through this study, we propose two algorithms. The first algorithm describes the concept of compression of domains at attribute level and we call it as 201C;Attribute Domain Compression201D;. This algorithm can be implemented on both row and columnar databases. The idea behind the algorithm is to reduce the size of large databases as to store them optimally. The second algorithm is also applicable for both concepts of databases but will optimally work for columnar databases. The idea behind the algorithm is to generalize the tuple domains by giving it a value say (n) such that all other n-1 tuples or at least maximum can be identified
A pattern database (PDB) is a heuristic function implemented as a lookup table that stores the lengt...
Compression can sometimes improve performance by making more of the data available to the processors...
We formulate a conceptual model for white-box compression, which represents the logical columns in t...
Domain encoding is a common technique to compress the columns of a column store and to accelerate ma...
Columnar databases have dominated the data analysis market for their superior performance in query p...
Column-oriented database system architectures invite a reevaluation of how and when data in database...
Column oriented database have continued to grow over the past few decades. C-Store, Vertica Monet DB...
A compression technique is presented that allows a high degree of compression but requires only loga...
Data compression is one way to gain better performance from a database. Compression is typically ach...
The multidimensional databases often use compression techniques in order to decrease the size of the...
One common pattern database compression technique is to merge adjacent database entries and store th...
In modern column-oriented databases, compression is important for improving I/O throughput and overa...
Loss-less data compression is attractive in database systems as it may facilitate query performance ...
Column oriented databases store columns contiguously on disk. The adjacency of values from the same ...
One of the big challenges in the world was the amount of data being stored, especially in Data Wareh...
A pattern database (PDB) is a heuristic function implemented as a lookup table that stores the lengt...
Compression can sometimes improve performance by making more of the data available to the processors...
We formulate a conceptual model for white-box compression, which represents the logical columns in t...
Domain encoding is a common technique to compress the columns of a column store and to accelerate ma...
Columnar databases have dominated the data analysis market for their superior performance in query p...
Column-oriented database system architectures invite a reevaluation of how and when data in database...
Column oriented database have continued to grow over the past few decades. C-Store, Vertica Monet DB...
A compression technique is presented that allows a high degree of compression but requires only loga...
Data compression is one way to gain better performance from a database. Compression is typically ach...
The multidimensional databases often use compression techniques in order to decrease the size of the...
One common pattern database compression technique is to merge adjacent database entries and store th...
In modern column-oriented databases, compression is important for improving I/O throughput and overa...
Loss-less data compression is attractive in database systems as it may facilitate query performance ...
Column oriented databases store columns contiguously on disk. The adjacency of values from the same ...
One of the big challenges in the world was the amount of data being stored, especially in Data Wareh...
A pattern database (PDB) is a heuristic function implemented as a lookup table that stores the lengt...
Compression can sometimes improve performance by making more of the data available to the processors...
We formulate a conceptual model for white-box compression, which represents the logical columns in t...