Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Any highly available data warehouse will use some form of data replication to tolerate machine failures. ,  demonstrate that  can leverage this data redundancy to build an integrated approach to recovery and high availability. Our approach, called HARBOR, revives a crashed site by querying remote, online sites for missing updates and uses timestamps to determine which tuples need to be copied or updated. HARBOR does not require a stable log, recovers without quiescing the system, allows replicated data to be stored non-identically, and is simpler than a log-based recovery algorithm. compare the runtime overhead and recovery performance of HARBOR to those of two-phase commit and ARIES, the gold standard for log-based recovery, on a three-node distributed database system. Our experiments demonstrate that HARBOR suffers lor runtime overhead, has recovery performance comparable to ARIES's, and can tolerate the fault of a worker and efficiently bring it back online.
['Edmond Lau', 'Samuel Madden']
I am writing a research paper on a idea An integrated approach to recovery and high availability in an updatable, distributed data warehouse
[{"from": "human", "value": "I am writing a research paper on a idea An integrated approach to recovery and high availability in an updatable, distributed data warehouse"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Any highly available data warehouse will use some form of data replication to tolerate machine failures. ,  demonstrate that  can leverage this data redundancy to build an integrated approach to recovery and high availability. Our approach, called HARBOR, revives a crashed site by querying remote, online sites for missing updates and uses timestamps to determine which tuples need to be copied or updated. HARBOR does not require a stable log, recovers without quiescing the system, allows replicated data to be stored non-identically, and is simpler than a log-based recovery algorithm. compare the runtime overhead and recovery performance of HARBOR to those of two-phase commit and ARIES, the gold standard for log-based recovery, on a three-node distributed database system. Our experiments demonstrate that HARBOR suffers lor runtime overhead, has recovery performance comparable to ARIES's, and can tolerate the fault of a worker and efficiently bring it back online."}]