Automatic tuning method of spark configuration parameters based on cluster scaling
A technology for configuring parameters and clusters, applied in the computer field, can solve the problems of complex model creation process and high time cost, and achieve the effect of lowering the threshold of optimization and reducing time cost.
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[0037] The present invention will be further described below in conjunction with the accompanying drawings.
[0038] Refer to attached figure 1 , to further describe the specific steps of the present invention.
[0039] Step 1, build a cluster.
[0040] Build a cluster composed of multiple computers with the same hardware configuration equipped with the distributed memory computing framework Spark.
[0041] Step 2, select the configuration parameter set.
[0042] From all the configuration parameters to be modified in the Spark cluster of the distributed memory computing framework, select the configuration parameters recommended to be modified in the optimization standard to form a set of configuration parameters to be optimized.
[0043] On the optimization page in the official documentation of the distributed memory computing framework Spark, the optimization standard specifies the configuration parameters that should be optimized.
[0044] Step 3, determine the value type...
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