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

Example 46 with ExecutionContext

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

the class DBDropTableNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] inObjects, final ExecutionContext exec) throws Exception {
    exec.setMessage("Droping table");
    final DatabaseConnectionPortObject incomingConnection = (DatabaseConnectionPortObject) inObjects[0];
    final CredentialsProvider cp = getCredentialsProvider();
    final DatabaseConnectionSettings connSettings = incomingConnection.getConnectionSettings(cp);
    final DatabaseUtility dbUtility = connSettings.getUtility();
    final StatementManipulator manipulator = dbUtility.getStatementManipulator();
    final String table2Drop = m_tableName.getStringValue();
    try {
        if (m_failIfNotExists.getBooleanValue() || connSettings.execute(cp, conn -> {
            return dbUtility.tableExists(conn, table2Drop);
        })) {
            connSettings.execute(manipulator.dropTable(table2Drop, m_cascade.getBooleanValue()), cp);
            exec.setMessage("Table " + table2Drop + " sucessful droped");
        } else {
            exec.setMessage("Table " + table2Drop + " does not exist in db");
        }
    } catch (SQLException ex) {
        Throwable cause = ExceptionUtils.getRootCause(ex);
        if (cause == null) {
            cause = ex;
        }
        throw new InvalidSettingsException("Error while validating drop statement: " + cause.getMessage(), ex);
    }
    return inObjects;
}

Example 47 with ExecutionContext

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

the class LoopEndJoinNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected BufferedDataTable[] execute(final BufferedDataTable[] inData, final ExecutionContext exec) throws Exception {
    boolean hasSameRowsInEachIteration = m_configuration.hasSameRowsInEachIteration();
    LoopStartNode startNode = getLoopStartNode();
    if (!(startNode instanceof LoopStartNodeTerminator)) {
        throw new IllegalStateException("Loop end is not connected" + " to matching/corresponding loop start node. You" + " are trying to create an infinite loop!");
    }
    boolean continueLoop = !((LoopStartNodeTerminator) startNode).terminateLoop();
    if (m_currentAppendTable == null) {
        m_currentAppendTable = copy(inData[0], false, exec);
    } else if (hasSameRowsInEachIteration) {
        boolean isCacheNew = m_iteration % 50 == 0;
        double amount = isCacheNew ? (1.0 / 3.0) : (1.0 / 2.0);
        ExecutionContext copyCtx = exec.createSubExecutionContext(amount);
        ExecutionContext joinCtx = exec.createSubExecutionContext(amount);
        exec.setProgress("Copying input");
        BufferedDataTable t = copy(inData[0], true, copyCtx);
        copyCtx.setProgress(1.0);
        exec.setProgress("Joining with previous input");
        m_currentAppendTable = exec.createJoinedTable(m_currentAppendTable, t, joinCtx);
        joinCtx.setProgress(1.0);
        if (isCacheNew) {
            exec.setProgress("Caching intermediate results (iteration " + m_iteration + ")");
            ExecutionContext ctx = exec.createSubExecutionContext(amount);
            // copy the whole table every 50 columns (avoids wrapping to much individual tables)
            // In this case the whole table is copied and column names DON'T need to be made unique (bugfix 6544)
            m_currentAppendTable = copy(m_currentAppendTable, m_appendIterSuffixForBackwardComp, ctx);
            ctx.setProgress(1.0);
        }
    } else {
        Joiner2Settings settings = new Joiner2Settings();
        settings.setCompositionMode(CompositionMode.MatchAll);
        settings.setDuplicateColumnSuffix(" (Iter #" + m_iteration + ")");
        settings.setDuplicateHandling(DuplicateHandling.AppendSuffix);
        settings.setEnableHiLite(false);
        // joining on RowIDs, this should not generate new row IDs but
        // only fill missing rows in either table
        settings.setJoinMode(JoinMode.FullOuterJoin);
        settings.setLeftIncludeAll(true);
        settings.setRightIncludeAll(true);
        // TODO to be replaced by Joiner2Settings.ROW_KEY_IDENTIFIER
        // once that is public
        settings.setLeftJoinColumns(new String[] { "$RowID$" });
        settings.setRightJoinColumns(new String[] { "$RowID$" });
        BufferedDataTable left = m_currentAppendTable;
        BufferedDataTable right = copy(inData[0], true, exec.createSubExecutionContext(0.1));
        Joiner joiner = new Joiner(left.getDataTableSpec(), right.getDataTableSpec(), settings);
        m_currentAppendTable = joiner.computeJoinTable(left, right, exec.createSubExecutionContext(0.9));
    }
    m_iteration += 1;
    if (continueLoop) {
        super.continueLoop();
        return null;
    } else {
        return new BufferedDataTable[] { m_currentAppendTable };
    }
}

Example 48 with ExecutionContext

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

the class StatisticCalculator method evaluate.

/**
 * @param dataTable actual data table to compute the
 * @param exec execution context
 * @return a potential warnings message or <code>null</code>
 * @throws CanceledExecutionException if the user cancels the execution
 */
public String evaluate(final BufferedDataTable dataTable, final ExecutionContext exec) throws CanceledExecutionException {
    for (Statistic stat : m_statistics) {
        stat.beforeEvaluation(dataTable.size());
    }
    if (!m_colToSortOn.isEmpty()) {
        ColumnBufferedDataTableSorter columnDataTableSorter;
        try {
            columnDataTableSorter = new ColumnBufferedDataTableSorter(dataTable.getDataTableSpec(), dataTable.size(), m_colToSortOn.toArray(new String[m_colToSortOn.size()]));
        } catch (InvalidSettingsException e) {
            throw new RuntimeException("Error on initialize the sorting", e);
        }
        exec.setMessage("Sorting Data.");
        final Iterator<DataRow> it = dataTable.iterator();
        final MutableLong count = new MutableLong();
        final ExecutionContext evalProgress = exec.createSubExecutionContext(0.3);
        final int[] specMapping = createSpecMapping(dataTable.getSpec(), m_colToSortOn.toArray(new String[m_colToSortOn.size()]));
        columnDataTableSorter.sort(dataTable, exec.createSubExecutionContext(0.7), new SortingConsumer() {

            @Override
            public void consume(final DataRow defaultRow) {
                DataRow next = it.next();
                evalProgress.setProgress(count.longValue() / (double) dataTable.size(), "Processing Row: " + next.getKey());
                count.increment();
                for (Statistic stat : m_statistics) {
                    stat.consumeRow(new OverwritingRow(next, defaultRow, specMapping));
                }
            }
        });
    } else {
        exec.setMessage("Evaluating statistics.");
        long count = 0;
        for (DataRow currRow : dataTable) {
            exec.setProgress(count++ / (double) dataTable.size(), "Processing Row: " + currRow.getKey());
            for (Statistic stat : m_statistics) {
                stat.consumeRow(currRow);
            }
        }
    }
    StringBuilder warnings = new StringBuilder();
    for (Statistic stat : m_statistics) {
        String warningString = stat.finish();
        if (warningString != null) {
            warnings.append(warningString);
            warnings.append("\n");
        }
    }
    return warnings.length() > 0 ? warnings.toString() : null;
}

Example 49 with ExecutionContext

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

the class Normalizer2 method doZScoreNorm.

/**
 * Does the Z-Score Normalization.
 *
 * @param exec an object to check for user cancelations. Can be <code>null</code>.
 * @throws CanceledExecutionException if user canceled
 * @return the normalized DataTable
 */
public AffineTransTable doZScoreNorm(final ExecutionContext exec) throws CanceledExecutionException {
    ExecutionContext statisticsExec = exec.createSubExecutionContext(.5);
    final Statistics3Table st = new Statistics3Table(m_table, false, 0, Collections.<String>emptyList(), statisticsExec);
    checkForMissVals(st);
    double[] mean = st.getMean();
    double[] stddev = st.getStandardDeviation();
    final double[] scales = new double[m_colindices.length];
    final double[] transforms = new double[m_colindices.length];
    final double[] mins = new double[m_colindices.length];
    final double[] maxs = new double[m_colindices.length];
    for (int i = 0; i < m_colindices.length; i++) {
        if (Double.isNaN(mean[m_colindices[i]])) {
            scales[i] = Double.NaN;
            transforms[i] = Double.NaN;
        } else {
            scales[i] = (stddev[m_colindices[i]] == 0.0 ? 1.0 : 1.0 / stddev[m_colindices[i]]);
            transforms[i] = -mean[m_colindices[i]] * scales[i];
        }
        mins[i] = Double.NaN;
        maxs[i] = Double.NaN;
    }
    String[] includes = getNames();
    String summary = "Z-Score (Gaussian) normalization on " + includes.length + " column(s)";
    AffineTransConfiguration configuration = new AffineTransConfiguration(includes, scales, transforms, mins, maxs, summary);
    return new AffineTransTable(m_table, configuration);
}

Example 50 with ExecutionContext

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

the class Normalizer2 method doMinMaxNorm.

/**
 * Does the Min-Max Normalization.
 *
 * @param newmax the new maximum
 * @param newmin the new minimum
 * @param exec an object to check for user cancelations. Can be <code>null</code>.
 * @throws CanceledExecutionException if user canceled
 * @return normalized DataTable
 */
public AffineTransTable doMinMaxNorm(final double newmax, final double newmin, final ExecutionContext exec) throws CanceledExecutionException {
    ExecutionContext statisticsExec = exec.createSilentSubExecutionContext(.5);
    Statistics3Table st;
    st = new Statistics3Table(m_table, false, 0, Collections.<String>emptyList(), statisticsExec);
    checkForMissVals(st);
    DataTableSpec spec = m_table.getDataTableSpec();
    double[] max = st.getMax();
    double[] min = st.getMin();
    final double[] scales = new double[m_colindices.length];
    final double[] transforms = new double[m_colindices.length];
    final double[] mins = new double[m_colindices.length];
    final double[] maxs = new double[m_colindices.length];
    for (int i = 0; i < transforms.length; i++) {
        DataColumnSpec cSpec = spec.getColumnSpec(m_colindices[i]);
        boolean isDouble = cSpec.getType().isCompatible(DoubleValue.class);
        if (!isDouble) {
            assert (!isDouble);
            scales[i] = Double.NaN;
            transforms[i] = Double.NaN;
            mins[i] = Double.NaN;
            maxs[i] = Double.NaN;
        } else {
            // scales and translation to [0,1]
            double maxI = max[m_colindices[i]];
            double minI = min[m_colindices[i]];
            scales[i] = (maxI == minI ? 1 : 1.0 / (maxI - minI));
            transforms[i] = -minI * scales[i];
            // scale and translation to [newmin, newmax]
            scales[i] *= (newmax - newmin);
            transforms[i] *= (newmax - newmin);
            transforms[i] += newmin;
            mins[i] = newmin;
            maxs[i] = newmax;
        }
    }
    String[] includes = getNames();
    String minS = DoubleFormat.formatDouble(newmin);
    String maxS = DoubleFormat.formatDouble(newmax);
    String summary = "Min/Max (" + minS + ", " + maxS + ") normalization " + "on " + includes.length + " column(s)";
    AffineTransConfiguration configuration = new AffineTransConfiguration(includes, scales, transforms, mins, maxs, summary);
    return new AffineTransTable(m_table, configuration);
}