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The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model.

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/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.cassandra.db.rows;

import java.util.*;

import com.google.common.collect.Iterators;
import com.google.common.collect.PeekingIterator;

import org.apache.cassandra.schema.ColumnMetadata;
import org.apache.cassandra.schema.TableMetadata;
import org.apache.cassandra.db.*;
import org.apache.cassandra.db.partitions.PartitionStatisticsCollector;
import org.apache.cassandra.utils.MergeIterator;

/**
 * Static utilities to work on Row objects.
 */
public abstract class Rows
{
    private Rows() {}

    public static final Row EMPTY_STATIC_ROW = BTreeRow.emptyRow(Clustering.STATIC_CLUSTERING);

    /**
     * Creates a new simple row builder.
     *
     * @param metadata the metadata of the table this is a row of.
     * @param clusteringValues the value for the clustering columns of the row to add to this build. There may be no
     * values if either the table has no clustering column, or if you want to edit the static row. Note that as a
     * shortcut it is also allowed to pass a {@code Clustering} object directly, in which case that should be the
     * only argument.
     * @return a newly created builder.
     */
    public static Row.SimpleBuilder simpleBuilder(TableMetadata metadata, Object... clusteringValues)
    {
        return new SimpleBuilders.RowBuilder(metadata, clusteringValues);
    }

    private static class StatsAccumulation
    {
        private static final long COLUMN_INCR = 1L << 32;
        private static final long CELL_INCR = 1L;

        private static long accumulateOnCell(PartitionStatisticsCollector collector, Cell cell, long l)
        {
            Cells.collectStats(cell, collector);
            return l + CELL_INCR;
        }

        private static long accumulateOnColumnData(PartitionStatisticsCollector collector, ColumnData cd, long l)
        {
            if (cd.column().isSimple())
            {
                l = accumulateOnCell(collector, (Cell) cd, l) + COLUMN_INCR;
            }
            else
            {
                ComplexColumnData complexData = (ComplexColumnData)cd;
                collector.update(complexData.complexDeletion());
                int startingCells = unpackCellCount(l);
                l = complexData.accumulate(StatsAccumulation::accumulateOnCell, collector, l);
                if (unpackCellCount(l) > startingCells)
                    l += COLUMN_INCR;
            }
            return l;
        }

        private static int unpackCellCount(long v)
        {
            return (int) (v & 0xFFFFFFFFL);
        }

        private static int unpackColumnCount(long v)
        {
            return (int) (v >>> 32);
        }
    }

    /**
     * Collect statistics on a given row.
     *
     * @param row the row for which to collect stats.
     * @param collector the stats collector.
     * @return the total number of cells in {@code row}.
     */
    public static int collectStats(Row row, PartitionStatisticsCollector collector)
    {
        assert !row.isEmpty();

        collector.update(row.primaryKeyLivenessInfo());
        collector.update(row.deletion().time());

        long result = row.accumulate(StatsAccumulation::accumulateOnColumnData, collector, 0);

        collector.updateColumnSetPerRow(StatsAccumulation.unpackColumnCount(result));
        return StatsAccumulation.unpackCellCount(result);
    }

    /**
     * Given the result ({@code merged}) of merging multiple {@code inputs}, signals the difference between
     * each input and {@code merged} to {@code diffListener}.
     * 

* Note that this method doesn't only emit cells etc where there's a difference. The listener is informed * of every corresponding entity between the merged and input rows, including those that are equal. * * @param diffListener the listener to which to signal the differences between the inputs and the merged result. * @param merged the result of merging {@code inputs}. * @param inputs the inputs whose merge yielded {@code merged}. */ @SuppressWarnings("resource") public static void diff(RowDiffListener diffListener, Row merged, Row...inputs) { Clustering clustering = merged.clustering(); LivenessInfo mergedInfo = merged.primaryKeyLivenessInfo().isEmpty() ? null : merged.primaryKeyLivenessInfo(); Row.Deletion mergedDeletion = merged.deletion().isLive() ? null : merged.deletion(); for (int i = 0; i < inputs.length; i++) { Row input = inputs[i]; LivenessInfo inputInfo = input == null || input.primaryKeyLivenessInfo().isEmpty() ? null : input.primaryKeyLivenessInfo(); Row.Deletion inputDeletion = input == null || input.deletion().isLive() ? null : input.deletion(); if (mergedInfo != null || inputInfo != null) diffListener.onPrimaryKeyLivenessInfo(i, clustering, mergedInfo, inputInfo); if (mergedDeletion != null || inputDeletion != null) diffListener.onDeletion(i, clustering, mergedDeletion, inputDeletion); } List> inputIterators = new ArrayList<>(1 + inputs.length); inputIterators.add(merged.iterator()); for (Row row : inputs) inputIterators.add(row == null ? Collections.emptyIterator() : row.iterator()); Iterator iter = MergeIterator.get(inputIterators, ColumnData.comparator, new MergeIterator.Reducer() { ColumnData mergedData; ColumnData[] inputDatas = new ColumnData[inputs.length]; public void reduce(int idx, ColumnData current) { if (idx == 0) mergedData = current; else inputDatas[idx - 1] = current; } protected Object getReduced() { for (int i = 0 ; i != inputDatas.length ; i++) { ColumnData input = inputDatas[i]; if (mergedData != null || input != null) { ColumnMetadata column = (mergedData != null ? mergedData : input).column; if (column.isSimple()) { diffListener.onCell(i, clustering, (Cell) mergedData, (Cell) input); } else { ComplexColumnData mergedData = (ComplexColumnData) this.mergedData; ComplexColumnData inputData = (ComplexColumnData) input; if (mergedData == null) { // Everything in inputData has been shadowed if (!inputData.complexDeletion().isLive()) diffListener.onComplexDeletion(i, clustering, column, null, inputData.complexDeletion()); for (Cell inputCell : inputData) diffListener.onCell(i, clustering, null, inputCell); } else if (inputData == null) { // Everything in inputData is new if (!mergedData.complexDeletion().isLive()) diffListener.onComplexDeletion(i, clustering, column, mergedData.complexDeletion(), null); for (Cell mergedCell : mergedData) diffListener.onCell(i, clustering, mergedCell, null); } else { if (!mergedData.complexDeletion().isLive() || !inputData.complexDeletion().isLive()) diffListener.onComplexDeletion(i, clustering, column, mergedData.complexDeletion(), inputData.complexDeletion()); PeekingIterator> mergedCells = Iterators.peekingIterator(mergedData.iterator()); PeekingIterator> inputCells = Iterators.peekingIterator(inputData.iterator()); while (mergedCells.hasNext() && inputCells.hasNext()) { int cmp = column.cellPathComparator().compare(mergedCells.peek().path(), inputCells.peek().path()); if (cmp == 0) diffListener.onCell(i, clustering, mergedCells.next(), inputCells.next()); else if (cmp < 0) diffListener.onCell(i, clustering, mergedCells.next(), null); else // cmp > 0 diffListener.onCell(i, clustering, null, inputCells.next()); } while (mergedCells.hasNext()) diffListener.onCell(i, clustering, mergedCells.next(), null); while (inputCells.hasNext()) diffListener.onCell(i, clustering, null, inputCells.next()); } } } } return null; } protected void onKeyChange() { mergedData = null; Arrays.fill(inputDatas, null); } }); while (iter.hasNext()) iter.next(); } public static Row merge(Row existing, Row update) { return merge(existing, update, ColumnData.noOp); } /** * Merges two rows. In addition to reconciling the cells in each row, the liveness info, and deletion times for * the row and complex columns are also merged. *

* Note that this method assumes that the provided rows can meaningfully be reconciled together. That is, * that the rows share the same clustering value, and belong to the same partition. * * @param existing * @param update * * @return the row resulting from the merge. */ public static Row merge(Row existing, Row update, ColumnData.PostReconciliationFunction onReconcile) { assert existing instanceof BTreeRow; assert update instanceof BTreeRow; return BTreeRow.merge((BTreeRow) existing, (BTreeRow) update, onReconcile); } /** * Returns a row that is obtained from the given existing row by removing everything that is shadowed by data in * the update row. In other words, produces the smallest result row such that * {@code merge(result, update, nowInSec) == merge(existing, update, nowInSec)} after filtering by rangeDeletion. * * @param existing source row * @param update shadowing row * @param rangeDeletion extra {@code DeletionTime} from covering tombstone */ public static Row removeShadowedCells(Row existing, Row update, DeletionTime rangeDeletion) { Row.Builder builder = BTreeRow.sortedBuilder(); Clustering clustering = existing.clustering(); builder.newRow(clustering); DeletionTime deletion = update.deletion().time(); if (rangeDeletion.supersedes(deletion)) deletion = rangeDeletion; LivenessInfo existingInfo = existing.primaryKeyLivenessInfo(); if (!deletion.deletes(existingInfo)) builder.addPrimaryKeyLivenessInfo(existingInfo); Row.Deletion rowDeletion = existing.deletion(); if (!deletion.supersedes(rowDeletion.time())) builder.addRowDeletion(rowDeletion); Iterator a = existing.iterator(); Iterator b = update.iterator(); ColumnData nexta = a.hasNext() ? a.next() : null, nextb = b.hasNext() ? b.next() : null; while (nexta != null) { int comparison = nextb == null ? -1 : nexta.column.compareTo(nextb.column); if (comparison <= 0) { ColumnData cura = nexta; ColumnMetadata column = cura.column; ColumnData curb = comparison == 0 ? nextb : null; if (column.isSimple()) { Cells.addNonShadowed((Cell) cura, (Cell) curb, deletion, builder); } else { ComplexColumnData existingData = (ComplexColumnData) cura; ComplexColumnData updateData = (ComplexColumnData) curb; DeletionTime existingDt = existingData.complexDeletion(); DeletionTime updateDt = updateData == null ? DeletionTime.LIVE : updateData.complexDeletion(); DeletionTime maxDt = updateDt.supersedes(deletion) ? updateDt : deletion; if (existingDt.supersedes(maxDt)) { builder.addComplexDeletion(column, existingDt); maxDt = existingDt; } Iterator> existingCells = existingData.iterator(); Iterator> updateCells = updateData == null ? null : updateData.iterator(); Cells.addNonShadowedComplex(column, existingCells, updateCells, maxDt, builder); } nexta = a.hasNext() ? a.next() : null; if (curb != null) nextb = b.hasNext() ? b.next() : null; } else { nextb = b.hasNext() ? b.next() : null; } } Row row = builder.build(); return row != null && !row.isEmpty() ? row : null; } }





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