bumped version number to v1.3.4

also added a paragraph on using compression level with training mode
as this is a recurrent question (see for example #1004)
This commit is contained in:
Yann Collet
2018-01-27 22:23:26 -08:00
parent 0fa96a6b78
commit 9f8ed23b5b
5 changed files with 30 additions and 16 deletions
+9 -5
View File
@@ -171,12 +171,12 @@ the last one takes effect.
DICTIONARY BUILDER
------------------
`zstd` offers _dictionary_ compression,
useful for very small files and messages.
It's possible to train `zstd` with some samples,
which greatly improves efficiency on small files and messages.
It's possible to train `zstd` with a set of samples,
the result of which is saved into a file called a `dictionary`.
Then during compression and decompression, reference the same dictionary.
It will improve compression ratio of small files.
Typical gains range from 10% (at 64KB) to x5 better (at <1KB).
Then during compression and decompression, reference the same dictionary,
using command `-D dictionaryFileName`.
Compression of small files similar to the sample set will be greatly improved.
* `--train FILEs`:
Use FILEs as training set to create a dictionary.
@@ -192,6 +192,10 @@ Typical gains range from 10% (at 64KB) to x5 better (at <1KB).
Dictionary saved into `file` (default name: dictionary).
* `--maxdict=#`:
Limit dictionary to specified size (default: 112640).
* `-#`:
Use `#` compression level during training (optional).
Will generate statistics more tuned for selected compression level,
resulting in a _small_ compression ratio improvement for this level.
* `-B#`:
Split input files in blocks of size # (default: no split)
* `--dictID=#`: