Overview of index file format

It is not necessary to understand the current implementation details of the index file format in order to use Apache Lucy effectively, but it may be helpful if you are interested in tweaking for high performance, exotic usage, or debugging and development.

On a file system, an index is a directory. The files inside have a hierarchical relationship: an index is made up of “segments”, each of which is an independent inverted index with its own subdirectory; each segment is made up of several component parts.

[index]--|
         |--snapshot_XXX.json
         |--schema_XXX.json
         |--write.lock
         |
         |--seg_1--|
         |         |--segmeta.json
         |         |--cfmeta.json
         |         |--cf.dat-------|
         |                         |--[lexicon]
         |                         |--[postings]
         |                         |--[documents]
         |                         |--[highlight]
         |                         |--[deletions]
         |
         |--seg_2--|
         |         |--segmeta.json
         |         |--cfmeta.json
         |         |--cf.dat-------|
         |                         |--[lexicon]
         |                         |--[postings]
         |                         |--[documents]
         |                         |--[highlight]
         |                         |--[deletions]
         |
         |--[...]--| 

Write-once philosophy

All segment directory names consist of the string “seg_” followed by a number in base 36: seg_1, seg_5m, seg_p9s2 and so on, with higher numbers indicating more recent segments. Once a segment is finished and committed, its name is never re-used and its files are never modified.

Old segments become obsolete and can be removed when their data has been consolidated into new segments during the process of segment merging and optimization. A fully-optimized index has only one segment.

Top-level entries

There are a handful of “top-level” files and directories which belong to the entire index rather than to a particular segment.

snapshot_XXX.json

A “snapshot” file, e.g. snapshot_m7p.json, is list of index files and directories. Because index files, once written, are never modified, the list of entries in a snapshot defines a point-in-time view of the data in an index.

Like segment directories, snapshot files also utilize the unique-base-36-number naming convention; the higher the number, the more recent the file. The appearance of a new snapshot file within the index directory constitutes an index update. While a new segment is being written new files may be added to the index directory, but until a new snapshot file gets written, a Searcher opening the index for reading won’t know about them.

schema_XXX.json

The schema file is a Schema object describing the index’s format, serialized as JSON. It, too, is versioned, and a given snapshot file will reference one and only one schema file.

locks

By default, only one indexing process may safely modify the index at any given time. Processes reserve an index by laying claim to the write.lock file within the locks/ directory. A smattering of other lock files may be used from time to time, as well.

A segment’s component parts

By default, each segment has up to five logical components: lexicon, postings, document storage, highlight data, and deletions. Binary data from these components gets stored in virtual files within the “cf.dat” compound file; metadata is stored in a shared “segmeta.json” file.

segmeta.json

The segmeta.json file is a central repository for segment metadata. In addition to information such as document counts and field numbers, it also warehouses arbitrary metadata on behalf of individual index components.

Lexicon

Each indexed field gets its own lexicon in each segment. The exact files involved depend on the field’s type, but generally speaking there will be two parts. First, there’s a primary lexicon-XXX.dat file which houses a complete term list associating terms with corpus frequency statistics, postings file locations, etc. Second, one or more “lexicon index” files may be present which contain periodic samples from the primary lexicon file to facilitate fast lookups.

Postings

“Posting” is a technical term from the field of information retrieval, defined as a single instance of a one term indexing one document. If you are looking at the index in the back of a book, and you see that “freedom” is referenced on pages 8, 86, and 240, that would be three postings, which taken together form a “posting list”. The same terminology applies to an index in electronic form.

Each segment has one postings file per indexed field. When a search is performed for a single term, first that term is looked up in the lexicon. If the term exists in the segment, the record in the lexicon will contain information about which postings file to look at and where to look.

The first thing any posting record tells you is a document id. By iterating over all the postings associated with a term, you can find all the documents that match that term, a process which is analogous to looking up page numbers in a book’s index. However, each posting record typically contains other information in addition to document id, e.g. the positions at which the term occurs within the field.

Documents

The document storage section is a simple database, organized into two files:

• documents.dat - Serialized documents.

• documents.ix - Document storage index, a solid array of 64-bit integers where each integer location corresponds to a document id, and the value at that location points at a file position in the documents.dat file.

Highlight data

The files which store data used for excerpting and highlighting are organized similarly to the files used to store documents.

• highlight.dat - Chunks of serialized highlight data, one per doc id.

• highlight.ix - Highlight data index – as with the documents.ix file, a solid array of 64-bit file pointers.

Deletions

When a document is “deleted” from a segment, it is not actually purged right away; it is merely marked as “deleted” via a deletions file. Deletions files contains bit vectors with one bit for each document in the segment; if bit #254 is set then document 254 is deleted, and if that document turns up in a search it will be masked out.

It is only when a segment’s contents are rewritten to a new segment during the segment-merging process that deleted documents truly go away.

Compound Files

If you peer inside an index directory, you won’t actually find any files named “documents.dat”, “highlight.ix”, etc. unless there is an indexing process underway. What you will find instead is one “cf.dat” and one “cfmeta.json” file per segment.

To minimize the need for file descriptors at search-time, all per-segment binary data files are concatenated together in “cf.dat” at the close of each indexing session. Information about where each file begins and ends is stored in cfmeta.json. When the segment is opened for reading, a single file descriptor per “cf.dat” file can be shared among several readers.

A Typical Search

Here’s a simplified narrative, dramatizing how a search for “freedom” against a given segment plays out:

1. The searcher asks the relevant Lexicon Index, “Do you know anything about ‘freedom’?” Lexicon Index replies, “Can’t say for sure, but if the main Lexicon file does, ‘freedom’ is probably somewhere around byte 21008”.

2. The main Lexicon tells the searcher “One moment, let me scan our records… Yes, we have 2 documents which contain ‘freedom’. You’ll find them in seg_6/postings-4.dat starting at byte 66991.”

3. The Postings file says “Yep, we have ‘freedom’, all right! Document id 40 has 1 ‘freedom’, and document 44 has 8. If you need to know more, like if any ‘freedom’ is part of the phrase ‘freedom of speech’, ask me about positions!

4. If the searcher is only looking for ‘freedom’ in isolation, that’s where it stops. It now knows enough to assign the documents scores against “freedom”, with the 8-freedom document likely ranking higher than the single-freedom document.