[PATCH 02/10] smb: client: compress: rework compression heuristics
Enzo Matsumiya <[email protected]>
| Newsgroups | org.kernel.vger.linux-cifs |
|---|---|
| Message-ID | <[email protected]> |
- add enum with *COMPRESSIBLE values
- is_compressible() is now check_compressible(), and is called from
smb_compress() instead of should_compress(); the latter only does
the basic checks (write >= 4K)
- compressibility check now also may return 'MAYBE_COMPRESSIBLE',
for cases when even with deeper analysis, it can't return a
decisive result
- rewrite Shannon entropy computation (original code was copied over
from btrfs, so it carelessly used their parameters)
- divide heuristics checks in stages:
1. check if buffer is filled with same byte (RLE)
2. check if partial RLE (first ~1% of buffer repeats same byte)
3. check whole buffer entropy
4. split buffer in 64k chunks and check entropy and byte distribution
(based on hardcoded thresholds)
- remove collect_sample() and collect_step() helpers, heuristics checks
are run on the entire buffer now
- remove calc_byte_distribution(), as it's a redundant entropy check
Signed-off-by: Enzo Matsumiya <[email protected]>
---
fs/smb/client/compress.c | 440 ++++++++++++++++++++++-----------------
1 file changed, 244 insertions(+), 196 deletions(-)
diff --git a/fs/smb/client/compress.c b/fs/smb/client/compress.c
index 5591a8d85037..7c08e2b843c2 100644
--- a/fs/smb/client/compress.c
+++ b/fs/smb/client/compress.c
@@ -1,6 +1,6 @@
// SPDX-License-Identifier: GPL-2.0-only
/*
- * Copyright (C) 2024, SUSE LLC
+ * Copyright (C) 2024-2026, SUSE LLC
*
* Authors: Enzo Matsumiya <[email protected]>
*
@@ -24,242 +24,277 @@
#include "../common/compress/compress.h"
#include "compress.h"
-/*
- * The heuristic_*() functions below try to determine data compressibility.
+/**
+ * freq_count() - Count symbols (bytes) frequencies in a buffer.
+ * @buf: uncompressed buffer
+ * @len: size of @buf
+ * @mem: (caller-allocated) auxiliary memory for parallel accumulators
+ * @count: on exit, set to unique byte count (alphabet size) in @buf
*
- * Derived from fs/btrfs/compression.c, changing coding style, some parameters, and removing
- * unused parts.
+ * This function counts all bytes' unique count and frequencies.
+ * Expect @mem to be 1024 * sizeof(u32) long and zeroed.
+ * Final frequencies will be stored on first 256 elements of @mem.
*
- * Read that file for better and more detailed explanation of the calculations.
+ * Function is optimized for OoO CPUs (straightforward iterative count is about 2-3x slower).
*
- * The algorithms are ran in a collected sample of the input (uncompressed) data.
- * The sample is formed of 2K reads in PAGE_SIZE intervals, with a maximum size of 4M.
+ * Return: max frequency found in @buf.
*
- * Parsing the sample goes from "low-hanging fruits" (fastest algorithms, likely compressible)
- * to "need more analysis" (likely uncompressible).
+ * (*) This is an adapted version of FSE's https://github.com/Cyan4973/FiniteStateEntropy
*/
+static noinline u32 freq_count(const u8 *buf, const u32 len, u32 *mem, u32 *count)
+{
+ const u8 *p = buf, *end = p + len;
+ u32 c = 0, max_freq = 0;
+ u32 v = mem_read32(p);
+ u32 *acc1 = mem;
+ u32 *acc2 = acc1 + 256;
+ u32 *acc3 = acc2 + 256;
+ u32 *acc4 = acc3 + 256;
+
+ p += sizeof(u32);
+
+ /* Count by stripes of 16 bytes. */
+ while (p < end - 15) {
+ u32 cached = v;
+
+ v = mem_read32(p);
+ p += 4;
+ acc1[(u8)cached]++;
+ acc2[(u8)(cached>>8)]++;
+ acc3[(u8)(cached>>16)]++;
+ acc4[(u8)(cached>>24)]++;
+
+ cached = v;
+ v = mem_read32(p);
+ p += 4;
+ acc1[(u8)cached]++;
+ acc2[(u8)(cached>>8)]++;
+ acc3[(u8)(cached>>16)]++;
+ acc4[(u8)(cached>>24)]++;
+
+ cached = v;
+ v = mem_read32(p);
+ p += 4;
+ acc1[(u8)cached]++;
+ acc2[(u8)(cached>>8)]++;
+ acc3[(u8)(cached>>16)]++;
+ acc4[(u8)(cached>>24)]++;
+
+ cached = v;
+ v = mem_read32(p);
+ p += 4;
+ acc1[(u8)cached]++;
+ acc2[(u8)(cached>>8)]++;
+ acc3[(u8)(cached>>16)]++;
+ acc4[(u8)(cached>>24)]++;
+ }
-struct bucket {
- unsigned int count;
-};
+ p -= 4;
+
+ /* Count lefotver symbols. */
+ while (p < end)
+ acc1[*p++]++;
+
+ /*
+ * Combine accumulators + store.
+ *
+ * Avoid dereferencing @count here because performance.
+ */
+ for (v = 0; v < 256; v++) {
+ acc1[v] += acc2[v] + acc3[v] + acc4[v];
+
+ if (acc1[v]) {
+ c++;
+ if (acc1[v] > max_freq)
+ max_freq = acc1[v];
+ }
+ }
-static inline size_t pow4(size_t n)
-{
- return n * n * n * n;
+ if (count)
+ *count = c;
+
+ return max_freq;
}
-/*
- * has_low_entropy() - Compute Shannon entropy of the sampled data.
- * @bkt: Bytes counts of the sample.
- * @slen: Size of the sample.
+/**
+ * calc_entropy() - Compute Shannon entropy of a sample symbols' frequencies.
+ * @freqs: frequency counts of the sample
+ * @len: size of the sample
+ * @scale: scale for final result
*
- * Return: true if the level (percentage of number of bits that would be required to
- * compress the data) is below the minimum threshold.
+ * @freqs may include zero freq symbols.
+ * The final sum is multiplied by @factor to fit callers' precision requirements.
*
- * Note:
- * There _is_ an entropy level here that's > 65 (minimum threshold) that would indicate a
- * possibility of compression, but compressing, or even further analysing, it would waste so much
- * resources that it's simply not worth it.
+ * Valid results interpretation for @factor == 1:
+ * < 6: definitely compressible
+ * 6 - 7: probably compressible, but needs other parameters/heuristics for decisive result
+ * > 7: probably uncompressible -- other parameters/heuristics _might_ evaluate to "somewhat
+ * compressible", but usually not much
*
- * Also Shannon entropy is the last computed heuristic; if we got this far and ended up
- * with uncertainty, just stay on the safe side and call it uncompressible.
+ * Return: approximate number of bits (scaled to @scale) per byte that would be required to
+ * compress the data.
*/
-static bool has_low_entropy(struct bucket *bkt, size_t slen)
+static __always_inline u32 calc_entropy(const u32 *freqs, const u32 len, const u32 scale)
{
- const size_t threshold = 65, max_entropy = 8 * ilog2(16);
- size_t i, p, p2, len, sum = 0;
-
- len = ilog2(pow4(slen));
+ const u32 len2 = ilog2(len);
+ size_t i, p, sum = 0;
- for (i = 0; i < 256 && bkt[i].count > 0; i++) {
- p = bkt[i].count;
- p2 = ilog2(pow4(p));
- sum += p * (len - p2);
+ for (i = 0; i < 256; i++) {
+ /* 0 freq won't skew the results (ilog2(n) also returns 0 if n < 2) */
+ p = freqs[i];
+ sum += p * (len2 - ilog2(p));
}
- sum /= slen;
-
- return ((sum * 100 / max_entropy) <= threshold);
+ return (sum * scale / len);
}
-#define BYTE_DIST_BAD 0
-#define BYTE_DIST_GOOD 1
-#define BYTE_DIST_MAYBE 2
/*
- * calc_byte_distribution() - Compute byte distribution on the sampled data.
- * @bkt: Byte counts of the sample.
- * @slen: Size of the sample.
- *
- * Return:
- * BYTE_DIST_BAD: A "hard no" for compression -- a computed uniform distribution of
- * the bytes (e.g. random or encrypted data).
- * BYTE_DIST_GOOD: High probability (normal (Gaussian) distribution) of the data being
- * compressible.
- * BYTE_DIST_MAYBE: When computed byte distribution resulted in "low > n < high"
- * grounds. has_low_entropy() should be used for a final decision.
+ * Heuristic limit values.
+ * These are based on 64k blocks.
*/
-static int calc_byte_distribution(struct bucket *bkt, size_t slen)
-{
- const size_t low = 64, high = 200, threshold = slen * 90 / 100;
- size_t sum = 0;
- int i;
-
- for (i = 0; i < low; i++)
- sum += bkt[i].count;
-
- if (sum > threshold)
- return BYTE_DIST_BAD;
-
- for (; i < high && bkt[i].count > 0; i++) {
- sum += bkt[i].count;
- if (sum > threshold)
- break;
- }
-
- if (i <= low)
- return BYTE_DIST_GOOD;
-
- if (i >= high)
- return BYTE_DIST_BAD;
-
- return BYTE_DIST_MAYBE;
-}
-
-static bool is_mostly_ascii(const struct bucket *bkt)
-{
- size_t count = 0;
- int i;
-
- for (i = 0; i < 256; i++)
- if (bkt[i].count > 0)
- /* Too many non-ASCII (0-63) bytes. */
- if (++count > 64)
- return false;
-
- return true;
-}
-
-static bool has_repeated_data(const u8 *sample, size_t len)
-{
- size_t s = len / 2;
-
- return (!memcmp(&sample[0], &sample[s], s));
-}
-
-static int cmp_bkt(const void *_a, const void *_b)
-{
- const struct bucket *a = _a, *b = _b;
-
- /* Reverse sort. */
- if (a->count > b->count)
- return -1;
-
- return 1;
-}
+static const u32 heuristic_freq_hi = 8000;
+static const u32 heuristic_freq_lo = 5000;
+static const u32 heuristic_entropy_hi = 800;
+static const u32 heuristic_entropy_mid = 700;
+static const u32 heuristic_entropy_lo = 600;
+static const u32 heuristic_alphabet_hi = 256;
+static const u32 heuristic_alphabet_lo = 128;
+
+enum {
+ UNCOMPRESSIBLE = 0,
+ COMPRESSIBLE,
+ MAYBE_COMPRESSIBLE,
+};
/*
- * Collect some 2K samples with 2K gaps between.
+ * Computes entropy and byte dominance of @buf, on a 64k block basis.
+ *
+ * Return: one of the *COMPRESSIBLE values
*/
-static int collect_sample(const struct iov_iter *source, ssize_t max, u8 *sample)
+static int check_compressible_chunks(const u8 *buf, const u32 len, u32 *freqs)
{
- struct iov_iter iter = *source;
- size_t s = 0;
-
- while (iov_iter_count(&iter) >= SZ_2K) {
- size_t part = umin(umin(iov_iter_count(&iter), SZ_2K), max);
- size_t n;
-
- n = copy_from_iter(sample + s, part, &iter);
- if (n != part)
- return -EFAULT;
+ int score = 0, boost = 0, n = 0;
+ const u32 freqs_size = 1024 * sizeof(u32);
+ const u32 max_samples = 64;
+ const u32 max_sample_len = (len / max_samples);
+ const u32 nsamples = umin(max_samples, len / max_sample_len);
+ const s32 half_samples = nsamples / 2;
+ const u8 *end = buf + len;
+
+ while (buf < end) {
+ u32 alphabet = 0;
+ const u32 remaining = end - buf;
+ const u32 slen = umin(max_sample_len, remaining);
+ const u32 max_freq = freq_count(buf, slen, freqs, &alphabet);
+ const u32 entropy = calc_entropy(freqs, slen, 100);
+
+ if (entropy < heuristic_entropy_mid && max_freq > heuristic_freq_hi)
+ score++;
+ else if (entropy >= heuristic_entropy_mid && max_freq < heuristic_freq_lo)
+ score--;
+
+ if (alphabet < heuristic_alphabet_hi) {
+ boost++;
+ if (alphabet < heuristic_alphabet_lo)
+ boost++;
+ }
+
+ /* Reward/penalty for really good/bad entropy. */
+ if (entropy > heuristic_entropy_hi)
+ boost -= 2;
+ else if (entropy < heuristic_entropy_lo)
+ boost += 2;
+
+ memset(freqs, 0, freqs_size);
+ buf += slen;
+ n++;
+ }
- s += n;
- max -= n;
+ /* Check how much the heuristics above impacted (at least) half of @buf. */
+ if (score + boost > 0 && score + boost < half_samples)
+ return MAYBE_COMPRESSIBLE;
- if (iov_iter_count(&iter) < PAGE_SIZE - SZ_2K)
- break;
+ if (score + boost > -half_samples) {
+ if (score > half_samples || score + boost > half_samples)
+ return COMPRESSIBLE;
- iov_iter_advance(&iter, SZ_2K);
+ return MAYBE_COMPRESSIBLE;
}
- return s;
+ return UNCOMPRESSIBLE;
}
/*
- * is_compressible() - Determines if a chunk of data is compressible.
- * @data: Iterator containing uncompressed data.
+ * Check @buf heuristics (entropy/distribution) to determine its compressibility level.
+ *
+ * Tests shows that this function is quite reliable in predicting data compressibility, matching
+ * very close with the behaviour of LZ77 compression success and failures.
*
- * Return: true if @data is compressible, false otherwise.
+ * This function allocates memory, callers must check for -ENOMEM.
*
- * Tests shows that this function is quite reliable in predicting data compressibility,
- * matching close to 1:1 with the behaviour of LZ77 compression success and failures.
+ * Return: one of the *COMPRESSIBLE values on success, -errno otherwise.
*/
-static bool is_compressible(const struct iov_iter *data)
+static __must_check int check_compressible(const u8 *buf, u32 len)
{
- const size_t read_size = SZ_2K, bkt_size = 256, max = SZ_4M;
- struct bucket *bkt = NULL;
- size_t len;
- u8 *sample;
- bool ret = false;
- int i;
-
- /* Preventive double check -- already checked in should_compress(). */
- len = iov_iter_count(data);
- if (unlikely(len < read_size))
- return ret;
-
- if (len - read_size > max)
- len = max;
-
- sample = kvzalloc(len, GFP_KERNEL);
- if (!sample) {
- WARN_ON_ONCE(1);
-
- return ret;
- }
-
- /* Sample 2K bytes per page of the uncompressed data. */
- i = collect_sample(data, len, sample);
- if (i <= 0) {
- WARN_ON_ONCE(1);
+ u32 entropy, *freqs, rle = 0, rle_boost = 0;
+ const u32 min_reps = (len / 100); /* ~1% of @len */
+ const u8 *p;
+ int ret;
- goto out;
- }
+ if (unlikely(!buf || !len))
+ return -EINVAL;
- len = i;
- ret = true;
+ /* Stage 1: RLE (@buf is filled with same byte, a.k.a Run-Length Encoding). */
+ p = memchr_inv(buf, *buf, len);
+ if (!p)
+ /* Full RLE */
+ return 1;
- if (has_repeated_data(sample, len))
- goto out;
+ /* Stage 2: partial/starting RLE (repeating bytes cover are at least @min_reps long). */
+ if (p - buf >= min_reps) {
+ rle = (p - buf);
- bkt = kzalloc_objs(*bkt, bkt_size);
- if (!bkt) {
- WARN_ON_ONCE(1);
- ret = false;
+ buf += rle;
+ len -= rle;
- goto out;
+ rle_boost = rle >> (ilog2(len) - 1);
}
- for (i = 0; i < len; i++)
- bkt[sample[i]].count++;
-
- if (is_mostly_ascii(bkt))
- goto out;
-
- /* Sort in descending order */
- sort(bkt, bkt_size, sizeof(*bkt), cmp_bkt, NULL);
-
- i = calc_byte_distribution(bkt, len);
- if (i != BYTE_DIST_MAYBE) {
- ret = !!i;
-
- goto out;
+ freqs = kcalloc(1024, sizeof(*freqs), GFP_KERNEL);
+ if (!freqs)
+ return -ENOMEM;
+
+ /*
+ * Stage 3: whole buffer entropy check (decisive results if too high or too low).
+ *
+ * Don't care about max freq or alphabet size here.
+ */
+ (void)freq_count(buf, len, freqs, NULL);
+ entropy = calc_entropy(freqs, len, 1);
+ ret = MAYBE_COMPRESSIBLE;
+
+ if (entropy >= 8)
+ ret = UNCOMPRESSIBLE;
+ else if (entropy < 6 || (rle_boost && entropy - rle_boost <= 6) || len <= SZ_64K)
+ ret = COMPRESSIBLE;
+
+ if (ret == MAYBE_COMPRESSIBLE) {
+ memset(freqs, 0, sizeof(u32) * 1024);
+
+ /*
+ * Stage 4: break down buffer into 64k chunks for more detailed analysis.
+ *
+ * Note that it's quite common to go from MAYBE_COMPRESSIBLE -> COMPRESSIBLE after
+ * chunks analysis.
+ *
+ * OTOH, getting again MAYBE_COMPRESSIBLE really means 'uncompressible' for
+ * compressors that focus on speed (e.g. LZ77).
+ * Compressors focused on compression ratio might yield a good compression.
+ */
+ ret = check_compressible_chunks(buf, len, freqs);
}
- ret = has_low_entropy(bkt, len);
-out:
- kvfree(sample);
- kfree(bkt);
+ kfree(freqs);
return ret;
}
@@ -275,7 +310,6 @@ static bool is_compressible(const struct iov_iter *data)
* - server has enabled compression for the share
* - it's a read or write request
* - (write only) request length is >= SMB_COMPRESS_MIN_LEN
- * - (write only) is_compressible() returns 1
*
* Return false otherwise.
*/
@@ -295,10 +329,7 @@ bool should_compress(const struct cifs_tcon *tcon, const struct smb_rqst *rq)
if (shdr->Command == SMB2_WRITE) {
const struct smb2_write_req *wreq = rq->rq_iov->iov_base;
- if (le32_to_cpu(wreq->Length) < SMB_COMPRESS_MIN_LEN)
- return false;
-
- return is_compressible(&rq->rq_iter);
+ return (le32_to_cpu(wreq->Length) >= SMB_COMPRESS_MIN_LEN);
}
return (shdr->Command == SMB2_READ);
@@ -332,6 +363,23 @@ int smb_compress(struct TCP_Server_Info *server, struct smb_rqst *rq, compress_s
goto err_free;
}
+ /*
+ * Even though smb_lz77_compress() runs quite fast on uncompressible data (it ends up
+ * usually just parsing the input buffer), this is much faster.
+ *
+ * So to keep things balanced (compress performance vs prediction accuracy), let's drop the
+ * uncompressible low-hanging fruits here and let smb_lz77_compress() handle the
+ * exceptions/rare cases.
+ */
+ ret = check_compressible(src, slen);
+
+ /* XXX: do something with MAYBE_COMPRESSIBLE */
+ if (ret != COMPRESSIBLE) {
+ if (ret >= 0)
+ ret = send_fn(server, 1, rq);
+ goto err_free;
+ }
+
dlen = smb_lz77_compressed_alloc_size(slen);
dst = kvzalloc(dlen, GFP_KERNEL);
if (!dst) {
--
2.54.0