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From "Adrien Grand (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (LUCENE-4599) Compressed term vectors
Date Wed, 19 Dec 2012 17:25:12 GMT

     [ https://issues.apache.org/jira/browse/LUCENE-4599?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Adrien Grand updated LUCENE-4599:
---------------------------------

    Attachment: LUCENE-4599.patch

New patch (still not committable yet) with better compression ratio thanks to the following
optimizations:
 * the block of data compressed by LZ4 only contains term and payload bytes (without their
lengths), everything else (positions, flags, term lengths, etc.) is stored using packed ints,
 * term freqs are encoded in a pfor-like way to save space (this was a 3x/4x decrease of the
space needed to store freqs),
 * when all fields have the same flags (a 3-bits int that says whether positions/offsets/payloads
are enabled), the flag is stored only once per distinct field,
 * when both positions and offsets are enabled, I compute average term lengths and only store
the difference between the start offset and the expected start offset computed from the average
term length and the position,
 * for lengths, this impl stores the difference between the indexed term length and the actual
length (endOffset - startOffset), with an optimization when they are always equal to 0 (can
happen with ASCII and an analyzer that does not perform stemming).

Depending on the size of docs, not the same data takes most space in a single chunk:
|| || Small docs (28 * 1K) || Large doc (1 * 750K) ||
| Total chunk size (positions and offsets enabled) | 21K | 450K |
| Term bytes | 11K (16K before compression) | 64K (84K before compression) |
| Term lengths | 2K | 8K |
| Positions | 3K | 215K |
| Offsets | 3K (4K if positions are disabled) | 150K (240K if positions are disabled) |
| Term freqs | 500 | 7K |
the rest is negligible

 * So with small docs, most of space is occupied by term bytes whereas with large docs positions
and offsets can easily take 80% of the chunk size.
 * Compression might not be as good as with stored fields, especially when docs are large
because terms have already been deduplicated.

Overall, the on-disk format is more compact than the Lucene40 term vectors format (positions
and offsets enabled, the number of documents indexed is not the same for small and large docs):
|| || Small docs || Large docs ||
| Lucene40 tvx | 160033 | 1633 |
| Lucene40 tvd | 49971 | 232 |
| Lucene40 tvf | 11279483 | 56640734 |
| Compressing tvx | 1116 | 78 |
| Compressing tvd | 7589550 | 44633841 |

This impl is 34% smaller than the Lucene40 one on small docs (mainly thanks to compression)
and 21% on large docs (mainly thanks to packed ints). If you have other ideas to improve this
ratio, let me know!

I still have to write more tests, clean up the patch, make reading term vectors more memory-efficient,
and implement efficient merging...
                
> Compressed term vectors
> -----------------------
>
>                 Key: LUCENE-4599
>                 URL: https://issues.apache.org/jira/browse/LUCENE-4599
>             Project: Lucene - Core
>          Issue Type: Task
>          Components: core/codecs, core/termvectors
>            Reporter: Adrien Grand
>            Assignee: Adrien Grand
>            Priority: Minor
>             Fix For: 4.1
>
>         Attachments: LUCENE-4599.patch, LUCENE-4599.patch
>
>
> We should have codec-compressed term vectors similarly to what we have with stored fields.

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