Best compression algorithm for binary data. Apr 9, 2024 · It can be done in two ways- lossless compression and lossy compression. Yes, gz is the default compression tool on Linux. Sep 20, 2023 · Data Types Data-type in simple terms gives us information about the type of data. Oct 25, 2008 · There's always lzip. All integers are positive. Data-types are classified as: Primitive or Built-in data types Some of the examples of primitive data types are as follows Variable named ch refers to the memory address 100 Feb 1, 2021 · Near-Lossless compression techniques is an another type of compression technique where the difference between the original and reconstructed data is guaranteed to vary from the respectively values in the original data by no more than a user-specified amount called as maximum absolute distortion (MAD) (Ansari et al. LZ4 is lossless compression algorithm, providing compression speed > 500 MB/s per core, scalable with multi-cores CPU. Binary Search Algorithm. For comparison, WinRar "Best" method with default options results in 0. Additionally, some algorithms involve trade-offs between speed and size – algorithms that compress faster tend to produce larger files. Specifically, lossless compression reduces the data size by replacing long symbols with a shorter Jul 6, 2010 · Is there another algorithm that would be able to compress this kind of data better? I'm using C++. Huffman in 1952 a A classic algorithm for binary data clustering is Bernoulli Mixture model. It features an extremely fast decoder, with speed in multiple GB/s per core, typically reaching RAM speed limits on multi-core systems. Quoting the README: This is a compression program optimised for large files. h, and either heatshrink_encoder. Moreover, at a reading speed of 10 ms ± Jan 28, 2021 · For on-the-fly compression, a faster algorithm is preferable even if it sub-optimally compresses the data, whereas an archival application may prefer higher compression power at the expense of Oct 19, 2015 · It first compresses 900 MB large data blocks using a dictionary method, and then it hands the cleaned-up data over to bzip2. Therefore, to overcome these challenges, compression has become necessary In this video we take a look at three different compression algorithms in Python. Data compression is a fundamental technique in computer science that For best compression ratio with LZMA2 use 1 or 2 CPU threads. Lossy compression reduces the size of data by removing unnecessary information, while there is no data loss in lossless compression. This paper examines the performance of a set Aug 25, 2023 · In data compression, lossy algorithms compress data while losing some details. What would be the best algorithm to compress this? I tried the deflate algorithm but that gives me only 50% compression. I'm reading the data from different satellites, and I was writing the data to the file one parameter at a time, which meant actual sequential readings where interrupted by data from other satellites. In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression. zstd 0m3. Limited Applicability: LZW compression is particularly effective for text-based data, but may not be as effective for other types of data, such as images or video, which have Mar 18, 2024 · However, there were some issues with the compression algorithms. Compressed Data - For example when transferring data between socket connections you'll most likely be dealing with binary data; Encryption/Compression Algorithms - Encryption and compression algorithms are often built using binary operations (e. Many factors affect choosing the best compression method for every data type. Dec 6, 2019 · Thus, the final compressed size of the data has very little to do with the serialization method, and almost everything to do with the compression method. Every data type has many suitable compression methods and algorithms. 📚 Programming Books & Merch 📚🐍 The Python Bible Book: ht Jan 5, 2024 · When selecting a data compression algorithm, you can consider multiple factors. 5 times faster. Mar 18, 2024 · Lossless compression is a class of data compression that reduces the size of a file without losing any data, unlike lossy compression. They reduce the number of bits used to represent the message, even if that reduces the quality of reconstructed data. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes". 5 Lossless compression and expansion uses fewer bits (you hope) Basic model for data compression May 10, 2024 · Huffman coding is a popular algorithm used for the lossless data compression. bzip2 is the best compromise between being enjoying a relatively broad install base and a rather good compression ratio, but requires a separate archiver. Data Compression is the technique through which, we can reduce the quantity of data, used to represent content without excessively reducing the quality of the content. Today, we’ll benchmark 5 widely-used general-purpose lossless data compression Mar 21, 2016 · The size depends on how small you need the resulting files to be, that is how long decompression may take. Generates a "compressed" representation C(B). (while keeping it streamable within dwarfs most of the time) Recently I stumbled upon mcm compression alg Aug 23, 2018 · I am looking for text compression algorithms (natural language compression, rather than compression of arbitrary binary data). Sep 18, 2019 · I've done some test using a Pickled object, lzma gave the best compression. Nov 12, 2008 · I have a large array with a range of integers that are mostly continuous, eg 1-100, 110-160, etc. org are unblocked. While standard data compression tools (e. If somebody has a link to an overview of all popular compression algorithms I'll just accept that as answer. It is fast, and despite its age it Sep 30, 2011 · Most compression algorithms will work equally bad on such data. This work aims at improving the lossless compression of binary images. , Huffman coding) Bit flags - For example assigning security levels of a user (e. org and *. The compression ratio of the resulting compression scheme heavily relies on the first problem: the model capacity. , 1998). ・To save time when transmitting it. Methods we've tried so far are using run length encoding, then a huffman coding, then converting the binary data to base64, and run length encoding but differentiating between zero and one using numeric values for one and alphabetical equivalents for zero (seems to give the best results). 238s: 117M: zstd -19 -T0: c -I"zstd -19 -T0" -f-19 gives the best possible compression and -T0 utilizes all cores. But, if you know a priori something about the nature of the files you will be compressing, you can optimize your algorithm for that particular type of file. To apply Binary Search algorithm: The data structure must be sorted. To reduce the size of a file, unnecessary information is removed or parts that repeat the same information are stored once. ZFP did not have an implementation to compress float16 data so the compression factor was not great (3. Not satisfied with standard schemes, we wanted to optimize emCompress, SEGGER’s compression library, for: Very fast decompression High compression ratio (uncompressed size divided by compressed size) Small decompressor Limited state in RAM when decompressing With some experimentation, […] Jul 23, 2019 · LZMA2 offered the best compression for this scenario, followed by Bzip and Gzip. while zstd won in terms of “maximum compression” it was super impressive how fast bzip2 accomplished the compression 😀 “maximum compression” toplist: 12784 MBytes (zstd) 12903 MBytes (7z) 12907 MBytes (xz) MGARD uses additional lossless compression on the binary multigrid data. kastatic. If you're interested in learning by watching or listening, check out a video about this open source project on our Facebook Open Source YouTube channel. Jun 21, 2023 · Use appropriate compression: Consider factors such as compression ratio, decompression speed, and CPU overhead to choose the best compression algorithms for your workflow. Bits in C(B) / bits in B. 999. Jul 27, 2021 · Compression techniques are essential for efficient data storage and transmission. pxz process used 3. May 21, 2024 · Compression Speed: LZW compression can be slower than some other compression algorithms, particularly for large files, due to the need to constantly update the dictionary. Zlib is a widely-used software library for data compression. That brought 1,5GB of data down to 313MB. LZS is one I'm familiar with. There is very little RAM available for the decompression; it is possible to decompress the data for a single glyph into RAM but not much more. The important metrics for the decompression algorithm is the size of the data plus the size of the algorithm (as they will reside in the same limited memory). The data is usually a JSON string and when it is saved in a file, it uses up to 10 Mb of disk. Sep 5, 2021 · The problem was that I wasn't writing the data to the file sequentially. ・Text, images, sound, video, … Basic concepts ancient (1950s), best technology recently developed. 5 quintillion bytes of data—so much that 90% of the data in the world today has been created in the last two years alone. You can find sample python code all over the GitHub while the former is more powerful but also more difficult. Data-types in C language are declarations for the variables. Mar 4, 2017 · I have made extensive tests with binary NBT (archive) data and all options that 7zip (archive) offers. Compression and Huffman Coding Supplemental reading in CLRS: Section 16. INTRODUCTION Dec 28, 2017 · One of the things that is driven from the top in SEGGER is that we can always do better. , zip and rar) are being used to compress sequence data (e. Supports zlib, gzip, and raw deflate streams. Oct 22, 2009 · An algorithm something like LZSS would probably be a good choice for an embedded platform. Apr 13, 2013 · Xz is the best format for well-rounded compression, while Gzip is very good for speed. Message. Yenc uses almost the full 0x00 to 0xFF range, each byte in the binary input simply copied to the text output, escaping only 0x00, 0x0A and 0x0D (and the escape character itself, which I don't remember what that was exactly). Binary data B we want to compress. Hence, we can divide the data compression algorithms into two broad categories: lossless and lossy data compression. BINARY to use the RDC (Ross Data Compression) algorithm, which is highly effective for compressing medium to large (several hundred bytes or larger) blocks of binary data. This makes it a great option for compressing sensitive data or important files. When compressing json files, it’s important to use the right tool for the job. Keywords- algorithms; data compression; j-bit encoding; JBE; lossless. Smaller file sizes can improve data locality and reduce I/O In our pursuit of developing a lossless image compression scheme that performs better than all other schemes over all types of images, is amenable for rigorous performance analysis, and can provided guaranteed compression for a given type of images, we step back and ask the most basic question related to image compression: where does the information lie in an image? Apr 23, 2019 · ・Parkinson’s law: data expands to fill space available. When a user sends the compressed data over the internet, the file received may or may not contains the same data as the original file. Optimize file and row group size: The size of files and row groups must balance efficient data access and storage. It uses a 2 kB dictionary for compression and decompression (the dictionary is the most recent 2 kB of the uncompressed data stream). The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Compression is an important component of the solutions available for Sep 11, 2023 · Huffman coding is a popular algorithm used for the lossless data compression. Sep 4, 2023 · Huffman Coding Algorithm. General purpose compression algorithms work by finding patterns in bits. The Lempel–Ziv–Markov chain algorithm (LZMA) is an algorithm used to perform lossless data compression. The demand for large-scale image data grows increasingly fast, resulting in a need for efficient image compression. Deflate, zlib, gzip — three names intertwined. Compression ratio. There are two forms of compression: lossless and lossy. Jun 22, 2016 · Higher compression can be achieved with a=1, higher values for d, fb and mc at the expense of increased compression time. Aug 31, 2016 · While lossless data compression is the focus of this post, there exists a related but very different field of lossy data compression, used primarily for images, audio, and video. , multiple genome sequences from the same species). But at the beginning of a new data set, there is no "past" to build upon. They are simple algorithms, and don't need much memory. lrzip is what you're really looking for, especially if you're compressing source code!. Aug 23, 2021 · In this blog post, we explain Zstandard (ZSTD), a fast data compression algorithm that offers best-in-kind performance, in a way that is super simple to understand. They work with any string data, and binary strings are just If you're seeing this message, it means we're having trouble loading external resources on our website. All kidding aside: Where compatibility is a concern, PKZIP (DEFLATE algorithm) still wins. May 18, 2009 · If your data is within a smaller range, you may well be able to leverage that. Since most compression algorithms are lossy, some information or data may be lost during compression, leading to lower accuracy or quality of data. To overcome this Apr 25, 2013 · Gzip is known to be "fine", which means compression ratio is okay, and speed is good. Bzip2 is decent for its compression ratio, although xz should probably be used in its place. In this work, we introduce HLRcompress, a high-performance, parallel implementation of an algebraic data compression using hierarchical low-rank (HLR) approximations with additional binary compression based on ZFP on various hardware platforms. Here are the set of compression algorithms we'll explain, grouped by data type: Integer compression: Delta encoding; Delta-of-delta encoding; Simple-8b; Run-length encoding; Floating point compression: XOR-based Should become THE data format for compressing XML data in the future (claimed to be the last necessary binary format). Aug 27, 2017 · Requirements for the compression algorithm. Example, integer, character, etc. But your results can vary based on your data, I'd recommend testing them with some sample data of your own. The data I data is also taken as an example of how the algorithm is decompressed. 3 19. The best was: *. . You should look into the Lempel-Ziv family of compression algorithms. Oct 16, 2023 · so all algorithms struggled to compress the (mostly binary data) file and managed to squeeze it down ~50%. DEFLATE compression and decompression exposed as Read/BufRead/Write streams. However, several compression programs and models are available on the ZPAQ page. If a user wants to maximize efficiency, they should select an algorithm that offers the best compression rate for their particular Aug 30, 2023 · Algorithms capable of optimizing human-readable data before it becomes an input are thus prone to getting miscast as wholly incapable of processing binary data. If you want more compression, other alternatives exist, such as 7z. 16857:1). We use binary encoding as it is generally mentioned as a minimal representation compared to other formats. 50-75% or better compression ratio for natural language. The compression algorithms that most people are familiar with are general purpose compression algorithms, such as zip, gzip or zstd. ” — IBM report on big data (2011) May 7, 2011 · Back then i thought that this concept could be the key to the most efficient compression algorithm ever. In 2012, a team of scientists from Johns Hopkins University published a genetic compression algorithm algorithm is intended to be combining with other data compression algorithms to optimize the compression ratio. My question is about automatic compression algorithms. What file compression format/algorithm has the best compression ratios (mainly for binary files of various types)? Compression and decompression time is irrelevant as this is for cold storage, and I have 36 GB of RAM. Aug 27, 2024 · Data compression, the process of reducing the amount of data needed for the storage or transmission of a given piece of information, typically by the use of encoding techniques. It has been under development since either 1996 or 1998 by Igor Pavlov [1] and was first used in the 7z format of the 7-Zip archiver. Access to any element of the data structure should take constant time. The decompression is performed when the binary data is sent to the receiving end. Lossless algorithms reconstruct original data without any loss. Note that the algorithm cannot be lossy. It does this by extending the rzip algorithm to accommodate variable memory sizes as well as making use of multiple compression algorithms. If you're behind a web filter, please make sure that the domains *. Choosing the best compression algorithm is a balancing game between the cost to store the data and the cost to compress the data, but you can choose the right balance according to your Parallel PXZ 4. You could (should) compress the data first (using any suitable compression algorithm, not necessarily an algorithm that's hex-specific), and then (if you need hex-encoding) hex-encode the compressed data. Unfortunately, managing, analyzing and specifically storing these large amounts of data become a major scientific challenge for bioinformatics. However, the extremely high data rate required for data transfer from sensors (e. Compress. , transducers) to the ultrasound imaging systems is a major bottleneck in the software-based architecture, especially in the context of real-time imaging. If you use LZMA2 with more than 2 threads, 7-zip splits data to chunks and compresses these chunks independently (2 threads per each chunk). frequently encountered) data will produce shorter output than "improbable" data. This can be useful in various scenarios, such as reducing storage requirements or optimizing data transmission over networks. This paper examines the performance of a set of lossless data compression algorithm, on different form of text data, implemented to evaluate the performance in compressing text data. To do so, copy heatshrink_common. 5 GiB at maximum. 1 Compression As you probably know at this point in your career, compression is a tool used to facilitate storing large data sets. WHAT IS SHANNON FANO CODING? Shannon Fano Algorithm is an entropy encoding technique for lossless data compression of multimedia. Huffman while he was a Sc. In Data Structure One of my favroite algorithms & technique is huffman coding and Greedy Algorithms. Below is the step-by-step algorithm for Binary Search: Jun 3, 2024 · In the quest for efficient data storage and transfer, compression algorithms play a pivotal role. Supports miniz_oxide and multiple zlib implementations. ・Parkinson’s law: data expands to fill space available. The problem is, they are taking a lot of space, like 50Gigs, I compressed all of them already with xz with max settings, but the compression rate is not good, when I open the iso files with vim, I can see that being binary images, they are full of zeros, so I wonder if there is a compression algorithm specifically designed for such files, or if ZIPX file format (WinZip, 2008) designed to improve compression ratio over ZIP with support for more compression algorithms. h, heatshrink_config. BZip2 Aug 20, 2022 · Hi, I deal with compression of compiled binary data and am always looking to get it better. Genetics compression algorithms are the latest generation of lossless algorithms that compress data (typically sequences of nucleotides) using both conventional compression algorithms and genetic algorithms adapted to the specific datatype. The larger the file and the more memory you have, the better the compression advantage this will provide, especially once the files are larger than 100MB. However, there are a few things ("preprocessing") that you can do to increase the compressibility of the data before feeding it to a gzip or deflate like algorithm. Aug 29, 2024 · Conditions to apply Binary Search Algorithm in a Data Structure. 5 Lossless compression and expansion uses fewer bits (you hope) Basic model for data compression . Long Range ZIP (lrzip) is an efficient data compression program for Linux that aims to optimize large binary files. This results in a prefix-free binary code meaning no code is a prefix of the another. flate2. Some of the most common and popular algorithms are ZIP, JPEG, MP3, GZIP, and LZ4. There are two different sorts of goals one might hope to achieve with compression: • Maximize ease of access, manipulation and processing In my case, the reading speed was an important factor, so the difference with other compression methods made me stray away from this particular compression algorithm for my specific use case. Who needs compression? ・Moore’s law: # transistors on a chip doubles every 18–24 months. – There is a standalone command-line program, heatshrink, but the encoder and decoder can also be used as libraries, independent of each other. kasandbox. If a non-zero number is specified, zstd uses that Mar 14, 2024 · What are these magical time-series compression algorithms? First of all, they’re not magic, but clever computer science techniques. So something like this: Sep 19, 2019 · developing a scalable compression algorithm that exploits this model’s theoretical compression potential. , GenBank flat file database), this approach has been criticized to be extravagant because genomic sequences often contain repetitive content (e. This algorithm basically uses the words as symbols, creates a dictionary from them, and replaces them with integers. c or heatshrink_decoder. 17 compression and is 1. lrzip. It works by assigning variable-length codes to input characters with the shorter codes assigned to more frequent characters. May 8, 2017 · You might be able to build a compression algorithm that compresses one type of file well, at the cost of compressing others worse. Software-based ultrasound imaging systems provide high flexibility that allows easy and fast adoption of newly developed algorithms. Aug 22, 2020 · Algorithms capable of optimizing human-readable data before it becomes an input are thus prone to getting miscast as wholly incapable of processing binary data. Best Practices for Using Json Compression. Reconstructs original bitstream B. g. If not, and you know more about the data than can be "intuited" by the compression algorithms, you should leverage that information. In truth, you should simply try running any of the common algorithms and see if the data is "compressed enough". 034s: 167M: zstd: c --zstd -f: zstd uses 1 core by default. The algorithm was developed by the David A. It provides a set of functions and algorithms that allow developers to compress and decompress data efficiently. D. Oct 7, 2016 · If the data has a predictable pattern then it's compressible. The algorithm finds a set of basis vectors and their Mar 24, 2020 · With the emergent evolution in DNA sequencing technology, a massive amount of genomic data is produced every day, mainly DNA sequences, craving for more storage and bandwidth. Apr 9, 2009 · This problem is common to all compression algorithms, and reason is, compression algorithms learn from past data how to compress future data. The next graph illustrates the compression speed per compression Most lossless compression programs do two things in sequence: the first step generates a statistical model for the input data, and the second step uses this model to map input data to bit sequences in such a way that "probable" (i. Recent advances in deep learning allow us to optimize probabilistic models of complex high-dimensional data efficiently. Introduction to Zlib. Deflate is the algorithm used by the zlib and gzip implementations. Oct 29, 2023 · Higher compression ratio settings can be memory-hungry. If you had a collection of numbers that always consisted of the same amount of numbers (say a collection of 10 numbers) and you could figure out a way to calculate a formula from that collection of numbers so that you could reconstruct it. The central idea of lossless compression is to exploit the statistical redundancy of the content in a file. The model can be fit using Bayesian methods and can be fit also using EM (Expectation Maximization). These are the types of compression that you can specify: CHAR to use the RLE (Run Length Encoding) compression algorithm, which works best for character data. 11 compression ratio and is approximately 6x slower, "Fastest" method gives 0. Mar 9, 2022 · We present a new lossy compression algorithm for statistical floating-point data through a representation learning with binary variables. At minimum and default compression level Deflate algorithm is used, at maximum compression level WinZip tries to determine the most fit algorithm from supported ones, including BZip2, LZMA and PPMd. Try the following: First, if possible, sort the tuples in ascending order. c (and their respective header) into your project. 9beta using its best possible compression. The truth remains, however: apart from pre-processing optimization, both binary and human-readable data can be treated as strings-of-bytes inputs and easily processed. Use the abstract ID first, then the timestamp. 11. Edit: Please no more suggestions to change the data itself. They are therefore agnostic to data types, and can be used on any stream of bits. Jun 20, 2021 · A high compression ratio for any algorithm does not imply it is the best algorithm for all data types. Nov 3, 2014 · Data is added to an AVRO object and object is binary encoded to write to Kafka. PPMd Dmitry Shkarin's PPMdH algorithm with small changes. I have seen for example An Efficient Compression Code for Text Databases. Huffman in 1952 a Apr 7, 2022 · Each line of "text" was a huge number that was converted from and to binary in the decoding and encoding process. Say, files with one hour of sensor data are small enough; then you just save one (compressed) file per hour. The performance of this algorithm is measured by comparing combination of different data compression algorithms. For example, we can use level 1 if speed is most important and level 22 if size is most important. Usually it provides high compression ratio and high speed for text files. e. Ex. Aug 31, 2016 · Zlib offers nine compression levels; Zstandard currently offers 22, which enables flexible, granular trade-offs between compression speed and ratios for future data. Because of this, they use a higher number of bits compared to lossy algorithms. There is a ZPAQ program that takes a configuration file to describe the compression algorithm, as well as other programs like ZPIPE that use a fixed compression algorithm. -- In the quest for efficient data storage and transfer, compression algorithms play a pivotal role. Jun 25, 2010 · So, any pointers on which algorithm is most suitable for compressing serialized Java objects (as well as arbitrary binary data) would be much appreciated. Being optimized for XML, it compresses XML more ways more efficient than any conventional compression algorithm. Compression predates digital technology, having been used in Morse Code, which assigned the shortest codes to the most Good compression has to necessarily exploit the empirical property of time series data in that close-in-time measurements are very similar if not exactly the same. Oct 29, 2011 · The specification does not describe the compression algorithm. Mar 18, 2024 · It’s a powerful data transformation method that is used in a lossless data compression algorithm. Data compression Compression reduces the size of a file: ・To save space when storing it. It is used to Aiming at these problems, this paper proposed a binary synchronous compression algorithm (BSCA), which includes three key parts: firstly, a feature selection method and a sample selection method based on variance analysis and random sampling comparison, respectively, are presented; Then, the proposed two methods handle the original dataset Oct 1, 2019 · those dynamically changing dictionary based algorithms work hard on producing optimal code for the continually evolving dictionary/table from previous input data in real time, sort of dynamic huffman code generation, but will not produce optimal code with drastically changing data pattern, unless you give it pretty big memory to store If you're seeing this message, it means we're having trouble loading external resources on our website. To understand how to best exploit this property, we rst study how the IEEE 754 double-precision binary representation of two values varies in com-parison to their decimal representation. With EXI, you can operate on compressed XML data on the fly (without the need to uncompress or re-compress it). Today, we’ll benchmark 5 widely-used general-purpose lossless data compression programs: gzip Sep 4, 2023 · Data compression is a technique used to reduce the size of a file. And it would be amazing if someone knows of an active project that relates to this topic (Apache didn't seem to have anything). May 28, 2020 · Take a look at these compression algorithms that reduce the file size of your data to make them more convenient and efficient. Jun 3, 2024 · Jun 3, 2024. zstd 1m18. The very high speed hardware description language (VHDL) modeling environment of Lempel-Ziv-Welch (LZW) algorithm for binary data compression is presented to ease the description, verification, simulation and hardware realization of the algorithm. We highlight the versatility Dec 27, 2008 · I have found that the compression algorithm tends to be more effective than choosing an alternative format. Named after Oct 28, 2022 · General Purpose Compression Algorithms. ・Most files have lots of redundancy. One of the key features of BWT is its ability to group together similar characters in a string, which is a key factor in achieving efficient compression. 50–75% or better compression ratio for natural language. To this end, we propose the use of a tree-based optimization algorithm, which searches for the best partitions of the input image into non-uniform blocks, and for the best combination of scan directions, with The script outputs a message indicating that the Json data has been compressed and saved. Expand. It is much faster than the other strong compression tools (bzip2, lzma), and some files it compresses even better than bzip2 or lzma. Understanding the differences between these strategies is critical for selecting the best solution depending on the unique requirements of various applications. , User=0001 Oct 28, 2021 · Decompression is the inverse compression process that, through a particular algorithm, restores compressed data to the state before compression. All numbers are unique and progressively increasing. “ Everyday, we create 2. If this is a 'real-time' compression, I would recommend investigating a lower-level Brotli or Zstandard compressor (the high level ones take a lot CPU - but do give very good compression). , microsatellite sequences) or many sequences exhibit high levels of similarity (e. In a distributed environment, large data files remain a major bottleneck. 7z, highest compression, algorythm LZMA2, biggest dictionary size and word size (for big files). It was then time to look at the compression speed. To solve this situation, Zstd offers a training mode, which can be used to tune the algorithm for a selected type of data. I. zqwxntcn mlry cwbli lraag czilmjw gfvta zjnpmajm vgyzxe shz hbbovf