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03_​Spark_​for_​Performance

Workflow

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 Data Measure WorkflowRessources and Times Create Local BigData Environment Table to Spark Spark Partitioning Spark RandomForests Learner Spark Predictor Spark Scorer Spark CategoryTo Number Spark Missing Value CSV Writer ContainerOutput (Table) ContainerInput (Table) Timer Info File Reader Cross Joiner Capture Accuracy 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 DataMeasure WorkflowRessources and Times Create Local BigData Environment Table to Spark Spark Partitioning Spark RandomForests Learner Spark Predictor Spark Scorer Spark CategoryTo Number Spark Missing Value CSV Writer ContainerOutput (Table) ContainerInput (Table) Timer Info File Reader Cross Joiner Capture Accuracy

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Nodes

03_​Spark_​for_​Performance consists of the following 38 nodes(s):

Plugins

03_​Spark_​for_​Performance contains nodes provided by the following 6 plugin(s):