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03_​Spark_​for_​Performance

Performance and Scalability Testing: Example KNIME with Spark

This workflows show how to learn a random forest using the KNIME Apache Spark nodes.

We here are measuring the speed of the workflow with the last metanode. In addition it collects the max used memory and the start parameters of this instantiation of the KNIME Analytics Platform.

Preprocessing Data Conversion and Transfer Performance and Scalability Testing: Example KNIME with SparkThis workflows show how to learn a random forest using the KNIME Apache Spark nodes.We here are measuring the speed of the workflow with the last metanode. In addition it collects the max used memory and the startparameters of this instantiation of the KNIME Analytics Platform. Metanode Input Port: Connected to first node to be measured.Timer Info Node Input Port:Connected to last node to be measured. Receivedata from caller workfowRead Input DataIncrease iterationsfor mutliple evaluationrounds Table to Spark Spark Partitioning Spark Scorer CSV Writer ContainerOutput (Table) ContainerInput (Table) File Reader Capture Accuracy Benchmark End(Memory Monitoring) Benchmark Start(Memory Monitoring) Combine Spark RandomForest Learner Spark Predictor(Classification) Create Local BigData Environment Preprocessing Data Conversion and Transfer Performance and Scalability Testing: Example KNIME with SparkThis workflows show how to learn a random forest using the KNIME Apache Spark nodes.We here are measuring the speed of the workflow with the last metanode. In addition it collects the max used memory and the startparameters of this instantiation of the KNIME Analytics Platform. Metanode Input Port: Connected to first node to be measured.Timer Info Node Input Port:Connected to last node to be measured. Receivedata from caller workfowRead Input DataIncrease iterationsfor mutliple evaluationroundsTable to Spark Spark Partitioning Spark Scorer CSV Writer ContainerOutput (Table) ContainerInput (Table) File Reader Capture Accuracy Benchmark End(Memory Monitoring) Benchmark Start(Memory Monitoring) Combine Spark RandomForest Learner Spark Predictor(Classification) Create Local BigData Environment

Nodes

Extensions

Links

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: iris.adae
Created at: 2019-02-15
On NodePit since: 2019-07-12
Last update: 2023-03-31
Created with KNIME version: v4.1.1