K. Ross and K. Zaman. Optimizing selections over datacubes. In Proceedings of the IEEE International Conference on Scientic and 127 Statistical Database Management, Berlin, July 2000. IEEE Computer Society. Home/Search Document Details and Download
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Bottom-Up Computation of Sparse and Iceberg CUBEs - Beyer, Ramakrishnan (1999) (77 citations) (Correct)
....the best existing algorithm for the CUBE problems discussed in this paper (sparse CUBEs and Iceberg CUBEs) Therefore, we only compare BUC to this algorithm. In recent independent work, researchers at Columbia University also found that pushing the HAVING clause into CUBE computation is beneficial [15]. They describe how to take advantage of HAVING predicates in PartitionedCube MemoryCube. Procedure BottomUpCube(input, dim) Inputs: input: The relation to aggregate. dim: The starting dimension for this iteration. Globals: constant numDims: The total number of dimensions. constant ....
K. A. Ross and K. A. Zaman. Optimizing selections over data cubes. Technical Report CUCS-018-98, Columbia University, Nov 1998. http://www.cs.- columbia.edu/ library/1998.html.
Computing and Querying Datacubes - Zaman Self-citation (Zaman) (Correct)
....in the following chapter. We present a performance study using synthetic and realworld data sets. Our results indicate substantial performance improvements for queries with selective conditions. These techniques are described in detail in Chapter 3 of this thesis. This work has been published as [RZ00a] 12 1.7 Serving Datacube Tuples from Main Memory For large datasets with many dimensions, the complete datacube may be very large. In order to support on line access to datacube results, one would like to perform some precomputation to enhance query performance. Existing schemes materialize ....
K. Ross and K. Zaman. Optimizing selections over datacubes. In Proceedings of the IEEE International Conference on Scientic and 127 Statistical Database Management, Berlin, July 2000. IEEE Computer Society.
Computing and Querying Datacubes - Zaman Self-citation (Zaman) (Correct)
....a path have been computed, we can carry out the sorting and the subsequent compression step. If no 1 cuboids are being computed on a path, we can use the default of sorting tuples immediately. In a similar fashion to 1 Specialization we can de ne n Specialization which is described in detail in [RZ98] The basic idea is to specialize on n cuboids for larger values of n. We believe that this optimization is not as useful as 1 Specialization which is why we do not discuss it here. 3.3.3 Generating Paths for Memory Cube In Memory Cube we generate a set of paths which cover the search lattice ....
....to exactly one slot, so we traverse just one list on an update. In general, we may need to check 2 d slots in the level 1 store for all possible tuples that might need to be updated. For a count based distribution, however, if a tuple t is materialized in the level 1 store, any generalization [RZ98] the tuple formed by replacing one or more attribute values by ALL s) of the tuple has at least as high a count and more ALL attributes, and so must also be present in the level 1 store. When a tuple t is added, the rst tuple we update is the tuple with ALL in every attribute position. We then ....
K. Ross and K. Zaman. Optimizing selections over data cubes. Technical Report CUCS-011-98, Department of Computer Science, Columbia University, USA, December 1998.
Optimizing Selections over Datacubes - Ross, Zaman (1998) (1 citation) Self-citation (Ross Zaman) (Correct)
....a path have been computed, we can carry out the sorting and the subsequent compression step. If no 1 cuboids are being computed on a path, we can use the default of sorting tuples immediately. In a similar fashion to 1 Specialization we can define n Specialization which is described in detail in [16]. The basic idea is to specialize on n cuboids for larger values of n. We believe that this optimization is not as useful as 1Specialization which is why we do not discuss it here. 3.3 Generating Paths for Memory Cube In Memory Cube we generate a set of paths which cover the search lattice and ....
....datacube algorithm of Ross and Srivastava. We present a performance study using synthetic and real world data sets. Our results indicate substantial performance improvements for queries with selective conditions. Extensions of our optimizations for range queries and hierarchies are discussed in [16]. Other algorithms for computation of the datacube are described in [1] Work on reasoning with aggregation constraints is described in [10, 12] The idea of moving predicates for query optimization has been investigated in [11] The monotonic properties of aggregations has been studied in [13] ....
K. Ross and K. Zaman. Optimizing selections over data cubes. Technical Report CUCS-011-98, Department of Computer Science, Columbia University, 1998.
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