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
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[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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