Tag Archives: LZP

Updated Compression Benchmarks – part 2

I have added the second set of benchmarks that demonstrate the effect of the different pre-processing options on compression ratio and speed. The results are available here: http://moinakg.github.io/pcompress/results2.html

All of these results have Global Dedupe enabled. These results also compare the effect of various compression algorithms on two completely different datasets. One is a set of VMDK files and another purely textual data. Some observations below:

  • In virtually all the cases using ‘-L’ and ‘-P’ switches results in the smallest file. Only in case of LZMA these options marginally deteriorate the compression ratio indicating that the reduction of redundancy is hurting LZMA. To identify which of the two hurts more I repeated the command (see the terminology in results page) with lzmaMt algo and only option ‘-L’ at compression level 6 on the CentOS vmdk tarball. The resultant size came to: 472314917. The size got from running with only option ‘-P’ is available in the results page: 469153825. Thus it is the LZP preprocessing that unsettles LZMA the most along with segment size of 64MB. Delta2 actually helps. Running the command with segment size of 256MB we see the following results – ‘-L’ and ‘-P’: 467946789, ‘-P’ only: 466076733, ‘-L’ only: . Once again Delta2 helps. At higher compression however, Delta2 is marginally worse as well.
  • There is some interesting behavior with respect to the PPMD algorithm. The time graph (red line) shows a relative spike for the CentOS graphs as compared to the Linux source tarball graphs. PPMD is an algorithm primarily suited for textual data so using it on non-textual data provides good compression but takes more time.
  • Both Libbsc and PPMD are especially good on the textual Linux source tar and are comparable to LZMA results while only taking a fraction of the time taken by LZMA. Especially Libbsc really rocks by producing better compression and being much faster as compared to LZMA. However i have seen decompression time with Libbsc to be quite high as compared to PPMD.

Pcompress 1.2 Released

Pcompress 1.2 is now available and can be grabbed from here: https://code.google.com/p/pcompress/downloads/list. This is a major release containing a large number of bug fixes and improvements. There are performance and stability improvements, code cleanup, resolution of corner cases etc. The biggest new additions to this release are the new Delta2 Encoding and support Keccak message digest. Keccak has been announced the NIST SHA3 standard secure hash. The SIMD (SSE) optimized variant of Keccak runs faster than SHA256 on x86 platforms. However it is still slower than SKEIN so SKEIN remains the default hash algorithm for data integrity verification. In addition Deduplication is now significantly faster.

Delta2 Encoding as I had mentioned in a previous post probes for embedded tables of numeric sequences in the data and encodes them by collapsing the arithmetic sequence into it’s parameters: starting value, increment/decrement, number of terms. This generally provides benefits across different kinds of data and can be combined with LZP preprocessing to enable the final compression algorithm to achieve the maximum compression ratio beyond what it can normally achieve. This encoding works very fast and still manages to detect a good amount of numeric sequences if they are present in the data.

I have extended the statistics mode to display additional data including throughput figures. Here is an output from a compression run of the silesia corpus test data set:

## CPU: Core i5 430M
## RAM: 8GB
## Compiler: Gcc 4.7.2
## Compression
./pcompress -D -c lz4 -l1 -L -P -s200m silesia.tar 
Scaling to 1 thread
Checksum computed at 241.321 MB/s
Original size: 206612480, blknum: 46913
Number of maxlen blocks: 0
Total Hashtable bucket collisions: 17225
Merge count: 46750
Deduped size: 206197375, blknum: 242, delta_calls: 0, delta_fails: 0
Chunking speed 112.189 MB/s, Overall Dedupe speed 100.880 MB/s
LZP: Insize: 206196371, Outsize: 192127556
LZP: Processed at 55.839 MB/s
DELTA2: srclen: 192127556, dstlen: 191899643
DELTA2: header overhead: 50800
DELTA2: Processed at 382.530 MB/s
Chunk compression speed 207.908 MB/s
## Decompression
./pcompress -d silesia.tar.pz silesia.tar.1 
Scaling to 4 threads
Chunk decompression speed 383.488 MB/s
DELTA2: Decoded at 3030.724 MB/s
Checksum computed at 244.235 MB/sls -l silesia.tar.pz 
-rw-rw-r--. 1 testuser testuser 99115899 Jan  5 21:36 silesia.tar.pz

Note that these are single-threaded performance figures. The entire file is being compressed in a single chunk. The default checksum is SKEIN. Look at the decoding speed of the Delta2 implementation. It is close to 3GB/s rate. Next lets check the performance of SSE optimized Keccak:

./pcompress -D -c lz4 -l1 -P -S KECCAK256 -s200m silesia.tar 
Scaling to 1 thread
Checksum computed at 143.904 MB/s
Original size: 206612480, blknum: 46913
Number of maxlen blocks: 0
Total Hashtable bucket collisions: 17225
Merge count: 46750
Deduped size: 206197375, blknum: 242, delta_calls: 0, delta_fails: 0
Chunking speed 111.601 MB/s, Overall Dedupe speed 100.352 MB/s
DELTA2: srclen: 206196371, dstlen: 201217172
DELTA2: header overhead: 570448
DELTA2: Processed at 360.383 MB/s
Chunk compression speed 213.226 MB/sls -l silesia.tar.pz 
-rw-rw-r--. 1 testuser testuser 100204566 Jan  5 21:34 silesia.tar.pz

This time I left out LZP to show the reduction using Delta2 alone. As you can see combining LZP and Delta2 gives the greatest reduction. Also see how much slower Keccak is compared to SKEIN. Note that I am using optimized 64-bit assembly implementation of Skein but it does not use SSE whereas Keccak uses SSE.

Next lets have a look at a dataset that has lots of embedded numeric data. I used a Global Topographic Elevation map data from USGS:

# Compression
./pcompress -c lz4 -l1 -P -s100m e020n40.tar 
Scaling to 1 thread
Checksum computed at 237.584 MB/s
DELTA2: srclen: 86599680, dstlen: 43707440
DELTA2: header overhead: 2024320
DELTA2: Processed at 279.484 MB/s
Chunk compression speed 211.112 MB/s

ls -l e020n40.tar.pz 
-rw-rw-r--. 1 testuser testuser 35360062 Jan  5 21:46 e020n40.tar.pz
# Decompression
./pcompress -d e020n40.tar.pz e020n40.tar.1 
Scaling to 4 threads
Chunk decompression speed 622.394 MB/s
DELTA2: Decoded at 1971.282 MB/s
Checksum computed at 246.015 MB/s

This time I left out dedupe and LZP. The Delta2 benefits are a lot more since there is a lot of numeric data. Also because there is a lot more Delta spans in the encoded dataset the decoding speed is also lesser. However it still decodes at 1.9 GB/s.

As can be seen Delta2 performance is on par with LZ4 can be used to improve LZ4 results with very little overhead.