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Migration from RDBMS to Column-Oriented NoSQL: Lessons Learned and Open Problems

机译:从RDBMS迁移到面向列的NoSQL:经验教训和打开问题

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Migration from RDBMS to NoSQL has become an important topic in a big data era. This paper provides a comprehensive study on important issues in the migration from RDBMS to NoSQL. We discuss the challenges faced in translating SQL queries; the effect of denormalization, secondary indexes, and join algorithms; and open problems. We focus on a column-oriented NoSQL, HBase, because it is widely used by many Internet enterprises such as Facebook, Twitter, and LinkedIn. Because HBase does not support SQL, we use Apache Phoenix as an SQL layer on top of HBase. Experimental results using TPC-H show that column-level denormalization with atomicity significandy improves query performance, the use of secondary indexes on foreign keys is not as effective as in RDBMSs, and the query optimizer of Phoenix is not very sophisticated. Important open problems are supporting complex SQL queries, automatic index selection, and optimizing SQL queries for NoSQL.
机译:从RDBMS迁移到NoSQL已成为大数据时代的重要主题。本文对从RDBMS迁移到NoSQL的重要问题进行了全面的研究。我们讨论翻译SQL查询时面临的挑战;二制化,二次指标和加入算法的影响;和打开问题。我们专注于面向列的NoSQL,HBase,因为它被许多互联网企业(如Facebook,Twitter和LinkedIn)广泛使用。因为HBase不支持SQL,所以我们在HBase顶部使用Apache Phoenix作为SQL图层。使用TPC-H的实验结果表明,具有原子性的列级非正规化提高了查询性能,外键对外键的二级索引并不像RDBMSS中那样有效,并且凤凰的查询优化器不是很复杂的。重要的打开问题正在支持复杂的SQL查询,自动索引选择和NoSQL的SQL查询。

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