http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-112582042-A

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filingDate 2020-11-13-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_adc59aad682c2e16812e1027680c7c25
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publicationDate 2021-03-30-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-112582042-A
titleOfInvention Method and system for synchronously detecting times of infected multi-drug-resistant bacteria cases based on MapReduce and big data management
abstract The utility model provides a method and a system for synchronously detecting the times of infected multi-drug resistant bacteria cases based on MapReduce and big data management, which divides the times of millions and millions of inpatients which exceed the memory and storage limit of a server into tens of millions and hundreds of millions of small tasks based on the MapReduce framework and by utilizing the parallel computing capability of machines under a distributed system, simultaneously executes the small tasks on a plurality of machines, and generates a final result by summarizing the intermediate output results of the small tasks. The invention can carry out massive parallel calculation on the big data of million-level, million-level and hundred million-level inpatient times according to various calibers such as provincial and urban areas, hospital levels, hospital beds, comprehensive and special departments, public standings, civil camps and the like, manages the infection related to multiple drug-resistant bacteria of all categories, realizes the accurate statistics of the times of cases of the multiple drug-resistant bacteria infected by hospitals, carries out the integral evaluation on the hospital infection, and realizes the integral prevention, control and management on the multiple drug-resistant bacteria infected by hospitals.
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