Inverting

Once the parsing phase is complete, use the invert command to turn a forward index into an inverted index. For example, assuming the existence of a forward index in the path path/to/forward/cw09b:

$ mkdir -p path/to/inverted
$ ./invert -i path/to/forward/cw09b \
    -o path/to/inverted/cw09b

Inverting an index requires the knowledge of the number of terms in the lexicon ahead of time. In the above example, the invert command assumes that a cw09b.termlex' file exists from the output of parse_collection` which is used to lookup the term count.

Note that the number of terms can be provided using --term-count in case the lexicon is not available or on a different path.

Inverted index format

A binary sequence is a sequence of integers prefixed by its length, where both the sequence integers and the length are written as 32-bit little-endian unsigned integers. An inverted index consists of 3 files, <basename>.docs, <basename>.freqs, <basename>.sizes:

• <basename>.docs starts with a singleton binary sequence where its only integer is the number of documents in the collection. It is then followed by one binary sequence for each posting list, in order of term-ids. Each posting list contains the sequence of document-ids containing the term.

• <basename>.freqs is composed of a one binary sequence per posting list, where each sequence contains the occurrence counts of the postings, aligned with the previous file (note however that this file does not have an additional singleton list at its beginning).

• <basename>.sizes is composed of a single binary sequence whose length is the same as the number of documents in the collection, and the i-th element of the sequence is the size (number of terms) of the i-th document.

Reading the inverted index using Python

Here is an example of a Python script reading the uncompressed inverted index format:

import os
import numpy as np

class InvertedIndex:
    def __init__(self, index_name):
        index_dir = os.path.join(index_name)
        self.docs = np.memmap(index_name + ".docs", dtype=np.uint32,
              mode='r')
        self.freqs = np.memmap(index_name + ".freqs", dtype=np.uint32,
              mode='r')

    def __iter__(self):
        i = 2
        while i < len(self.docs):
            size = self.docs[i]
            yield (self.docs[i+1:size+i+1], self.freqs[i-1:size+i-1])
            i += size+1

    def __next__(self):
        return self

for i, (docs, freqs) in enumerate(InvertedIndex("cw09b")):
    print(i, docs, freqs)