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*
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* under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2.1 of
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*
* This software is distributed in the hope that it will be useful,
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
* Lesser General Public License for more details.
*
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package org.infinispan.distribution;
import org.infinispan.distribution.ch.ConsistentHash;
import org.infinispan.remoting.transport.Address;
import org.infinispan.remoting.transport.jgroups.JGroupsAddress;
import org.infinispan.test.AbstractInfinispanTest;
import org.infinispan.util.Util;
import org.testng.annotations.Test;
import java.util.*;
import java.util.concurrent.TimeUnit;
import static java.lang.Math.*;
/**
* Tests the uniformity of the distribution hash algo.
*
* @author Manik Surtani
* @since 4.0
*/
@Test(testName = "distribution.ConsistentHashPerfTest", groups = "manual", description = "Disabled until we can configure Surefire to skip manual tests")
public class ConsistentHashPerfTest extends AbstractInfinispanTest {
private List<Address> createAddresses(int numNodes) {
Random r = new Random();
List<Address> addresses = new ArrayList<Address>(numNodes);
while (addresses.size() < numNodes)
addresses.add(new JGroupsAddress(new org.jgroups.util.UUID(r.nextLong(), r.nextLong())));
return addresses;
}
public void testSpeed() {
int[] numNodes = {1, 2, 3, 4, 10, 100, 1000};
int iterations = 100000;
// warmup
doPerfTest(10, 2, iterations);
for (int numOwners = 1; numOwners < 5; numOwners++) {
System.out.println("numOwners=" + numOwners);
for (int nn: numNodes) {
Long duration = doPerfTest(nn, numOwners, iterations);
System.out.println("With "+nn+" cache(s), time to do " + iterations + " lookups was " + Util.prettyPrintTime(TimeUnit.NANOSECONDS.toMillis(duration)));
}
}
}
private Long doPerfTest(int numNodes, int numOwners, int iterations) {
ConsistentHash ch = BaseDistFunctionalTest.createNewConsistentHash(createAddresses(numNodes));
int dummy = 0;
long start = System.nanoTime();
for (int i = 0; i < iterations; i++) {
Object key = i;
dummy += ch.locateOwners(key).size();
}
long duration = System.nanoTime() - start;
assert dummy == iterations * min(numOwners, numNodes);
return duration;
}
public void testDistribution() {
final int numKeys = 10000;
final int[] numNodes = {1, 2, 3, 4, 10, 100, 1000};
List<Object> keys = new ArrayList<Object>(numKeys);
for (int i = 0; i < numKeys; i++) keys.add(i);
for (int nn : numNodes) {
doTestDistribution(numKeys, nn, keys);
}
}
private void doTestDistribution(int numKeys, int numNodes, List<Object> keys) {
ConsistentHash ch = BaseDistFunctionalTest.createNewConsistentHash(createAddresses(numNodes));
Map<Address, Integer> distribution = new HashMap<Address, Integer>();
for (Object key : keys) {
Address a = ch.locateOwners(key).get(0);
if (distribution.containsKey(a)) {
int i = distribution.get(a);
distribution.put(a, i + 1);
} else {
distribution.put(a, 1);
}
}
System.out.printf("\nTesting distribution with %d keys, %d nodes\n", numKeys, numNodes);
//System.out.println("" + distribution);
// calc numbers
ArrayList<Integer> counts = new ArrayList<Integer>(distribution.values());
Collections.sort(counts);
// When we go to 100 nodes, one or two nodes may not receive any keys and would cause the next assertion to fail
//assert numNodes == counts.size() : "Only reached " + distribution.size() + " nodes : " + distribution;
// instead we add a 0 for all the nonexistent keys in the distribution map and do the calculations
for (int i = 0; i < numNodes - counts.size(); i++)
counts.add(0, 0);
double mean = 0;
int sum = 0;
for (Integer count : counts) sum += count;
assert sum == numKeys;
mean = sum / numNodes;
double variance = 0;
for (Integer count : counts) variance += (count - mean) * (count - mean);
double stdDev = sqrt(variance);
double avgAbsDev = 0;
for (Integer count : counts) avgAbsDev += abs(count - mean);
avgAbsDev /= numNodes;
int median = counts.get(numNodes / 2);
ArrayList<Integer> medianDevs = new ArrayList<Integer>(numNodes);
for (Integer count : counts) medianDevs.add(abs(count - median));
Collections.sort(medianDevs);
int medianAbsDev = medianDevs.get(numNodes / 2);
System.out.printf("Mean = %f, median = %d\n", mean, median);
System.out.printf("Standard deviation = %.3f, or %.3f%%\n", stdDev, stdDev / mean * 100);
System.out.printf("Average absolute deviation = %.3f, or %.3f%%\n", avgAbsDev, avgAbsDev / mean * 100);
System.out.printf("Median absolute deviation = %d or %.3f%%\n", medianAbsDev, (double)medianAbsDev / mean * 100);
}
}