private static void BuildPostingsFile(string folder, NaiveInvertedIndex index, string[] dictionary, long[] vocabPositions)
{
// now build the postings file.
FileStream postingsFile = new FileStream(Path.Combine(folder, "postings.bin"), FileMode.Create);
// simultaneously build the vocabulary table on disk, mapping a term index to a
// file location in the postings file.
FileStream vocabTable = new FileStream(Path.Combine(folder, "vocabTable.bin"), FileMode.Create);
// the first thing we must write to the vocabTable file is the number of vocab terms.
byte[] tSize = BitConverter.GetBytes(dictionary.Length);
if (BitConverter.IsLittleEndian)
Array.Reverse(tSize);
vocabTable.Write(tSize, 0, tSize.Length);
int vocabI = 0;
foreach (string s in dictionary) {
// for each string in dictionary, retrieve its postings.
var postings = index.GetPostings(s);
// write the vocab table entry for this term: the byte location of the term in the vocab list file,
// and the byte location of the postings for the term in the postings file.
byte[] vPositionBytes = BitConverter.GetBytes(vocabPositions[vocabI]);
if (BitConverter.IsLittleEndian)
Array.Reverse(vPositionBytes);
vocabTable.Write(vPositionBytes, 0, vPositionBytes.Length);
byte[] pPositionBytes = BitConverter.GetBytes(postingsFile.Position);
if (BitConverter.IsLittleEndian)
Array.Reverse(pPositionBytes);
vocabTable.Write(pPositionBytes, 0, pPositionBytes.Length);
// write the postings file for this term. first, the document frequency for the term, then
// the document IDs, encoded as gaps.
byte[] docFreqBytes = BitConverter.GetBytes(postings.Count);
if (BitConverter.IsLittleEndian)
Array.Reverse(docFreqBytes);
postingsFile.Write(docFreqBytes, 0, docFreqBytes.Length);
int lastDocId = 0;
foreach (int docId in postings) {
byte[] docIdBytes = BitConverter.GetBytes(docId - lastDocId); // encode a gap, not a doc ID
if (BitConverter.IsLittleEndian)
Array.Reverse(docIdBytes);
postingsFile.Write(docIdBytes, 0, docIdBytes.Length);
lastDocId = docId;
}
vocabI++;
}
vocabTable.Close();
postingsFile.Close();
}
private static void BuildIndexForDirectory(string folder)
{
NaiveInvertedIndex index = new NaiveInvertedIndex();
// Index the directory using a naive index
IndexFiles(folder, index);
// at this point, "index" contains the in-memory inverted index
// now we save the index to disk, building three files: the postings index,
// the vocabulary list, and the vocabulary table.
// the array of terms
string[] dictionary = index.GetDictionary();
// an array of positions in the vocabulary file
long[] vocabPositions = new long[dictionary.Length];
BuildVocabFile(folder, dictionary, vocabPositions);
BuildPostingsFile(folder, index, dictionary, vocabPositions);
}
private static void IndexFiles(string folder, NaiveInvertedIndex index)
{
int documentID = 0;
Console.WriteLine("Indexing " + Path.Combine(Environment.CurrentDirectory, folder));
foreach (string fileName in Directory.EnumerateFiles(
Path.Combine(Environment.CurrentDirectory, folder))) {
if (fileName.EndsWith(".txt")) {
IndexFile(fileName, index, documentID);
documentID++;
}
}
}
private static void IndexFile(string fileName, NaiveInvertedIndex index,
int documentID)
{
try {
SimpleTokenStream stream = new SimpleTokenStream(fileName);
while (stream.HasNextToken) {
string term = stream.NextToken();
var stemmed = PorterStemmer.ProcessToken(term);
if (!string.IsNullOrEmpty(stemmed))
index.AddTerm(stemmed, documentID);
}
}
catch (Exception ex) {
Console.WriteLine(ex);
}
}