| url | https://ispranproceedings.elpub.ru/jour/article/view/986 |
| work_keys_str_mv | AT ayupigul comparativestudyparalleljoinalgorithmsformapreduceenvironment |