Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Suppose a long-running analytical query is executing on a database server and has been allocated a large amount of physical memory. A high-priority task comes in and  need to run it immediately with all available resources.  have several choices.  could swap out the old query to disk, but writing out a large execution state may take too much time. Another option is to terminate the old query and restart it after the new task completes, but  would waste all the work already performed by the old query. Yet another alternative is to periodically checkpoint the query during execution, but traditional synchronous checkpointing carries high overhead. ,  advocate a database-centric approach to implementing query suspension and resumption, with negligible execution overhead, bounded suspension cost, and efficient resumption. The basic idea is to let each physical query operator perform lightight checkpointing according to its own semantics, and coordinate asynchronous checkpoints among operators through a novel contracting mechanism. At the time of suspension,  find an optimized suspend plan for the query, which may involve a combination of dumping current state to disk and going back to previous checkpoints. The plan seeks to minimize the suspend/resume overhead while observing the constraint on suspension time. Our approach requires only small changes to the iterator interface, which  have implemented in the PREDATOR database system. Experiments with our implementation demonstrate significant advantages of our approach over traditional alternatives.
['Badrish Chandramouli', 'Christopher N. Bond', 'Shivnath Babu', 'Jun Yang']
I am writing a research paper on a idea Query suspend and resume
[{"from": "human", "value": "I am writing a research paper on a idea Query suspend and resume"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Suppose a long-running analytical query is executing on a database server and has been allocated a large amount of physical memory. A high-priority task comes in and  need to run it immediately with all available resources.  have several choices.  could swap out the old query to disk, but writing out a large execution state may take too much time. Another option is to terminate the old query and restart it after the new task completes, but  would waste all the work already performed by the old query. Yet another alternative is to periodically checkpoint the query during execution, but traditional synchronous checkpointing carries high overhead. ,  advocate a database-centric approach to implementing query suspension and resumption, with negligible execution overhead, bounded suspension cost, and efficient resumption. The basic idea is to let each physical query operator perform lightight checkpointing according to its own semantics, and coordinate asynchronous checkpoints among operators through a novel contracting mechanism. At the time of suspension,  find an optimized suspend plan for the query, which may involve a combination of dumping current state to disk and going back to previous checkpoints. The plan seeks to minimize the suspend/resume overhead while observing the constraint on suspension time. Our approach requires only small changes to the iterator interface, which  have implemented in the PREDATOR database system. Experiments with our implementation demonstrate significant advantages of our approach over traditional alternatives."}]