mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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282 lines
17 KiB
C++
282 lines
17 KiB
C++
/*
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* Copyright (c) 2016-present, Yann Collet, Facebook, Inc.
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* All rights reserved.
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*
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* This source code is licensed under both the BSD-style license (found in the
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* LICENSE file in the root directory of this source tree) and the GPLv2 (found
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* in the COPYING file in the root directory of this source tree).
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* You may select, at your option, one of the above-listed licenses.
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*/
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#ifndef DICTBUILDER_H_001
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#define DICTBUILDER_H_001
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#if defined (__cplusplus)
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extern "C" {
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#endif
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/*====== Dependencies ======*/
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#include <stddef.h> /* size_t */
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/* ===== ZDICTLIB_API : control library symbols visibility ===== */
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#ifndef ZDICTLIB_VISIBILITY
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# if defined(__GNUC__) && (__GNUC__ >= 4)
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# define ZDICTLIB_VISIBILITY __attribute__ ((visibility ("default")))
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# else
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# define ZDICTLIB_VISIBILITY
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# endif
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#endif
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#if defined(ZSTD_DLL_EXPORT) && (ZSTD_DLL_EXPORT==1)
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# define ZDICTLIB_API __declspec(dllexport) ZDICTLIB_VISIBILITY
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#elif defined(ZSTD_DLL_IMPORT) && (ZSTD_DLL_IMPORT==1)
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# define ZDICTLIB_API __declspec(dllimport) ZDICTLIB_VISIBILITY /* It isn't required but allows to generate better code, saving a function pointer load from the IAT and an indirect jump.*/
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#else
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# define ZDICTLIB_API ZDICTLIB_VISIBILITY
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#endif
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/*! ZDICT_trainFromBuffer():
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* Train a dictionary from an array of samples.
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* Redirect towards ZDICT_optimizeTrainFromBuffer_fastCover() single-threaded, with d=8, steps=4,
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* f=20, and accel=1.
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* Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
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* supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
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* The resulting dictionary will be saved into `dictBuffer`.
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
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* or an error code, which can be tested with ZDICT_isError().
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* Note: Dictionary training will fail if there are not enough samples to construct a
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* dictionary, or if most of the samples are too small (< 8 bytes being the lower limit).
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* If dictionary training fails, you should use zstd without a dictionary, as the dictionary
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* would've been ineffective anyways. If you believe your samples would benefit from a dictionary
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* please open an issue with details, and we can look into it.
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* Note: ZDICT_trainFromBuffer()'s memory usage is about 6 MB.
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* Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
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* It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
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* In general, it's recommended to provide a few thousands samples, though this can vary a lot.
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* It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
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*/
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ZDICTLIB_API size_t ZDICT_trainFromBuffer(void* dictBuffer, size_t dictBufferCapacity,
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const void* samplesBuffer,
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const size_t* samplesSizes, unsigned nbSamples);
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/*====== Helper functions ======*/
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ZDICTLIB_API unsigned ZDICT_getDictID(const void* dictBuffer, size_t dictSize); /**< extracts dictID; @return zero if error (not a valid dictionary) */
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ZDICTLIB_API unsigned ZDICT_isError(size_t errorCode);
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ZDICTLIB_API const char* ZDICT_getErrorName(size_t errorCode);
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#ifdef ZDICT_STATIC_LINKING_ONLY
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/* ====================================================================================
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* The definitions in this section are considered experimental.
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* They should never be used with a dynamic library, as they may change in the future.
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* They are provided for advanced usages.
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* Use them only in association with static linking.
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* ==================================================================================== */
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typedef struct {
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int compressionLevel; /* optimize for a specific zstd compression level; 0 means default */
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unsigned notificationLevel; /* Write log to stderr; 0 = none (default); 1 = errors; 2 = progression; 3 = details; 4 = debug; */
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unsigned dictID; /* force dictID value; 0 means auto mode (32-bits random value) */
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} ZDICT_params_t;
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/*! ZDICT_cover_params_t:
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* k and d are the only required parameters.
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* For others, value 0 means default.
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*/
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typedef struct {
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unsigned k; /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */
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unsigned d; /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */
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unsigned steps; /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */
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unsigned nbThreads; /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */
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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 */
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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 */
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unsigned shrinkDictMaxRegression; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */
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ZDICT_params_t zParams;
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} ZDICT_cover_params_t;
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typedef struct {
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unsigned k; /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */
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unsigned d; /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */
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unsigned f; /* log of size of frequency array : constraint: 0 < f <= 31 : 1 means default(20)*/
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unsigned steps; /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */
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unsigned nbThreads; /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */
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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 */
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unsigned accel; /* Acceleration level: constraint: 0 < accel <= 10, higher means faster and less accurate, 0 means default(1) */
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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 */
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unsigned shrinkDictMaxRegression; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */
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ZDICT_params_t zParams;
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} ZDICT_fastCover_params_t;
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/*! ZDICT_trainFromBuffer_cover():
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* Train a dictionary from an array of samples using the COVER algorithm.
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* Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
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* supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
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* The resulting dictionary will be saved into `dictBuffer`.
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
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* or an error code, which can be tested with ZDICT_isError().
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* See ZDICT_trainFromBuffer() for details on failure modes.
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* Note: ZDICT_trainFromBuffer_cover() requires about 9 bytes of memory for each input byte.
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* Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
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* It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
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* In general, it's recommended to provide a few thousands samples, though this can vary a lot.
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* It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
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*/
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ZDICTLIB_API size_t ZDICT_trainFromBuffer_cover(
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void *dictBuffer, size_t dictBufferCapacity,
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const void *samplesBuffer, const size_t *samplesSizes, unsigned nbSamples,
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ZDICT_cover_params_t parameters);
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/*! ZDICT_optimizeTrainFromBuffer_cover():
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* The same requirements as above hold for all the parameters except `parameters`.
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* This function tries many parameter combinations and picks the best parameters.
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* `*parameters` is filled with the best parameters found,
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* dictionary constructed with those parameters is stored in `dictBuffer`.
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*
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* All of the parameters d, k, steps are optional.
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* If d is non-zero then we don't check multiple values of d, otherwise we check d = {6, 8}.
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* if steps is zero it defaults to its default value.
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* If k is non-zero then we don't check multiple values of k, otherwise we check steps values in [50, 2000].
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*
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
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* or an error code, which can be tested with ZDICT_isError().
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* On success `*parameters` contains the parameters selected.
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* See ZDICT_trainFromBuffer() for details on failure modes.
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* 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.
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*/
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ZDICTLIB_API size_t ZDICT_optimizeTrainFromBuffer_cover(
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void* dictBuffer, size_t dictBufferCapacity,
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const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples,
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ZDICT_cover_params_t* parameters);
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/*! ZDICT_trainFromBuffer_fastCover():
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* Train a dictionary from an array of samples using a modified version of COVER algorithm.
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* Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
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* supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
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* d and k are required.
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* All other parameters are optional, will use default values if not provided
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* The resulting dictionary will be saved into `dictBuffer`.
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
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* or an error code, which can be tested with ZDICT_isError().
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* See ZDICT_trainFromBuffer() for details on failure modes.
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* Note: ZDICT_trainFromBuffer_fastCover() requires 6 * 2^f bytes of memory.
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* Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
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* It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
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* In general, it's recommended to provide a few thousands samples, though this can vary a lot.
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* It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
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*/
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ZDICTLIB_API size_t ZDICT_trainFromBuffer_fastCover(void *dictBuffer,
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size_t dictBufferCapacity, const void *samplesBuffer,
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const size_t *samplesSizes, unsigned nbSamples,
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ZDICT_fastCover_params_t parameters);
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/*! ZDICT_optimizeTrainFromBuffer_fastCover():
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* The same requirements as above hold for all the parameters except `parameters`.
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* This function tries many parameter combinations (specifically, k and d combinations)
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* and picks the best parameters. `*parameters` is filled with the best parameters found,
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* dictionary constructed with those parameters is stored in `dictBuffer`.
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* All of the parameters d, k, steps, f, and accel are optional.
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* If d is non-zero then we don't check multiple values of d, otherwise we check d = {6, 8}.
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* if steps is zero it defaults to its default value.
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* If k is non-zero then we don't check multiple values of k, otherwise we check steps values in [50, 2000].
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* If f is zero, default value of 20 is used.
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* If accel is zero, default value of 1 is used.
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*
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
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* or an error code, which can be tested with ZDICT_isError().
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* On success `*parameters` contains the parameters selected.
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* See ZDICT_trainFromBuffer() for details on failure modes.
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* Note: ZDICT_optimizeTrainFromBuffer_fastCover() requires about 6 * 2^f bytes of memory for each thread.
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*/
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ZDICTLIB_API size_t ZDICT_optimizeTrainFromBuffer_fastCover(void* dictBuffer,
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size_t dictBufferCapacity, const void* samplesBuffer,
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const size_t* samplesSizes, unsigned nbSamples,
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ZDICT_fastCover_params_t* parameters);
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/*! ZDICT_finalizeDictionary():
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* Given a custom content as a basis for dictionary, and a set of samples,
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* finalize dictionary by adding headers and statistics.
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*
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* Samples must be stored concatenated in a flat buffer `samplesBuffer`,
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* supplied with an array of sizes `samplesSizes`, providing the size of each sample in order.
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*
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* dictContentSize must be >= ZDICT_CONTENTSIZE_MIN bytes.
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* maxDictSize must be >= dictContentSize, and must be >= ZDICT_DICTSIZE_MIN bytes.
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*
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`),
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* or an error code, which can be tested by ZDICT_isError().
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* Note: ZDICT_finalizeDictionary() will push notifications into stderr if instructed to, using notificationLevel>0.
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* Note 2: dictBuffer and dictContent can overlap
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*/
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#define ZDICT_CONTENTSIZE_MIN 128
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#define ZDICT_DICTSIZE_MIN 256
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ZDICTLIB_API size_t ZDICT_finalizeDictionary(void* dictBuffer, size_t dictBufferCapacity,
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const void* dictContent, size_t dictContentSize,
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const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples,
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ZDICT_params_t parameters);
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typedef struct {
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unsigned selectivityLevel; /* 0 means default; larger => select more => larger dictionary */
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ZDICT_params_t zParams;
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} ZDICT_legacy_params_t;
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/*! ZDICT_trainFromBuffer_legacy():
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* Train a dictionary from an array of samples.
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* Samples must be stored concatenated in a single flat buffer `samplesBuffer`,
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* supplied with an array of sizes `samplesSizes`, providing the size of each sample, in order.
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* The resulting dictionary will be saved into `dictBuffer`.
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* `parameters` is optional and can be provided with values set to 0 to mean "default".
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* @return: size of dictionary stored into `dictBuffer` (<= `dictBufferCapacity`)
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* or an error code, which can be tested with ZDICT_isError().
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* See ZDICT_trainFromBuffer() for details on failure modes.
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* Tips: In general, a reasonable dictionary has a size of ~ 100 KB.
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* It's possible to select smaller or larger size, just by specifying `dictBufferCapacity`.
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* In general, it's recommended to provide a few thousands samples, though this can vary a lot.
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* It's recommended that total size of all samples be about ~x100 times the target size of dictionary.
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* Note: ZDICT_trainFromBuffer_legacy() will send notifications into stderr if instructed to, using notificationLevel>0.
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*/
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ZDICTLIB_API size_t ZDICT_trainFromBuffer_legacy(
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void *dictBuffer, size_t dictBufferCapacity,
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const void *samplesBuffer, const size_t *samplesSizes, unsigned nbSamples,
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ZDICT_legacy_params_t parameters);
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/* Deprecation warnings */
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/* It is generally possible to disable deprecation warnings from compiler,
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for example with -Wno-deprecated-declarations for gcc
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or _CRT_SECURE_NO_WARNINGS in Visual.
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Otherwise, it's also possible to manually define ZDICT_DISABLE_DEPRECATE_WARNINGS */
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#ifdef ZDICT_DISABLE_DEPRECATE_WARNINGS
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# define ZDICT_DEPRECATED(message) ZDICTLIB_API /* disable deprecation warnings */
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#else
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# define ZDICT_GCC_VERSION (__GNUC__ * 100 + __GNUC_MINOR__)
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# if defined (__cplusplus) && (__cplusplus >= 201402) /* C++14 or greater */
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# define ZDICT_DEPRECATED(message) [[deprecated(message)]] ZDICTLIB_API
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# elif (ZDICT_GCC_VERSION >= 405) || defined(__clang__)
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# define ZDICT_DEPRECATED(message) ZDICTLIB_API __attribute__((deprecated(message)))
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# elif (ZDICT_GCC_VERSION >= 301)
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# define ZDICT_DEPRECATED(message) ZDICTLIB_API __attribute__((deprecated))
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# elif defined(_MSC_VER)
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# define ZDICT_DEPRECATED(message) ZDICTLIB_API __declspec(deprecated(message))
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# else
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# pragma message("WARNING: You need to implement ZDICT_DEPRECATED for this compiler")
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# define ZDICT_DEPRECATED(message) ZDICTLIB_API
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# endif
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#endif /* ZDICT_DISABLE_DEPRECATE_WARNINGS */
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ZDICT_DEPRECATED("use ZDICT_finalizeDictionary() instead")
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size_t ZDICT_addEntropyTablesFromBuffer(void* dictBuffer, size_t dictContentSize, size_t dictBufferCapacity,
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const void* samplesBuffer, const size_t* samplesSizes, unsigned nbSamples);
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#endif /* ZDICT_STATIC_LINKING_ONLY */
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#if defined (__cplusplus)
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}
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#endif
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#endif /* DICTBUILDER_H_001 */
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