/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.flink.graph.drivers;
import org.apache.flink.client.program.ProgramParametrizationException;
import org.apache.flink.graph.asm.dataset.ChecksumHashCode.Checksum;
import org.junit.Assume;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.junit.runners.Parameterized;
@RunWith(Parameterized.class)
public class ClusteringCoefficientITCase
extends CopyableValueDriverBaseITCase {
public ClusteringCoefficientITCase(String idType, TestExecutionMode mode) {
super(idType, mode);
}
private String[] parameters(int scale, String order, String simplify, String output) {
return new String[] {
"--algorithm", "ClusteringCoefficient", "--order", order,
"--input", "RMatGraph", "--scale", Integer.toString(scale), "--type", idType, "--simplify", simplify,
"--output", output};
}
@Test
public void testLongDescription() throws Exception {
String expected = regexSubstring(new ClusteringCoefficient().getLongDescription());
expectedOutputFromException(
new String[]{"--algorithm", "ClusteringCoefficient"},
expected,
ProgramParametrizationException.class);
}
@Test
public void testHashWithSmallDirectedRMatGraph() throws Exception {
long checksum;
switch (idType) {
case "byte":
case "short":
case "char":
case "integer":
checksum = 0x0000003621c62ca1L;
break;
case "long":
checksum = 0x0000003b74c6719bL;
break;
case "string":
checksum = 0x0000003ab67abea8L;
break;
default:
throw new IllegalArgumentException("Unknown type: " + idType);
}
String expected = "\n" +
new Checksum(117, checksum) + "\n" +
"triplet count: 29286, triangle count: 11466, global clustering coefficient: 0.39151813[0-9]+\n" +
"vertex count: 117, average clustering coefficient: 0.45125697[0-9]+\n";
expectedOutput(parameters(7, "directed", "directed", "hash"), expected);
}
@Test
public void testHashWithSmallUndirectedRMatGraph() throws Exception {
long directed_checksum;
long undirected_checksum;
switch (idType) {
case "byte":
case "short":
case "char":
case "integer":
directed_checksum = 0x0000003875b38c43L;
undirected_checksum = 0x0000003c20344c75L;
break;
case "long":
directed_checksum = 0x0000003671970c59L;
undirected_checksum = 0x0000003939645d8cL;
break;
case "string":
directed_checksum = 0x0000003be109a770L;
undirected_checksum = 0x0000003b8c98d14aL;
break;
default:
throw new IllegalArgumentException("Unknown type: " + idType);
}
String expected = "\n" +
"triplet count: 29286, triangle count: 11466, global clustering coefficient: 0.39151813[0-9]+\n" +
"vertex count: 117, average clustering coefficient: 0.57438679[0-9]+\n";
expectedOutput(parameters(7, "directed", "undirected", "hash"),
"\n" + new Checksum(117, directed_checksum) + expected);
expectedOutput(parameters(7, "undirected", "undirected", "hash"),
"\n" + new Checksum(117, undirected_checksum) + expected);
}
@Test
public void testHashWithLargeDirectedRMatGraph() throws Exception {
// computation is too large for collection mode
Assume.assumeFalse(mode == TestExecutionMode.COLLECTION);
long checksum;
switch (idType) {
case "byte":
return;
case "short":
case "char":
case "integer":
checksum = 0x0000067a9d18e7f3L;
break;
case "long":
checksum = 0x00000694a90ee6d4L;
break;
case "string":
checksum = 0x000006893e3b314fL;
break;
default:
throw new IllegalArgumentException("Unknown type: " + idType);
}
String expected = "\n" +
new Checksum(3349, checksum) + "\n" +
"triplet count: 9276207, triangle count: 1439454, global clustering coefficient: 0.15517700[0-9]+\n" +
"vertex count: 3349, average clustering coefficient: 0.24571815[0-9]+\n";
expectedOutput(parameters(12, "directed", "directed", "hash"), expected);
}
@Test
public void testHashWithLargeUndirectedRMatGraph() throws Exception {
// computation is too large for collection mode
Assume.assumeFalse(mode == TestExecutionMode.COLLECTION);
long directed_checksum;
long undirected_checksum;
switch (idType) {
case "byte":
return;
case "short":
case "char":
case "integer":
directed_checksum = 0x00000681fad1587eL;
undirected_checksum = 0x0000068713b3b7f1L;
break;
case "long":
directed_checksum = 0x000006928a6301b1L;
undirected_checksum = 0x000006a399edf0e6L;
break;
case "string":
directed_checksum = 0x000006749670a2f7L;
undirected_checksum = 0x0000067f19c6c4d5L;
break;
default:
throw new IllegalArgumentException("Unknown type: " + idType);
}
String expected = "\n" +
"triplet count: 9276207, triangle count: 1439454, global clustering coefficient: 0.15517700[0-9]+\n" +
"vertex count: 3349, average clustering coefficient: 0.33029442[0-9]+\n";
expectedOutput(parameters(12, "directed", "undirected", "hash"),
"\n" + new Checksum(3349, directed_checksum) + expected);
expectedOutput(parameters(12, "undirected", "undirected", "hash"),
"\n" + new Checksum(3349, undirected_checksum) + expected);
}
}