Finding an optimal db_block_size
Hi,
I want to find an optimal DB_BLOCK_SIZE by running my tests against 4k,8k and 16k block sizes. I have studied one huge otn forum link regarding db_block_sizes but still I'm confused. I've not got much from that link.
So, I want to conduct my own tests for my research about finding an optimal db block size. I've few questions which I want to be sure before running my tests. So that later when I put my results here for expert opinions, tests should be proper tests and that I note proper things regarding my testing.
First of all is it ok to create 4k and 16k tablespaces in my 8k block size 11g (11.1.0.6.0) db or I've to create separate 4k and 16k databases. Does it matter or no difference whatever way is chosen?
Secondly, in case if i will have to create separate databases of 4k and 16k, do I also need to set db_file_multiblock_read_count? or what, if I do not need to create separate dbs. something like this:
2k block * 512 MBRC = 1MB
4k block * 256 MBRC = 1MB
8k block * 128 MBRC = 1MB
16k block * 64 MBRC = 1MB
to equalize the testing or Oracle itself will set value for db_file_multiblock_read_count.
Currently, db_block_size=8192 and db_file_multiblock_read_count=64
Thirdly, what things to consider for proper testing like ELAPSED TIME (that the query is faster in particular db_block_size) or anything else?
Thanks alot.
Regards
John-M wrote:
I would be very surprised if changing block size could make that much of an improvement. Perhaps you should explain on what basis you believe changing the block size will improve performance instead of say changing the OS, changing the server, replacing the network cards, changing one of the hundreds of initialization parameters or any combination of all of these.
Or are you just changing something and measuring elapsed time because you can, instead of finding something that is slow, understanding why and then addressing the specific problem?why you would be surprised, ofcourse changing block size can make much improvement. I've done some tests already but will post my results after doing them properly. Well I've interests in this topic, I can explain later when I'm done with this work that changing block size can improve performance or not.See this: http://richardfoote.wordpress.com/category/index-block-size/
>
Seeing the other things like u said server,OS etc could be a secondary issue. I'm testing everything on the same machine. H/w, OS everything will be same for each block size. So, I can see the difference.
You can see an almost 100% performance improvement on that basis simply by running the query again,Yeah that I know. It's coming from the cache so obviously there will be 100% improvement. But what do u want to say by this thing...running the query again.....it's useless...... I always run only one time,second time it'll come from cache so there is no need to note down the elapsed time.Ohhhhh, this could be wrong on so many levels. If you just want a single user system reading everything from a big dumb disk, just use Access or something, you don't need Oracle.
Modern systems have cache in several places, and Oracle is biased towards optimistic write and concurrency. To find an optimal block size, you need to define test conditions appropriate to your use under load. Dan and Hans have pointed out test harnesses and many other issues, not the least of which is configuration dependent bugs. Running things only once is like saying how fast your PC is by how long it takes to boot up. That's just irrelevant to how fast it is when you are running things.
>
Even in my big table (800MB) tables, I delete each n every thing, shutdown/restart the db and restart my computer that there should be no doubt in my mind that data is coming from cache/ram etc during my second block size run.800MB is not big. I've lost thumb drives bigger than that.
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Space utilization and optimal row size in Data Blocks in Oracle 11g
Hi,
My main concern till now is to find the Optimal no. of rows/tuples per one oracle data block of size 8192. For that purpose i'm doing different kind of testing.
I created one table:
SQL> create table t5
2 (x char(2000));
Table created.
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why 3 block are EMPTY_BLOCKS allocated all the time?
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How can I see this CHAIN_CNT column value other than 0?
How can actually I find the optimal no. of rows/tuples in 1 data block that will not increase OVERHEAD on the system.
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Thanks in Advance.
Best Regards,
Kamkamy555 wrote:
If you want to suggest something it'll be nice of yo.I can't disclose my main concern :)If you can't disclose what you mean by "optimal" and you can't disclose what "overhead" you are concerned about, I'm not sure that anyone could answer your question.
In this scenerio 3 rows (each of around 2006 bytes) are inserted into into one BLOCK of 8192 i.e. 8192-6006=2186. 2186 is the PCTFREE or
what?PCTFREE is a percentage. You haven't specified what you set it to, but that decreases the space in a block available for inserts to 8192 * (1 - PCTFREE/100).
How can I see this CHAIN_CNT column value other than 0?Why do you believe there would be chained rows? You would need to use the ANALYZE command to populate the CHAIN_CNT column.
How can actually I find the optimal no. of rows/tuples in 1 data block that will not increase OVERHEAD on the system.Since you can't disclose what "optimal" means or what "overhead" you're concerned with, I don't see how this question could be answered.
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Path Finder in a 2D Grid Map With Different Terrain Types
I have been thinking for a while on path finding game algoritms and I can up with one idea witch I want to publish. The goal of my project is when I have a 2 dimensional grid map where squares can have different movement cost, like in Civilization II, to find the shortest way from one point in the map to another. I've used the Breathed First Search Engine. If you are not familiar to this search engine it is better to read about it first because I am not fcusing on it and I assume that you now how it works. You can read about it at the book "Practical Artificial Intelligence Programming in Java" writen by Mark Watson, witch is freely distributed at www.markwatson.com.
Actually the idea of this 2D grid path finder is to use a third dimension witch have a size equal to the highest movement cost among all terrain types. This helps solving the problem with the different movement cost of the squates. By adding this abstract third dimension it is posible to use the Breadth First Search Engine.
I this example the movementcost of a terrain type is always the same, no matter from witch square to with are you going (like in Civilization II but I haven't included roads or railroads). For example if you want to go from one square A to another square B with movement cost X (A and B are attached) you must go "up stairs" in the third dimension X - 1 times and then move to square B. But when you step on square B you are again at the lowest floor. So if you want to come back to the previous square A and it have movement cost Y first you must go floor Y and then jump in square A. And now you are again at the lowest floor at square A. When you move from one square to another you go always at the lowest floor. This is the way I handle with different movement costs.
When you find the path to the goal point it is in 3 dimensions. So you must just project it in the 2D map and that's all you have the shortest path.
I am sure this is not the best way to code this search engine but this is just the first scratch with no optimisation and so on. If I make a 100x100 randomly generated map it takes on my configuration(400Mhz Pentium II CPU with ASUS P2B MotherBoard on 100 MHz and 256 MB SD RAM on 133 MHz but because of my MB on 100MHz) around 1000 miliseconds (1000 miliseconds = 1 second) to find the shortest path from (1, 1) to (100, 100) witch is pretty good compare to the goTo function in Civilization II witch does not finds the shortest path at all and have made hundrets of gamers angry. This is amazing that nowadays there are so many games with bad path finding.
This project includes:
1. The PathFinder class witch does the jub.
2. The Map class witch has a generator for a random map in it.
3. The class TerrainType, every square on the map is based on this class.
4. The class TerrainTypes witch is the set of all terrain types used in the map.
5. The class PathFinderTest witch just test the path finder.
To test this project put all files in one directory and run PathFinderTest.java.
Map.java:
import java.util.Vector;
import java.util.Random;
//This class just creates a random map and keeps it. I will not comment on this.
class Map {
//here is kept the information about the terrain types placed in the map. Where
//every terrain type has a specific movement cost.
private int[][] terrain;
public TerrainTypes terrainTypes;
private int landMass;
private int width;
private int height;
private int highestMovementCost;
public Map(int aWidth, int aHeight) {
width = aWidth;
height = aHeight;
terrainTypes = new TerrainTypes();
highestMovementCost = terrainTypes.getHighestMovementCost();
terrain = new int[width][height];
landMass = 0;
generateRandomMap();
public void clearGoalAndStartLocFromWater(int sx, int sy, int gx, int gy) {
terrain[gx][gy] = 0;
terrain[sx][sy] = 0;
private void expandWater() {
int waterConstant = 40;
int waterExpansion = 2;
int[][] moreWater = new int[width][height];
Random randomizer = new Random();
for (int t = 0; waterExpansion > t; t++) {
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
if (i + 1 >= 0 && j >= 0 && i + 1 < width && j < height) {
if (terrain[i + 1][j] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i + 1][j] = 1;
if (i + 1 >= 0 && j - 1 >= 0 && i + 1 < width && j - 1 < height) {
if (terrain[i + 1][j - 1] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i + 1][j - 1] = 1;
if (i >= 0 && j - 1 >= 0 && i < width && j - 1 < height) {
if (terrain[i][j - 1] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i][j - 1] = 1;
if (i - 1 >= 0 && j - 1 >= 0 && i - 1 < width && j - 1 < height) {
if (terrain[i - 1][j - 1] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i - 1][j - 1] = 1;
if (i - 1 >= 0 && j >= 0 && i - 1 < width && j < height) {
if (terrain[i - 1][j] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i - 1][j] = 1;
if (i - 1 >= 0 && j + 1 >= 0 && i - 1 < width && j + 1 < height) {
if (terrain[i - 1][j + 1] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i - 1][j + 1] = 1;
if (i >= 0 && j + 1 >= 0 && i < width && j + 1 < height) {
if (terrain[i][j + 1] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i][j + 1] = 1;
if (i + 1 >= 0 && j + 1 >= 0 && i + 1 < width && j + 1 < height) {
if (terrain[i + 1][j + 1] != 4) {
if (randomizer.nextInt(waterConstant) == 0)
moreWater[i + 1][j + 1] = 1;
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
if (moreWater[i][j] == 1) {
terrain[i][j] = 4;
private void generateRandomMap() {
Random randomizer = new Random();
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
if (randomizer.nextInt(3) == 1)
terrain[i][j] = 0;
else if (randomizer.nextInt(2) == 1)
terrain[i][j] = 1;
else if (randomizer.nextInt(2) == 1)
terrain[i][j] = 3;
else if (randomizer.nextInt(2) == 1)
terrain[i][j] = 2;
else if (randomizer.nextInt(2) == 1)
terrain[i][j] = 2;
else if (randomizer.nextInt(2) == 1)
terrain[i][j] = 1;
else if (randomizer.nextInt(2) == 1)
terrain[i][j] = 3;
else
terrain[i][j] = randomizer.nextInt(5);
expandWater();
for (int i = 0; i < width; i++) {
for (int j = 0; j < height; j++) {
if (terrain[i][j] != 0)
landMass++;
public int getMapHeight() {
return height;
public int getMapWidth() {
return width;
public int getSquareID(int x, int y) {
return terrain[x][y];
public int getSquareMovementCost(int x, int y) {
return terrainTypes.getMovementCost(terrain[x][y]);
}PathFinder.java:
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.util.Vector;
public class PathFinder {
private BufferedReader consoleReader = new BufferedReader(new InputStreamReader(System.in));
//The array t3D[][] represents the 2D square map where t3D.leght = map width
//and t3D[x].lenght = map width (-1 < x < t3D.leght). The third dimension
//is refered to the square's movement cost, witch is definite by terrain.
//The fourth dimension will be with lenght = 3. When running the search engine
//(expanding the explored squares) this 3 values will keep the position of
//the previous square in 3 dimension, witch are width, height and the maximum
//movement cost among all squares.
private int[][][][] squares3DReference;
//Keeps information witch squares are visited.
private boolean[][][] visitedSquares;
private Map map;
//this is the queue used in the Breathed First Seatch.
private Vector queue3D;
//Here is saved the shortest path
private Vector path2D;
private int highestMovementCost;
public PathFinder(Map aMap) {
map = aMap;
queue3D = new Vector();
path2D = new Vector();
squares3DReference = new int[map.getMapWidth()][map.getMapHeight()][][];
visitedSquares = new boolean[map.getMapWidth()][map.getMapHeight()][];
highestMovementCost = map.terrainTypes.getHighestMovementCost();
buildAbstract3DTerrain();
private void buildAbstract3DTerrain() {
for (int x = 0; x < map.getMapWidth(); x++) {
for (int y = 0; y <map.getMapHeight(); y++) {
int movementCost = map.terrainTypes.getMovementCost(map.getSquareID(x, y));
if ( movementCost > 0) {
visitedSquares[x][y] = new boolean[highestMovementCost];
squares3DReference[x][y] = new int[highestMovementCost][3];
for (int z = 0; z < highestMovementCost; z++) {
for (int t = 0; t < 3; t++) {
squares3DReference[x][y][z][t] = -1;
private boolean isMoveValid(int x, int y, int z, int x2, int y2, int z2) {
if ( x < 0 || y < 0 || z < 0 || x2 < 0 || y2 < 0 || z2 < 0 || x >= map.getMapWidth() || y >= map.getMapHeight() || z >= highestMovementCost || x2 >= map.getMapWidth() || y2 >= map.getMapHeight() || z2 >= highestMovementCost)
return false;
if (map.terrainTypes.getMovementCost(map.getSquareID(x2, y2)) < 1)
return false;
if (visitedSquares[x2][y2][z2])
return false;
if (x == x2 && y == y2)
return true;
else {
if (z == map.terrainTypes.getMovementCost(map.getSquareID(x2, y2)) - 1)
return true;
else
return false;
private void clearPreviousSearchData() {
queue3D.clear();
path2D.clear();
for (int x = 0; x < map.getMapWidth(); x++) {
for (int y = 0; y < map.getMapHeight(); y++) {
if (squares3DReference[x][y] != null) {
for (int z = 0; z < highestMovementCost; z++) {
visitedSquares[x][y][z] = false;
for (int t = 0; t < 3; t++) {
squares3DReference[x][y][z][t] = -1;
private Vector copyPath2D() {
Vector path = new Vector();
for (int i = 0; i < path2D.size(); i++) {
path.add(path2D.get(i));
return path;
public Vector findPath(int sX, int sY, int gX, int gY) {
int head = 0;
int tail = 0;
int x = sX;
int y = sY;
int z = 0;
visitedSquares[x][y][z] = true;
mainLoop: {
while (tail <= head) {
int[][] moves = getPosibleMoves(x, y, z);
for (int i = 0; i < 9; i++) {
if (moves[i] != null) {
squares3DReference[moves[0]][moves[i][1]][moves[i][2]][0] = x;
squares3DReference[moves[i][0]][moves[i][1]][moves[i][2]][1] = y;
squares3DReference[moves[i][0]][moves[i][1]][moves[i][2]][2] = z;
queue3D.add(moves[i]);
if (moves[i][0] == gX && moves[i][1] == gY) {
break mainLoop;
visitedSquares[moves[i][0]][moves[i][1]][moves[i][2]] = true;
head++;
if (queue3D.size() == 0 || queue3D.size() == tail)
break mainLoop;
int[] nextInQueue = ((int[]) queue3D.get(tail));
x = nextInQueue[0];
y = nextInQueue[1];
z = nextInQueue[2];
tail++;
if (squares3DReference[gX][gY][0][0] == -1) {
clearPreviousSearchData();
return path2D;
fillpath2D(sX, sY, gX, gY);
Vector path = copyPath2D();
clearPreviousSearchData();
return path;
private int[][] getPosibleMoves(int x, int y, int z) {
int[][] moves = new int[9][3];
if (isMoveValid(x, y, z, x + 1, y, 0)) {
moves[0][0] = x + 1;
moves[0][1] = y;
moves[0][2] = 0;
else
moves[0] = null;
if (isMoveValid(x, y, z, x + 1, y - 1, 0)) {
moves[1][0] = x + 1;
moves[1][1] = y - 1;
moves[1][2] = 0;
else
moves[1] = null;
if (isMoveValid(x, y, z, x, y - 1, 0)) {
moves[2][0] = x;
moves[2][1] = y - 1;
moves[2][2] = 0;
else
moves[2] = null;
if (isMoveValid(x, y, z, x - 1, y - 1, 0)) {
moves[3][0] = x - 1;
moves[3][1] = y - 1;
moves[3][2] = 0;
else
moves[3] = null;
if (isMoveValid(x, y, z, x - 1, y, 0)) {
moves[4][0] = x - 1;
moves[4][1] = y;
moves[4][2] = 0;
else
moves[4] = null;
if (isMoveValid(x, y, z, x - 1, y + 1, 0)) {
moves[5][0] = x - 1;
moves[5][1] = y + 1;
moves[5][2] = 0;
else
moves[5] = null;
if (isMoveValid(x, y, z, x, y + 1, 0)) {
moves[6][0] = x;
moves[6][1] = y + 1;
moves[6][2] = 0;
else
moves[6] = null;
if (isMoveValid(x, y, z, x + 1, y + 1, 0)) {
moves[7][0] = x + 1;
moves[7][1] = y + 1;
moves[7][2] = 0;
else
moves[7] = null;
if (isMoveValid(x, y, z, x, y, z + 1)) {
moves[8][0] = x;
moves[8][1] = y;
moves[8][2] = z + 1;
else
moves[8] = null;
return moves;
private void fillpath2D(int sX, int sY, int gX, int gY) {
int[] gLoc = {gX, gY};
path2D.add(gLoc);
int x = gX;
int y = gY;
int z = 0;
while (x != sX || y != sY) {
int x2 = squares3DReference[x][y][z][0];
int y2 = squares3DReference[x][y][z][1];
int z2 = squares3DReference[x][y][z][2];
x = x2;
y = y2;
z = z2;
if (z == 0) {
int[] loc = {x, y};
path2D.insertElementAt(loc, 0);
PathFinderTest.java
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.util.Vector;
public class PathFinderTest {
static BufferedReader consoleReader = new BufferedReader(new InputStreamReader(System.in));
static Map map;
static int startX;
static int startY;
static int goalX;
static int goalY;
public static void main(String[] args) throws Exception {
System.out.print("Enter map size.\nx = ");
int width = Integer.parseInt(consoleReader.readLine());
System.out.print("y = ");
int height = Integer.parseInt(consoleReader.readLine());
System.out.print("Enter strting location.\nx = ");
startX = Integer.parseInt(consoleReader.readLine()) - 1;
System.out.print("y = ");
startY = Integer.parseInt(consoleReader.readLine()) - 1;
System.out.print("Enter goal location.\nx = ");
goalX = Integer.parseInt(consoleReader.readLine()) - 1;
System.out.print("y = ");
goalY = Integer.parseInt(consoleReader.readLine()) - 1;
if (goalX < 0 || goalY < 0 || startX < 0 || startY < 0 || goalX >= width || goalY >= height || startX >= width || startY >= height) {
System.out.println("Invalid parameters found. Program will exit");
System.exit(0);
map = new Map(width, height);
map.clearGoalAndStartLocFromWater(startX, startY, goalX, goalY);
printSolution(new Vector());
PathFinder pathFinder = new PathFinder(map);
long before = System.currentTimeMillis();
Vector path = pathFinder.findPath(startX, startY, goalX, goalY);
long after = System.currentTimeMillis();
long time = after - before;
printSolution(path);
if (path.size() == 0)
System.out.println("No path found.");
else
System.out.println("Path found.");
System.out.println("Finding the path took " + time + " milliseconds");
static void printSolution(Vector path) {
boolean[][] pathOnMap = new boolean[map.getMapWidth()][map.getMapHeight()];
for (int i = 0; path.size() > i; i++) {
int[] move = (int[]) path.get(i);
pathOnMap[move[0]][move[1]] = true;
for (int y = 0; y < map.getMapHeight(); y++) {
for (int x = 0; x < map.getMapWidth(); x++) {
System.out.print(" ");
if (pathOnMap[x][y] == false)
System.out.print(" ");
else
System.out.print("0");
if (x == startX && y == startY)
System.out.print("S");
else if (x == goalX && y == goalY)
System.out.print("G");
else
System.out.print(map.terrainTypes.getNameFirstLetter(map.getSquareID(x, y)));
System.out.println();
System.out.println();
}TerrainType.java:
public class TerrainType {
private int movementCost;
private String name;
TerrainType(int aMovementCost, String aName) {
movementCost = aMovementCost;
name = aName;
public int getMovementCost() {
return movementCost;
public String getName() {
return name;
public String getNameFirstLetter() {
return name.substring(0, 1).toUpperCase();
}TerrainTypes.java:
import java.util.Vector;
public class TerrainTypes {
//Here are saved the terrain types with the map has. ElementAt 'i' in
//setOfTypes is represented by the number in Map.terrain[x][y] witch is
//equal to i, were x, y are random integer as soon as they do not
//throw ArrayIndexOutOfBoundsException. Actually this is a coding to know
//a specific square in the map to witch terrain type is refered in setOfTypes.
private Vector setOfTypes;
public TerrainTypes() {
setOfTypes = new Vector();
setOfTypes.add(new TerrainType(1, "Plains"));
setOfTypes.add(new TerrainType(2, "Forst"));
setOfTypes.add(new TerrainType(3, "Jungle"));
setOfTypes.add(new TerrainType(4, "Mountain"));
setOfTypes.add(new TerrainType(-1, "X"));
public int getMovementCost(int i) {
return ((TerrainType) setOfTypes.get(i)).getMovementCost();
public String getName(int i) {
return ((TerrainType) setOfTypes.get(i)).getName();
public String getNameFirstLetter(int i) {
return ((TerrainType) setOfTypes.get(i)).getNameFirstLetter();
public int getHighestMovementCost() {
int max = 1;
for (int i = 0; setOfTypes.size() > i; i++) {
int movementCost = ((TerrainType) setOfTypes.get(i)).getMovementCost();
if ( movementCost > 0) {
if (max < movementCost)
max = movementCost;
return max;
}I hope this program will be helpful.
SogartarWhy is such a smart guy like you not using A*
It is a general known algorithm which will find the
optimal solution in a finite search-space (within a minimal time).
The calculation time for the A* algorithm is influenced by two parameters:
1 - cumulative cost
2 - minimal expected additional cost
The calculation of these two costs has a great influence on the
solution.
I think the actual problems most games experience with shortest path calculatoin are
1 - very little time to spent calculating the shortest path
The quickest solution might be the best for the game
If your solution takes 1 second for the calculation of a path for one element on the board (100x100)
What would it take for the game to calculate the path for all elements controlled by the computer ??
If the computer controls two players which each have 50 elements to control, it would take forever...
Don't even consider the usage of a larger board (200x200 would take 4 seconds/element when
algorithm has complexity O(n))
2 - low priority.
Users tend to forgive a bad shortest path-algorithm most of the time,
but not a bad display, bad pictures,...
This is why most shortest-path algorithms within games were
developed as a depth first search,
within some earlier games this was even developed as
a rule which went straight to the endlocation and
takes a right/left turn when blocked by water/wall/...
So the actual steps you should take are:
1 - develop a normal breath-first search (to get going)
2 - develop a normal depth-first search (to compare speed and solution with)
3 - develop a normal dijkstra algorithm (sometimes called A)
4 - develop a best first algorithm (called A*)
5 - develop other AI-algorithms building upon A* (tabu-search, limited memory A*,...)
6 - develop some other AI-algorithms (Genetic Algorithms, Simulated Annealing,...)
7 - compare and tweak/change all search-algorithms for
7 - a - size of maps (small versus huge)
7 - b - optimality of the solution
7 - c - actual usage for your game
8 - !!! very important !!!
Share the developed path algorithms along with remarks about speed, map-size,...
with the rest of us. I would be very interested in such library.
kind regards, -
Hi,
I need to find an optimal size of a undo tablespace and redo log files... we are designing a new database as per the formulas that are given in many websites is "UndoSpace = [UR * (UPS * DBS)] + (DBS * 24)" .... but we still didn't build the database and not sure of those values... so how to design in that cases...
Please help us at earliest..
Regards,
RamuRamu Jagini wrote:
Hi,
I need to find an optimal size of a undo tablespace and redo log files... we are designing a new database as per the formulas that are given in many websites is "UndoSpace = [UR * (UPS * DBS)] + (DBS * 24)" .... but we still didn't build the database and not sure of those values... so how to design in that cases...
Please help us at earliest..
Regards,
RamuYou can only find it by empirical testing unless you know those values, which you can only find by empirical testing. The variance from certain feature usage alone can be orders of magnitude, and besides that programming style has a huge influence, as does actual user load. Beyond that, rare operations like massive loads and end of cycle processing may have much different needs. Tom Kyte makes a good case for saying you should leave large undo around for those cases, "wasted" disk is much cheaper than dealing with the lack of undo at critical times. Since you can tune redo log switching with timeouts, you might as well have redo sized for the rare cases too. You have to load the test data anyways, so that's a good first cut.
Once you have a reasonable test going you can get advice from the db. Requirements can change over time, too. -
Optimal Video Settings for Projectors
Hi Guys,
Really need your help on this one. My goal is to find the
optimal video format, data-rate and frame-rate to import 2-3 min
video pieces into director. I have the latest versions of Director
and Sorensen.
The projector size is 1000 x 700 pixels to be distributed on
dvd.
The original video files are mixed formats. I have some 640 x
425 AVI CAD movies, some DV movies at NTSC resolution and some 720
x 540 QTVR files converted to .avi.
The file types I am testing at the moment are SWF and
QUICKTIME .MOV, with mixed results on different systems. The best
results so far are from converting to SWF at 2500 kbps with 25 fps
keeping original size. I am then stretching the movies in director
to fit 1000 x 670.
Ideally I would like each movie to play back at a setting of
1000 x 670 inside the projector, so that I can add movie controls
at the bottom of the projector.
Can anyone point me in the right direction? Am I doing
something wrong here or is this the reality of using Director for
what I am trying to acheive. I seem to be spending hours trying
various formats and data-rates but with very average performance....doesn't really sound like a Lingo question but maybe
someone can help.
Craig Wollman
Lingo Specialist
Word of Mouth Productions
212-928-9581
www.wordofmouthpros.com
"martynrlee" <[email protected]> wrote in
message
news:ettocs$8ko$[email protected]..
> Hi Guys,
>
> Really need your help on this one. My goal is to find
the optimal video
> format, data-rate and frame-rate to import 2-3 min video
pieces into
> director.
> I have the latest versions of Director and Sorensen.
>
> The projector size is 1000 x 700 pixels to be
distributed on dvd.
>
> The original video files are mixed formats. I have some
640 x 425 AVI CAD
> movies, some DV movies at NTSC resolution and some 720 x
540 QTVR files
> converted to .avi.
>
> The file types I am testing at the moment are SWF and
QUICKTIME .MOV, with
> mixed results on different systems. The best results so
far are from
> converting
> to SWF at 2500 kbps with 25 fps keeping original size. I
am then
> stretching the
> movies in director to fit 1000 x 670.
>
> Ideally I would like each movie to play back at a
setting of 1000 x 670
> inside
> the projector, so that I can add movie controls at the
bottom of the
> projector.
>
> Can anyone point me in the right direction? Am I doing
something wrong
> here or
> is this the reality of using Director for what I am
trying to acheive. I
> seem
> to be spending hours trying various formats and
data-rates but with very
> average performance.
>
>
> -
Optimal settings in BT Home Hub Page, which do you...
Hi,
I just wanted to know what different people find for optimal settings in there BT Home Hub page. Do you go for:-
A
1. 802.11 b/g/n (Recommended)
2. 802.11 n 40MHz
B
1. WPA & WPA 2 (Recommended)
2. WPA 2 Only
3. WPA Only
4. WEP (64/40 bits)
5. None
C
1. UPnP on or off
2. Extended UPnP Security on or off
D
1. DMZ Enable yes or no (What particular device you want all it sending too, Console, Desktop, Laptop, Sky, Iphone etc.., which one?.)
E
1. Firewall - Default/Block all/ Disabled
Which of these settings do you use for the best experience online with loading pages, speeds (Download/uploads), best experience for online gaming (pings etc..) and also for devices such as consoles, Wii U, 360, PS3, PS Vita, DS3 etc..
Please tell me, I would like to know who gets the best experience out of there settings.
Thanks,
Please click on pink star to the left and say thanks if I have helped you at all!. Thank you. Home Hub Page- http://bthomehub.home/
BT Speed test- http://www.speedtest.btwholesale.com/
Speedtest:-http://diagnostics.bt.com/login/?workflow=Speed
Net Connect test- http://netalyzr.icsi.berkeley.edu/index.htmlHi all,
To stop online intruders from anywhere in the world gaining access to your Hub, Network (ie devices connected to your home network) a firewall monitions the outgoing and incoming data that flows through the home hub so it can block suspicious data packets that may cause harm to your network.
Disabling your Home Hub firewall can open up your network to external attack, so you need to take appropriate security measures to protect your network.
BT strongly recommends that the firewall is not left disabled as this makes your network very vulnerable to attack by hackers.
Hope that helps.
jac_95 | BT.com Help Site | BT Service Status
Someone Solved Your Question?
Please let other members know by clicking on ’Mark as Accepted Solution’
Try a Search
See if someone in the community had the same problem and how they got it resolved. -
I have a homework assignment that I'm really stuck on. I'm not looking for code (I'm sure I could find that if I wanted, but I really want to UNDERSTAND this).
I need to make a recursive method to find the OPTIMAL solution (least number of bins used).
The professor basically gave us an algorithm to use, but it confuses the heck out of me. I seriously think I could do this other ways, but I don't think we are allowed.
Here is what was given to us (I'll post my couple of questions below):
If there are no items left, there is nothing left to pack; return the current set of bins(base case).
For the recursive case:
1) Make a (deep) copy of the list of items, and remove one item from it.
2) For every bin, make a (deep copy) of the entire set of bins, and place the item in that bin. If the item fits, recursively apply the algorithm with the same number of bins, the modified list of items (the copy made above), and the copied set of bins with the item added.
3) Do the same thing as (2) except place the item in a new (previously empty) bin in the copied set.
4) Pick the best result from steps (2) and (3) (the one with the fewest bins) and return it.
OK, the part I don't get is the "for every bin, make a (deep) copy of the entire set of bins". ---If the first item tested (in the first copied set of bins) fits, the algorithm is recursed.. So I don't really grasp how it would actually test the item in every other bin. I know I must be missing something here, but I've spent at least 15 hours on this and have gotten virtually nowhere on this portion of the assignment.
This is obviously supposed to be an exhaustive search, since being an NP problem that would be the only way to attain an optimal solution. I tried coding what I thought was meant by this above pseudo-algorithm, but without testing every bin, i only ended up with a first-fit result.
If someone could give me a bit of insight into what is meant by the line "for every bin, make a (deep) copy of the entire set of bins", and how it could possibly be applied so that the recursion doesn't just happen before the item is placed into following bins it would be greatly appreciated.
I don't want to post any code here because I don't want it to look like another "do my homework" post, but if someone wants to see where I'm at, I can do so. Also, before anyone says I should just ask the professor or whatever, he is Chinese with a REALLY strong accent, and so are all the assistants (really...), and I can't understand a word they say. So although I'm attending all lectures, I'm still basically teaching myself. :Pin step 4 he asks you to return the best result obtained in steps 2 or 3.
Yes, in step 2, if it fits in the first bin you will trigger a recursion, BUT you simply remember the result of that optimal fit (counting how many bins it took) and go on to try the next slot.
If there were N bins when you started, you wil be making potentially N recursive calls in step 2 (though you will remember the results of only one of those), you will then make one more recursive call in step 3, and you will return one single result - namely the set of bins that took the fewest total count from those N+1 trials. -
Third Party Process and Inventory
We are using the SAP function "Third-Party Processing". We are using the function in it's standard (SAP R/3 4.7).
The auditor now has the following issue: Shipping the goods starts after paying the goods. Out of this, while shipping the goods, we are the owner of them. In this circumstance the ship is our warehouse.
SAP does not allow an Inventory Management within Third-Party Processing:
"Since a third-party order involves a movement from the vendor direct to the customer, Inventory Management is not in any way affected. If you wish to document the movement in the system, however, you can create a goods receipt for the third-party order."
With the SAP functions in this scenario it is correct that the warehouse stock is not being impacted. This is a conflict with the opinion of the auditor.
Let me explain in detail what is wrong out of the view of our auditor:
For example we initiated the order of a customer in June and we have paid the goods in June. The shipment starts in June and the goods will arive in July. Due to the fact, that we are the owner of the goods on the ship, we have to increase the stock. This is the opinion of our auditor.
Does any body know, how to solve the issue? How do you manage Third Party Processing & Inventory?Some auditors just dont understand the SAP process. Instead of talking to weak users, they should talk to SAP directly.
What about shipments from standard sales orders that are shipped end of June and do arrive at the customer in July?
When do you bill your customer? when the goods arrives there, or earlier? Depending on the Incoterms you may still be the owner until the truck is unloaded.
If you change your process and post goods receipt to your warehouse, then you show inventory where no physical inventory is, you posted a goods receipt without a physical receipt. I am sure the next auditor will not allow such therotical process.
Get together, IT consultants of FI and MM and SD, strong business people for the same modules and the auditor, and discuss and find an optimal solution.And let the auidor sign the decision paper!!! Very important, I recently had to convice German auditors because they had different opinion than the Australian and US auditors of the same auditing company (and the issue had nothing to do with local legal requirements). -
PLEASE HELP ME WITH DM PROBLEM
Hi Guys,
I kindly ask for your help with regards to my DM project. As you might recall, I am working on a project that is related to the field of agriculture and that has as an objective to find the "optimal values" of the operating conditions that affect the outcome (the amount of meat produced i.e. the weight) of an animal production (chicken broilers in my case). To do so, I have to use historical data of previous productions as my training dataset. The length a production cycle is typically around 44 days. For each production, a data acquisition system stores the real-time and historical data of hundreds of parameters. These parameters represent sensor measurements of all the operating conditions (current temperature, set point temperature, humidity, static pressure, etc...) and these are what I refer to as the inputs. The operating costs and the production outcome are what I refer to as outputs. The operating cost is indirectly computed from parameters like water consumption, feed consumption, heater/cooling runtimes, and lighting runtime; and the outcome of a production is defined by parameters like animal mortality and conversion factor (amount of feed in Lbs to produce 1Lb of meat). So the main objective of this project is to find the set of optimal daily values (1value/day) for the inputs that would minimize the operating costs and conversion ratio outputs.
The biggest problem I am facing right now is the following: The historical data that I have in the DB are time series for each measured parameter. Some of these time series follow some kind of cyclic pattern (e.g. daily water/feed consumption ) while others follow an increasing/decreasing trend (animal weight, total heater run time, total water/feed consumption ..). My goal is to be able to come up with a model that suggests a set of curves for the optimal daily values throughout the length of the production cycle, one curve for each measured input/output parameter. This model would allow the farmer to closely monitor his production on a daily basis to make sure his production parameters follow the optimal curves suggested by my model. I have looked at ANN and I think it might be the solution to my problem since it allows to model multiple input/outputs problems (Am I wrong?), but I could not figure out a way to model the inputs/outputs as time series (an array of values for each parameter). As far as I know, all kinds of classifiers accept only single valued samples.
One approach would be to create one classifier/day (e.g. for day1: extract a single value for each parameter and use these values as a training sample and repeat this for all previous production to construct the training set). The problem with this approach is that 44 or so classifiers will be constructed (hard to manage all of this) and each of these resulting ANN will be some kind of typical average of the training data but not necessarily the optimal values leading to the best production outcome, if I am not mistaken.
Another approach would be to find a way to feed in the inputs and outputs as time series (an array of 44 daily values for each input/output parameter). In this case, there would be only one resulting ANN and the training samples, would be a set of arrays for each parameter, as opposed to single daily parameter values in the first case. The problem is, I could not find any classifier that would allow me to do that.
Another issue that I have is the amount of data. While a single production cycle could represent 1-2GB of data, the length of the production cycle (44 days) makes it difficult to have 100s of production cycle historical data, as I could gather data for no more than 7 full cycles/year. Fortunately, a farm can have many production units (5-10 barns/site in big sites), so this makes it possible to have 40-70 cycles/yr. My question is: would this be enough to come up with an acceptably accurate model or is it necessary to have hundreds of samples?
Thanks for taking the time to reading this lengthy post, and I really appreciate your help and thank you in advance.
Cheers.Hi Guys,
I would really appreciate any help please. Maybe I was not precise enough
last time, so I am going to decribe things more clearly with examples.
Since the produced model will be used as part of an alarm/flagging
system, I will have to produce a curve of each of the parameters of
interest using 4 values/day=once/6h, and do this for the 44 days, this
is to flag and correct any abnormal behaviour ASAP. So, the whole
curve would have 4*44=176 values. E.g. for the water consumption
curve: day1: 12AM=65Gal, 6AM=150, 12PM ... DAY44=6PM=1500Gal. I would
have to come up with similar curves for each of the parameters of
interest (inputs/outputs). Now as far as ANNs are concerned, do I
have to produce 176 of these ANNs, one for each predicted value?
ANN1: input1 (temperature-value Day1@12AM) input2 (humidity-value
Day1@12AM)... output1 (feed consumption-value Day1@12AM), output2
(heater_runtime-values Day1@12AM)... and train the ANN with the 50-60
samples (Day1@12AM) from previous productions. This would produce an
ANN for predicting the value of each parameter for Day1@12AM for
future productions, etc.... This would quite intensive
computationally, so I am wondering if there is a better way to maybe
feed-in all the 176 values time series in one shot to have something
like input1(temperature-values 1-176), input2(humidity-values
1-176)... output1(feed consumption-values 1-176), output2 (heater
runtime-values 1-175)... and this will produce only one ANN which
will predict the 176 values for all parameters of future productions?
I would really appreciate your help as I am really stuck at this.
Cheers. -
Help me stabilize this jRun configuration (CF9/Win2k3/IIS6)
Hi everyone,
We've been struggling to keep our multi-server configuration stable for quite some time now. At the end of last month we were running under CF 7.0.2 on a two servers setup (one instance each). At that point we managed to get our uptime to around 1 week per instance before they would restart by themselves. Since the beginning of the month we upgraded to CF 9 and we're back to square one with multi-restart a day.
Our current configuration is 2 Win2k3 servers, running a cluster of 4 instances, 2 instances per server. At this point we are pretty certain this is due to improper JVM settings.
We've been toying with them and while some are more stable than others we never quite got it right.
From the default:
java.args=-server -Xmx512m -Dsun.io.useCanonCaches=false -XX:MaxPermSize=192m -XX:+UseParallelGC -Dcoldfusion.rootDir={application.home}/
To currently:
java.args=-server -Xmx896m -Dsun.io.useCanonCaches=false -XX:MaxPermSize=512m -XX:SurvivorRatio=8 -XX:TargetSurvivorRatio=90 -XX:+UseParallelGC -Dcoldfusion.rootDir={application.home}/ -verbose:gc -Xloggc:c:/Jrun4/logs/gc/gcInstance1b.log
We have determined that we do need more than the default 512MB simply by monitoring with FusionReactor, on average our amount of memory consumed is hovering in the mid 300MB and can go up to low 700MB under heavy load.
Most of the crash will be logged in jrun4/bin/hs_err_pid*.log always an "Out of swap space"
The latest crash from yesterday generated the following log:
From it, I gather that its the PSPermGen that is full (most logs will show the same before a crash), which is why we increased MaxPermSize but the total still show as 107520K!??! I've attached the GC log after the HS_ERR. No one here is a jRun expert, just developpers tasked with fixing this as best as we possibly can so any help would be greatly appreciated!!
# A fatal error has been detected by the Java Runtime Environment:
# java.lang.OutOfMemoryError: requested 2264248 bytes for Chunk::new. Out of swap space?
# Internal Error (allocation.cpp:215), pid=15224, tid=4960
# Error: Chunk::new
# JRE version: 6.0_14-b08
# Java VM: Java HotSpot(TM) Server VM (14.0-b16 mixed mode windows-x86 )
# If you would like to submit a bug report, please visit:
# http://java.sun.com/webapps/bugreport/crash.jsp
--------------- T H R E A D ---------------
Current thread (0x5c69c800): JavaThread "CompilerThread1" daemon [_thread_in_native, id=4960, stack(0x5ce70000,0x5cf70000)]
Stack: [0x5ce70000,0x5cf70000], sp=0x5cf6e90c, free space=1018k
Native frames: (J=compiled Java code, j=interpreted, Vv=VM code, C=native code)
V [jvm.dll+0x306157]
V [jvm.dll+0xf7d2c]
V [jvm.dll+0x3915c]
V [jvm.dll+0x393f3]
V [jvm.dll+0x16a470]
V [jvm.dll+0xa9552]
V [jvm.dll+0xd7843]
V [jvm.dll+0xd7f6c]
V [jvm.dll+0x9e082]
V [jvm.dll+0xda0e0]
V [jvm.dll+0xdac6f]
V [jvm.dll+0x2e63f4]
V [jvm.dll+0x267dac]
C [MSVCR71.dll+0x9565]
C [kernel32.dll+0x2482f]
Current CompileTask:
C2:3749 ! cfdspInit2ecfm988339296.runPage()Ljava/lang/Object; (4792 bytes)
--------------- P R O C E S S ---------------
Java Threads: ( => current thread )
0x6f812800 JavaThread "task" daemon [_thread_blocked, id=12580, stack(0x6acb0000,0x6adb0000)]
0x79981800 JavaThread "task" daemon [_thread_blocked, id=14328, stack(0x6a940000,0x6aa40000)]
0x7882a800 JavaThread "task" daemon [_thread_blocked, id=6132, stack(0x6a840000,0x6a940000)]
0x6eb97800 JavaThread "task" daemon [_thread_blocked, id=1756, stack(0x6a740000,0x6a840000)]
0x6f221800 JavaThread "task" daemon [_thread_blocked, id=14024, stack(0x6a640000,0x6a740000)]
0x6f668800 JavaThread "task" daemon [_thread_blocked, id=15956, stack(0x69740000,0x69840000)]
0x62887400 JavaThread "RMI TCP Connection(10140)-192.168.40.35" daemon [_thread_in_native, id=11024, stack(0x628d0000,0x629d0000)]
0x61ec3800 JavaThread "RMI TCP Connection(idle)" daemon [_thread_blocked, id=5848, stack(0x60b80000,0x60c80000)]
0x788d2c00 JavaThread "RMI TCP Connection(idle)" daemon [_thread_blocked, id=13348, stack(0x60460000,0x60560000)]
0x7955e400 JavaThread "RMI TCP Connection(10136)-192.168.40.35" daemon [_thread_in_native, id=10912, stack(0x639d0000,0x63ad0000)]
0x621c5400 JavaThread "RMI TCP Connection(idle)" daemon [_thread_blocked, id=3308, stack(0x64ed0000,0x64fd0000)]
0x619fb400 JavaThread "RMI TCP Connection(10132)-192.168.40.34" daemon [_thread_in_native, id=7784, stack(0x642d0000,0x643d0000)]
0x62719c00 JavaThread "jrpp-821" [_thread_in_native, id=5124, stack(0x60360000,0x60460000)]
0x78751400 JavaThread "jrpp-820" [_thread_in_native, id=16240, stack(0x60180000,0x60280000)]
0x7fa71400 JavaThread "jrpp-819" [_thread_in_native, id=15228, stack(0x5fb80000,0x5fc80000)]
0x78ccb400 JavaThread "RMI TCP Connection(idle)" daemon [_thread_blocked, id=6224, stack(0x64ad0000,0x64bd0000)]
0x6edc8c00 JavaThread "RMI TCP Connection(10123)-192.168.40.34" daemon [_thread_in_native, id=4592, stack(0x632d0000,0x633d0000)]
0x6e37a400 JavaThread "jrpp-818" [_thread_in_native, id=2712, stack(0x617d0000,0x618d0000)]
0x62816c00 JavaThread "jrpp-817" [_thread_in_native, id=11972, stack(0x60980000,0x60a80000)]
0x6fab2400 JavaThread "RMI TCP Connection(10074)-192.168.40.34" daemon [_thread_in_native, id=8124, stack(0x64dd0000,0x64ed0000)]
0x78769400 JavaThread "RMI TCP Connection(10050)-192.168.40.34" daemon [_thread_in_native, id=8720, stack(0x60a80000,0x60b80000)]
0x5c82ac00 JavaThread "RMI TCP Connection(10030)-192.168.40.34" daemon [_thread_in_native, id=12620, stack(0x62cd0000,0x62dd0000)]
0x61ee6800 JavaThread "task" daemon [_thread_in_native, id=5936, stack(0x60d80000,0x60e80000)]
0x6e239c00 JavaThread "scheduler-28" [_thread_blocked, id=13084, stack(0x69a40000,0x69b40000)]
0x61cc2400 JavaThread "RMI TCP Connection(10001)-192.168.40.34" daemon [_thread_in_native, id=3300, stack(0x5fe80000,0x5ff80000)]
0x5da0a400 JavaThread "scheduler-27" [_thread_blocked, id=5764, stack(0x62fd0000,0x630d0000)]
0x5c82a400 JavaThread "scheduler-26" [_thread_blocked, id=15592, stack(0x61290000,0x61390000)]
0x7963bc00 JavaThread "scheduler-25" [_thread_blocked, id=1564, stack(0x60880000,0x60980000)]
0x61f3a800 JavaThread "RMI RenewClean-[192.168.40.34:4835]" daemon [_thread_in_native, id=12824, stack(0x62bd0000,0x62cd0000)]
0x6df88800 JavaThread "web-3" [_thread_in_native, id=10008, stack(0x667d0000,0x668d0000)]
0x6e27dc00 JavaThread "scheduler-3" [_thread_blocked, id=7512, stack(0x63ad0000,0x63bd0000)]
0x5dd3b400 JavaThread "scheduler-24" [_thread_blocked, id=7552, stack(0x629d0000,0x62ad0000)]
0x6ebcd800 JavaThread "AWT-Windows" daemon [_thread_in_native, id=8736, stack(0x60080000,0x60180000)]
0x6f595400 JavaThread "FusionReactor Web Server (Server Thread Pool Member Thread-8617)" daemon [_thread_blocked, id=7408, stack(0x5fd80000,0x5fe80000)]
0x5d9d3800 JavaThread "scheduler-2" [_thread_blocked, id=1884, stack(0x60e80000,0x60f80000)]
0x619d4400 JavaThread "scheduler-23" [_thread_blocked, id=7984, stack(0x616d0000,0x617d0000)]
0x62748800 JavaThread "RMI RenewClean-[192.168.40.34:4547]" daemon [_thread_blocked, id=12652, stack(0x60c80000,0x60d80000)]
0x61a28400 JavaThread "MultiThreadedHttpConnectionManager cleanup" daemon [_thread_blocked, id=7212, stack(0x5fc80000,0x5fd80000)]
0x00717400 JavaThread "DestroyJavaVM" [_thread_blocked, id=12764, stack(0x00030000,0x00130000)]
0x6261dc00 JavaThread "scheduler-1" [_thread_blocked, id=9928, stack(0x64800000,0x64900000)]
0x5d508400 JavaThread "Java2D Disposer" daemon [_thread_blocked, id=11168, stack(0x65fd0000,0x660d0000)]
0x62186800 JavaThread "worker #4" daemon [_thread_blocked, id=15864, stack(0x66cd0000,0x66dd0000)]
0x6e827c00 JavaThread "worker #3" daemon [_thread_blocked, id=15700, stack(0x663d0000,0x664d0000)]
0x625a4c00 JavaThread "worker #2" daemon [_thread_blocked, id=2940, stack(0x662d0000,0x663d0000)]
0x622d5000 JavaThread "worker #1" daemon [_thread_blocked, id=12548, stack(0x661d0000,0x662d0000)]
0x5d7ffc00 JavaThread "worker #0" daemon [_thread_blocked, id=9384, stack(0x660d0000,0x661d0000)]
0x5d406800 JavaThread "Thread-49" [_thread_blocked, id=9248, stack(0x65c20000,0x65d20000)]
0x622a8000 JavaThread "obj-skimmer" daemon [_thread_blocked, id=3680, stack(0x640d0000,0x641d0000)]
0x620d7800 JavaThread "obj-skimmer" daemon [_thread_blocked, id=12312, stack(0x63fd0000,0x640d0000)]
0x62351800 JavaThread "obj-skimmer" daemon [_thread_blocked, id=11708, stack(0x63dd0000,0x63ed0000)]
0x5dedd800 JavaThread "obj-skimmer" daemon [_thread_blocked, id=8800, stack(0x5f9d0000,0x5fad0000)]
0x5dec6400 JavaThread "obj-skimmer" daemon [_thread_blocked, id=14688, stack(0x5f8d0000,0x5f9d0000)]
0x5d519c00 JavaThread "obj-skimmer" daemon [_thread_blocked, id=4868, stack(0x5f7d0000,0x5f8d0000)]
0x5d7cec00 JavaThread "obj-skimmer" daemon [_thread_blocked, id=12844, stack(0x5f6d0000,0x5f7d0000)]
0x62515800 JavaThread "obj-skimmer" daemon [_thread_blocked, id=7396, stack(0x5f5d0000,0x5f6d0000)]
0x6283e400 JavaThread "obj-skimmer" daemon [_thread_blocked, id=6164, stack(0x5f4d0000,0x5f5d0000)]
0x5c731c00 JavaThread "scheduler-0" [_thread_blocked, id=11724, stack(0x5f3d0000,0x5f4d0000)]
0x621e9000 JavaThread "Thread-41" daemon [_thread_blocked, id=3196, stack(0x5ef90000,0x5f090000)]
0x5d32f800 JavaThread "jndi-5" [_thread_blocked, id=2808, stack(0x63ed0000,0x63fd0000)]
0x5da96c00 JavaThread "Timer-8" daemon [_thread_blocked, id=9864, stack(0x733a0000,0x734a0000)]
0x61f0e000 JavaThread "Timer-7" [_thread_blocked, id=3116, stack(0x732a0000,0x733a0000)]
0x623f2c00 JavaThread "Timer-6" [_thread_blocked, id=3528, stack(0x731a0000,0x732a0000)]
0x5d327c00 JavaThread "scheduler-22" [_thread_blocked, id=3612, stack(0x730a0000,0x731a0000)]
0x621bc400 JavaThread "FusionReactor Web Server (Server Thread Pool Member Thread-36)" daemon [_thread_blocked, id=13668, stack(0x72ea0000,0x72fa0000)]
0x61981400 JavaThread "FusionReactor Web Server (Server Thread Pool Member Thread-35)" daemon [_thread_blocked, id=15540, stack(0x72da0000,0x72ea0000)]
0x5d9dcc00 JavaThread "FusionReactor Request Monitor" [_thread_blocked, id=3464, stack(0x72ca0000,0x72da0000)]
0x5ddeb400 JavaThread "FusionReactor FD/R Remote Data Collector for {CF_Instance2a.jrun4.lcbwebott02}" [_thread_blocked, id=9760, stack(0x72ba0000,0x72ca0000)]
0x5dcf9400 JavaThread "FusionReactor Web Server" [_thread_in_native, id=12396, stack(0x72aa0000,0x72ba0000)]
0x5df7a400 JavaThread "FusionReactor Enterprise Service - Local Metrics Cache" daemon [_thread_blocked, id=9780, stack(0x729a0000,0x72aa0000)]
0x5def8400 JavaThread "Timer-5" daemon [_thread_blocked, id=1640, stack(0x728a0000,0x729a0000)]
0x621a4c00 JavaThread "Timer-4" daemon [_thread_blocked, id=13496, stack(0x727a0000,0x728a0000)]
0x5da2a400 JavaThread "Timer-3" daemon [_thread_blocked, id=5568, stack(0x726a0000,0x727a0000)]
0x61b60c00 JavaThread "Timer-2" daemon [_thread_blocked, id=10724, stack(0x725a0000,0x726a0000)]
0x622bbc00 JavaThread "Timer-1" daemon [_thread_blocked, id=8252, stack(0x724a0000,0x725a0000)]
0x5d840c00 JavaThread "Thread-25" daemon [_thread_blocked, id=13204, stack(0x71fa0000,0x720a0000)]
0x6e037c00 JavaThread "Timer-0" daemon [_thread_blocked, id=10944, stack(0x70670000,0x70770000)]
0x5d815400 JavaThread "task" daemon [_thread_blocked, id=8680, stack(0x71da0000,0x71ea0000)]
0x5dea9800 JavaThread "task" daemon [_thread_blocked, id=8052, stack(0x71570000,0x71670000)]
0x6228c000 JavaThread "Thread-23" daemon [_thread_blocked, id=11888, stack(0x71170000,0x71270000)]
0x6228c800 JavaThread "Thread-22" daemon [_thread_blocked, id=15232, stack(0x70f70000,0x71070000)]
0x62289000 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=8972, stack(0x70e70000,0x70f70000)]
0x5da2ac00 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=11732, stack(0x70d70000,0x70e70000)]
0x6e181c00 JavaThread "task" daemon [_thread_blocked, id=15432, stack(0x70870000,0x70970000)]
0x5db7e400 JavaThread "task" daemon [_thread_blocked, id=15828, stack(0x70770000,0x70870000)]
0x61c3dc00 JavaThread "Thread-21" daemon [_thread_blocked, id=12384, stack(0x6d9b0000,0x6dab0000)]
0x6e052800 JavaThread "Thread-20" daemon [_thread_blocked, id=1760, stack(0x6d500000,0x6d600000)]
0x61af4400 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=8832, stack(0x6d400000,0x6d500000)]
0x627dd400 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=5612, stack(0x6d1b0000,0x6d2b0000)]
0x5da64000 JavaThread "Thread-19" [_thread_blocked, id=15120, stack(0x6c6b0000,0x6c7b0000)]
0x6229d800 JavaThread "task" daemon [_thread_blocked, id=6736, stack(0x6ccb0000,0x6cdb0000)]
0x5de23400 JavaThread "task" daemon [_thread_blocked, id=15424, stack(0x6cbb0000,0x6ccb0000)]
0x621f6c00 JavaThread "task" daemon [_thread_blocked, id=6324, stack(0x6b0b0000,0x6b1b0000)]
0x5d3b5400 JavaThread "scheduler-21" [_thread_blocked, id=4284, stack(0x6aeb0000,0x6afb0000)]
0x624c2800 JavaThread "Thread-17" daemon [_thread_blocked, id=6100, stack(0x6bdb0000,0x6beb0000)]
0x624e6800 JavaThread "Thread-16" daemon [_thread_blocked, id=9080, stack(0x6bcb0000,0x6bdb0000)]
0x621e5400 JavaThread "task" daemon [_thread_blocked, id=14136, stack(0x6bbb0000,0x6bcb0000)]
0x6215e800 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=9112, stack(0x6b9b0000,0x6bab0000)]
0x62522000 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=7220, stack(0x6b8b0000,0x6b9b0000)]
0x622a8800 JavaThread "Thread-15" daemon [_thread_blocked, id=15848, stack(0x6afb0000,0x6b0b0000)]
0x622b1400 JavaThread "task" daemon [_thread_blocked, id=4512, stack(0x6adb0000,0x6aeb0000)]
0x62163400 JavaThread "Thread-14" daemon [_thread_blocked, id=3944, stack(0x6abb0000,0x6acb0000)]
0x622b2c00 JavaThread "task" daemon [_thread_blocked, id=12724, stack(0x6aab0000,0x6abb0000)]
0x623aa800 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=7736, stack(0x6a540000,0x6a640000)]
0x623a9400 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=13556, stack(0x6a440000,0x6a540000)]
0x62010000 JavaThread "scheduler-20" [_thread_blocked, id=13884, stack(0x69d40000,0x69e40000)]
0x5d4e0c00 JavaThread "Thread-13" daemon [_thread_blocked, id=14880, stack(0x69640000,0x69740000)]
0x621a0000 JavaThread "Thread-12" daemon [_thread_blocked, id=10732, stack(0x69440000,0x69540000)]
0x5d41e800 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=8964, stack(0x69340000,0x69440000)]
0x62216c00 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=6644, stack(0x69240000,0x69340000)]
0x61b5b800 JavaThread "scheduler-19" [_thread_blocked, id=10856, stack(0x68f40000,0x69040000)]
0x62178400 JavaThread "scheduler-18" [_thread_blocked, id=10184, stack(0x68e40000,0x68f40000)]
0x62177000 JavaThread "scheduler-17" [_thread_blocked, id=6816, stack(0x68d40000,0x68e40000)]
0x62176000 JavaThread "scheduler-16" [_thread_blocked, id=7700, stack(0x68c40000,0x68d40000)]
0x62174000 JavaThread "scheduler-15" [_thread_blocked, id=8296, stack(0x68b40000,0x68c40000)]
0x61b60000 JavaThread "scheduler-14" [_thread_blocked, id=6212, stack(0x68a40000,0x68b40000)]
0x61b5e800 JavaThread "scheduler-13" [_thread_blocked, id=6868, stack(0x68940000,0x68a40000)]
0x61b5d800 JavaThread "scheduler-12" [_thread_blocked, id=12472, stack(0x68840000,0x68940000)]
0x62168400 JavaThread "scheduler-11" [_thread_blocked, id=9468, stack(0x68740000,0x68840000)]
0x62167000 JavaThread "scheduler-10" [_thread_blocked, id=7224, stack(0x68640000,0x68740000)]
0x62165800 JavaThread "scheduler-9" [_thread_blocked, id=3520, stack(0x68540000,0x68640000)]
0x5d41b400 JavaThread "scheduler-8" [_thread_blocked, id=11824, stack(0x68440000,0x68540000)]
0x5d419c00 JavaThread "scheduler-7" [_thread_blocked, id=4956, stack(0x68340000,0x68440000)]
0x620dc400 JavaThread "scheduler-6" [_thread_blocked, id=14988, stack(0x68240000,0x68340000)]
0x620db400 JavaThread "scheduler-5" [_thread_blocked, id=9580, stack(0x68140000,0x68240000)]
0x5d3cf400 JavaThread "scheduler-4" [_thread_blocked, id=10220, stack(0x68040000,0x68140000)]
0x5dc40c00 JavaThread "scheduler-3" [_thread_blocked, id=6780, stack(0x67ed0000,0x67fd0000)]
0x621a4400 JavaThread "scheduler-2" [_thread_blocked, id=9216, stack(0x67dd0000,0x67ed0000)]
0x619d5400 JavaThread "scheduler-1" [_thread_blocked, id=7032, stack(0x67ad0000,0x67bd0000)]
0x5dd32400 JavaThread "scheduler-0" [_thread_blocked, id=15420, stack(0x665d0000,0x666d0000)]
0x5df2bc00 JavaThread "Transaction Domain PrivateJmsDomain" [_thread_blocked, id=15384, stack(0x67cd0000,0x67dd0000)]
0x5d2f7800 JavaThread "clock" daemon [_thread_blocked, id=7236, stack(0x67bd0000,0x67cd0000)]
0x5d41f400 JavaThread "Transaction Domain DefaultDomain" [_thread_blocked, id=3908, stack(0x679d0000,0x67ad0000)]
0x6223bc00 JavaThread "tyrex.util.daemonMaster" daemon [_thread_blocked, id=15468, stack(0x677d0000,0x678d0000)]
0x621bcc00 JavaThread "task" daemon [_thread_blocked, id=7364, stack(0x676d0000,0x677d0000)]
0x5df2d400 JavaThread "task" daemon [_thread_blocked, id=6052, stack(0x670d0000,0x671d0000)]
0x5d927800 JavaThread "Thread-10" daemon [_thread_blocked, id=8776, stack(0x66bd0000,0x66cd0000)]
0x61944c00 JavaThread "Thread-9" daemon [_thread_blocked, id=12100, stack(0x66ad0000,0x66bd0000)]
0x620be400 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=13248, stack(0x669d0000,0x66ad0000)]
0x5d52f400 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=15988, stack(0x668d0000,0x669d0000)]
0x5d8dd400 JavaThread "task" daemon [_thread_blocked, id=12096, stack(0x664d0000,0x665d0000)]
0x5d4cd400 JavaThread "task" daemon [_thread_blocked, id=12332, stack(0x65ed0000,0x65fd0000)]
0x5dc4e400 JavaThread "Thread-8" daemon [_thread_blocked, id=11804, stack(0x659d0000,0x65ad0000)]
0x5dce2400 JavaThread "Thread-7" daemon [_thread_blocked, id=13224, stack(0x658d0000,0x659d0000)]
0x61ca1c00 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=992, stack(0x657d0000,0x658d0000)]
0x61abb400 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=8984, stack(0x656d0000,0x657d0000)]
0x5d87ac00 JavaThread "jndi-3" [_thread_blocked, id=10016, stack(0x654d0000,0x655d0000)]
0x5da66800 JavaThread "jndi-2" [_thread_in_native, id=15032, stack(0x653d0000,0x654d0000)]
0x5de6bc00 JavaThread "jndi-1" [_thread_blocked, id=10964, stack(0x652d0000,0x653d0000)]
0x61ca2400 JavaThread "jndi-0" [_thread_blocked, id=13736, stack(0x651d0000,0x652d0000)]
0x61918000 JavaThread "task" daemon [_thread_blocked, id=1892, stack(0x64cd0000,0x64dd0000)]
0x61917c00 JavaThread "task" daemon [_thread_blocked, id=2692, stack(0x64bd0000,0x64cd0000)]
0x61a64400 JavaThread "Thread-6" daemon [_thread_blocked, id=3580, stack(0x644d0000,0x645d0000)]
0x5db8d400 JavaThread "Thread-5" daemon [_thread_blocked, id=15852, stack(0x645d0000,0x646d0000)]
0x5df10800 JavaThread "Thread-4" daemon [_thread_blocked, id=12984, stack(0x643d0000,0x644d0000)]
0x5da1c000 JavaThread "RMI RenewClean-[192.168.40.35:1941]" daemon [_thread_blocked, id=9096, stack(0x641d0000,0x642d0000)]
0x5df7b800 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=6672, stack(0x63cd0000,0x63dd0000)]
0x5dbef800 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=13076, stack(0x63bd0000,0x63cd0000)]
0x5d335c00 JavaThread "jms-fifo-5" [_thread_blocked, id=5108, stack(0x638d0000,0x639d0000)]
0x5dc50400 JavaThread "jms-fifo-4" [_thread_blocked, id=588, stack(0x637d0000,0x638d0000)]
0x5daaa000 JavaThread "jms-fifo-3" [_thread_blocked, id=9968, stack(0x636d0000,0x637d0000)]
0x5d4eb800 JavaThread "jms-fifo-2" [_thread_blocked, id=5636, stack(0x635d0000,0x636d0000)]
0x61a40400 JavaThread "jms-fifo-1" [_thread_blocked, id=15884, stack(0x634d0000,0x635d0000)]
0x5dbf6800 JavaThread "RMI RenewClean-[192.168.40.35:2178]" daemon [_thread_blocked, id=8716, stack(0x631d0000,0x632d0000)]
0x5d455c00 JavaThread "RMI RenewClean-[192.168.40.34:2233]" daemon [_thread_blocked, id=14028, stack(0x614d0000,0x615d0000)]
0x5dc71400 JavaThread "RMI RenewClean-[192.168.40.34:3534]" daemon [_thread_blocked, id=7068, stack(0x613d0000,0x614d0000)]
0x5d509000 JavaThread "RMI Scheduler(0)" daemon [_thread_blocked, id=10984, stack(0x5ed90000,0x5ee90000)]
0x5d819c00 JavaThread "snapshot thread" daemon [_thread_blocked, id=10840, stack(0x5eb90000,0x5ec90000)]
0x5d7b3400 JavaThread "discovery announcement" daemon [_thread_blocked, id=6580, stack(0x5ea90000,0x5eb90000)]
0x5c810800 JavaThread "multicast request" daemon [_thread_in_native, id=11208, stack(0x5e990000,0x5ea90000)]
0x5c74a400 JavaThread "unicast request" daemon [_thread_in_native, id=1328, stack(0x5e890000,0x5e990000)]
0x5d303800 JavaThread "event expire" daemon [_thread_blocked, id=7796, stack(0x5e790000,0x5e890000)]
0x5c7b8800 JavaThread "service expire" daemon [_thread_blocked, id=15348, stack(0x5e690000,0x5e790000)]
0x5c7b8400 JavaThread "Thread-3" daemon [_thread_blocked, id=13080, stack(0x5e590000,0x5e690000)]
0x5d3b6800 JavaThread "Thread-2" daemon [_thread_blocked, id=6772, stack(0x5e490000,0x5e590000)]
0x5d3b6400 JavaThread "multicast announcement timer" daemon [_thread_blocked, id=13304, stack(0x5e390000,0x5e490000)]
0x5d4e1c00 JavaThread "multicast discovery announcement listener" daemon [_thread_in_native, id=10632, stack(0x5e290000,0x5e390000)]
0x5d3d5400 JavaThread "GC Daemon" daemon [_thread_blocked, id=13068, stack(0x5e190000,0x5e290000)]
0x5d492800 JavaThread "RMI Reaper" [_thread_blocked, id=6540, stack(0x5e090000,0x5e190000)]
0x5c6cc000 JavaThread "RMI TCP Accept-0" daemon [_thread_in_native, id=10780, stack(0x5df90000,0x5e090000)]
0x5c69fc00 JavaThread "Low Memory Detector" daemon [_thread_blocked, id=8196, stack(0x5cf70000,0x5d070000)]
=>0x5c69c800 JavaThread "CompilerThread1" daemon [_thread_in_native, id=4960, stack(0x5ce70000,0x5cf70000)]
0x5c697c00 JavaThread "CompilerThread0" daemon [_thread_blocked, id=5152, stack(0x5cd70000,0x5ce70000)]
0x5c696400 JavaThread "Attach Listener" daemon [_thread_blocked, id=14576, stack(0x5cc70000,0x5cd70000)]
0x5c695400 JavaThread "Signal Dispatcher" daemon [_thread_blocked, id=16064, stack(0x5cb70000,0x5cc70000)]
0x5bf5f800 JavaThread "Finalizer" daemon [_thread_blocked, id=16192, stack(0x5ca70000,0x5cb70000)]
0x5bf5e400 JavaThread "Reference Handler" daemon [_thread_blocked, id=7228, stack(0x5c970000,0x5ca70000)]
Other Threads:
0x5c691000 VMThread [stack: 0x5c870000,0x5c970000] [id=8468]
0x5c6a1c00 WatcherThread [stack: 0x5d070000,0x5d170000] [id=10620]
VM state:not at safepoint (normal execution)
VM Mutex/Monitor currently owned by a thread: None
Heap
PSYoungGen total 89856K, used 19025K [0x55490000, 0x5b6f0000, 0x5b810000)
eden space 79232K, 16% used [0x55490000,0x561a64c0,0x5a1f0000)
from space 10624K, 52% used [0x5ac90000,0x5b20e2f8,0x5b6f0000)
to space 10752K, 0% used [0x5a1f0000,0x5a1f0000,0x5ac70000)
PSOldGen total 460416K, used 308422K [0x23810000, 0x3f9b0000, 0x55490000)
object space 460416K, 66% used [0x23810000,0x36541bb8,0x3f9b0000)
PSPermGen total 107520K, used 106079K [0x03810000, 0x0a110000, 0x23810000)
object space 107520K, 98% used [0x03810000,0x09fa7e40,0x0a110000)
Dynamic libraries:
0x00400000 - 0x00411000 C:\JRun4\bin\jrun.exe
0x7c800000 - 0x7c8c2000 C:\WINDOWS\system32\ntdll.dll
0x77e40000 - 0x77f42000 C:\WINDOWS\system32\kernel32.dll
0x7d1e0000 - 0x7d27c000 C:\WINDOWS\system32\ADVAPI32.dll
0x77c50000 - 0x77cef000 C:\WINDOWS\system32\RPCRT4.dll
0x76f50000 - 0x76f63000 C:\WINDOWS\system32\Secur32.dll
0x78520000 - 0x785c3000 C:\WINDOWS\WinSxS\x86_Microsoft.VC90.CRT_1fc8b3b9a1e18e3b_9.0.21022.8_x-ww_D08D0375\MSVCR 90.dll
0x6db60000 - 0x6df6a000 C:\JRun4\jre\bin\server\jvm.dll
0x77380000 - 0x77411000 C:\WINDOWS\system32\USER32.dll
0x77c00000 - 0x77c49000 C:\WINDOWS\system32\GDI32.dll
0x76aa0000 - 0x76acd000 C:\WINDOWS\system32\WINMM.dll
0x7c340000 - 0x7c396000 C:\JRun4\bin\MSVCR71.dll
0x76290000 - 0x762ad000 C:\WINDOWS\system32\IMM32.DLL
0x7f000000 - 0x7f009000 C:\WINDOWS\system32\LPK.DLL
0x75490000 - 0x754f5000 C:\WINDOWS\system32\USP10.dll
0x6d860000 - 0x6d86c000 C:\JRun4\jre\bin\verify.dll
0x6d3e0000 - 0x6d3ff000 C:\JRun4\jre\bin\java.dll
0x6d340000 - 0x6d348000 C:\JRun4\jre\bin\hpi.dll
0x76b70000 - 0x76b7b000 C:\WINDOWS\system32\PSAPI.DLL
0x6d8a0000 - 0x6d8af000 C:\JRun4\jre\bin\zip.dll
0x6d6c0000 - 0x6d6d3000 C:\JRun4\jre\bin\net.dll
0x71c00000 - 0x71c17000 C:\WINDOWS\system32\WS2_32.dll
0x77ba0000 - 0x77bfa000 C:\WINDOWS\system32\msvcrt.dll
0x71bf0000 - 0x71bf8000 C:\WINDOWS\system32\WS2HELP.dll
0x71b20000 - 0x71b61000 C:\WINDOWS\System32\mswsock.dll
0x76ed0000 - 0x76efa000 C:\WINDOWS\system32\DNSAPI.dll
0x76f70000 - 0x76f77000 C:\WINDOWS\System32\winrnr.dll
0x76f10000 - 0x76f3e000 C:\WINDOWS\system32\WLDAP32.dll
0x76f80000 - 0x76f85000 C:\WINDOWS\system32\rasadhlp.dll
0x5d630000 - 0x5d63c000 C:\JRun4\bin\portscan.dll
0x5f270000 - 0x5f2ca000 C:\WINDOWS\system32\hnetcfg.dll
0x71ae0000 - 0x71ae8000 C:\WINDOWS\System32\wshtcpip.dll
0x68000000 - 0x68035000 C:\WINDOWS\system32\rsaenh.dll
0x76920000 - 0x769e2000 C:\WINDOWS\system32\USERENV.dll
0x71c40000 - 0x71c97000 C:\WINDOWS\system32\netapi32.dll
0x6d7b0000 - 0x6d7b6000 C:\JRun4\jre\bin\rmi.dll
0x6d6e0000 - 0x6d6e9000 C:\JRun4\jre\bin\nio.dll
0x5f190000 - 0x5f197000 C:\JRun4\bin\FusionReactor.dll
0x77d00000 - 0x77d8b000 C:\WINDOWS\system32\OLEAUT32.dll
0x77670000 - 0x777a9000 C:\WINDOWS\system32\ole32.dll
0x5f1a0000 - 0x5f1aa000 C:\WINDOWS\system32\perfos.dll
0x6d840000 - 0x6d848000 C:\JRun4\jre\bin\sunmscapi.dll
0x761b0000 - 0x76243000 C:\WINDOWS\system32\CRYPT32.dll
0x76190000 - 0x761a2000 C:\WINDOWS\system32\MSASN1.dll
0x5f090000 - 0x5f110000 C:\JRun4\servers\CF_Instance2a\cfusion.ear\cfusion.war\WEB-INF\cfusion\lib\izmjniado.dll
0x76cf0000 - 0x76d0a000 C:\WINDOWS\system32\iphlpapi.dll
0x76cd0000 - 0x76ce9000 C:\WINDOWS\system32\MPRAPI.dll
0x76df0000 - 0x76e24000 C:\WINDOWS\system32\ACTIVEDS.dll
0x76dc0000 - 0x76de8000 C:\WINDOWS\system32\adsldpc.dll
0x76b80000 - 0x76bae000 C:\WINDOWS\system32\credui.dll
0x7c8d0000 - 0x7d0cf000 C:\WINDOWS\system32\SHELL32.dll
0x7d180000 - 0x7d1d2000 C:\WINDOWS\system32\SHLWAPI.dll
0x76a80000 - 0x76a98000 C:\WINDOWS\system32\ATL.DLL
0x76e30000 - 0x76e3c000 C:\WINDOWS\system32\rtutils.dll
0x7e020000 - 0x7e02f000 C:\WINDOWS\system32\SAMLIB.dll
0x770e0000 - 0x771e8000 C:\WINDOWS\system32\SETUPAPI.dll
0x77420000 - 0x77523000 C:\WINDOWS\WinSxS\x86_Microsoft.Windows.Common-Controls_6595b64144ccf1df_6.0.3790.3959_x- ww_D8713E55\comctl32.dll
0x5f200000 - 0x5f223000 C:\JRun4\servers\CF_Instance2a\cfusion.ear\cfusion.war\WEB-INF\cfusion\lib\CFXNeo.dll
0x5f230000 - 0x5f243000 C:\JRun4\servers\cfusion\cfusion-ear\cfusion-war\WEB-INF\cfusion\lib\cfregistry.dll
0x647d0000 - 0x647e3000 C:\JRun4\servers\CF_Instance2a\cfusion.ear\cfusion.war\WEB-INF\cfusion\lib\cfregistry.dll
0x65ad0000 - 0x65c1a000 C:\JRun4\jre\bin\awt.dll
0x64a00000 - 0x64a27000 C:\WINDOWS\system32\WINSPOOL.DRV
0x77530000 - 0x775c7000 C:\WINDOWS\WinSxS\x86_Microsoft.Windows.Common-Controls_6595b64144ccf1df_5.82.3790.3959_x -ww_78FCF8D0\comctl32.dll
0x6d2e0000 - 0x6d334000 C:\JRun4\jre\bin\fontmanager.dll
0x64900000 - 0x6490e000 C:\JRun4\servers\CF_Instance2a\cfusion.ear\cfusion.war\WEB-INF\cfusion\lib\NeoUUID.dll
0x6d610000 - 0x6d619000 C:\JRun4\jre\bin\management.dll
0x5f2d0000 - 0x5f380000 K:\Instance\Core\WEB02_2a_cfx_image_mx.dll
0x73eb0000 - 0x73fd1000 C:\WINDOWS\system32\MFC42.DLL
0x60280000 - 0x60351000 C:\WINDOWS\system32\WININET.dll
0x5f380000 - 0x5f389000 C:\WINDOWS\system32\Normaliz.dll
0x5fad0000 - 0x5fb15000 C:\WINDOWS\system32\iertutil.dll
0x71bb0000 - 0x71bb9000 C:\WINDOWS\system32\WSOCK32.dll
0x5f390000 - 0x5f3cd000 C:\WINDOWS\system32\ODBC32.dll
0x762b0000 - 0x762f9000 C:\WINDOWS\system32\comdlg32.dll
0x5fb20000 - 0x5fb30000 C:\WINDOWS\system32\MSVCIRT.dll
0x607e0000 - 0x607f7000 C:\WINDOWS\system32\odbcint.dll
0x5ec90000 - 0x5ecb4000 C:\JRun4\jre\bin\jpeg.dll
0x5ecd0000 - 0x5ecdb000 C:\JRun4\servers\CF_Instance2a\cfusion.ear\cfusion.war\WEB-INF\cfusion\lib\clib_jiio_util .dll
0x61180000 - 0x6128c000 C:\JRun4\servers\CF_Instance2a\cfusion.ear\cfusion.war\WEB-INF\cfusion\lib\clib_jiio_sse2 .dll
0x5ed00000 - 0x5ed23000 C:\JRun4\jre\bin\dcpr.dll
VM Arguments:
jvm_args: -Xmx896m -Dsun.io.useCanonCaches=false -XX:MaxPermSize=512m -XX:+UseParallelGC -Dcoldfusion.rootDir=C:\JRun4/ -verbose:gc -Xloggc:c:/Jrun4/logs/gc/gcInstance2a.log -Djmx.invoke.getters=true
java_command: <unknown>
Launcher Type: generic
Environment Variables:
PATH=C:\JRun4\servers\cfusion\cfusion-ear\cfusion-war\WEB-INF\cfusion\lib;C:\JRun4\servers \cfusion\cfusion-ear\cfusion-war\WEB-INF\cfusion\jintegra\bin;C:\JRun4\servers\cfusion\cfu sion-ear\cfusion-war\WEB-INF\cfusion\jintegra\bin\international;C:\JRun4\servers\cfusion\c fusion-ear\cfusion-war\WEB-INF\cfusion\lib\oosdk\classes\win;C:\Program Files\Windows Resource Kits\Tools\;C:\Program Files\Support Tools\;C:\Perl\bin\;C:\JRun4\verity\k2\_nti40\bin;C:\Program Files\EMC\PowerPath\;C:\WINDOWS\system32;C:\WINDOWS;C:\WINDOWS\System32\Wbem;C:\Program Files\Dell\SysMgt\RAC4;C:\Program Files\Dell\SysMgt\oma\bin;C:\Program Files\Microsoft SQL Server\80\Tools\Binn\;C:\Program Files\Microsoft SQL Server\90\Tools\binn\;C:\Program Files\Microsoft SQL Server\90\DTS\Binn\;C:\Program Files\Microsoft SQL Server\90\Tools\Binn\VSShell\Common7\IDE\;C:\PROGRA~1\SAAZOD\zScripts\
USERNAME=lcbadmin
OS=Windows_NT
PROCESSOR_IDENTIFIER=x86 Family 15 Model 4 Stepping 8, GenuineIntel
--------------- S Y S T E M ---------------
OS: Windows Server 2003 family Build 3790 Service Pack 2
CPU:total 8 (2 cores per cpu, 2 threads per core) family 15 model 4 stepping 8, cmov, cx8, fxsr, mmx, sse, sse2, sse3, ht
Memory: 4k page, physical 2097151k(2097151k free), swap 4194303k(4194303k free)
vm_info: Java HotSpot(TM) Server VM (14.0-b16) for windows-x86 JRE (1.6.0_14-b08), built on May 21 2009 07:57:57 by "java_re" with MS VC++ 7.1
time: Tue May 18 21:48:13 2010
elapsed time: 154379 seconds
0.381: [GC 3072K->717K(7680K), 0.0028050 secs]
0.578: [GC 3789K->923K(7680K), 0.0026605 secs]
2.581: [GC 3995K->1086K(7680K), 0.0028255 secs]
2.860: [GC 4158K->1283K(7680K), 0.0042886 secs]
3.056: [GC 4355K->1467K(7680K), 0.0028442 secs]
3.231: [GC 4537K->1648K(11008K), 0.0025800 secs]
3.713: [GC 7792K->2190K(11008K), 0.0040999 secs]
3.985: [GC 4856K->2263K(17408K), 0.0025673 secs]
3.988: [Full GC 2263K->2146K(17408K), 0.0487271 secs]
4.696: [GC 14434K->3018K(16832K), 0.0051747 secs]
5.486: [GC 14858K->3805K(16192K), 0.0045260 secs]
6.045: [GC 15197K->4709K(16000K), 0.0074686 secs]
6.053: [Full GC 4709K->4451K(22464K), 0.1103924 secs]
6.787: [GC 15039K->5937K(22528K), 0.0117950 secs]
7.218: [GC 16625K->7804K(22912K), 0.0099954 secs]
7.573: [GC 18492K->10050K(24704K), 0.0144209 secs]
8.256: [GC 21826K->10582K(25024K), 0.0079624 secs]
8.639: [GC 22358K->10701K(27776K), 0.0130334 secs]
8.652: [Full GC 10701K->7499K(36096K), 0.1193615 secs]
10.349: [GC 21067K->8260K(36160K), 0.0036341 secs]
14.083: [GC 21828K->10306K(37184K), 0.0113857 secs]
15.701: [GC 25090K->9822K(37696K), 0.0059270 secs]
16.614: [GC 24606K->11610K(38272K), 0.0164009 secs]
16.824: [GC 26842K->11008K(38976K), 0.0064352 secs]
17.759: [GC 26240K->11017K(40128K), 0.0056167 secs]
17.967: [GC 27657K->11008K(40384K), 0.0056861 secs]
18.194: [GC 27648K->11008K(42240K), 0.0062386 secs]
18.530: [GC 29504K->11009K(42176K), 0.0052893 secs]
19.610: [GC 29505K->11657K(43200K), 0.0098857 secs]
19.912: [GC 31561K->11633K(43712K), 0.0067032 secs]
20.364: [GC 31537K->12066K(45184K), 0.0081479 secs]
20.805: [GC 32470K->12014K(45440K), 0.0109562 secs]
22.058: [GC 33262K->17043K(46848K), 0.0195642 secs]
23.211: [GC 39571K->19376K(47424K), 0.0259335 secs]
24.402: [GC 41904K->20994K(50112K), 0.0253877 secs]
25.890: [GC 44930K->21307K(50624K), 0.0184082 secs]
26.371: [GC 45243K->22727K(52160K), 0.0178302 secs]
26.884: [GC 47687K->23246K(53120K), 0.0208570 secs]
27.995: [GC 48206K->25664K(54592K), 0.0241083 secs]
29.207: [GC 51298K->31755K(57792K), 0.0290945 secs]
29.236: [Full GC 31755K->27853K(74304K), 0.3884927 secs]
29.924: [GC 46184K->38399K(76288K), 0.0460258 secs]
30.401: [GC 62847K->55516K(80192K), 0.0404456 secs]
30.441: [Full GC 55516K->51591K(107648K), 0.3037522 secs]
30.873: [GC 62219K->59963K(115968K), 0.0441025 secs]
31.388: [GC 84732K->72340K(118976K), 0.0392704 secs]
31.756: [GC 97172K->90818K(126720K), 0.0627947 secs]
31.819: [Full GC 90818K->89854K(162432K), 0.3339941 secs]
32.169: [GC 92791K->90051K(162432K), 0.0469329 secs]
32.477: [GC 117269K->98790K(164992K), 0.0352808 secs]
33.032: [GC 128657K->112415K(164992K), 0.0569482 secs]
33.625: [GC 142303K->129501K(167872K), 0.0829067 secs]
33.708: [Full GC 129501K->128716K(214720K), 0.3245804 secs]
34.410: [GC 133817K->130014K(214720K), 0.0563804 secs]
47.633: [GC 162782K->137909K(216000K), 0.0515256 secs]
49.988: [GC 171957K->141420K(216000K), 0.0516951 secs]
51.694: [GC 175468K->145781K(216000K), 0.1004621 secs]
51.795: [Full GC 145781K->134519K(260224K), 0.5717566 secs]
53.350: [GC 168567K->136461K(260224K), 0.0109643 secs]
54.436: [GC 170509K->141065K(260224K), 0.0167210 secs]
55.290: [GC 175113K->145039K(260224K), 0.0231981 secs]
56.200: [GC 179087K->151640K(260224K), 0.0254553 secs]
57.069: [GC 185688K->159187K(260224K), 0.0374343 secs]
58.092: [GC 193235K->165658K(260224K), 0.0415577 secs]
58.735: [GC 199706K->171695K(260224K), 0.0381981 secs]
59.441: [GC 205743K->177923K(260224K), 0.0466761 secs]
60.138: [GC 211971K->184639K(260224K), 0.0398748 secs]
60.178: [Full GC 184639K->184545K(308672K), 0.6346645 secs]
61.473: [GC 218593K->191727K(308672K), 0.0228897 secs]
62.103: [GC 225775K->198230K(308672K), 0.0452323 secs]
62.593: [GC 232278K->204937K(308672K), 0.0441287 secs]
63.152: [GC 238985K->210234K(308672K), 0.0466643 secs]
63.631: [GC 244282K->214332K(308672K), 0.0308136 secs]
64.069: [GC 248380K->220520K(308672K), 0.0310264 secs]
64.490: [GC 254568K->224630K(307648K), 0.0338149 secs]
64.887: [GC 258678K->227375K(281664K), 0.0177588 secs]
65.336: [GC 261423K->232312K(307456K), 0.0275194 secs]
66.622: [GC 268984K->233248K(307584K), 0.0294454 secs]
68.689: [GC 269920K->233475K(307200K), 0.0303114 secs]
70.063: [GC 272323K->233989K(308224K), 0.0319816 secs]
70.948: [GC 272827K->236267K(309504K), 0.0381517 secs]
72.151: [GC 276971K->243396K(309760K), 0.0479739 secs]
72.810: [GC 284100K->256970K(305792K), 0.0670952 secs]
73.202: [GC 291018K->241617K(308672K), 0.0469614 secs]
73.250: [Full GC 241617K->241374K(365888K), 1.0516054 secs]
75.419: [GC 274751K->244364K(365888K), 0.0663203 secs]
76.501: [GC 278366K->244598K(365888K), 0.0116506 secs]
77.218: [GC 278646K->249688K(365376K), 0.0161159 secs]
77.761: [GC 283736K->249237K(340544K), 0.0173527 secs]
78.002: [GC 283285K->249652K(366336K), 0.1664675 secs]
78.802: [GC 286066K->250024K(364736K), 0.0352561 secs]
86.046: [GC 286428K->246641K(365952K), 0.0169778 secs]
89.807: [GC 286513K->247751K(366080K), 0.0128220 secs]
104.515: [GC 287623K->247447K(365824K), 0.0143550 secs]
105.456: [GC 290071K->247027K(367168K), 0.0130806 secs]
107.171: [GC 289651K->251837K(364800K), 0.0211884 secs]
107.490: [GC 296701K->253512K(366848K), 0.0189826 secs]
107.981: [GC 298376K->251486K(365760K), 0.0193742 secs]
109.163: [GC 298971K->250285K(367168K), 0.0158604 secs]
115.811: [GC 297773K->250474K(365760K), 0.0139898 secs]
118.378: [GC 299946K->254646K(367168K), 0.0217229 secs]
119.027: [GC 304118K->259176K(367296K), 0.0324158 secs]
119.615: [GC 308840K->262151K(368896K), 0.0358532 secs]
120.623: [GC 311815K->270706K(366784K), 0.0824720 secs]
121.470: [GC 316146K->279753K(371584K), 0.0766884 secs]
122.268: [GC 325193K->288492K(360192K), 0.1021346 secs]
122.929: [GC 322540K->294521K(365888K), 0.0907757 secs]
123.531: [GC 328569K->300541K(365888K), 0.0978875 secs]
124.140: [GC 334589K->305907K(365888K), 0.0988647 secs]
124.703: [GC 339955K->311069K(365888K), 0.0951130 secs]
125.315: [GC 345117K->312745K(365888K), 0.0801517 secs]
125.533: [GC 346793K->313321K(365888K), 0.0943218 secs]
125.627: [Full GC 313321K->279735K(412288K), 1.3003860 secs]
126.992: [GC 313783K->280075K(412288K), 0.0125182 secs]
127.076: [GC 314123K->280267K(412288K), 0.0065298 secs]
128.996: [GC 314315K->283281K(412288K), 0.0107040 secs]
129.398: [GC 317329K->283830K(412288K), 0.0095192 secs]
129.695: [GC 317878K->283843K(412288K), 0.0104606 secs]
134.828: [GC 317891K->284435K(412288K), 0.0091083 secs]
135.574: [GC 318483K->287393K(412288K), 0.0108201 secs]
135.749: [GC 321441K->286125K(412288K), 0.0087844 secs]
135.795: [GC 320173K->286269K(412288K), 0.0064130 secs]
135.841: [GC 320317K->286401K(412288K), 0.0059679 secs]
136.118: [GC 320449K->286916K(412288K), 0.0069953 secs]
136.761: [GC 320964K->288092K(412288K), 0.0079408 secs]
138.931: [GC 322140K->288414K(412288K), 0.0071464 secs]
155.109: [GC 322462K->290915K(412288K), 0.0073039 secs]
162.080: [GC 324963K->290026K(378752K), 0.0085490 secs]
166.335: [GC 324074K->292428K(409984K), 0.0075349 secs]
166.668: [GC 327820K->293701K(383808K), 0.0110931 secs]
167.470: [GC 329093K->295465K(406464K), 0.0431141 secs]
167.814: [GC 332777K->297419K(408256K), 0.0173732 secs]
168.042: [GC 334731K->295698K(406976K), 0.0249668 secs]
168.530: [GC 336018K->294099K(408128K), 0.0117701 secs]
186.485: [GC 334406K->294290K(405568K), 0.0099247 secs]
189.467: [GC 337042K->293803K(407552K), 0.0092321 secs]
192.025: [GC 336555K->294114K(405184K), 0.0144861 secs]
192.537: [GC 338658K->293848K(406848K), 0.0096140 secs]
198.694: [GC 338392K->294634K(404800K), 0.0275907 secs]
200.414: [GC 340714K->295225K(406208K), 0.0243144 secs]
201.828: [GC 341305K->294499K(404800K), 0.0191665 secs]
202.519: [GC 342051K->294865K(405824K), 0.0105044 secs]
207.017: [GC 342417K->295663K(404992K), 0.0190171 secs]
218.114: [GC 344495K->297980K(405760K), 0.0192997 secs]
218.433: [GC 346812K->296451K(407424K), 0.0127834 secs]
219.292: [GC 346819K->296114K(407168K), 0.0103118 secs]
227.933: [GC 346482K->298582K(407936K), 0.0205685 secs]
228.202: [GC 350358K->299398K(408192K), 0.0224917 secs]
228.984: [GC 351174K->297324K(410048K), 0.0120500 secs]
231.777: [GC 351722K->297050K(410816K), 0.0146803 secs]
236.016: [GC 351431K->297635K(411136K), 0.0126529 secs]
239.092: [GC 353955K->298634K(411840K), 0.0155092 secs]
239.552: [GC 354954K->299904K(413120K), 0.0215851 secs]
252.632: [GC 357566K->298439K(413440K), 0.0137175 secs]
269.175: [GC 356103K->298922K(414016K), 0.0170458 secs]
273.686: [GC 358166K->299811K(414592K), 0.0213339 secs]
275.229: [GC 359066K->301064K(415616K), 0.0209921 secs]
288.095: [GC 361412K->304481K(416000K), 0.0232993 secs]
288.392: [GC 364833K->303245K(418624K), 0.0226790 secs]
301.675: [GC 364685K->302009K(418816K), 0.0362261 secs]
307.093: [GC 363449K->300955K(419392K), 0.0126385 secs]
309.805: [GC 364430K->301618K(420160K), 0.0126741 secs]
325.062: [GC 365106K->302651K(420352K), 0.0151472 secs]
339.201: [GC 367545K->301935K(420928K), 0.0181489 secs]
346.999: [GC 366831K->301900K(420864K), 0.0125003 secs]
348.433: [GC 367756K->303969K(421312K), 0.0198808 secs]
357.384: [GC 369825K->302469K(421888K), 0.0198447 secs]
358.633: [GC 369349K->303806K(422272K), 0.3034111 secs]
359.588: [GC 370686K->306106K(427136K), 0.3337606 secs]
360.523: [GC 378170K->306180K(427392K), 0.0179965 secs]
361.119: [GC 378244K->304632K(434688K), 0.0256676 secs]
364.956: [GC 384248K->303336K(434880K), 0.0169394 secs]
365.935: [GC 382952K->305060K(434624K), 0.0194296 secs]
368.833: [GC 385060K->305320K(434944K), 0.0149410 secs]
370.448: [GC 385320K->304360K(435200K), 0.0216550 secs]
377.487: [GC 385185K->306224K(435456K), 0.0202275 secs]
385.574: [GC 387056K->305525K(435392K), 0.0180600 secs]
388.927: [GC 386805K->306564K(435648K), 0.0175783 secs]
391.674: [GC 387844K->309037K(434304K), 0.0254813 secs]
407.514: [GC 388909K->308487K(433600K), 0.0175757 secs]
409.194: [GC 388359K->311467K(432512K), 0.0209529 secs]
414.063: [GC 388395K->314784K(433728K), 0.0241777 secs]
415.431: [GC 391712K->313315K(430912K), 0.0223951 secs]
430.083: [GC 387427K->314564K(430592K), 0.0232336 secs]
439.450: [GC 388676K->315193K(430400K), 0.0247885 secs]
441.171: [GC 386745K->312782K(431040K), 0.0169260 secs]
452.250: [GC 384334K->313844K(430720K), 0.0202268 secs]
460.522: [GC 385844K->319503K(430976K), 0.2599954 secs]
468.974: [GC 391503K->322586K(424064K), 0.0422984 secs]
469.474: [GC 387095K->323360K(424512K), 0.0407064 secs]
477.136: [GC 387872K->322728K(425728K), 0.0311824 secs]
478.559: [GC 384552K->323311K(421760K), 0.0272584 secs]
484.216: [GC 385128K->322961K(425280K), 0.0298063 secs]
495.042: [GC 383377K->323348K(425472K), 0.0294568 secs]
507.955: [GC 383750K->323970K(424128K), 0.0292337 secs]
513.449: [GC 384514K->323429K(424832K), 0.0228552 secs]
522.316: [GC 383973K->324246K(424256K), 0.0451143 secs]
529.871: [GC 385935K->326326K(424896K), 0.0519706 secs]
530.225: [GC 388022K->324837K(426240K), 0.0314384 secs]
534.490: [GC 388133K->324714K(425792K), 0.0241508 secs]
563.372: [GC 388010K->324722K(427456K), 0.0246593 secs]
572.215: [GC 390130K->324496K(427200K), 0.0251314 secs]
573.388: [GC 389904K->324967K(427712K), 0.0333442 secs]
585.876: [GC 391143K->325337K(416128K), 0.0146273 secs]
588.092: [GC 391513K->326307K(427840K), 0.0150402 secs]
590.242: [GC 391587K->327561K(417344K), 0.0243195 secs]
597.280: [GC 392841K->326350K(427904K), 0.0166214 secs]
605.425: [GC 391822K->325727K(427776K), 0.0130987 secs]
621.244: [GC 391199K->326293K(427840K), 0.0137431 secs]
631.514: [GC 392213K->325980K(427968K), 0.0116427 secs]
635.911: [GC 391900K->326451K(427840K), 0.0144855 secs]
642.943: [GC 393075K->327191K(428096K), 0.0141549 secs]
650.865: [GC 393815K->328001K(427136K), 0.0262237 secs]
654.381: [GC 395201K->327424K(427712K), 0.0161351 secs]
654.834: [GC 394624K->327019K(428288K), 0.0150662 secs]
665.058: [GC 395243K->327139K(427904K), 0.0115758 secs]
673.535: [GC 395352K->326908K(427776K), 0.0198125 secs]
695.278: [GC 396284K->327746K(428352K), 0.0181528 secs]
704.497: [GC 397122K->328052K(427456K), 0.0190775 secs]
711.387: [GC 398196K->329218K(428096K), 0.0499620 secs]
719.837: [GC 399362K->328605K(427200K), 0.0170412 secs]
735.922: [GC 399517K->327069K(427776K), 0.0145175 secs]
736.804: [GC 397981K->327242K(428416K), 0.0110488 secs]
747.130: [GC 398986K->328367K(428224K), 0.0190119 secs]
749.678: [GC 400104K->327812K(428224K), 0.0143051 secs]
767.357: [GC 400452K->328673K(428416K), 0.0338326 secs]
772.008: [GC 401313K->330038K(428352K), 0.0205973 secs]
773.157: [GC 403446K->328909K(428544K), 0.0178709 secs]
773.757: [GC 402310K->328315K(429696K), 0.0140103 secs]
779.192: [GC 403187K->329304K(429440K), 0.0122486 secs]
784.114: [GC 404184K->329444K(429376K), 0.0136336 secs]
800.024: [GC 405604K->330673K(430016K), 0.0161595 secs]
810.128: [GC 406833K->329507K(430208K), 0.0155031 secs]
822.611: [GC 406518K->328618K(430656K), 0.0159114 secs]
830.465: [GC 405674K->329259K(430720K), 0.0134547 secs]
832.320: [GC 406955K->331849K(431040K), 0.0192622 secs]
839.589: [GC 409543K->330317K(431488K), 0.0152272 secs]
846.029: [GC 408841K->330677K(431936K), 0.0146644 secs]
855.691: [GC 409205K->330917K(432000K), 0.0147851 secs]
857.089: [GC 410085K->329282K(432256K), 0.0113335 secs]
862.172: [GC 408450K->330507K(433280K), 0.0744561 secs]
864.102: [GC 410827K->329939K(433152K), 0.0602524 secs]
871.764: [GC 410259K->337849K(432896K), 0.0464115 secs]
873.725: [GC 418041K->340453K(435264K), 0.0492662 secs]
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881.246: [GC 423156K->354299K(420736K), 0.0444023 secs]
881.291: [Full GC 354299K->184625K(324608K), 1.7573846 secs]
885.122: [GC 247345K->189442K(330496K), 0.0344186 secs]
890.421: [GC 252162K->189400K(329792K), 0.0117897 secs]
892.905: [GC 252312K->191219K(330240K), 0.0194622 secs]
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896.839: [GC 254816K->190146K(330368K), 0.0139860 secs]
901.632: [GC 254400K->189745K(330304K), 0.0130588 secs]
909.589: [GC 255600K->191848K(331008K), 0.0234403 secs]
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921.147: [GC 258939K->193093K(330752K), 0.0297285 secs]
925.261: [GC 260293K->192604K(330368K), 0.0226062 secs]
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953.023: [GC 261717K->192548K(331008K), 0.0233991 secs]
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998.709: [GC 268457K->192952K(333568K), 0.0181598 secs]
1004.050: [GC 267448K->192375K(333952K), 0.0159302 secs]
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1013.933: [GC 267661K->194230K(334400K), 0.0254282 secs]
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1091.405: [GC 272168K->193745K(336192K), 0.0133192 secs]
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1179.512: [GC 273585K->194432K(337792K), 0.0153779 secs]
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1195.271: [GC 275190K->196552K(337984K), 0.0223260 secs]
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1256.108: [GC 276737K->195947K(339904K), 0.0238248 secs]
1267.525: [GC 278315K->195033K(340352K), 0.0569615 secs]
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1376.770: [GC 283224K->200903K(339136K), 0.0309814 secs]
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1423.983: [GC 279419K->199784K(339264K), 0.0155648 secs]
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1434.942: [GC 281249K->200341K(339584K), 0.0223844 secs]
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1532.011: [GC 284019K->200888K(335296K), 0.0148204 secs]
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1574.922: [GC 289719K->228796K(334784K), 1.5292558 secs]
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1594.496: [GC 298233K->251601K(323072K), 0.0251024 secs]
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1597.865: [GC 278951K->240314K(372800K), 0.0389260 secs]
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2939.749: [GC 3Hi! Thanks for the reply,
After much googling we've finally found a stable configuration.
java.args=-server -Xmx768m -Xss64k -Dsun.io.useCanonCaches=false -XX:MaxPermSize=512m -XX:+UseParallelGC -Dcoldfusion.rootDir={application.home}/ -verbose:gc -Xloggc:c:/Jrun4/logs/gc/gcInstance1b.log
I tried playing with the survivor ratio but came back to the default when I didn't notice much improvement. In the end what did it (pretty sure) is -Xss to reduce the requests size living on the stack. Our large initial heap, perm + overhead combined with the default request size was causing the JVM to go over and blow up I think.
We've been stable for over a month now, the next step for us is to reduce the MaxPermSize a little at a time to find our optimal range. -
Using my 60GB black ipod in my car
i recently purchased this ipod, and decided to get the silver dlo docking/charging system for my car. this is the one that you simply plug into the power outlet, where a cig lighter normally is. everything works fine, except for the tiny detail that its not corresponding with my equally expensive sound system (amp and woofers). i'm not sure what the problem is, but hopefully it is something simple. i just wanted some feedback before i took it to my audio guy. anybody have any suggestions?
> silver dlo docking/charging system the one that you simply plug into the power outlet, its not corresponding with my equally expensive sound system (amp and woofers)
I too have DLO Docking cradle and a 60GB Black pod. Mine works great. I tried a number of different FM transmitters and docks prior to the DLO.
I recently had a variety of rental cars and found that while the DLO offered a rich full sound with my Mustang, a Mazda mini-van and was fine with a KIA, it was okay with a Porsche Boxtser, lousy with a Dodge Durango, and just a tad better with a Nissan Xtreme. My conclusion was that it depends on the vehicle. The physical distance to the radio seemed to have some effect in the vehicles when there was not ideal transmission.
Since you have amps and woofers (and an audio guy!) I think I would opt for the hardwired plug in that goes directly to your audio system. But failing that, yeah, it sounds like there is an internal issue with your stereo that prevents the reception of the signal. The alternative, of course, is to keep buying different FM transmitters until you find the optimal combination for your vehicle. That's what I did.
Good luck!
Acer Ferrari Windows XP -
Display Resolution Poor in OSX while great in Win 7
I have a 2011 MacBook Pro and I recently purchased a Samsung SyncMaster TA550 monitor/TV that I was hoping to use as a monitor. I am able to get the monitor to work through a mini DisplayPort to HDMI convertor, but the resolution and color on the monitor is very poor. In order to check that I didn't just have a bad cable, I was able to bootcamp into Windows 7 to check out the external monitor. In Windows 7 the monitor works perfectly. Both the color and the resolution are flawless. Any ideas?
Keywords: MBP, macbook-pro, samsung, T24A350, T24A550, monitor, display, solution, optimised settings
Computer : Macbook PRO mid 2011 version (but I guess it will work for earlier and future models as well)
Monitor : Samsung T24A350 (also works for the T24A550 and other monitor/tv models)
Problem : Solve poor quality of the monitor screen if using default settings
When connected to the Samsung monitor/tv, the screen quality is very poor if using the default settings.
However with the following procedure/settings the screen quality of this monitor is excellent!
It took me quite a while to find the optimized settings for the Samsung monitor T24A350 connected to a Macbook-pro via the minidisplay port -> HDMI adapter -> HDMI cable -> HDMI IN 1 (Samsung monitor). It is in the manual, but I overlooked it initially. The confusion is that the mini display port apparently is a DVI port and needs a special setting to work properly.
PROCEDURE (see also page 21 of the English or Dutch user manual
1. Select Source on the remote control
2. Select PC
3. Select SOURCE -> TOOLS -> Edit Name -> Enter
4. When connecting a PC to HDMI IN 1 (mini display port) with DVI to HDMI cable, change the mode name to "DVI PC" from the pull down menu
I guess the same setting is required if you use the mini display port to VGA adapter. However I did not check this.
Regards,
Leo.
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