git/bloom.c

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#include "git-compat-util.h"
#include "bloom.h"
#include "diff.h"
#include "diffcore.h"
#include "revision.h"
#include "hashmap.h"
#include "commit-graph.h"
#include "commit.h"
define_commit_slab(bloom_filter_slab, struct bloom_filter);
struct bloom_filter_slab bloom_filters;
struct pathmap_hash_entry {
struct hashmap_entry entry;
const char path[FLEX_ARRAY];
};
static uint32_t rotate_left(uint32_t value, int32_t count)
{
uint32_t mask = 8 * sizeof(uint32_t) - 1;
count &= mask;
return ((value << count) | (value >> ((-count) & mask)));
}
bloom.c: introduce core Bloom filter constructs Introduce the constructs for Bloom filters, Bloom filter keys and Bloom filter settings. For details on what Bloom filters are and how they work, refer to Dr. Derrick Stolee's blog post [1]. It provides a concise explanation of the adoption of Bloom filters as described in [2] and [3]. Implementation specifics: 1. We currently use 7 and 10 for the number of hashes and the size of each entry respectively. They served as great starting values, the mathematical details behind this choice are described in [1] and [4]. The implementation, while not completely open to it at the moment, is flexible enough to allow for tweaking these settings in the future. Note: The performance gains we have observed with these values are significant enough that we did not need to tweak these settings. The performance numbers are included in the cover letter of this series and in the commit message of the subsequent commit where we use Bloom filters to speed up `git log -- path`. 2. As described in [1] and [3], we do not need 7 independent hashing functions. We use the Murmur3 hashing scheme, seed it twice and then combine those to procure an arbitrary number of hash values. 3. The filters will be sized according to the number of changes in each commit, in multiples of 8 bit words. [1] Derrick Stolee "Supercharging the Git Commit Graph IV: Bloom Filters" https://devblogs.microsoft.com/devops/super-charging-the-git-commit-graph-iv-Bloom-filters/ [2] Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese "An Improved Construction for Counting Bloom Filters" http://theory.stanford.edu/~rinap/papers/esa2006b.pdf https://doi.org/10.1007/11841036_61 [3] Peter C. Dillinger and Panagiotis Manolios "Bloom Filters in Probabilistic Verification" http://www.ccs.neu.edu/home/pete/pub/Bloom-filters-verification.pdf https://doi.org/10.1007/978-3-540-30494-4_26 [4] Thomas Mueller Graf, Daniel Lemire "Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters" https://arxiv.org/abs/1912.08258 Helped-by: Derrick Stolee <dstolee@microsoft.com> Reviewed-by: Jakub Narębski <jnareb@gmail.com> Signed-off-by: Garima Singh <garima.singh@microsoft.com> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2020-03-30 00:31:25 +00:00
static inline unsigned char get_bitmask(uint32_t pos)
{
return ((unsigned char)1) << (pos & (BITS_PER_WORD - 1));
}
static int load_bloom_filter_from_graph(struct commit_graph *g,
struct bloom_filter *filter,
struct commit *c)
{
uint32_t lex_pos, start_index, end_index;
while (c->graph_pos < g->num_commits_in_base)
g = g->base_graph;
/* The commit graph commit 'c' lives in doesn't carry bloom filters. */
if (!g->chunk_bloom_indexes)
return 0;
lex_pos = c->graph_pos - g->num_commits_in_base;
end_index = get_be32(g->chunk_bloom_indexes + 4 * lex_pos);
if (lex_pos > 0)
start_index = get_be32(g->chunk_bloom_indexes + 4 * (lex_pos - 1));
else
start_index = 0;
filter->len = end_index - start_index;
filter->data = (unsigned char *)(g->chunk_bloom_data +
sizeof(unsigned char) * start_index +
BLOOMDATA_CHUNK_HEADER_SIZE);
return 1;
}
/*
* Calculate the murmur3 32-bit hash value for the given data
* using the given seed.
* Produces a uniformly distributed hash value.
* Not considered to be cryptographically secure.
* Implemented as described in https://en.wikipedia.org/wiki/MurmurHash#Algorithm
*/
uint32_t murmur3_seeded(uint32_t seed, const char *data, size_t len)
{
const uint32_t c1 = 0xcc9e2d51;
const uint32_t c2 = 0x1b873593;
const uint32_t r1 = 15;
const uint32_t r2 = 13;
const uint32_t m = 5;
const uint32_t n = 0xe6546b64;
int i;
uint32_t k1 = 0;
const char *tail;
int len4 = len / sizeof(uint32_t);
uint32_t k;
for (i = 0; i < len4; i++) {
uint32_t byte1 = (uint32_t)data[4*i];
uint32_t byte2 = ((uint32_t)data[4*i + 1]) << 8;
uint32_t byte3 = ((uint32_t)data[4*i + 2]) << 16;
uint32_t byte4 = ((uint32_t)data[4*i + 3]) << 24;
k = byte1 | byte2 | byte3 | byte4;
k *= c1;
k = rotate_left(k, r1);
k *= c2;
seed ^= k;
seed = rotate_left(seed, r2) * m + n;
}
tail = (data + len4 * sizeof(uint32_t));
switch (len & (sizeof(uint32_t) - 1)) {
case 3:
k1 ^= ((uint32_t)tail[2]) << 16;
/*-fallthrough*/
case 2:
k1 ^= ((uint32_t)tail[1]) << 8;
/*-fallthrough*/
case 1:
k1 ^= ((uint32_t)tail[0]) << 0;
k1 *= c1;
k1 = rotate_left(k1, r1);
k1 *= c2;
seed ^= k1;
break;
}
seed ^= (uint32_t)len;
seed ^= (seed >> 16);
seed *= 0x85ebca6b;
seed ^= (seed >> 13);
seed *= 0xc2b2ae35;
seed ^= (seed >> 16);
return seed;
bloom.c: introduce core Bloom filter constructs Introduce the constructs for Bloom filters, Bloom filter keys and Bloom filter settings. For details on what Bloom filters are and how they work, refer to Dr. Derrick Stolee's blog post [1]. It provides a concise explanation of the adoption of Bloom filters as described in [2] and [3]. Implementation specifics: 1. We currently use 7 and 10 for the number of hashes and the size of each entry respectively. They served as great starting values, the mathematical details behind this choice are described in [1] and [4]. The implementation, while not completely open to it at the moment, is flexible enough to allow for tweaking these settings in the future. Note: The performance gains we have observed with these values are significant enough that we did not need to tweak these settings. The performance numbers are included in the cover letter of this series and in the commit message of the subsequent commit where we use Bloom filters to speed up `git log -- path`. 2. As described in [1] and [3], we do not need 7 independent hashing functions. We use the Murmur3 hashing scheme, seed it twice and then combine those to procure an arbitrary number of hash values. 3. The filters will be sized according to the number of changes in each commit, in multiples of 8 bit words. [1] Derrick Stolee "Supercharging the Git Commit Graph IV: Bloom Filters" https://devblogs.microsoft.com/devops/super-charging-the-git-commit-graph-iv-Bloom-filters/ [2] Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese "An Improved Construction for Counting Bloom Filters" http://theory.stanford.edu/~rinap/papers/esa2006b.pdf https://doi.org/10.1007/11841036_61 [3] Peter C. Dillinger and Panagiotis Manolios "Bloom Filters in Probabilistic Verification" http://www.ccs.neu.edu/home/pete/pub/Bloom-filters-verification.pdf https://doi.org/10.1007/978-3-540-30494-4_26 [4] Thomas Mueller Graf, Daniel Lemire "Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters" https://arxiv.org/abs/1912.08258 Helped-by: Derrick Stolee <dstolee@microsoft.com> Reviewed-by: Jakub Narębski <jnareb@gmail.com> Signed-off-by: Garima Singh <garima.singh@microsoft.com> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2020-03-30 00:31:25 +00:00
}
void fill_bloom_key(const char *data,
size_t len,
struct bloom_key *key,
const struct bloom_filter_settings *settings)
bloom.c: introduce core Bloom filter constructs Introduce the constructs for Bloom filters, Bloom filter keys and Bloom filter settings. For details on what Bloom filters are and how they work, refer to Dr. Derrick Stolee's blog post [1]. It provides a concise explanation of the adoption of Bloom filters as described in [2] and [3]. Implementation specifics: 1. We currently use 7 and 10 for the number of hashes and the size of each entry respectively. They served as great starting values, the mathematical details behind this choice are described in [1] and [4]. The implementation, while not completely open to it at the moment, is flexible enough to allow for tweaking these settings in the future. Note: The performance gains we have observed with these values are significant enough that we did not need to tweak these settings. The performance numbers are included in the cover letter of this series and in the commit message of the subsequent commit where we use Bloom filters to speed up `git log -- path`. 2. As described in [1] and [3], we do not need 7 independent hashing functions. We use the Murmur3 hashing scheme, seed it twice and then combine those to procure an arbitrary number of hash values. 3. The filters will be sized according to the number of changes in each commit, in multiples of 8 bit words. [1] Derrick Stolee "Supercharging the Git Commit Graph IV: Bloom Filters" https://devblogs.microsoft.com/devops/super-charging-the-git-commit-graph-iv-Bloom-filters/ [2] Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese "An Improved Construction for Counting Bloom Filters" http://theory.stanford.edu/~rinap/papers/esa2006b.pdf https://doi.org/10.1007/11841036_61 [3] Peter C. Dillinger and Panagiotis Manolios "Bloom Filters in Probabilistic Verification" http://www.ccs.neu.edu/home/pete/pub/Bloom-filters-verification.pdf https://doi.org/10.1007/978-3-540-30494-4_26 [4] Thomas Mueller Graf, Daniel Lemire "Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters" https://arxiv.org/abs/1912.08258 Helped-by: Derrick Stolee <dstolee@microsoft.com> Reviewed-by: Jakub Narębski <jnareb@gmail.com> Signed-off-by: Garima Singh <garima.singh@microsoft.com> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2020-03-30 00:31:25 +00:00
{
int i;
const uint32_t seed0 = 0x293ae76f;
const uint32_t seed1 = 0x7e646e2c;
const uint32_t hash0 = murmur3_seeded(seed0, data, len);
const uint32_t hash1 = murmur3_seeded(seed1, data, len);
key->hashes = (uint32_t *)xcalloc(settings->num_hashes, sizeof(uint32_t));
for (i = 0; i < settings->num_hashes; i++)
key->hashes[i] = hash0 + i * hash1;
}
void add_key_to_filter(const struct bloom_key *key,
struct bloom_filter *filter,
const struct bloom_filter_settings *settings)
bloom.c: introduce core Bloom filter constructs Introduce the constructs for Bloom filters, Bloom filter keys and Bloom filter settings. For details on what Bloom filters are and how they work, refer to Dr. Derrick Stolee's blog post [1]. It provides a concise explanation of the adoption of Bloom filters as described in [2] and [3]. Implementation specifics: 1. We currently use 7 and 10 for the number of hashes and the size of each entry respectively. They served as great starting values, the mathematical details behind this choice are described in [1] and [4]. The implementation, while not completely open to it at the moment, is flexible enough to allow for tweaking these settings in the future. Note: The performance gains we have observed with these values are significant enough that we did not need to tweak these settings. The performance numbers are included in the cover letter of this series and in the commit message of the subsequent commit where we use Bloom filters to speed up `git log -- path`. 2. As described in [1] and [3], we do not need 7 independent hashing functions. We use the Murmur3 hashing scheme, seed it twice and then combine those to procure an arbitrary number of hash values. 3. The filters will be sized according to the number of changes in each commit, in multiples of 8 bit words. [1] Derrick Stolee "Supercharging the Git Commit Graph IV: Bloom Filters" https://devblogs.microsoft.com/devops/super-charging-the-git-commit-graph-iv-Bloom-filters/ [2] Flavio Bonomi, Michael Mitzenmacher, Rina Panigrahy, Sushil Singh, George Varghese "An Improved Construction for Counting Bloom Filters" http://theory.stanford.edu/~rinap/papers/esa2006b.pdf https://doi.org/10.1007/11841036_61 [3] Peter C. Dillinger and Panagiotis Manolios "Bloom Filters in Probabilistic Verification" http://www.ccs.neu.edu/home/pete/pub/Bloom-filters-verification.pdf https://doi.org/10.1007/978-3-540-30494-4_26 [4] Thomas Mueller Graf, Daniel Lemire "Xor Filters: Faster and Smaller Than Bloom and Cuckoo Filters" https://arxiv.org/abs/1912.08258 Helped-by: Derrick Stolee <dstolee@microsoft.com> Reviewed-by: Jakub Narębski <jnareb@gmail.com> Signed-off-by: Garima Singh <garima.singh@microsoft.com> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2020-03-30 00:31:25 +00:00
{
int i;
uint64_t mod = filter->len * BITS_PER_WORD;
for (i = 0; i < settings->num_hashes; i++) {
uint64_t hash_mod = key->hashes[i] % mod;
uint64_t block_pos = hash_mod / BITS_PER_WORD;
filter->data[block_pos] |= get_bitmask(hash_mod);
}
}
void init_bloom_filters(void)
{
init_bloom_filter_slab(&bloom_filters);
}
static int pathmap_cmp(const void *hashmap_cmp_fn_data,
const struct hashmap_entry *eptr,
const struct hashmap_entry *entry_or_key,
const void *keydata)
{
const struct pathmap_hash_entry *e1, *e2;
e1 = container_of(eptr, const struct pathmap_hash_entry, entry);
e2 = container_of(entry_or_key, const struct pathmap_hash_entry, entry);
return strcmp(e1->path, e2->path);
}
struct bloom_filter *get_bloom_filter(struct repository *r,
struct commit *c,
int compute_if_not_present)
{
struct bloom_filter *filter;
struct bloom_filter_settings settings = DEFAULT_BLOOM_FILTER_SETTINGS;
int i;
struct diff_options diffopt;
int max_changes = 512;
if (bloom_filters.slab_size == 0)
return NULL;
filter = bloom_filter_slab_at(&bloom_filters, c);
if (!filter->data) {
load_commit_graph_info(r, c);
if (c->graph_pos != COMMIT_NOT_FROM_GRAPH &&
r->objects->commit_graph->chunk_bloom_indexes) {
if (load_bloom_filter_from_graph(r->objects->commit_graph, filter, c))
return filter;
else
return NULL;
}
}
if (filter->data || !compute_if_not_present)
return filter;
repo_diff_setup(r, &diffopt);
diffopt.flags.recursive = 1;
diffopt.detect_rename = 0;
diffopt.max_changes = max_changes;
diff_setup_done(&diffopt);
/* ensure commit is parsed so we have parent information */
repo_parse_commit(r, c);
if (c->parents)
diff_tree_oid(&c->parents->item->object.oid, &c->object.oid, "", &diffopt);
else
diff_tree_oid(NULL, &c->object.oid, "", &diffopt);
diffcore_std(&diffopt);
if (diff_queued_diff.nr <= max_changes) {
struct hashmap pathmap;
struct pathmap_hash_entry *e;
struct hashmap_iter iter;
hashmap_init(&pathmap, pathmap_cmp, NULL, 0);
for (i = 0; i < diff_queued_diff.nr; i++) {
const char *path = diff_queued_diff.queue[i]->two->path;
/*
* Add each leading directory of the changed file, i.e. for
* 'dir/subdir/file' add 'dir' and 'dir/subdir' as well, so
* the Bloom filter could be used to speed up commands like
* 'git log dir/subdir', too.
*
* Note that directories are added without the trailing '/'.
*/
do {
char *last_slash = strrchr(path, '/');
FLEX_ALLOC_STR(e, path, path);
hashmap_entry_init(&e->entry, strhash(path));
if (!hashmap_get(&pathmap, &e->entry, NULL))
hashmap_add(&pathmap, &e->entry);
else
free(e);
if (!last_slash)
last_slash = (char*)path;
*last_slash = '\0';
} while (*path);
diff_free_filepair(diff_queued_diff.queue[i]);
}
filter->len = (hashmap_get_size(&pathmap) * settings.bits_per_entry + BITS_PER_WORD - 1) / BITS_PER_WORD;
filter->data = xcalloc(filter->len, sizeof(unsigned char));
hashmap_for_each_entry(&pathmap, &iter, e, entry) {
struct bloom_key key;
fill_bloom_key(e->path, strlen(e->path), &key, &settings);
add_key_to_filter(&key, filter, &settings);
}
hashmap_free_entries(&pathmap, struct pathmap_hash_entry, entry);
} else {
for (i = 0; i < diff_queued_diff.nr; i++)
diff_free_filepair(diff_queued_diff.queue[i]);
filter->data = NULL;
filter->len = 0;
}
free(diff_queued_diff.queue);
DIFF_QUEUE_CLEAR(&diff_queued_diff);
return filter;
}
revision.c: use Bloom filters to speed up path based revision walks Revision walk will now use Bloom filters for commits to speed up revision walks for a particular path (for computing history for that path), if they are present in the commit-graph file. We load the Bloom filters during the prepare_revision_walk step, currently only when dealing with a single pathspec. Extending it to work with multiple pathspecs can be explored and built on top of this series in the future. While comparing trees in rev_compare_trees(), if the Bloom filter says that the file is not different between the two trees, we don't need to compute the expensive diff. This is where we get our performance gains. The other response of the Bloom filter is '`:maybe', in which case we fall back to the full diff calculation to determine if the path was changed in the commit. We do not try to use Bloom filters when the '--walk-reflogs' option is specified. The '--walk-reflogs' option does not walk the commit ancestry chain like the rest of the options. Incorporating the performance gains when walking reflog entries would add more complexity, and can be explored in a later series. Performance Gains: We tested the performance of `git log -- <path>` on the git repo, the linux and some internal large repos, with a variety of paths of varying depths. On the git and linux repos: - we observed a 2x to 5x speed up. On a large internal repo with files seated 6-10 levels deep in the tree: - we observed 10x to 20x speed ups, with some paths going up to 28 times faster. Helped-by: Derrick Stolee <dstolee@microsoft.com Helped-by: SZEDER Gábor <szeder.dev@gmail.com> Helped-by: Jonathan Tan <jonathantanmy@google.com> Signed-off-by: Garima Singh <garima.singh@microsoft.com> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2020-04-06 16:59:52 +00:00
int bloom_filter_contains(const struct bloom_filter *filter,
const struct bloom_key *key,
const struct bloom_filter_settings *settings)
{
int i;
uint64_t mod = filter->len * BITS_PER_WORD;
if (!mod)
return -1;
for (i = 0; i < settings->num_hashes; i++) {
uint64_t hash_mod = key->hashes[i] % mod;
uint64_t block_pos = hash_mod / BITS_PER_WORD;
if (!(filter->data[block_pos] & get_bitmask(hash_mod)))
return 0;
}
return 1;
}