Java tutorial
/* * Druid - a distributed column store. * Copyright (C) 2012 Metamarkets Group Inc. * * This program is free software; you can redistribute it and/or * modify it under the terms of the GNU General Public License * as published by the Free Software Foundation; either version 2 * of the License, or (at your option) any later version. * * This program is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with this program; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. */ package com.metamx.druid.master; import com.google.common.collect.MinMaxPriorityQueue; import com.metamx.common.Pair; import com.metamx.druid.client.DataSegment; import com.metamx.emitter.EmittingLogger; import org.joda.time.DateTime; import org.joda.time.Interval; import java.util.Comparator; import java.util.List; public class CostBalancerStrategy implements BalancerStrategy { private static final EmittingLogger log = new EmittingLogger(CostBalancerStrategy.class); private static final int DAY_IN_MILLIS = 1000 * 60 * 60 * 24; private static final int SEVEN_DAYS_IN_MILLIS = 7 * DAY_IN_MILLIS; private static final int THIRTY_DAYS_IN_MILLIS = 30 * DAY_IN_MILLIS; private final DateTime referenceTimestamp; public CostBalancerStrategy(DateTime referenceTimestamp) { this.referenceTimestamp = referenceTimestamp; } @Override public ServerHolder findNewSegmentHomeReplicator(DataSegment proposalSegment, List<ServerHolder> serverHolders) { ServerHolder holder = chooseBestServer(proposalSegment, serverHolders, false).rhs; if (holder != null && !holder.isServingSegment(proposalSegment)) { return holder; } return null; } @Override public ServerHolder findNewSegmentHomeBalancer(DataSegment proposalSegment, List<ServerHolder> serverHolders) { return chooseBestServer(proposalSegment, serverHolders, true).rhs; } /** * For assignment, we want to move to the lowest cost server that isn't already serving the segment. * * @param proposalSegment A DataSegment that we are proposing to move. * @param serverHolders An iterable of ServerHolders for a particular tier. * * @return A ServerHolder with the new home for a segment. */ private Pair<Double, ServerHolder> chooseBestServer(final DataSegment proposalSegment, final Iterable<ServerHolder> serverHolders, boolean includeCurrentServer) { Pair<Double, ServerHolder> bestServer = Pair.of(Double.POSITIVE_INFINITY, null); final long proposalSegmentSize = proposalSegment.getSize(); for (ServerHolder server : serverHolders) { if (includeCurrentServer || !server.isServingSegment(proposalSegment)) { /** Don't calculate cost if the server doesn't have enough space or is loading the segment */ if (proposalSegmentSize > server.getAvailableSize() || server.isLoadingSegment(proposalSegment)) { continue; } /** The contribution to the total cost of a given server by proposing to move the segment to that server is... */ double cost = 0f; /** the sum of the costs of other (exclusive of the proposalSegment) segments on the server */ for (DataSegment segment : server.getServer().getSegments().values()) { if (!proposalSegment.equals(segment)) { cost += computeJointSegmentCosts(proposalSegment, segment); } } /** plus the costs of segments that will be loaded */ for (DataSegment segment : server.getPeon().getSegmentsToLoad()) { cost += computeJointSegmentCosts(proposalSegment, segment); } if (cost < bestServer.lhs) { bestServer = Pair.of(cost, server); } } } return bestServer; } /** * This defines the unnormalized cost function between two segments. There is a base cost given by * the minimum size of the two segments and additional penalties. * recencyPenalty: it is more likely that recent segments will be queried together * dataSourcePenalty: if two segments belong to the same data source, they are more likely to be involved * in the same queries * gapPenalty: it is more likely that segments close together in time will be queried together * * @param segment1 The first DataSegment. * @param segment2 The second DataSegment. * * @return The joint cost of placing the two DataSegments together on one node. */ public double computeJointSegmentCosts(final DataSegment segment1, final DataSegment segment2) { final Interval gap = segment1.getInterval().gap(segment2.getInterval()); final double baseCost = Math.min(segment1.getSize(), segment2.getSize()); double recencyPenalty = 1; double dataSourcePenalty = 1; double gapPenalty = 1; if (segment1.getDataSource().equals(segment2.getDataSource())) { dataSourcePenalty = 2; } double maxDiff = Math.max(referenceTimestamp.getMillis() - segment1.getInterval().getEndMillis(), referenceTimestamp.getMillis() - segment2.getInterval().getEndMillis()); double segment1diff = referenceTimestamp.getMillis() - segment1.getInterval().getEndMillis(); double segment2diff = referenceTimestamp.getMillis() - segment2.getInterval().getEndMillis(); if (segment1diff < SEVEN_DAYS_IN_MILLIS && segment2diff < SEVEN_DAYS_IN_MILLIS) { recencyPenalty = (2 - segment1diff / SEVEN_DAYS_IN_MILLIS) * (2 - segment2diff / SEVEN_DAYS_IN_MILLIS); } /** gap is null if the two segment intervals overlap or if they're adjacent */ if (gap == null) { gapPenalty = 2; } else { long gapMillis = gap.toDurationMillis(); if (gapMillis < THIRTY_DAYS_IN_MILLIS) { gapPenalty = 2 - gapMillis / THIRTY_DAYS_IN_MILLIS; } } final double cost = baseCost * recencyPenalty * dataSourcePenalty * gapPenalty; return cost; } public BalancerSegmentHolder pickSegmentToMove(final List<ServerHolder> serverHolders) { ReservoirSegmentSampler sampler = new ReservoirSegmentSampler(); return sampler.getRandomBalancerSegmentHolder(serverHolders); } /** * Calculates the initial cost of the Druid segment configuration. * * @param serverHolders A list of ServerHolders for a particular tier. * * @return The initial cost of the Druid tier. */ public double calculateInitialTotalCost(final List<ServerHolder> serverHolders) { double cost = 0; for (ServerHolder server : serverHolders) { DataSegment[] segments = server.getServer().getSegments().values().toArray(new DataSegment[] {}); for (int i = 0; i < segments.length; ++i) { for (int j = i; j < segments.length; ++j) { cost += computeJointSegmentCosts(segments[i], segments[j]); } } } return cost; } /** * Calculates the cost normalization. This is such that the normalized cost is lower bounded * by 1 (e.g. when each segment gets its own compute node). * * @param serverHolders A list of ServerHolders for a particular tier. * * @return The normalization value (the sum of the diagonal entries in the * pairwise cost matrix). This is the cost of a cluster if each * segment were to get its own compute node. */ public double calculateNormalization(final List<ServerHolder> serverHolders) { double cost = 0; for (ServerHolder server : serverHolders) { for (DataSegment segment : server.getServer().getSegments().values()) { cost += computeJointSegmentCosts(segment, segment); } } return cost; } @Override public void emitStats(String tier, MasterStats stats, List<ServerHolder> serverHolderList) { final double initialTotalCost = calculateInitialTotalCost(serverHolderList); final double normalization = calculateNormalization(serverHolderList); final double normalizedInitialCost = initialTotalCost / normalization; stats.addToTieredStat("initialCost", tier, (long) initialTotalCost); stats.addToTieredStat("normalization", tier, (long) normalization); stats.addToTieredStat("normalizedInitialCostTimesOneThousand", tier, (long) (normalizedInitialCost * 1000)); log.info("[%s]: Initial Total Cost: [%f], Normalization: [%f], Initial Normalized Cost: [%f]", tier, initialTotalCost, normalization, normalizedInitialCost); } }