Files
OpenRA/OpenRA.Mods.Common/Pathfinder/PathSearch.cs
RoosterDragon 519be4374c Fixed pooling of layers used for pathfinding.
The previous implementation:
- Was failing to dispose of pooled layers.
- Was using a finalizer to allow undisposed layers to be reused.

This means all pooled layers are kept alive indefinitely until the map changes. If the finalizer is slow for any reason then the pathfiinder will allocate new layers when the pool runs out. Since these new layers are eventually stuffed back into the pool when the finalizer does run, this can theoretically leak unbounded memory until the pool goes out of scope. In practice it would leak tens of megabytes.

The new implementation ensures layers are disposed and pooled correctly to allow proper memory reuse. It also introduces some safeguards against memory leaks:
- A cap is set on the number of pooled layers. If more concurrent layers are needed than this, then the excess layers will not be pooled but instead be allowed to be garbage collected.
- No finalizer. An implementation that fails to call dispose simply allows the layer to be garbage collected instead.
2015-09-16 21:25:46 +01:00

161 lines
4.9 KiB
C#

#region Copyright & License Information
/*
* Copyright 2007-2015 The OpenRA Developers (see AUTHORS)
* This file is part of OpenRA, which is free software. It is made
* available to you under the terms of the GNU General Public License
* as published by the Free Software Foundation. For more information,
* see COPYING.
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using System.Runtime.CompilerServices;
using OpenRA.Mods.Common.Traits;
using OpenRA.Primitives;
namespace OpenRA.Mods.Common.Pathfinder
{
public sealed class PathSearch : BasePathSearch
{
static readonly ConditionalWeakTable<World, CellInfoLayerPool> LayerPoolTable = new ConditionalWeakTable<World, CellInfoLayerPool>();
static readonly ConditionalWeakTable<World, CellInfoLayerPool>.CreateValueCallback CreateLayerPool = world => new CellInfoLayerPool(world.Map);
static CellInfoLayerPool LayerPoolForWorld(World world)
{
return LayerPoolTable.GetValue(world, CreateLayerPool);
}
public override IEnumerable<Pair<CPos, int>> Considered
{
get { return considered; }
}
LinkedList<Pair<CPos, int>> considered;
#region Constructors
private PathSearch(IGraph<CellInfo> graph)
: base(graph)
{
considered = new LinkedList<Pair<CPos, int>>();
}
public static IPathSearch Search(World world, MobileInfo mi, Actor self, bool checkForBlocked, Func<CPos, bool> goalCondition)
{
var graph = new PathGraph(LayerPoolForWorld(world), mi, self, world, checkForBlocked);
var search = new PathSearch(graph);
search.isGoal = goalCondition;
search.heuristic = loc => 0;
return search;
}
public static IPathSearch FromPoint(World world, MobileInfo mi, Actor self, CPos from, CPos target, bool checkForBlocked)
{
var graph = new PathGraph(LayerPoolForWorld(world), mi, self, world, checkForBlocked);
var search = new PathSearch(graph)
{
heuristic = DefaultEstimator(target)
};
search.isGoal = loc =>
{
var locInfo = search.Graph[loc];
return locInfo.EstimatedTotal - locInfo.CostSoFar == 0;
};
if (world.Map.Contains(from))
search.AddInitialCell(from);
return search;
}
public static IPathSearch FromPoints(World world, MobileInfo mi, Actor self, IEnumerable<CPos> froms, CPos target, bool checkForBlocked)
{
var graph = new PathGraph(LayerPoolForWorld(world), mi, self, world, checkForBlocked);
var search = new PathSearch(graph)
{
heuristic = DefaultEstimator(target)
};
search.isGoal = loc =>
{
var locInfo = search.Graph[loc];
return locInfo.EstimatedTotal - locInfo.CostSoFar == 0;
};
foreach (var sl in froms.Where(sl => world.Map.Contains(sl)))
search.AddInitialCell(sl);
return search;
}
protected override void AddInitialCell(CPos location)
{
var cost = heuristic(location);
Graph[location] = new CellInfo(0, cost, location, CellStatus.Open);
var connection = new GraphConnection(location, cost);
OpenQueue.Add(connection);
StartPoints.Add(connection);
considered.AddLast(new Pair<CPos, int>(location, 0));
}
#endregion
/// <summary>
/// This function analyzes the neighbors of the most promising node in the Pathfinding graph
/// using the A* algorithm (A-star) and returns that node
/// </summary>
/// <returns>The most promising node of the iteration</returns>
public override CPos Expand()
{
var currentMinNode = OpenQueue.Pop().Destination;
var currentCell = Graph[currentMinNode];
Graph[currentMinNode] = new CellInfo(currentCell.CostSoFar, currentCell.EstimatedTotal, currentCell.PreviousPos, CellStatus.Closed);
if (Graph.CustomCost != null && Graph.CustomCost(currentMinNode) == Constants.InvalidNode)
return currentMinNode;
foreach (var connection in Graph.GetConnections(currentMinNode))
{
// Calculate the cost up to that point
var gCost = currentCell.CostSoFar + connection.Cost;
var neighborCPos = connection.Destination;
var neighborCell = Graph[neighborCPos];
// Cost is even higher; next direction:
if (neighborCell.Status == CellStatus.Closed || gCost >= neighborCell.CostSoFar)
continue;
// Now we may seriously consider this direction using heuristics. If the cell has
// already been processed, we can reuse the result (just the difference between the
// estimated total and the cost so far
int hCost;
if (neighborCell.Status == CellStatus.Open)
hCost = neighborCell.EstimatedTotal - neighborCell.CostSoFar;
else
hCost = heuristic(neighborCPos);
var estimatedCost = gCost + hCost;
Graph[neighborCPos] = new CellInfo(gCost, estimatedCost, currentMinNode, CellStatus.Open);
if (neighborCell.Status != CellStatus.Open)
OpenQueue.Add(new GraphConnection(neighborCPos, estimatedCost));
if (Debug)
{
if (gCost > MaxCost)
MaxCost = gCost;
considered.AddLast(new Pair<CPos, int>(neighborCPos, gCost));
}
}
return currentMinNode;
}
}
}