Spark parameter adaptive optimization method and system
An optimization method and self-adaptive technology, which can be applied in the fields of electrical digital data processing, resource allocation, program control design, etc., and can solve problems such as complex parameter tuning of Spark.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Example Embodiment
[0068] Example
[0069] In this case, a Spark cluster is built with four servers with 14 cores available and 44GB of available memory. The application model is the spatial intersection calculation of trajectory data points and road network data.
[0070] Step 1. Collect experimental data for model training.
[0071] As shown in Table 1, the Spark application is submitted under the corresponding parameter value space. In this embodiment, 140746 pieces of task execution measurement information are collected. Among them, the data volume ranges from 50 million to 50 million. The amount of data increases until the upper limit of the amount of data that can be processed by the current parameter configuration. The collected task measurement data is processed and input into the neural network model for training. The parameters of the model are shown in Table 2. The test data set is used to evaluate the model, and the average prediction deviation of the execution time of a single task is ab...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap