Java* API Reference for Intel® Data Analytics Acceleration Library 2019 Update 4

SortingDenseBatch.java

/* file: SortingDenseBatch.java */
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/*
// Content:
// Java example of sorting the observations matrix
*/
package com.intel.daal.examples.sorting;
import com.intel.daal.algorithms.sorting.Batch;
import com.intel.daal.algorithms.sorting.InputId;
import com.intel.daal.algorithms.sorting.Method;
import com.intel.daal.algorithms.sorting.Result;
import com.intel.daal.algorithms.sorting.ResultId;
import com.intel.daal.data_management.data_source.DataSource;
import com.intel.daal.data_management.data_source.FileDataSource;
import com.intel.daal.examples.utils.Service;
import com.intel.daal.services.DaalContext;
class SortingDenseBatch {
/* Input data set parameters */
private static final String datasetFileName = "../data/batch/sorting.csv";
private static DaalContext context = new DaalContext();
public static void main(String[] args) throws java.io.FileNotFoundException, java.io.IOException {
/* Retrieve the input data */
FileDataSource dataSource = new FileDataSource(context, datasetFileName,
DataSource.DictionaryCreationFlag.DoDictionaryFromContext,
DataSource.NumericTableAllocationFlag.DoAllocateNumericTable);
dataSource.loadDataBlock();
/* Print the input observations matrix */
Service.printNumericTable("Initial matrix of observations:", dataSource.getNumericTable());
/* Create an algorithm to sort data */
Batch algorithm = new Batch(context, Float.class, Method.defaultDense);
algorithm.input.set(InputId.data, dataSource.getNumericTable());
/* Sort data observations */
Result res = algorithm.compute();
Service.printNumericTable("Sorted matrix of observations:", res.get(ResultId.sortedData));
context.dispose();
}
}

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