Add documentation for BPF_MAP_TYPE_BLOOM_FILTER including
kernel BPF helper usage, userspace usage and examples.
Signed-off-by: Donald Hunter <donald.hunter@xxxxxxxxx>
---
Documentation/bpf/map_bloom_filter.rst | 158 +++++++++++++++++++++++++
1 file changed, 158 insertions(+)
create mode 100644 Documentation/bpf/map_bloom_filter.rst
diff --git a/Documentation/bpf/map_bloom_filter.rst b/Documentation/bpf/map_bloom_filter.rst
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+.. SPDX-License-Identifier: GPL-2.0-only
+.. Copyright (C) 2022 Red Hat, Inc.
+
+=========================
+BPF_MAP_TYPE_BLOOM_FILTER
+=========================
+
+.. note::
+ - ``BPF_MAP_TYPE_BLOOM_FILTER`` was introduced in kernel version 5.16
+
+``BPF_MAP_TYPE_BLOOM_FILTER`` provides a BPF bloom filter map. Bloom
+filters are a space-efficient probabilistic data structure used to
+quickly test whether an element exists in a set. In a bloom filter,
+false positives are possible whereas false negatives are not.
+
+The bloom filter map does not have keys, only values. When the bloom
+filter map is created, it must be created with a ``key_size`` of 0. The
+bloom filter map supports two operations:
+
+- push: adding an element to the map
+- peek: determining whether an element is present in the map
+
+BPF programs must use ``bpf_map_push_elem`` to add an element to the
+bloom filter map and ``bpf_map_peek_elem`` to query the map. These
+operations are exposed to userspace applications using the existing
+``bpf`` syscall in the following way:
+
+- ``BPF_MAP_UPDATE_ELEM`` -> push
+- ``BPF_MAP_LOOKUP_ELEM`` -> peek
+
+The ``max_entries`` size that is specified at map creation time is used
+to approximate a reasonable bitmap size for the bloom filter, and is not
+otherwise strictly enforced. If the user wishes to insert more entries
+into the bloom filter than ``max_entries``, this may lead to a higher
+false positive rate.
+
+The number of hashes to use for the bloom filter is configurable using
+the lower 4 bits of ``map_extra`` in ``union bpf_attr`` at map creation
+time. If no number is specified, the default used will be 5 hash
+functions. In general, using more hashes decreases both the false
+positive rate and the speed of a lookup.
+
+It is not possible to delete elements from a bloom filter map. A bloom
+filter map may be used as an inner map. The user is responsible for
+synchronising concurrent updates and lookups to ensure no false negative
+lookups occur.
+
+Usage
+=====
+
+Kernel BPF
+----------
+
+.. c:function::
+ long bpf_map_push_elem(struct bpf_map *map, const void *value, u64 flags)
+
+A ``value`` can be added to a bloom filter using the
+``bpf_map_push_elem()`` helper. The ``flags`` parameter must be set to
+``BPF_ANY`` when adding an entry to the bloom filter. This helper
+returns ``0`` on success, or negative error in case of failure.
+
+.. c:function::
+ long bpf_map_peek_elem(struct bpf_map *map, void *value)
+
+The ``bpf_map_peek_elem()`` helper is used to determine whether
+``value`` is present in the bloom filter map. This helper returns ``0``
+if ``value`` is probably present in the map, or ``-ENOENT`` if ``value``
+is definitely not present in the map.
+
+Userspace
+---------
+
+.. c:function::
+ int bpf_map_update_elem (int fd, const void *key, const void *value, __u64 flags)
+
+A userspace program can add a ``value`` to a bloom filter using libbpf's
+``bpf_map_update_elem`` function. The ``key`` parameter must be set to
+``NULL`` and ``flags`` must be set to ``BPF_ANY``. Returns ``0`` on
+success, or negative error in case of failure.
+
+.. c:function::
+ int bpf_map_lookup_elem (int fd, const void *key, void *value)
+
+A userspace program can determine the presence of ``value`` in a bloom
+filter using libbpf's ``bpf_map_lookup_elem`` function. The ``key``
+parameter must be set to ``NULL``. Returns ``0`` if ``value`` is
+probably present in the map, or ``-ENOENT`` if ``value`` is definitely
+not present in the map.
+
+Examples
+========
+
+Kernel BPF
+----------
+
+This snippet shows how to declare a bloom filter in a BPF program:
+
+.. code-block:: c
+
+ struct {
+ __uint(type, BPF_MAP_TYPE_BLOOM_FILTER);
+ __type(value, __u32);
+ __uint(max_entries, 1000);
+ __uint(map_extra, 3);
+ } bloom_filter SEC(".maps");
+
+This snippet shows how to determine presence of a value in a bloom
+filter in a BPF program:
+
+.. code-block:: c
+
+ void *lookup(__u32 key)
+ {
+ if (bpf_map_peek_elem(&bloom_filter, &key) == 0) {
+ /* Verify not a false positive and fetch an associated
+ * value using a secondary lookup, e.g. in a hash table
+ */
+ return bpf_map_lookup_elem(&hash_table, &key);
+ }
+ return 0;
+ }
+
+Userspace
+---------
+
+This snippet shows how to use libbpf to create a bloom filter map from
+userspace:
+
+.. code-block:: c
+
+ int create_bloom()
+ {
+ LIBBPF_OPTS(bpf_map_create_opts, opts,
+ .map_extra = 3); /* number of hashes */
+
+ return bpf_map_create(BPF_MAP_TYPE_BLOOM_FILTER,
+ "ipv6_bloom", /* name */
+ 0, /* key size, must be zero */
+ sizeof(ipv6_addr), /* value size */
+ 10000, /* max entries */
+ &opts); /* create options */
+ }
+
+This snippet shows how to add an element to a bloom filter from
+userspace:
+
+.. code-block:: c
+
+ int add_element(__u32 value)
+ {
+ return bpf_map_update_elem(bloom_fd, 0, &value, BPF_ANY);
+ }
+
+
+References
+==========
+
+https://lwn.net/ml/bpf/20210831225005.2762202-1-joannekoong@xxxxxx/
--
2.35.1
