GDL

Efficiently Querying the Indexed Compressed XML Data (IQX)

ISSN : 0975-5705
Journal from gdlhub / 2017-08-14 11:52:33
Oleh : Radha Senthilkumar and Kannan Arputharaj, International Journal of Database Management Systems
Dibuat : 2012-06-26, dengan 1 file

Keyword : XML, XPath, Indexing, Query processing.
Subjek : Efficiently Querying the Indexed Compressed XML Data (IQX)
Url : http://airccse.org/journal/ijdms/papers/3311ijdms12.pdf
Sumber pengambilan dokumen : Internet

Extensible Mark-up Language was designed to carry data which provides a platform to define own tags.


XML documents are immense in nature. As a result there has been an ever growing need for developing an


efficient storage structure and high-performance techniques to query efficiently. QUICX (Query and


Update Support for Indexed and Compressed XML) is the compact storage structure which gives highest


compression ratio than many of the queriable compressors available today. The data are compressed using


LZW approach, and stored compactly. Indexing is done for the data stored in the containers, there by


further increasing the compression ratio. These also reduce the time for querying the storage structure.


Index files are created only for highly redundant files which is larger in size. IQCX support simple,


aggregate, conditional, compound, nested and correlation predicate queries. All queries except simple


query use the index files. The reduced execution time proves the efficiency of the indexing technique.

Deskripsi Alternatif :

Extensible Mark-up Language was designed to carry data which provides a platform to define own tags.


XML documents are immense in nature. As a result there has been an ever growing need for developing an


efficient storage structure and high-performance techniques to query efficiently. QUICX (Query and


Update Support for Indexed and Compressed XML) is the compact storage structure which gives highest


compression ratio than many of the queriable compressors available today. The data are compressed using


LZW approach, and stored compactly. Indexing is done for the data stored in the containers, there by


further increasing the compression ratio. These also reduce the time for querying the storage structure.


Index files are created only for highly redundant files which is larger in size. IQCX support simple,


aggregate, conditional, compound, nested and correlation predicate queries. All queries except simple


query use the index files. The reduced execution time proves the efficiency of the indexing technique.

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