An Efficient Advanced SQL-to-MapReduce Translator to Improve Big Data - Fawzya Ramadan
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Toimitus 12-18 arkipäivässä
30 päivän palautusoikeus
MapReduce has become an effective framework for processing and analysing huge data size in large systems. On the other hand, SQL Query is necessary to build an efficient and flexible SQL translator to MapReduce framework. The need of optimized SQL translator that can deal with advanced queries is very necessary, which can increase the performance of data analysis with growing of BigBig Data DataData. Hive s ... Täydellinen kuvaus
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Kuvaus
MapReduce has become an effective framework for processing and analysing huge data size in large systems. On the other hand, SQL Query is necessary to build an efficient and flexible SQL translator to MapReduce framework. The need of optimized SQL translator that can deal with advanced queries is very necessary, which can increase the performance of data analysis with growing of BigBig Data DataData. Hive supports queries which called HiveQL. HiveQL offers the same features as SQL, which still difficult to deal with complex SQL queries. Consequently, manual translation of HiveQL often leads to poor performance.Also, Flink has become an effective framework to Big Data analysis in large cluster systems. On the other hand, FLink doesn¿t support any Query language. So, the designing and implementing SQL to FLink Translator is needed to execute SQL Query over FLink. The work in this book adopts these limitations of SQL translators and proposes two contributions which considered as SQL¿to-MapReduce translators to improve Big Data analysis.
Lisätietoja
| Kirjoittaja | Fawzya Ramadan |
|---|---|
| Julkaisija | LAP LAMBERT Academic Publishing |
| Julkaisuvuosi | 2016 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783659927775 |