Examples with GroupByTable org.knime.base.node.preproc.groupby.GroupByTable used on opensource projects

Example 1 with GroupByTable

use of org.knime.base.node.preproc.groupby.GroupByTable 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 2 with GroupByTable

use of org.knime.base.node.preproc.groupby.GroupByTable in project knime-core by knime.

the class CrosstabNodeModel method createGroupByTable.

/**
 * Create group-by table.
 * @param exec execution context
 * @param table input table to group
 * @param groupByCols column selected for group-by operation
 * @return table with group and aggregation columns
 * @throws CanceledExecutionException if the group-by table generation was
 *         canceled externally
 */
private final GroupByTable createGroupByTable(final ExecutionContext exec, final BufferedDataTable table, final List<String> groupByCols) throws CanceledExecutionException {
    final int maxUniqueVals = Integer.MAX_VALUE;
    final boolean enableHilite = m_settings.getEnableHiliting();
    final boolean retainOrder = false;
    final ColumnNamePolicy colNamePolicy = ColumnNamePolicy.AGGREGATION_METHOD_COLUMN_NAME;
    final GlobalSettings globalSettings = GlobalSettings.builder().setFileStoreFactory(FileStoreFactory.createWorkflowFileStoreFactory(exec)).setGroupColNames(groupByCols).setMaxUniqueValues(maxUniqueVals).setValueDelimiter(GlobalSettings.STANDARD_DELIMITER).setDataTableSpec(table.getDataTableSpec()).setNoOfRows(table.size()).setAggregationContext(AggregationContext.ROW_AGGREGATION).build();
    ColumnAggregator collAggregator = null;
    if (null != m_settings.getWeightColumn()) {
        final String weightColumn = m_settings.getWeightColumn();
        // the column aggregator for the weighting column
        final boolean inclMissing = false;
        final DataColumnSpec originalColSpec = table.getDataTableSpec().getColumnSpec(weightColumn);
        final OperatorColumnSettings opColSettings = new OperatorColumnSettings(inclMissing, originalColSpec);
        collAggregator = new ColumnAggregator(originalColSpec, new NonNegativeSumOperator(globalSettings, opColSettings), inclMissing);
    } else {
        // use any column, does not matter as long as it exists and
        // include missing is true;
        final boolean inclMissing = true;
        final DataColumnSpec originalColSpec = table.getDataTableSpec().getColumnSpec(groupByCols.get(0));
        final OperatorColumnSettings opColSettings = new OperatorColumnSettings(inclMissing, originalColSpec);
        collAggregator = new ColumnAggregator(originalColSpec, new CountOperator(globalSettings, opColSettings), inclMissing);
    }
    final GroupByTable resultTable = new BigGroupByTable(exec, table, groupByCols, new ColumnAggregator[] { collAggregator }, globalSettings, enableHilite, colNamePolicy, retainOrder);
    if (enableHilite) {
        setHiliteMapping(new DefaultHiLiteMapper(resultTable.getHiliteMapping()));
    }
    // check for skipped columns
    final String warningMsg = resultTable.getSkippedGroupsMessage(3, 3);
    if (warningMsg != null) {
        setWarningMessage(warningMsg);
    }
    return resultTable;
}

Example 3 with GroupByTable

use of org.knime.base.node.preproc.groupby.GroupByTable in project knime-core by knime.

the class Pivot2NodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected PortObject[] execute(final PortObject[] inData, final ExecutionContext exec) throws Exception {
    final BufferedDataTable table = (BufferedDataTable) inData[0];
    final List<String> groupAndPivotCols = createAllColumns();
    final BufferedDataTable groupTable;
    final String orderPivotColumnName;
    ExecutionContext groupAndPivotExec = exec.createSubExecutionContext(0.5);
    ExecutionContext groupExec = exec.createSubExecutionContext(0.25);
    ExecutionContext pivotExec = exec.createSubExecutionContext(0.25);
    double progMainTotal = 0.0;
    double progMainTableAppendIndexForSort = isProcessInMemory() || isRetainOrder() ? 1.0 : 0.0;
    progMainTotal += progMainTableAppendIndexForSort;
    double progMainTableGroup = 5.0;
    progMainTotal += progMainTableGroup;
    double progMainTableInMemSort = isProcessInMemory() ? 3.0 : 0.0;
    progMainTotal += progMainTableInMemSort;
    double progMainTableGetPivots = 1.0;
    progMainTotal += progMainTableGetPivots;
    double progMainTableFillPivots = 1.0;
    progMainTotal += progMainTableFillPivots;
    double progMainTableRestoreSort = isProcessInMemory() || isRetainOrder() ? 1.0 : 0.0;
    progMainTotal += progMainTableRestoreSort;
    double progMainTableReplaceRowKey = isProcessInMemory() ? 1.0 : 0.0;
    progMainTotal += progMainTableReplaceRowKey;
    if (isProcessInMemory() || isRetainOrder()) {
        exec.setMessage("Keeping row order");
        final String retainOrderCol = DataTableSpec.getUniqueColumnName(table.getDataTableSpec(), "#pivot_order#");
        // append temp. id column with minimum-aggregation method
        final ColumnAggregator[] colAggregators = getColumnAggregators().toArray(new ColumnAggregator[0]);
        final Set<String> workingCols = new LinkedHashSet<String>();
        workingCols.addAll(groupAndPivotCols);
        for (final ColumnAggregator ca : colAggregators) {
            workingCols.add(ca.getOriginalColName());
        }
        workingCols.add(retainOrderCol);
        final BufferedDataTable appTable = GroupByTable.appendOrderColumn(groupAndPivotExec.createSubExecutionContext(progMainTableAppendIndexForSort / progMainTotal), table, workingCols, retainOrderCol);
        final DataColumnSpec retainOrderColSpec = appTable.getSpec().getColumnSpec(retainOrderCol);
        final ColumnAggregator[] aggrs = new ColumnAggregator[colAggregators.length + 1];
        System.arraycopy(colAggregators, 0, aggrs, 0, colAggregators.length);
        aggrs[colAggregators.length] = new ColumnAggregator(retainOrderColSpec, AggregationMethods.getRowOrderMethod(), true);
        orderPivotColumnName = getColumnNamePolicy().createColumName(aggrs[colAggregators.length]);
        exec.setMessage("Grouping main table");
        final GroupByTable groupByTable = createGroupByTable(groupAndPivotExec.createSubExecutionContext(progMainTableGroup / progMainTotal), appTable, groupAndPivotCols, isProcessInMemory(), false, /* retain order always false; handled by pivoting */
        Arrays.asList(aggrs));
        // true then sort table by group&pivot columns
        if (isProcessInMemory()) {
            exec.setMessage("Sorting group table");
            final boolean[] sortDirection = new boolean[groupAndPivotCols.size()];
            // ensure that missing values are at the end by sorting in ascending order
            Arrays.fill(sortDirection, true);
            final SortedTable sortedGroupByTable = new SortedTable(groupByTable.getBufferedTable(), groupAndPivotCols, sortDirection, groupAndPivotExec.createSubExecutionContext(progMainTableInMemSort / progMainTotal));
            groupTable = sortedGroupByTable.getBufferedDataTable();
        } else {
            groupTable = groupByTable.getBufferedTable();
        }
    } else {
        exec.setMessage("Grouping main table");
        final GroupByTable groupByTable = createGroupByTable(groupAndPivotExec.createSubExecutionContext(progMainTableGroup / progMainTotal), table, groupAndPivotCols, isProcessInMemory(), false, getColumnAggregators());
        groupTable = groupByTable.getBufferedTable();
        orderPivotColumnName = null;
    }
    final List<String> pivotCols = m_pivotCols.getIncludeList();
    final int[] pivotIdx = new int[pivotCols.size()];
    final DataTableSpec groupSpec = groupTable.getSpec();
    final Set<String>[] combPivots = createCombinedPivots(groupSpec, pivotCols);
    for (int i = 0; i < pivotIdx.length; i++) {
        pivotIdx[i] = groupSpec.findColumnIndex(pivotCols.get(i));
    }
    exec.setProgress("Determining pivots...");
    ExecutionContext fillExec = groupAndPivotExec.createSubExecutionContext(progMainTableGetPivots / progMainTotal);
    final long groupTableSize = groupTable.size();
    long groupIndex = 0;
    for (final DataRow row : groupTable) {
        for (int i = 0; i < pivotIdx.length; i++) {
            if (combPivots[i] == null) {
                combPivots[i] = new LinkedHashSet<String>();
            }
            final DataCell cell = row.getCell(pivotIdx[i]);
            if (cell.isMissing()) {
                if (!m_ignoreMissValues.getBooleanValue()) {
                    combPivots[i].add(cell.toString());
                }
            } else {
                combPivots[i].add(cell.toString());
            }
        }
        fillExec.setProgress(groupIndex++ / (double) groupTableSize, String.format("Group \"%s\" (%d/%d)", row.getKey(), groupIndex, groupTableSize));
        fillExec.checkCanceled();
    }
    final Map<String, Integer> pivotStarts = new LinkedHashMap<String, Integer>();
    final DataTableSpec outSpec = createOutSpec(groupSpec, combPivots, pivotStarts, orderPivotColumnName);
    exec.setProgress("Filling pivot table");
    BufferedDataTable pivotTable = fillPivotTable(groupTable, outSpec, pivotStarts, groupAndPivotExec.createSubExecutionContext(progMainTableFillPivots / progMainTotal), orderPivotColumnName);
    if (orderPivotColumnName != null) {
        exec.setMessage("Restoring row order");
        final SortedTable sortedPivotTable = new SortedTable(pivotTable, Arrays.asList(new String[] { orderPivotColumnName }), new boolean[] { true }, groupAndPivotExec.createSubExecutionContext(progMainTableRestoreSort / progMainTotal));
        pivotTable = sortedPivotTable.getBufferedDataTable();
        final ColumnRearranger colre = new ColumnRearranger(pivotTable.getSpec());
        colre.remove(orderPivotColumnName);
        pivotTable = exec.createColumnRearrangeTable(pivotTable, colre, exec.createSilentSubProgress(0.0));
    }
    // temp fix for bug 3286
    if (isProcessInMemory()) {
        // if process in memory is true, RowKey's needs to be re-computed
        final BufferedDataContainer rowkeyBuf = groupAndPivotExec.createSubExecutionContext(progMainTableReplaceRowKey / progMainTotal).createDataContainer(pivotTable.getSpec());
        long rowIndex = 0;
        for (DataRow row : pivotTable) {
            rowkeyBuf.addRowToTable(new DefaultRow(RowKey.createRowKey(rowIndex++), row));
        }
        rowkeyBuf.close();
        pivotTable = rowkeyBuf.getTable();
    }
    groupAndPivotExec.setProgress(1.0);
    /* Fill the 3rd port */
    exec.setMessage("Determining pivot totals");
    double progPivotTotal = 0.0;
    double progPivotGroup = 5.0;
    progPivotTotal += progPivotGroup;
    double progPivotFillMissing = 1.0;
    progPivotTotal += progPivotFillMissing;
    double progPivotFillPivots = 1.0;
    progPivotTotal += progPivotFillPivots;
    double progPivotOverallTotals = m_totalAggregation.getBooleanValue() ? 5.0 : 0.0;
    progPivotTotal += progPivotOverallTotals;
    // create pivot table only on pivot columns (for grouping)
    // perform pivoting: result in single line
    final GroupByTable rowGroup = createGroupByTable(pivotExec.createSubExecutionContext(progPivotGroup / progPivotTotal), table, m_pivotCols.getIncludeList(), isProcessInMemory(), isRetainOrder(), getColumnAggregators());
    final BufferedDataTable rowGroupTable = rowGroup.getBufferedTable();
    // fill group columns with missing cells
    final ColumnRearranger colre = new ColumnRearranger(rowGroupTable.getDataTableSpec());
    for (int i = 0; i < getGroupByColumns().size(); i++) {
        final DataColumnSpec cspec = outSpec.getColumnSpec(i);
        final CellFactory factory = new SingleCellFactory(cspec) {

            /**
             * {@inheritDoc}
             */
            @Override
            public DataCell getCell(final DataRow row) {
                return DataType.getMissingCell();
            }
        };
        colre.insertAt(i, factory);
    }
    final BufferedDataTable groupedRowTable = exec.createColumnRearrangeTable(rowGroupTable, colre, pivotExec.createSubExecutionContext(progPivotFillMissing / progPivotTotal));
    BufferedDataTable pivotRowsTable = fillPivotTable(groupedRowTable, outSpec, pivotStarts, pivotExec.createSubExecutionContext(progPivotFillPivots / progPivotTotal), null);
    if (orderPivotColumnName != null) {
        final ColumnRearranger colre2 = new ColumnRearranger(pivotRowsTable.getSpec());
        colre2.remove(orderPivotColumnName);
        pivotRowsTable = exec.createColumnRearrangeTable(pivotRowsTable, colre2, exec.createSilentSubProgress(0.0));
    }
    // total aggregation without grouping
    if (m_totalAggregation.getBooleanValue()) {
        @SuppressWarnings("unchecked") final GroupByTable totalGroup = createGroupByTable(pivotExec.createSubExecutionContext(progPivotOverallTotals / progPivotTotal), table, Collections.EMPTY_LIST, isProcessInMemory(), isRetainOrder(), getColumnAggregators());
        final BufferedDataTable totalGroupTable = totalGroup.getBufferedTable();
        final DataTableSpec pivotsRowsSpec = pivotRowsTable.getSpec();
        final DataTableSpec totalGroupSpec = totalGroupTable.getSpec();
        final DataTableSpec overallTotalSpec = new DataTableSpec(pivotsRowsSpec, totalGroupSpec);
        final BufferedDataContainer buf = exec.createDataContainer(overallTotalSpec);
        if (pivotRowsTable.size() > 0) {
            final List<DataCell> pivotTotalsCells = new ArrayList<DataCell>();
            final DataRow pivotsRow = pivotRowsTable.iterator().next();
            for (final DataCell cell : pivotsRow) {
                pivotTotalsCells.add(cell);
            }
            final DataRow totalGroupRow = totalGroupTable.iterator().next();
            for (final DataCell cell : totalGroupRow) {
                pivotTotalsCells.add(cell);
            }
            buf.addRowToTable(new DefaultRow(new RowKey("Totals"), pivotTotalsCells));
        }
        buf.close();
        pivotRowsTable = buf.getTable();
    }
    pivotExec.setProgress(1.0);
    /* Fill the 2nd port: important to create this last since it will create
         * the final hilite handler (mapping) for port #1 AND #2 (bug 3270) */
    exec.setMessage("Creating group totals");
    // create group table only on group columns; no pivoting
    final BufferedDataTable columnGroupTable = createGroupByTable(groupExec, table, getGroupByColumns()).getBufferedTable();
    return new PortObject[] { // pivot table
    pivotTable, // group totals
    columnGroupTable, // pivot and overall totals
    pivotRowsTable };
}

Example 4 with GroupByTable

use of org.knime.base.node.preproc.groupby.GroupByTable in project knime-core by knime.

the class NumericOutliersIntervalsCalculator method getGroupByTable.

/**
 * Constructs the group by table in accordance with the given settings.
 *
 * @param inTable the input data table
 * @param exec the execution context
 * @return the group by table w.r.t. the selected settings
 * @throws CanceledExecutionException if the user has canceled the execution
 */
private GroupByTable getGroupByTable(final BufferedDataTable inTable, final ExecutionContext exec) throws CanceledExecutionException {
    // get the global settings
    final GlobalSettings gSettings = getGlobalSettings(inTable);
    // create the column aggregators
    final ColumnAggregator[] agg = getAggretators(inTable.getDataTableSpec(), gSettings);
    // init and return the GroupByTable obeying the chosen memory settings
    final GroupByTable t;
    if (m_inMemory) {
        t = new MemoryGroupByTable(exec, inTable, Arrays.stream(m_groupColNames).collect(Collectors.toList()), agg, gSettings, false, COLUMN_NAME_POLICY, false);
    } else {
        t = new BigGroupByTable(exec, inTable, Arrays.stream(m_groupColNames).collect(Collectors.toList()), agg, gSettings, false, COLUMN_NAME_POLICY, false);
    }
    return t;
}

Example 5 with GroupByTable

use of org.knime.base.node.preproc.groupby.GroupByTable in project knime-core by knime.

the class CrosstabNodeModel method execute.

/**
 * {@inheritDoc}
 */
@Override
protected BufferedDataTable[] execute(final BufferedDataTable[] inData, final ExecutionContext exec) throws Exception {
    final BufferedDataTable table = inData[0];
    final List<String> cols = Arrays.asList(new String[] { m_settings.getRowVarColumn(), m_settings.getColVarColumn() });
    final GroupByTable groupTable = createGroupByTable(exec.createSubExecutionContext(0.6), table, cols);
    final BufferedDataTable freqTable = groupTable.getBufferedTable();
    // the index of the row variable in the group table
    final int rowVarI = 0;
    // the index of the column variable in the group table
    final int colVarI = 1;
    // the index of the frequency in the group table
    final int freqI = 2;
    final CrosstabTotals totals = computeTotals(freqTable, rowVarI, colVarI, freqI);
    final CrosstabProperties naming = CrosstabProperties.create(m_settings.getNamingVersion());
    final CrosstabStatisticsCalculator stats = new CrosstabStatisticsCalculator(freqTable, rowVarI, colVarI, freqI, totals, naming);
    stats.run(exec.createSubExecutionContext(0.1));
    final BufferedDataTable propsTable = stats.getTable();
    final int cellChiSquareI = propsTable.getDataTableSpec().findColumnIndex(naming.getCellChiSquareName());
    // create output table
    final BufferedDataContainer cont = exec.createDataContainer(createOutSpec(table.getSpec()));
    final RowIterator freqIter = freqTable.iterator();
    final RowIterator statsIter = propsTable.iterator();
    final Map<String, Integer> props = new LinkedHashMap<String, Integer>();
    for (int i = 0; i < m_settings.getProperties().size(); i++) {
        final String prop = m_settings.getProperties().get(i);
        props.put(prop, i + 2);
    }
    for (long i = 0; i < freqTable.size(); i++) {
        final DataCell[] cells = new DataCell[props.size() + 2];
        final DataRow freqRow = freqIter.next();
        // add the row variable
        final DataCell rowVar = freqRow.getCell(rowVarI);
        cells[0] = rowVar;
        // add the column variable
        final DataCell colVar = freqRow.getCell(colVarI);
        cells[1] = colVar;
        // the frequency
        final DataCell freqCell = freqRow.getCell(freqI);
        final double freq = freqCell.isMissing() ? 0.0 : ((DoubleValue) freqCell).getDoubleValue();
        addToCells(cells, props, naming.getFrequencyName(), new DoubleCell(freq));
        // the cell chi-square
        final DataRow statsRow = statsIter.next();
        addToCells(cells, props, naming.getCellChiSquareName(), statsRow.getCell(cellChiSquareI));
        // the total
        final double total = totals.getTotal();
        addToCells(cells, props, naming.getTotalCountName(), new DoubleCell(total));
        // the rowTotal
        final double rowTotal = totals.getRowTotal().get(rowVar);
        addToCells(cells, props, naming.getTotalRowCountName(), new DoubleCell(rowTotal));
        // the column Total
        final double colTotal = totals.getColTotal().get(colVar);
        addToCells(cells, props, naming.getTotalColCountName(), new DoubleCell(colTotal));
        // the percent = frequency / total
        final double percent = 100 * (freq / total);
        addToCells(cells, props, naming.getPercentName(), new DoubleCell(percent));
        // the row percent
        final double rowPercent = 0.0 == freq ? 0.0 : 100.0 * (freq / rowTotal);
        addToCells(cells, props, naming.getRowPercentName(), new DoubleCell(rowPercent));
        // the col percent
        final double colPercent = 0.0 == freq ? 0.0 : 100.0 * (freq / colTotal);
        addToCells(cells, props, naming.getColPercentName(), new DoubleCell(colPercent));
        // the expected frequency
        final double expected = 0.0 == total ? 0.0 : colTotal / total * rowTotal;
        addToCells(cells, props, naming.getExpectedFrequencyName(), new DoubleCell(expected));
        // the deviation (the difference of the frequency to the
        // expected frequency)
        final double deviation = freq - expected;
        addToCells(cells, props, naming.getDeviationName(), new DoubleCell(deviation));
        final DefaultRow row = new DefaultRow(RowKey.createRowKey(i), cells);
        cont.addRowToTable(row);
    }
    cont.close();
    m_outTable = cont.getTable();
    m_statistics = stats.getStatistics();
    m_statOutTable = stats.getStatistics().getTable();
    m_totals = totals;
    return new BufferedDataTable[] { m_outTable, m_statOutTable };
}