The CDF experiment started data taking in April 2001,The data are organized into datasets which contain events of similar physics properties and reconstruction version.the information about datasets is stored in the D...The CDF experiment started data taking in April 2001,The data are organized into datasets which contain events of similar physics properties and reconstruction version.the information about datasets is stored in the Data File Catalog,a relational database.This information is presented to the data processing framework as objects which are retrieved using compound keys.The objects and the keys are designed to be the algorithms' view of information stored in the database.Objects may use several DB tables.A database interface management layer exists for the purpose of managing the mapping of persistent data to transient objects that can be used by the framework.This layer exists between the algorithm code and the code which reads directly from datanbase tables.At the user end,it places get/put interface on a top of a transient class for retrieval or storage of objects of this class using a key.Data File Catalog code makes use of this facility and contains all the code needed to manipulate CDF Data File Catalog from a C++ program or from the command prompt,It supports an Oracle interface using OTL,and a mSQL interface,This code and the Oravcle implementation of Data File Catalog were subjected to test during CDF Commissioning Run last fall and during first weeks of Run II in April.It performed exceptionally well.展开更多
To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this ...To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this approach utilizes the consistency among the data on the disk. A feature pattern library is established based on different types of fries according to the internal constructions of text. Data on sectors will be classified automatically by data clustering and evaluating. When the conflict happens on data classification, the digestion will be initiated by adopting context pattern. Based on this approach, the paper achieved the data recovery system aiming at pattern matching of txt, word and PDF fries. Raw and formatting recovery tests proved that the system works well.展开更多
文摘The CDF experiment started data taking in April 2001,The data are organized into datasets which contain events of similar physics properties and reconstruction version.the information about datasets is stored in the Data File Catalog,a relational database.This information is presented to the data processing framework as objects which are retrieved using compound keys.The objects and the keys are designed to be the algorithms' view of information stored in the database.Objects may use several DB tables.A database interface management layer exists for the purpose of managing the mapping of persistent data to transient objects that can be used by the framework.This layer exists between the algorithm code and the code which reads directly from datanbase tables.At the user end,it places get/put interface on a top of a transient class for retrieval or storage of objects of this class using a key.Data File Catalog code makes use of this facility and contains all the code needed to manipulate CDF Data File Catalog from a C++ program or from the command prompt,It supports an Oracle interface using OTL,and a mSQL interface,This code and the Oravcle implementation of Data File Catalog were subjected to test during CDF Commissioning Run last fall and during first weeks of Run II in April.It performed exceptionally well.
文摘To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this approach utilizes the consistency among the data on the disk. A feature pattern library is established based on different types of fries according to the internal constructions of text. Data on sectors will be classified automatically by data clustering and evaluating. When the conflict happens on data classification, the digestion will be initiated by adopting context pattern. Based on this approach, the paper achieved the data recovery system aiming at pattern matching of txt, word and PDF fries. Raw and formatting recovery tests proved that the system works well.
