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>

1 files changed, 48 insertions, 0 deletions

diff --git a/t/helper/test-bloom.c b/t/helper/test-bloom.c
index 60ee204368..20460cde77 100644
--- a/t/helper/test-bloom.c
+++ b/t/helper/test-bloom.c
@@ -2,6 +2,36 @@
 #include "bloom.h"
 #include "test-tool.h"
 
+struct bloom_filter_settings settings = DEFAULT_BLOOM_FILTER_SETTINGS;
+
+static void add_string_to_filter(const char *data, struct bloom_filter *filter) {
+		struct bloom_key key;
+		int i;
+
+		fill_bloom_key(data, strlen(data), &key, &settings);
+		printf("Hashes:");
+		for (i = 0; i < settings.num_hashes; i++){
+			printf("0x%08x|", key.hashes[i]);
+		}
+		printf("\n");
+		add_key_to_filter(&key, filter, &settings);
+}
+
+static void print_bloom_filter(struct bloom_filter *filter) {
+	int i;
+
+	if (!filter) {
+		printf("No filter.\n");
+		return;
+	}
+	printf("Filter_Length:%d\n", (int)filter->len);
+	printf("Filter_Data:");
+	for (i = 0; i < filter->len; i++){
+		printf("%02x|", filter->data[i]);
+	}
+	printf("\n");
+}
+
 int cmd__bloom(int argc, const char **argv)
 {
 	if (!strcmp(argv[1], "get_murmur3")) {
@@ -9,5 +39,23 @@ int cmd__bloom(int argc, const char **argv)
 		printf("Murmur3 Hash with seed=0:0x%08x\n", hashed);
 	}
 
+    if (!strcmp(argv[1], "generate_filter")) {
+		struct bloom_filter filter;
+		int i = 2;
+		filter.len =  (settings.bits_per_entry + BITS_PER_WORD - 1) / BITS_PER_WORD;
+		filter.data = xcalloc(filter.len, sizeof(unsigned char));
+
+		if (!argv[2]){
+			die("at least one input string expected");
+		}
+
+		while (argv[i]) {
+			add_string_to_filter(argv[i], &filter);
+			i++;
+		}
+
+		print_bloom_filter(&filter);
+	}
+
 	return 0;
 }
\ No newline at end of file