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Cluster Temporal Data Indexing Method Based on Memory Computing

A temporal data and in-memory computing technology, applied in database indexing, structured data retrieval, digital data information retrieval, etc., can solve problems such as impractical, excessive cluster load capacity, etc., to reduce size and query delay , Optimize the effect of excessive storage space

Active Publication Date: 2021-10-29
ANHUI UNIVERSITY OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

If this kind of temporal index algorithm based on external memory is applied to the memory computing framework of the cluster, excessive memory consumption is a huge challenge to the load capacity of the cluster, and it is obvious to use high-consumption memory capacity in exchange for a certain query speed not very practical

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  • Cluster Temporal Data Indexing Method Based on Memory Computing
  • Cluster Temporal Data Indexing Method Based on Memory Computing
  • Cluster Temporal Data Indexing Method Based on Memory Computing

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Embodiment Construction

[0033] specific implementation plan

[0034] Apache Spark is a cluster big data processing framework based on memory computing, which is in line with our application scope, so we choose Apache Spark cluster as an example to introduce in detail, and the cluster configuration will not be described in detail. In order to make the above and other objects, features and advantages of the present invention more obvious, the present invention will be described in detail below with reference to the accompanying drawings and examples.

[0035] combine Figure 1-Figure 4 , a temporal data indexing method based on cluster memory computing proposed by the present invention belongs to a two-layer indexing method. First, the data is partitioned, and a lightweight index is established for the partitions, and then the internal Array data set of the present invention is established. The temporal index of . In the process of partitioning, relevant optimizations are carried out according to the...

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Abstract

The present invention provides a temporal data indexing method based on cluster memory computing. By adopting a double-layer indexing method, the data is first partitioned, and a lightweight index is established for the partitions, and then the temporal data of the present invention is established in the internal Array data set. state index. In the process of partitioning, relevant optimizations are carried out according to the establishment process of the temporal index, which reduces the space consumption of indexing within the partition. Partitioning speeds up the pruning process of the data set during the query, improves the efficiency of the query, and optimizes the temporal index. The creation and query costs. The present invention can reduce the size of the index space while ensuring a certain query speed, and optimize the problem of excessive storage space in similar indexes; meanwhile, it reduces the query delay of temporal big data and improves the overall throughput.

Description

technical field [0001] The invention relates to a cluster temporal data indexing method based on memory computing, which belongs to the fields of cloud computing and temporal big data. Background technique [0002] Temporal data is a series of data representing the state at a certain point in time, describing the state information of the measured subject in the historical time dimension, such as hydrological monitoring, factory equipment monitoring, communication monitoring, financial industry index data, etc. Timely and effective analysis of time-series data can discover the historical and regularity of the development of things, and can guide the corresponding decision-making and judgment. Faced with the temporal data in today's massive data (for example, a connected car generates 25G data per hour), how to effectively perform query processing is still a hot research issue. [0003] In recent years, some index structures for efficient query of temporal data have emerged i...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/22G06F16/2458
Inventor 郑啸刘厚凯吴宣够秦峰
Owner ANHUI UNIVERSITY OF TECHNOLOGY