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Spark PCA

Tools & Services Apache Spark Mining Dimensionality Reduction
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This node performs a principal component analysis (PCA) on the given data using the Apache Spark implementation . The input data is projected from its original feature space into a space of (possibly) lower dimension with a minimum of information loss.

Node details

Input ports
  1. Type: Spark Data
    Spark DataFrame/RDD
    Input Spark DataFrame/RDD
Output ports
  1. Type: Spark Data
    Projected Input DataFrame/RDD
    The input DataFrame/RDD projected onto the principal components. Input columns that were not included in the principal component analysis are retained.
  2. Type: Spark Data
    Principal Component Matrix
    A DataFrame/RDD with the principal components matrix.

Extension

The Spark PCA node is part of this extension:

Related workflows & nodes

  1. Local big data Irish meter
    Hive Spark Spark PCA
    +7
    This workflow uses a portion of the Irish Energy Meter dataset, and presents a simple ana…
    knime > Examples > 10_Big_Data > 02_Spark_Executor > 09_Big_Data_Irish_Meter_on_Spark_only
  2. Local big data Irish meter
    Hive Spark Spark PCA
    +7
    This workflow uses a portion of the Irish Energy Meter dataset, and presents a simple ana…
    knime > Education > Courses > L4-BD Introduction to Big Data with KNIME Analytics Platform > 3_Spark > 4_Examples > 09_Big_Data_Irish_Meter_on_Spark_only