Examples with ExecutionContext org.knime.core.node.ExecutionContext used on opensource projects

Example 6 with ExecutionContext

use of org.knime.core.node.ExecutionContext in project knime-core by knime.

the class NumericOutliersIntervalsCalculator method calculatePermittedIntervals.

/**
 * Calculates the permitted intervals.
 *
 * @param inTable the data table for which the outliers have to be detected
 * @param exec the execution context
 * @return returns the mapping between groups and the permitted intervals for each outlier column
 * @throws Exception if the execution failed, due to internal reasons or cancelation from the outside
 */
NumericOutliersModel calculatePermittedIntervals(final BufferedDataTable inTable, final ExecutionContext exec) throws Exception {
    // the quartile calculation progress
    final double quartilesProgress = 0.8;
    // the interval calculation progress
    final double intervalsProgress = 1 - quartilesProgress;
    // start the computation of the first and third quartile (and some additional stuff)
    exec.setMessage(STATISTICS_MSG);
    GroupByTable t;
    // out of memory exception while initializing/cloning the aggregators. However, this is very unlikely
    try {
        ExecutionContext quartilesCalcExec = exec.createSubExecutionContext(quartilesProgress);
        t = getGroupByTable(inTable, quartilesCalcExec);
        quartilesCalcExec.setProgress(1.0);
    } catch (final OutOfMemoryError e) {
        throw new IllegalArgumentException(MEMORY_EXCEPTION, e);
    }
    // carried out inside the memory
    if (!t.getSkippedGroupsByColName().isEmpty()) {
        throw new IllegalArgumentException(MEMORY_EXCEPTION);
    }
    // start the permitted interval calculation
    exec.setMessage(INTERVAL_MSG);
    // interval subexecution context
    ExecutionContext intervalExec = exec.createSubExecutionContext(intervalsProgress);
    // calculate the permitted intervals and store them to the model
    final NumericOutliersModel model = calcPermittedIntervals(intervalExec, t.getBufferedTable());
    // update the progress and return the permitted intervals
    exec.setProgress(1);
    // return the model
    return model;
}

Example 7 with ExecutionContext

use of org.knime.core.node.ExecutionContext in project knime-core by knime.

the class NewToOldTimeNodeModel method createStreamableOperator.

/**
 * {@inheritDoc}
 */
@Override
public StreamableOperator createStreamableOperator(final PartitionInfo partitionInfo, final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    return new StreamableOperator() {

        @Override
        public StreamableOperatorInternals saveInternals() {
            return null;
        }

        @Override
        public void runFinal(final PortInput[] inputs, final PortOutput[] outputs, final ExecutionContext exec) throws Exception {
            final RowInput in = (RowInput) inputs[0];
            final RowOutput out = (RowOutput) outputs[0];
            final DataTableSpec inSpec = in.getDataTableSpec();
            String[] includeList = m_colSelect.applyTo(inSpec).getIncludes();
            final int[] includeIndeces = Arrays.stream(includeList).mapToInt(s -> inSpec.findColumnIndex(s)).toArray();
            DataRow row;
            while ((row = in.poll()) != null) {
                exec.checkCanceled();
                DataCell[] datacells = new DataCell[includeIndeces.length];
                for (int i = 0; i < includeIndeces.length; i++) {
                    if (m_isReplaceOrAppend.getStringValue().equals(OPTION_REPLACE)) {
                        final DataColumnSpecCreator dataColumnSpecCreator = new DataColumnSpecCreator(includeList[i], DateAndTimeCell.TYPE);
                        final ConvertTimeCellFactory cellFac = new ConvertTimeCellFactory(dataColumnSpecCreator.createSpec(), includeIndeces[i]);
                        datacells[i] = cellFac.getCells(row)[0];
                    } else {
                        final DataColumnSpec dataColSpec = new UniqueNameGenerator(inSpec).newColumn(includeList[i] + m_suffix.getStringValue(), DateAndTimeCell.TYPE);
                        final ConvertTimeCellFactory cellFac = new ConvertTimeCellFactory(dataColSpec, includeIndeces[i]);
                        datacells[i] = cellFac.getCells(row)[0];
                    }
                }
                if (m_isReplaceOrAppend.getStringValue().equals(OPTION_REPLACE)) {
                    out.push(new ReplacedColumnsDataRow(row, datacells, includeIndeces));
                } else {
                    out.push(new AppendedColumnRow(row, datacells));
                }
            }
            in.close();
            out.close();
        }
    };
}

Example 8 with ExecutionContext

use of org.knime.core.node.ExecutionContext in project knime-core by knime.

the class DateTimeToStringNodeModel method createStreamableOperator.

/**
 * {@inheritDoc}
 */
@Override
public StreamableOperator createStreamableOperator(final PartitionInfo partitionInfo, final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    return new StreamableOperator() {

        @Override
        public void runFinal(final PortInput[] inputs, final PortOutput[] outputs, final ExecutionContext exec) throws Exception {
            final RowInput in = (RowInput) inputs[0];
            final RowOutput out = (RowOutput) outputs[0];
            final DataTableSpec inSpec = in.getDataTableSpec();
            final String[] includeList = m_colSelect.applyTo(inSpec).getIncludes();
            final int[] includeIndeces = Arrays.stream(m_colSelect.applyTo(inSpec).getIncludes()).mapToInt(s -> inSpec.findColumnIndex(s)).toArray();
            final boolean isReplace = m_isReplaceOrAppend.getStringValue().equals(OPTION_REPLACE);
            DataRow row;
            while ((row = in.poll()) != null) {
                exec.checkCanceled();
                DataCell[] datacells = new DataCell[includeIndeces.length];
                for (int i = 0; i < includeIndeces.length; i++) {
                    if (isReplace) {
                        final DataColumnSpecCreator dataColumnSpecCreator = new DataColumnSpecCreator(includeList[i], StringCell.TYPE);
                        final TimeToStringCellFactory cellFac = new TimeToStringCellFactory(dataColumnSpecCreator.createSpec(), includeIndeces[i]);
                        datacells[i] = cellFac.getCell(row);
                    } else {
                        final DataColumnSpec dataColSpec = new UniqueNameGenerator(inSpec).newColumn(includeList[i] + m_suffix.getStringValue(), StringCell.TYPE);
                        final TimeToStringCellFactory cellFac = new TimeToStringCellFactory(dataColSpec, includeIndeces[i]);
                        datacells[i] = cellFac.getCell(row);
                    }
                }
                if (isReplace) {
                    out.push(new ReplacedColumnsDataRow(row, datacells, includeIndeces));
                } else {
                    out.push(new AppendedColumnRow(row, datacells));
                }
            }
            in.close();
            out.close();
        }
    };
}

Example 9 with ExecutionContext

use of org.knime.core.node.ExecutionContext in project knime-core by knime.

the class TreeEnsembleClassificationPredictorNodeModel method createStreamableOperator.

/**
 * {@inheritDoc}
 */
@Override
public StreamableOperator createStreamableOperator(final PartitionInfo partitionInfo, final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    return new StreamableOperator() {

        @Override
        public void runFinal(final PortInput[] inputs, final PortOutput[] outputs, final ExecutionContext exec) throws Exception {
            TreeEnsembleModelPortObject model = (TreeEnsembleModelPortObject) ((PortObjectInput) inputs[0]).getPortObject();
            TreeEnsembleModelPortObjectSpec modelSpec = model.getSpec();
            DataTableSpec dataSpec = (DataTableSpec) inSpecs[1];
            final TreeEnsemblePredictor pred = new TreeEnsemblePredictor(modelSpec, model, dataSpec, m_configuration);
            ColumnRearranger rearranger = pred.getPredictionRearranger();
            StreamableFunction func = rearranger.createStreamableFunction(1, 0);
            func.runFinal(inputs, outputs, exec);
        }
    };
}

Example 10 with ExecutionContext

use of org.knime.core.node.ExecutionContext in project knime-core by knime.

the class TreeEnsembleRegressionPredictorNodeModel method createStreamableOperator.

/**
 * {@inheritDoc}
 */
@Override
public StreamableOperator createStreamableOperator(final PartitionInfo partitionInfo, final PortObjectSpec[] inSpecs) throws InvalidSettingsException {
    return new StreamableOperator() {

        @Override
        public void runFinal(final PortInput[] inputs, final PortOutput[] outputs, final ExecutionContext exec) throws Exception {
            TreeEnsembleModelPortObject model = (TreeEnsembleModelPortObject) ((PortObjectInput) inputs[0]).getPortObject();
            TreeEnsembleModelPortObjectSpec modelSpec = model.getSpec();
            DataTableSpec dataSpec = (DataTableSpec) inSpecs[1];
            final TreeEnsemblePredictor pred = new TreeEnsemblePredictor(modelSpec, model, dataSpec, m_configuration);
            ColumnRearranger rearranger = pred.getPredictionRearranger();
            StreamableFunction func = rearranger.createStreamableFunction(1, 0);
            func.runFinal(inputs, outputs, exec);
        }
    };
}