+ *
+ * What?
+ * =====
+ *
+ * A flow classifier holds any number of "rules", each of which specifies
+ * values to match for some fields or subfields and a priority. Each OpenFlow
+ * table is implemented as a flow classifier.
+ *
+ * The classifier has two primary design goals. The first is obvious: given a
+ * set of packet headers, as quickly as possible find the highest-priority rule
+ * that matches those headers. The following section describes the second
+ * goal.
+ *
+ *
+ * "Un-wildcarding"
+ * ================
+ *
+ * A primary goal of the flow classifier is to produce, as a side effect of a
+ * packet lookup, a wildcard mask that indicates which bits of the packet
+ * headers were essential to the classification result. Ideally, a 1-bit in
+ * any position of this mask means that, if the corresponding bit in the packet
+ * header were flipped, then the classification result might change. A 0-bit
+ * means that changing the packet header bit would have no effect. Thus, the
+ * wildcarded bits are the ones that played no role in the classification
+ * decision.
+ *
+ * Such a wildcard mask is useful with datapaths that support installing flows
+ * that wildcard fields or subfields. If an OpenFlow lookup for a TCP flow
+ * does not actually look at the TCP source or destination ports, for example,
+ * then the switch may install into the datapath a flow that wildcards the port
+ * numbers, which in turn allows the datapath to handle packets that arrive for
+ * other TCP source or destination ports without additional help from
+ * ovs-vswitchd. This is useful for the Open vSwitch software and,
+ * potentially, for ASIC-based switches as well.
+ *
+ * Some properties of the wildcard mask:
+ *
+ * - "False 1-bits" are acceptable, that is, setting a bit in the wildcard
+ * mask to 1 will never cause a packet to be forwarded the wrong way.
+ * As a corollary, a wildcard mask composed of all 1-bits will always
+ * yield correct (but often needlessly inefficient) behavior.
+ *
+ * - "False 0-bits" can cause problems, so they must be avoided. In the
+ * extreme case, a mask of all 0-bits is only correct if the classifier
+ * contains only a single flow that matches all packets.
+ *
+ * - 0-bits are desirable because they allow the datapath to act more
+ * autonomously, relying less on ovs-vswitchd to process flow setups,
+ * thereby improving performance.
+ *
+ * - We don't know a good way to generate wildcard masks with the maximum
+ * (correct) number of 0-bits. We use various approximations, described
+ * in later sections.
+ *
+ * - Wildcard masks for lookups in a given classifier yield a
+ * non-overlapping set of rules. More specifically:
+ *
+ * Consider an classifier C1 filled with an arbitrary collection of rules
+ * and an empty classifier C2. Now take a set of packet headers H and
+ * look it up in C1, yielding a highest-priority matching rule R1 and
+ * wildcard mask M. Form a new classifier rule R2 out of packet headers
+ * H and mask M, and add R2 to C2 with a fixed priority. If one were to
+ * do this for every possible set of packet headers H, then this
+ * process would not attempt to add any overlapping rules to C2, that is,
+ * any packet lookup using the rules generated by this process matches at
+ * most one rule in C2.
+ *
+ * During the lookup process, the classifier starts out with a wildcard mask
+ * that is all 0-bits, that is, fully wildcarded. As lookup proceeds, each
+ * step tends to add constraints to the wildcard mask, that is, change
+ * wildcarded 0-bits into exact-match 1-bits. We call this "un-wildcarding".
+ * A lookup step that examines a particular field must un-wildcard that field.
+ * In general, un-wildcarding is necessary for correctness but undesirable for
+ * performance.
+ *
+ *
+ * Basic Classifier Design
+ * =======================
+ *
+ * Suppose that all the rules in a classifier had the same form. For example,
+ * suppose that they all matched on the source and destination Ethernet address
+ * and wildcarded all the other fields. Then the obvious way to implement a
+ * classifier would be a hash table on the source and destination Ethernet
+ * addresses. If new classification rules came along with a different form,
+ * you could add a second hash table that hashed on the fields matched in those
+ * rules. With two hash tables, you look up a given flow in each hash table.
+ * If there are no matches, the classifier didn't contain a match; if you find
+ * a match in one of them, that's the result; if you find a match in both of
+ * them, then the result is the rule with the higher priority.
+ *
+ * This is how the classifier works. In a "struct classifier", each form of
+ * "struct cls_rule" present (based on its ->match.mask) goes into a separate
+ * "struct cls_subtable". A lookup does a hash lookup in every "struct
+ * cls_subtable" in the classifier and tracks the highest-priority match that
+ * it finds. The subtables are kept in a descending priority order according
+ * to the highest priority rule in each subtable, which allows lookup to skip
+ * over subtables that can't possibly have a higher-priority match than already
+ * found. Eliminating lookups through priority ordering aids both classifier
+ * primary design goals: skipping lookups saves time and avoids un-wildcarding
+ * fields that those lookups would have examined.
+ *
+ * One detail: a classifier can contain multiple rules that are identical other
+ * than their priority. When this happens, only the highest priority rule out
+ * of a group of otherwise identical rules is stored directly in the "struct
+ * cls_subtable", with the other almost-identical rules chained off a linked
+ * list inside that highest-priority rule.
+ *
+ *
+ * Staged Lookup (Wildcard Optimization)
+ * =====================================
+ *
+ * Subtable lookup is performed in ranges defined for struct flow, starting
+ * from metadata (registers, in_port, etc.), then L2 header, L3, and finally
+ * L4 ports. Whenever it is found that there are no matches in the current
+ * subtable, the rest of the subtable can be skipped.
+ *
+ * Staged lookup does not reduce lookup time, and it may increase it, because
+ * it changes a single hash table lookup into multiple hash table lookups.
+ * It reduces un-wildcarding significantly in important use cases.
+ *
+ *
+ * Prefix Tracking (Wildcard Optimization)
+ * =======================================
+ *
+ * Classifier uses prefix trees ("tries") for tracking the used
+ * address space, enabling skipping classifier tables containing
+ * longer masks than necessary for the given address. This reduces
+ * un-wildcarding for datapath flows in parts of the address space
+ * without host routes, but consulting extra data structures (the
+ * tries) may slightly increase lookup time.
+ *
+ * Trie lookup is interwoven with staged lookup, so that a trie is
+ * searched only when the configured trie field becomes relevant for
+ * the lookup. The trie lookup results are retained so that each trie
+ * is checked at most once for each classifier lookup.
+ *
+ * This implementation tracks the number of rules at each address
+ * prefix for the whole classifier. More aggressive table skipping
+ * would be possible by maintaining lists of tables that have prefixes
+ * at the lengths encountered on tree traversal, or by maintaining
+ * separate tries for subsets of rules separated by metadata fields.
+ *
+ * Prefix tracking is configured via OVSDB "Flow_Table" table,
+ * "fieldspec" column. "fieldspec" is a string map where a "prefix"
+ * key tells which fields should be used for prefix tracking. The
+ * value of the "prefix" key is a comma separated list of field names.
+ *
+ * There is a maximum number of fields that can be enabled for any one
+ * flow table. Currently this limit is 3.
+ *
+ *
+ * Partitioning (Lookup Time and Wildcard Optimization)
+ * ====================================================
+ *
+ * Suppose that a given classifier is being used to handle multiple stages in a
+ * pipeline using "resubmit", with metadata (that is, the OpenFlow 1.1+ field
+ * named "metadata") distinguishing between the different stages. For example,
+ * metadata value 1 might identify ingress rules, metadata value 2 might
+ * identify ACLs, and metadata value 3 might identify egress rules. Such a
+ * classifier is essentially partitioned into multiple sub-classifiers on the
+ * basis of the metadata value.
+ *
+ * The classifier has a special optimization to speed up matching in this
+ * scenario:
+ *
+ * - Each cls_subtable that matches on metadata gets a tag derived from the
+ * subtable's mask, so that it is likely that each subtable has a unique
+ * tag. (Duplicate tags have a performance cost but do not affect
+ * correctness.)
+ *
+ * - For each metadata value matched by any cls_rule, the classifier
+ * constructs a "struct cls_partition" indexed by the metadata value.
+ * The cls_partition has a 'tags' member whose value is the bitwise-OR of
+ * the tags of each cls_subtable that contains any rule that matches on
+ * the cls_partition's metadata value. In other words, struct
+ * cls_partition associates metadata values with subtables that need to
+ * be checked with flows with that specific metadata value.
+ *
+ * Thus, a flow lookup can start by looking up the partition associated with
+ * the flow's metadata, and then skip over any cls_subtable whose 'tag' does
+ * not intersect the partition's 'tags'. (The flow must also be looked up in
+ * any cls_subtable that doesn't match on metadata. We handle that by giving
+ * any such cls_subtable TAG_ALL as its 'tags' so that it matches any tag.)
+ *
+ * Partitioning saves lookup time by reducing the number of subtable lookups.
+ * Each eliminated subtable lookup also reduces the amount of un-wildcarding.
+ *
+ *
+ * Thread-safety
+ * =============
+ *
+ * The classifier may safely be accessed by many reader threads concurrently or
+ * by a single writer. */