It provides high compression ratio and very fast decompression. Even old versions of 7-Zip can decompress archives created with LZMA method. LZMA It's base compression method for 7z format. Here is a rough copy/paste of the compression method section: Method Description.
These smaller files take up less space on hard drives and are transmitted faster to other systems. Software helps with data processing through compression, which encodes information, like text, pictures, and other forms of digital data, using fewer bits than the original. When it comes to innovating on storing and transmitting that data, at Facebook we're making advancements not only in hardware — such as larger hard drives and faster networking equipment — but in software as well.
Also, have a look at MSSQL Compressed Backup on codeplex. 3, is used to.You can still use opensource compression tools like gzip, 7Zip, bzip2 or QuickLZ after the backup compression to benefit. In this example, a light compression level, e.g. The more time spent compressing to a smaller file, the slower the data is to process.LZMA compression method has a very good compression rate but at the cost of being very slow.
Over the years, other algorithms have offered either better compression or faster compression, but rarely both. For two decades, it has provided an impressive balance between speed and space, and, as a result, it is used in almost every modern electronic device (and, not coincidentally, used to transmit every byte of the very blog post you are reading). Comparison of compression methods for database dumpsToday, the reigning data compression standard is Deflate, the core algorithm inside Zip, gzip, and zlib. File Compression in the Multi-Core Era.
As a result, it improves upon the trade-offs made by other compression algorithms and has a wide range of applicability with very high decompression speed. Zstandard combines recent compression breakthroughs, like Finite State Entropy, with a performance-first design — and then optimizes the implementation for the unique properties of modern CPUs. 128 MB, 1.38 GB.We're thrilled to announce Zstandard 1.0, a new compression algorithm and implementation designed to scale with modern hardware and compress smaller and faster. Ultra64 (best), 64 MB, 708 MB.
Compression speed: How quickly we can make the data smaller, measured in MB/s of input data consumed. Compression ratio: The original size (numerator) compared with the compressed size (denominator), measured in unitless data as a size ratio of 1.0 or greater. Comparing compressionThere are three standard metrics for comparing compression algorithms and implementations:
Each of these algorithms offers different trade-offs: lz4 aims for speed, xz aims for higher compression ratios, and zlib aims for a good balance of speed and size. To represent the algorithms that Zstandard is expected to work on, in this post we'll use the Silesia corpus, a data set of files that represent the typical data types used every day.Some algorithms and implementations commonly used today are zlib, lz4, and xz. However, Zstandard, like zlib, is meant for general-purpose compression for a variety of data types.
These were the commands (which use the default compression levels for both tools):Zstd -c -3 silesia.tar > silesia.tar.zst # 67,432,740 bytesGzip -c -6 silesia.tar > silesia.tar.gz # 68,235,522 bytesIf an algorithm is scalable, it has the ability to adapt to a wide variety of requirements, and Zstandard is designed to excel in today's landscape and to scale into the future. This chart shows the comparison of the gzip and zstd command line tools on Centos 7 built with the system's default compiler.The tests were each conducted 10 times, with the minimum times taken, and were conducted on ramdisk to avoid filesystem overhead. In these cases, performance is often affected by overhead, such as checksumming. However, Zstandard, at the default setting, shows substantial improvements in both compression speed and decompression speed, while compressing at the same ratio as zlib.While pure algorithm performance is important when compression is embedded within a larger application, it is extremely common to also use command line tools for compression — say, for compressing log files, tarballs, or other similar data meant for storage or transfer. The fastest algorithm, lz4, results in lower compression ratios xz, which has the highest compression ratio, suffers from a slow compression speed.
For the Silesia corpus, decompression speed — regardless of ratio — was approximately 550 MB/s for Zstandard and 270 MB/s for zlib. Likewise, you can pick a ratio and see how fast the algorithms are when they achieve that level.For any vertical line (i.e., compression speed), Zstandard achieves a higher compression ratio. To compare the algorithms, you can pick a speed to see the various ratios the algorithms achieve at that speed. The x-axis is a decreasing logarithmic scale in megabytes per second the y-axis is the compression ratio achieved. For example, we can use level 1 if speed is most important and level 22 if size is most important.Below is a chart of the compression speed and ratio achieved for all levels of Zstandard and zlib. Zlib offers nine compression levels Zstandard currently offers 22, which enables flexible, granular trade-offs between compression speed and ratios for future data.
For compatibility with a broad range of receiving systems, where memory may be limited, it is recommended to limit memory usage to 8 MB. For example, the lower of the 22 levels use 1 MB or less. But, today's computing environment can access much more memory — even in mobile and embedded environments.Zstandard has no inherent limit and can address terabytes of memory (although it rarely does). It scales to much higher compression ratios, while sustaining lightning-fast decompression speeds.Zstandard improves upon zlib by combining several recent innovations and targeting modern hardware: MemoryBy design, zlib is limited to a 32 KB window, which was a sensible choice in the early '90s.
A new generation Huffman decoder, Huff0, is able to decode multiple symbols in parallel with a single core. Therefore, in this example:C must wait for a to be calculated first, and only then will c calculation start.It means that, to take advantage of the modern CPU, one has to design a flow of operations with few or no data dependencies.This is achieved with Zstandard by separating data into multiple parallel streams. A format designed for parallel executionToday's CPUs are very powerful and can issue several instructions per cycle, thanks to multiple ALUs (arithmetic logic units) and increasingly advanced out-of-order execution design.Then both a and c will be calculated in parallel.This is possible only if there is no relation between them.
The more ALUs that are being used, the more work the CPU is doing, and hence the faster compression is occurring. At each clock cycle, the CPU is able to issue the result of multiple operations, depending on available ALUs. Branchless designNew CPUs are more powerful and reach very high frequencies, but this is only possible thanks to a multi-stage approach, where an instruction is split into a pipeline of multiple steps.
Best Compression Method Full And Instructions
When the bet is right, the pipeline remains full and instructions are issued continuously. They do so intelligently, thanks to a branch predictor, which tells them in essence the most probable result of evaluating condition. A cautious CPU would wait for the result of condition before working on either branch, which would be extremely wasteful.Today's CPUs gamble. Consider the following simple situation: if (condition) doSomething() else doSomethingElse()When it encounters this, the CPU does not know what to do, since it depends on the value of condition.
Today, it is so important that it's essential to design formats compatible with branchless algorithms. This is called a pipeline flush, and is extremely costly in modern CPUs.Twenty-five years ago, pipeline flush was a non-issue.
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