public void map(
Object key, Text value, OutputCollector<IntWritable, Text> output, Reporter reporter)
throws IOException {
// vid neighbors_num n1 n2 ...
// vid color 1/0 "COLOR"
String str = value.toString();
if (str.endsWith(COLOR)) {
// color table
String[] tokens = str.substring(0, str.length() - 5).split("\\s+");
int change = Integer.parseInt(tokens[2]);
if (change == 1) {
IntWritable SourceId = new IntWritable(Integer.parseInt(tokens[0]));
StringBuilder sb = new StringBuilder();
sb.append(tokens[1]);
sb.append(" ");
sb.append(tokens[2]);
sb.append(COLOR);
output.collect(SourceId, new Text(sb.toString()));
}
} else {
// edge table
String[] tokens = value.toString().split("\\s+");
IntWritable SourceId = new IntWritable(Integer.parseInt(tokens[0]));
StringBuilder sb = new StringBuilder();
for (int i = 1; i < tokens.length; i++) {
if (sb.length() != 0) sb.append(" ");
sb.append(tokens[i]);
}
output.collect(SourceId, new Text(sb.toString()));
}
}
public void testInputFormat() {
try {
JobConf conf = new JobConf();
String TMP_DIR = System.getProperty("test.build.data", "/tmp");
Path filename = new Path("file:///" + TMP_DIR + "/tmpSeqFile");
SequenceFile.Writer sfw =
SequenceFile.createWriter(
FileSystem.getLocal(conf),
conf,
filename,
ChukwaArchiveKey.class,
ChunkImpl.class,
SequenceFile.CompressionType.NONE,
Reporter.NULL);
StringBuilder buf = new StringBuilder();
int offsets[] = new int[lines.length];
for (int i = 0; i < lines.length; ++i) {
buf.append(lines[i]);
buf.append("\n");
offsets[i] = buf.length() - 1;
}
ChukwaArchiveKey key = new ChukwaArchiveKey(0, "datatype", "sname", 0);
ChunkImpl val = new ChunkImpl("datatype", "sname", 0, buf.toString().getBytes(), null);
val.setRecordOffsets(offsets);
sfw.append(key, val);
sfw.append(key, val); // write it twice
sfw.close();
long len = FileSystem.getLocal(conf).getFileStatus(filename).getLen();
InputSplit split = new FileSplit(filename, 0, len, (String[]) null);
ChukwaInputFormat in = new ChukwaInputFormat();
RecordReader<LongWritable, Text> r = in.getRecordReader(split, conf, Reporter.NULL);
LongWritable l = r.createKey();
Text line = r.createValue();
for (int i = 0; i < lines.length * 2; ++i) {
boolean succeeded = r.next(l, line);
assertTrue(succeeded);
assertEquals(i, l.get());
assertEquals(lines[i % lines.length], line.toString());
System.out.println("read line: " + l.get() + " " + line);
}
boolean succeeded = r.next(l, line);
assertFalse(succeeded);
} catch (IOException e) {
e.printStackTrace();
fail("IO exception " + e);
}
}
public void map(
Object key, Text value, OutputCollector<IntWritable, Text> output, Reporter reporter)
throws IOException {
// id color
// id color 1/0 "COLOR"
String[] tokens = value.toString().split("\\s+");
IntWritable SourceId = new IntWritable(Integer.parseInt(tokens[0]));
StringBuilder sb = new StringBuilder();
for (int i = 1; i < tokens.length; i++) {
if (sb.length() != 0) sb.append(" ");
sb.append(tokens[i]);
}
output.collect(SourceId, new Text(sb.toString()));
}
/**
* Make a path relative with respect to a root path. absPath is always assumed to descend from
* root. Otherwise returned path is null.
*/
static String makeRelative(Path root, Path absPath) {
if (!absPath.isAbsolute()) {
throw new IllegalArgumentException("!absPath.isAbsolute(), absPath=" + absPath);
}
String p = absPath.toUri().getPath();
StringTokenizer pathTokens = new StringTokenizer(p, "/");
for (StringTokenizer rootTokens = new StringTokenizer(root.toUri().getPath(), "/");
rootTokens.hasMoreTokens(); ) {
if (!rootTokens.nextToken().equals(pathTokens.nextToken())) {
return null;
}
}
StringBuilder sb = new StringBuilder();
for (; pathTokens.hasMoreTokens(); ) {
sb.append(pathTokens.nextToken());
if (pathTokens.hasMoreTokens()) {
sb.append(Path.SEPARATOR);
}
}
return sb.length() == 0 ? "." : sb.toString();
}
public void map(Text key, Text value, Context context)
throws InterruptedException, IOException {
String filename = key.toString();
String json = value.toString();
// Make sure the input is valid
if (!(filename.isEmpty() || json.isEmpty())) {
// Change the json-type feature to Mat-type feature
Mat descriptor = json2mat(json);
if (descriptor != null) {
// Read the query feature from the cache in Hadoop
Mat query_features;
String pathStr = context.getConfiguration().get("featureFilePath");
FileSystem fs = FileSystem.get(context.getConfiguration());
FSDataInputStream fsDataInputStream = fs.open(new Path(pathStr));
StringBuilder sb = new StringBuilder();
// Use a buffer to read the query_feature
int remain = fsDataInputStream.available();
while (remain > 0) {
int read;
byte[] buf = new byte[BUF_SIZE];
read = fsDataInputStream.read(buf, fsDataInputStream.available() - remain, BUF_SIZE);
sb.append(new String(buf, 0, read, StandardCharsets.UTF_8));
remain = remain - read;
System.out.println("remain:" + remain + "\tread:" + read + "\tsb.size:" + sb.length());
}
// Read the query_feature line by line
// Scanner sc = new Scanner(fsDataInputStream, "UTF-8");
// StringBuilder sb = new StringBuilder();
// while (sc.hasNextLine()) {
// sb.append(sc.nextLine());
// }
// String query_json = sb.toString();
// String query_json = new String(buf, StandardCharsets.UTF_8);
String query_json = sb.toString();
fsDataInputStream.close();
query_features = json2mat(query_json);
// Get the similarity of the current database image against the query image
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
MatOfDMatch matches = new MatOfDMatch();
// Ensure the two features have same length of cols (the feature extracted are all 128
// cols(at least in this case))
if (query_features.cols() == descriptor.cols()) {
matcher.match(query_features, descriptor, matches);
DMatch[] dMatches = matches.toArray();
// Calculate the max/min distances
// double max_dist = Double.MAX_VALUE;
// double min_dist = Double.MIN_VALUE;
double max_dist = 0;
double min_dist = 100;
for (int i = 0; i < dMatches.length; i++) {
double dist = dMatches[i].distance;
if (min_dist > dist) min_dist = dist;
if (max_dist < dist) max_dist = dist;
}
// Only distances ≤ threshold are good matches
double threshold = max_dist * THRESHOLD_FACTOR;
// double threshold = min_dist * 2;
LinkedList<DMatch> goodMatches = new LinkedList<DMatch>();
for (int i = 0; i < dMatches.length; i++) {
if (dMatches[i].distance <= threshold) {
goodMatches.addLast(dMatches[i]);
}
}
// Get the ratio of good_matches to all_matches
double ratio = (double) goodMatches.size() / (double) dMatches.length;
System.out.println("*** current_record_filename:" + filename + " ***");
System.out.println("feature:" + descriptor + "\nquery_feature:" + query_features);
System.out.println(
"min_dist of keypoints:" + min_dist + " max_dist of keypoints:" + max_dist);
System.out.println(
"total_matches:" + dMatches.length + "\tgood_matches:" + goodMatches.size());
// System.out.println("type:" + descriptor.type() + " channels:" +
// descriptor.channels() + " rows:" + descriptor.rows() + " cols:" + descriptor.cols());
// System.out.println("qtype:" + query_features.type() + "
// qchannels:" + query_features.channels() + " qrows:" + query_features.rows() + "
// qcols:" + query_features.cols());
System.out.println();
if (ratio > PERCENTAGE_THRESHOLD) {
// Key:1 Value:filename|ratio
context.write(ONE, new Text(filename + "|" + ratio));
// context.write(ONE, new Text(filename + "|" +
// String.valueOf(goodMatches.size())));
}
} else {
System.out.println("The size of the features are not equal");
}
} else {
// a null pointer, do nothing
System.out.println("A broken/null feature:" + filename);
System.out.println();
}
}
}