16,581 research outputs found
Pattern tree-based XOLAP rollup operator for XML complex hierarchies
With the rise of XML as a standard for representing business data, XML data
warehousing appears as a suitable solution for decision-support applications.
In this context, it is necessary to allow OLAP analyses on XML data cubes.
Thus, XQuery extensions are needed. To define a formal framework and allow
much-needed performance optimizations on analytical queries expressed in
XQuery, defining an algebra is desirable. However, XML-OLAP (XOLAP) algebras
from the literature still largely rely on the relational model. Hence, we
propose in this paper a rollup operator based on a pattern tree in order to
handle multidimensional XML data expressed within complex hierarchies
Formal Representation of the SS-DB Benchmark and Experimental Evaluation in EXTASCID
Evaluating the performance of scientific data processing systems is a
difficult task considering the plethora of application-specific solutions
available in this landscape and the lack of a generally-accepted benchmark. The
dual structure of scientific data coupled with the complex nature of processing
complicate the evaluation procedure further. SS-DB is the first attempt to
define a general benchmark for complex scientific processing over raw and
derived data. It fails to draw sufficient attention though because of the
ambiguous plain language specification and the extraordinary SciDB results. In
this paper, we remedy the shortcomings of the original SS-DB specification by
providing a formal representation in terms of ArrayQL algebra operators and
ArrayQL/SciQL constructs. These are the first formal representations of the
SS-DB benchmark. Starting from the formal representation, we give a reference
implementation and present benchmark results in EXTASCID, a novel system for
scientific data processing. EXTASCID is complete in providing native support
both for array and relational data and extensible in executing any user code
inside the system by the means of a configurable metaoperator. These features
result in an order of magnitude improvement over SciDB at data loading,
extracting derived data, and operations over derived data.Comment: 32 pages, 3 figure
Explain3D: Explaining Disagreements in Disjoint Datasets
Data plays an important role in applications, analytic processes, and many
aspects of human activity. As data grows in size and complexity, we are met
with an imperative need for tools that promote understanding and explanations
over data-related operations. Data management research on explanations has
focused on the assumption that data resides in a single dataset, under one
common schema. But the reality of today's data is that it is frequently
un-integrated, coming from different sources with different schemas. When
different datasets provide different answers to semantically similar questions,
understanding the reasons for the discrepancies is challenging and cannot be
handled by the existing single-dataset solutions.
In this paper, we propose Explain3D, a framework for explaining the
disagreements across disjoint datasets (3D). Explain3D focuses on identifying
the reasons for the differences in the results of two semantically similar
queries operating on two datasets with potentially different schemas. Our
framework leverages the queries to perform a semantic mapping across the
relevant parts of their provenance; discrepancies in this mapping point to
causes of the queries' differences. Exploiting the queries gives Explain3D an
edge over traditional schema matching and record linkage techniques, which are
query-agnostic. Our work makes the following contributions: (1) We formalize
the problem of deriving optimal explanations for the differences of the results
of semantically similar queries over disjoint datasets. (2) We design a 3-stage
framework for solving the optimal explanation problem. (3) We develop a
smart-partitioning optimizer that improves the efficiency of the framework by
orders of magnitude. (4)~We experiment with real-world and synthetic data to
demonstrate that Explain3D can derive precise explanations efficiently
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