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Strategies for array data retrieval from a relational back-end based on access patterns

机译:基于访问模式的关系反向末端的阵列数据检索策略

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摘要

Multidimensional numeric arrays are often serialized to binary formats for efficient storage and processing. These representations can be stored as binary objects in existing relational database management systems. To minimize data transfer overhead when arrays are large and only parts of arrays are accessed, it is favorable to split these arrays into separately stored chunks. We process queries expressed in an extended graph query language SPARQL, treating arrays as node values and having syntax for specifying array projection, element and range selection operations as part of a query. When a query selects parts of one or more arrays, only the relevant chunks of each array should be retrieved from the relational database. The retrieval is made by automatically generated SQL queries. We evaluate different strategies for partitioning the array content, and for generating the SQL queries that retrieve it on demand. For this purpose, we present a mini-benchmark, featuring a number of typical array access patterns. We draw some actionable conclusions from the performance numbers.
机译:多维数字阵列通常序列化为二进制格式,以实现高效的存储和处理。这些表示可以存储为现有关系数据库管理系统中的二进制对象。为了最大限度地减少数据传输开销时阵列大而且仅访问阵列部分时,有利的是将这些阵列分成单独存储的块。我们处理以扩展图查询语言SPARQL表示的查询,将数组视为节点值,并具有用于指定数组投影,元素和范围选择操作的语法作为查询的一部分。当查询选择一个或多个数组的部分时,只能从关系数据库中检索每个数组的相关块。通过自动生成的SQL查询进行检索。我们评估了用于分区数组内容的不同策略,并用于生成按需检索它的SQL查询。为此目的,我们提出了一个迷你基准,其中包含了许多典型的数组访问模式。我们从绩效数字中得出一些可行的结论。

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