| /* | |
| * Copyright (c) Meta Platforms, Inc. and affiliates. | |
| * All rights reserved. | |
| * | |
| * This source code is licensed under both the BSD-style license (found in the | |
| * LICENSE file in the root directory of this source tree) and the GPLv2 (found | |
| * in the COPYING file in the root directory of this source tree). | |
| * You may select, at your option, one of the above-listed licenses. | |
| */ | |
| /*====== Dependencies ======*/ | |
| extern "C" { | |
| /* ===== ZDICTLIB_API : control library symbols visibility ===== */ | |
| /* Backwards compatibility with old macro name */ | |
| /******************************************************************************* | |
| * Zstd dictionary builder | |
| * | |
| * FAQ | |
| * === | |
| * Why should I use a dictionary? | |
| * ------------------------------ | |
| * | |
| * Zstd can use dictionaries to improve compression ratio of small data. | |
| * Traditionally small files don't compress well because there is very little | |
| * repetition in a single sample, since it is small. But, if you are compressing | |
| * many similar files, like a bunch of JSON records that share the same | |
| * structure, you can train a dictionary on ahead of time on some samples of | |
| * these files. Then, zstd can use the dictionary to find repetitions that are | |
| * present across samples. This can vastly improve compression ratio. | |
| * | |
| * When is a dictionary useful? | |
| * ---------------------------- | |
| * | |
| * Dictionaries are useful when compressing many small files that are similar. | |
| * The larger a file is, the less benefit a dictionary will have. Generally, | |
| * we don't expect dictionary compression to be effective past 100KB. And the | |
| * smaller a file is, the more we would expect the dictionary to help. | |
| * | |
| * How do I use a dictionary? | |
| * -------------------------- | |
| * | |
| * Simply pass the dictionary to the zstd compressor with | |
| * `ZSTD_CCtx_loadDictionary()`. The same dictionary must then be passed to | |
| * the decompressor, using `ZSTD_DCtx_loadDictionary()`. There are other | |
| * more advanced functions that allow selecting some options, see zstd.h for | |
| * complete documentation. | |
| * | |
| * What is a zstd dictionary? | |
| * -------------------------- | |
| * | |
| * A zstd dictionary has two pieces: Its header, and its content. The header | |
| * contains a magic number, the dictionary ID, and entropy tables. These | |
| * entropy tables allow zstd to save on header costs in the compressed file, | |
| * which really matters for small data. The content is just bytes, which are | |
| * repeated content that is common across many samples. | |
| * | |
| * What is a raw content dictionary? | |
| * --------------------------------- | |
| * | |
| * A raw content dictionary is just bytes. It doesn't have a zstd dictionary | |
| * header, a dictionary ID, or entropy tables. Any buffer is a valid raw | |
| * content dictionary. | |
| * | |
| * How do I train a dictionary? | |
| * ---------------------------- | |
| * | |
| * Gather samples from your use case. These samples should be similar to each | |
| * other. If you have several use cases, you could try to train one dictionary | |
| * per use case. | |
| * | |
| * Pass those samples to `ZDICT_trainFromBuffer()` and that will train your | |
| * dictionary. There are a few advanced versions of this function, but this | |
| * is a great starting point. If you want to further tune your dictionary | |
| * you could try `ZDICT_optimizeTrainFromBuffer_cover()`. If that is too slow | |
| * you can try `ZDICT_optimizeTrainFromBuffer_fastCover()`. | |
| * | |
| * If the dictionary training function fails, that is likely because you | |
| * either passed too few samples, or a dictionary would not be effective | |
| * for your data. Look at the messages that the dictionary trainer printed, | |
| * if it doesn't say too few samples, then a dictionary would not be effective. | |
| * | |
| * How large should my dictionary be? | |
| * ---------------------------------- | |
| * | |
| * A reasonable dictionary size, the `dictBufferCapacity`, is about 100KB. | |
| * The zstd CLI defaults to a 110KB dictionary. You likely don't need a | |
| * dictionary larger than that. But, most use cases can get away with a | |
| * smaller dictionary. The advanced dictionary builders can automatically | |
| * shrink the dictionary for you, and select the smallest size that doesn't | |
| * hurt compression ratio too much. See the `shrinkDict` parameter. | |
| * A smaller dictionary can save memory, and potentially speed up | |
| * compression. | |
| * | |
| * How many samples should I provide to the dictionary builder? | |
| * ------------------------------------------------------------ | |
| * | |
| * We generally recommend passing ~100x the size of the dictionary | |
| * in samples. A few thousand should suffice. Having too few samples | |
| * can hurt the dictionaries effectiveness. Having more samples will | |
| * only improve the dictionaries effectiveness. But having too many | |
| * samples can slow down the dictionary builder. | |
| * | |
| * How do I determine if a dictionary will be effective? | |
| * ----------------------------------------------------- | |
| * | |
| * Simply train a dictionary and try it out. You can use zstd's built in | |
| * benchmarking tool to test the dictionary effectiveness. | |
| * | |
| * # Benchmark levels 1-3 without a dictionary | |
| * zstd -b1e3 -r /path/to/my/files | |
| * # Benchmark levels 1-3 with a dictionary | |
| * zstd -b1e3 -r /path/to/my/files -D /path/to/my/dictionary | |
| * | |
| * When should I retrain a dictionary? | |
| * ----------------------------------- | |
| * | |
| * You should retrain a dictionary when its effectiveness drops. Dictionary | |
| * effectiveness drops as the data you are compressing changes. Generally, we do | |
| * expect dictionaries to "decay" over time, as your data changes, but the rate | |
| * at which they decay depends on your use case. Internally, we regularly | |
| * retrain dictionaries, and if the new dictionary performs significantly | |
| * better than the old dictionary, we will ship the new dictionary. | |
| * | |
| * I have a raw content dictionary, how do I turn it into a zstd dictionary? | |
| * ------------------------------------------------------------------------- | |
| * | |
| * If you have a raw content dictionary, e.g. by manually constructing it, or | |
| * using a third-party dictionary builder, you can turn it into a zstd | |
| * dictionary by using `ZDICT_finalizeDictionary()`. You'll also have to | |
| * provide some samples of the data. It will add the zstd header to the | |
| * raw content, which contains a dictionary ID and entropy tables, which | |
| * will improve compression ratio, and allow zstd to write the dictionary ID | |
| * into the frame, if you so choose. | |
| * | |
| * Do I have to use zstd's dictionary builder? | |
| * ------------------------------------------- | |
| * | |
| * No! You can construct dictionary content however you please, it is just | |
| * bytes. It will always be valid as a raw content dictionary. If you want | |
| * a zstd dictionary, which can improve compression ratio, use | |
| * `ZDICT_finalizeDictionary()`. | |
| * | |
| * What is the attack surface of a zstd dictionary? | |
| * ------------------------------------------------ | |
| * | |
| * Zstd is heavily fuzz tested, including loading fuzzed dictionaries, so | |
| * zstd should never crash, or access out-of-bounds memory no matter what | |
| * the dictionary is. However, if an attacker can control the dictionary | |
| * during decompression, they can cause zstd to generate arbitrary bytes, | |
| * just like if they controlled the compressed data. | |
| * | |
| ******************************************************************************/ | |
| /*! ZDICT_trainFromBuffer(): | |
| * Train a dictionary from an array of samples. | |
| * Redirect towards ZDICT_optimizeTrainFromBuffer_fastCover() single-threaded, with d=8, steps=4, | |
| * f=20, and accel=1. | |
| * Samples must be stored concatenated in a single flat buffer `samplesBuffer`, | |
| * supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order. | |
| * The resulting dictionary will be saved into `dictBuffer`. | |
| * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`) | |
| * or an error code, which can be tested with ZDICT_isError(). | |
| * Note: Dictionary training will fail if there are not enough samples to construct a | |
| * dictionary, or if most of the samples are too small (< 8 bytes being the lower limit). | |
| * If dictionary training fails, you should use zstd without a dictionary, as the dictionary | |
| * would've been ineffective anyways. If you believe your samples would benefit from a dictionary | |
| * please open an issue with details, and we can look into it. | |
| * Note: ZDICT_trainFromBuffer()'s memory usage is about 6 MB. | |
| * Tips: In general, a reasonable dictionary has a size of ~ 100 KB. | |
| * It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`. | |
| * In general, it's recommended to provide a few thousands samples, though this can vary a lot. | |
| * It's recommended that total size of all samples be about ~x100 times the target size of dictionary. | |
| */ | |
| ZDICTLIB_API size_t ZDICT_trainFromBuffer(void* dictBuffer, size_t dictBufferCapacity, | |
| const void* samplesBuffer, | |
| const size_t* samplesSizes, unsigned nbSamples); | |
| typedef struct { | |
| int compressionLevel; /**< optimize for a specific zstd compression level; 0 means default */ | |
| unsigned notificationLevel; /**< Write log to stderr; 0 = none (default); 1 = errors; 2 = progression; 3 = details; 4 = debug; */ | |
| unsigned dictID; /**< force dictID value; 0 means auto mode (32-bits random value) | |
| * NOTE: The zstd format reserves some dictionary IDs for future use. | |
| * You may use them in private settings, but be warned that they | |
| * may be used by zstd in a public dictionary registry in the future. | |
| * These dictionary IDs are: | |
| * - low range : <= 32767 | |
| * - high range : >= (2^31) | |
| */ | |
| } ZDICT_params_t; | |
| /*! ZDICT_finalizeDictionary(): | |
| * Given a custom content as a basis for dictionary, and a set of samples, | |
| * finalize dictionary by adding headers and statistics according to the zstd | |
| * dictionary format. | |
| * | |
| * Samples must be stored concatenated in a flat buffer `samplesBuffer`, | |
| * supplied with an array of sizes `samplesSizes`, providing the size of each | |
| * sample in order. The samples are used to construct the statistics, so they | |
| * should be representative of what you will compress with this dictionary. | |
| * | |
| * The compression level can be set in `parameters`. You should pass the | |
| * compression level you expect to use in production. The statistics for each | |
| * compression level differ, so tuning the dictionary for the compression level | |
| * can help quite a bit. | |
| * | |
| * You can set an explicit dictionary ID in `parameters`, or allow us to pick | |
| * a random dictionary ID for you, but we can't guarantee no collisions. | |
| * | |
| * The dstDictBuffer and the dictContent may overlap, and the content will be | |
| * appended to the end of the header. If the header + the content doesn't fit in | |
| * maxDictSize the beginning of the content is truncated to make room, since it | |
| * is presumed that the most profitable content is at the end of the dictionary, | |
| * since that is the cheapest to reference. | |
| * | |
| * `maxDictSize` must be >= max(dictContentSize, ZDICT_DICTSIZE_MIN). | |
| * | |
| * @return: size of dictionary stored into `dstDictBuffer` (<= `maxDictSize`), | |
| * or an error code, which can be tested by ZDICT_isError(). | |
| * Note: ZDICT_finalizeDictionary() will push notifications into stderr if | |
| * instructed to, using notificationLevel>0. | |
| * NOTE: This function currently may fail in several edge cases including: | |
| * * Not enough samples | |
| * * Samples are uncompressible | |
| * * Samples are all exactly the same | |
| */ | |
| ZDICTLIB_API size_t ZDICT_finalizeDictionary(void* dstDictBuffer, size_t maxDictSize, | |
| const void* dictContent, size_t dictContentSize, | |
| const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples, | |
| ZDICT_params_t parameters); | |
| /*====== Helper functions ======*/ | |
| ZDICTLIB_API unsigned ZDICT_getDictID(const void* dictBuffer, size_t dictSize); /**< extracts dictID; @return zero if error (not a valid dictionary) */ | |
| ZDICTLIB_API size_t ZDICT_getDictHeaderSize(const void* dictBuffer, size_t dictSize); /* returns dict header size; returns a ZSTD error code on failure */ | |
| ZDICTLIB_API unsigned ZDICT_isError(size_t errorCode); | |
| ZDICTLIB_API const char* ZDICT_getErrorName(size_t errorCode); | |
| } | |
| extern "C" { | |
| /* This can be overridden externally to hide static symbols. */ | |
| /* ==================================================================================== | |
| * The definitions in this section are considered experimental. | |
| * They should never be used with a dynamic library, as they may change in the future. | |
| * They are provided for advanced usages. | |
| * Use them only in association with static linking. | |
| * ==================================================================================== */ | |
| /* Deprecated: Remove in v1.6.0 */ | |
| /*! ZDICT_cover_params_t: | |
| * k and d are the only required parameters. | |
| * For others, value 0 means default. | |
| */ | |
| typedef struct { | |
| unsigned k; /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */ | |
| unsigned d; /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */ | |
| unsigned steps; /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */ | |
| unsigned nbThreads; /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */ | |
| double splitPoint; /* Percentage of samples used for training: Only used for optimization : the first nbSamples * splitPoint samples will be used to training, the last nbSamples * (1 - splitPoint) samples will be used for testing, 0 means default (1.0), 1.0 when all samples are used for both training and testing */ | |
| unsigned shrinkDict; /* Train dictionaries to shrink in size starting from the minimum size and selects the smallest dictionary that is shrinkDictMaxRegression% worse than the largest dictionary. 0 means no shrinking and 1 means shrinking */ | |
| unsigned shrinkDictMaxRegression; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */ | |
| ZDICT_params_t zParams; | |
| } ZDICT_cover_params_t; | |
| typedef struct { | |
| unsigned k; /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */ | |
| unsigned d; /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */ | |
| unsigned f; /* log of size of frequency array : constraint: 0 < f <= 31 : 1 means default(20)*/ | |
| unsigned steps; /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */ | |
| unsigned nbThreads; /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */ | |
| double splitPoint; /* Percentage of samples used for training: Only used for optimization : the first nbSamples * splitPoint samples will be used to training, the last nbSamples * (1 - splitPoint) samples will be used for testing, 0 means default (0.75), 1.0 when all samples are used for both training and testing */ | |
| unsigned accel; /* Acceleration level: constraint: 0 < accel <= 10, higher means faster and less accurate, 0 means default(1) */ | |
| unsigned shrinkDict; /* Train dictionaries to shrink in size starting from the minimum size and selects the smallest dictionary that is shrinkDictMaxRegression% worse than the largest dictionary. 0 means no shrinking and 1 means shrinking */ | |
| unsigned shrinkDictMaxRegression; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */ | |
| ZDICT_params_t zParams; | |
| } ZDICT_fastCover_params_t; | |
| /*! ZDICT_trainFromBuffer_cover(): | |
| * Train a dictionary from an array of samples using the COVER algorithm. | |
| * Samples must be stored concatenated in a single flat buffer `samplesBuffer`, | |
| * supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order. | |
| * The resulting dictionary will be saved into `dictBuffer`. | |
| * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`) | |
| * or an error code, which can be tested with ZDICT_isError(). | |
| * See ZDICT_trainFromBuffer() for details on failure modes. | |
| * Note: ZDICT_trainFromBuffer_cover() requires about 9 bytes of memory for each input byte. | |
| * Tips: In general, a reasonable dictionary has a size of ~ 100 KB. | |
| * It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`. | |
| * In general, it's recommended to provide a few thousands samples, though this can vary a lot. | |
| * It's recommended that total size of all samples be about ~x100 times the target size of dictionary. | |
| */ | |
| ZDICTLIB_STATIC_API size_t ZDICT_trainFromBuffer_cover( | |
| void *dictBuffer, size_t dictBufferCapacity, | |
| const void *samplesBuffer, const size_t *samplesSizes, unsigned nbSamples, | |
| ZDICT_cover_params_t parameters); | |
| /*! ZDICT_optimizeTrainFromBuffer_cover(): | |
| * The same requirements as above hold for all the parameters except `parameters`. | |
| * This function tries many parameter combinations and picks the best parameters. | |
| * `*parameters` is filled with the best parameters found, | |
| * dictionary constructed with those parameters is stored in `dictBuffer`. | |
| * | |
| * All of the parameters d, k, steps are optional. | |
| * If d is non-zero then we don't check multiple values of d, otherwise we check d = {6, 8}. | |
| * if steps is zero it defaults to its default value. | |
| * If k is non-zero then we don't check multiple values of k, otherwise we check steps values in [50, 2000]. | |
| * | |
| * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`) | |
| * or an error code, which can be tested with ZDICT_isError(). | |
| * On success `*parameters` contains the parameters selected. | |
| * See ZDICT_trainFromBuffer() for details on failure modes. | |
| * Note: ZDICT_optimizeTrainFromBuffer_cover() requires about 8 bytes of memory for each input byte and additionally another 5 bytes of memory for each byte of memory for each thread. | |
| */ | |
| ZDICTLIB_STATIC_API size_t ZDICT_optimizeTrainFromBuffer_cover( | |
| void* dictBuffer, size_t dictBufferCapacity, | |
| const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples, | |
| ZDICT_cover_params_t* parameters); | |
| /*! ZDICT_trainFromBuffer_fastCover(): | |
| * Train a dictionary from an array of samples using a modified version of COVER algorithm. | |
| * Samples must be stored concatenated in a single flat buffer `samplesBuffer`, | |
| * supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order. | |
| * d and k are required. | |
| * All other parameters are optional, will use default values if not provided | |
| * The resulting dictionary will be saved into `dictBuffer`. | |
| * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`) | |
| * or an error code, which can be tested with ZDICT_isError(). | |
| * See ZDICT_trainFromBuffer() for details on failure modes. | |
| * Note: ZDICT_trainFromBuffer_fastCover() requires 6 * 2^f bytes of memory. | |
| * Tips: In general, a reasonable dictionary has a size of ~ 100 KB. | |
| * It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`. | |
| * In general, it's recommended to provide a few thousands samples, though this can vary a lot. | |
| * It's recommended that total size of all samples be about ~x100 times the target size of dictionary. | |
| */ | |
| ZDICTLIB_STATIC_API size_t ZDICT_trainFromBuffer_fastCover(void *dictBuffer, | |
| size_t dictBufferCapacity, const void *samplesBuffer, | |
| const size_t *samplesSizes, unsigned nbSamples, | |
| ZDICT_fastCover_params_t parameters); | |
| /*! ZDICT_optimizeTrainFromBuffer_fastCover(): | |
| * The same requirements as above hold for all the parameters except `parameters`. | |
| * This function tries many parameter combinations (specifically, k and d combinations) | |
| * and picks the best parameters. `*parameters` is filled with the best parameters found, | |
| * dictionary constructed with those parameters is stored in `dictBuffer`. | |
| * All of the parameters d, k, steps, f, and accel are optional. | |
| * If d is non-zero then we don't check multiple values of d, otherwise we check d = {6, 8}. | |
| * if steps is zero it defaults to its default value. | |
| * If k is non-zero then we don't check multiple values of k, otherwise we check steps values in [50, 2000]. | |
| * If f is zero, default value of 20 is used. | |
| * If accel is zero, default value of 1 is used. | |
| * | |
| * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`) | |
| * or an error code, which can be tested with ZDICT_isError(). | |
| * On success `*parameters` contains the parameters selected. | |
| * See ZDICT_trainFromBuffer() for details on failure modes. | |
| * Note: ZDICT_optimizeTrainFromBuffer_fastCover() requires about 6 * 2^f bytes of memory for each thread. | |
| */ | |
| ZDICTLIB_STATIC_API size_t ZDICT_optimizeTrainFromBuffer_fastCover(void* dictBuffer, | |
| size_t dictBufferCapacity, const void* samplesBuffer, | |
| const size_t* samplesSizes, unsigned nbSamples, | |
| ZDICT_fastCover_params_t* parameters); | |
| typedef struct { | |
| unsigned selectivityLevel; /* 0 means default; larger => select more => larger dictionary */ | |
| ZDICT_params_t zParams; | |
| } ZDICT_legacy_params_t; | |
| /*! ZDICT_trainFromBuffer_legacy(): | |
| * Train a dictionary from an array of samples. | |
| * Samples must be stored concatenated in a single flat buffer `samplesBuffer`, | |
| * supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order. | |
| * The resulting dictionary will be saved into `dictBuffer`. | |
| * `parameters` is optional and can be provided with values set to 0 to mean "default". | |
| * @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`) | |
| * or an error code, which can be tested with ZDICT_isError(). | |
| * See ZDICT_trainFromBuffer() for details on failure modes. | |
| * Tips: In general, a reasonable dictionary has a size of ~ 100 KB. | |
| * It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`. | |
| * In general, it's recommended to provide a few thousands samples, though this can vary a lot. | |
| * It's recommended that total size of all samples be about ~x100 times the target size of dictionary. | |
| * Note: ZDICT_trainFromBuffer_legacy() will send notifications into stderr if instructed to, using notificationLevel>0. | |
| */ | |
| ZDICTLIB_STATIC_API size_t ZDICT_trainFromBuffer_legacy( | |
| void* dictBuffer, size_t dictBufferCapacity, | |
| const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples, | |
| ZDICT_legacy_params_t parameters); | |
| /* Deprecation warnings */ | |
| /* It is generally possible to disable deprecation warnings from compiler, | |
| for example with -Wno-deprecated-declarations for gcc | |
| or _CRT_SECURE_NO_WARNINGS in Visual. | |
| Otherwise, it's also possible to manually define ZDICT_DISABLE_DEPRECATE_WARNINGS */ | |
| ZDICT_DEPRECATED("use ZDICT_finalizeDictionary() instead") | |
| ZDICTLIB_STATIC_API | |
| size_t ZDICT_addEntropyTablesFromBuffer(void* dictBuffer, size_t dictContentSize, size_t dictBufferCapacity, | |
| const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples); | |
| } | |