Containers

SortedMap and SortedSet keep their keys in order, which is what iteration, scan and slice erase rest on. HashMap and HashSet are the same stores over an open-addressed core, and offer point access only:

cache = st.HashMap(key=str)
cache['a'] = 1
cache['a'], len(cache), 'a' in cache      # (1, 1, True)

cache.scan()                              # AttributeError — no ordering to scan
list(cache)                               # TypeError — not iterable

The absent methods are absent from the type rather than refused at the call, so reaching for one fails the way a typo fails. Everything else is shared — the same key layouts, the same isolation and sharing choices, the same transactions — so one st.transaction() may span ordered and unordered stores together.

Terminology first, since both words are overloaded:

• “Concurrency” does not imply threads. Several transactions can be open on one thread.
• “Consistency” does not imply strict serializability. Weaker levels exist, and each store here names the one it targets as a compile-time isolation_k rather than leaving you to infer it.

Headers group as:

  basic_*               → Cores. Own their memory, no transactions, one thread.
    ├─ basic_vector<T, Alloc>
    ├─ basic_avl_tree<T, Comparator, Alloc>
    ├─ basic_wb_tree<T, Comparator, Alloc>          # also `rank` and `select`
    ├─ basic_hash_table<T, Hash, Equals, Alloc>     # grows, iterates, rehashes
    ├─ basic_flat_set<T, Comparator, Kit, Alloc>    # sorted, one allocation, searched a row at a time
    ├─ basic_ring<T, Alloc>                         # first-in first-out, capacity fixed at `make`
    ├─ basic_hash_index<T, Index, Hash, Alloc, Kit> # keys to record positions, capacity fixed, no tombstones
    ├─ basic_fixed_pool<T, Index, Alloc>             # records taken and vacated by index, handles that go stale
    ├─ basic_growing_pool<T, Index, Alloc>     # the same in chunks that never move, read beside its growth
    └─ intrusive_list<Index>                        # first-in first-out through the records' own `next`

  Immutable, built once and never written
    ├─ immutable_b_tree<T, KeysPerRow, Kit, Alloc>     # keys on every level
    ├─ immutable_splus_tree<T, KeysPerRow, Kit, Alloc> # every key in the leaves, separators above
    ├─ immutable_elias_fano<T, Alloc>                  # non-decreasing integers in a few bits apiece
    └─ immutable_packed_array<T, Alloc>                # integers as distances from a base, one width each

  atomic_*              → Pinned core. Fixed capacity, atomic per slot, callback reads.
    └─ atomic_hash_table<T, Hash, Equals, Alloc>    # the one type that runs on a GPU
       ↑ ::adopt(std::move(growable).release())     ↓ ::adopt(std::move(pinned).release())

  atomic_intrusive_stack<T, Ref>  → any thread pushes, one takes all, no capacity

  *_store               → 2-phase commit, watch and CAS.
    ├─ monotonic_store<Core>                        # one visible version per key
    ├─ snapshot_store<Core>                         # every version a live reader can still name
    └─ reference_store<T, Comparator, Alloc>        # the same contract over `std::set`, kept as the oracle
       ↓ either of the first two wraps a core; either of these wraps a store
    ├─ locked_store<Store, Mutex>                   # one lock spans a whole commit
    └─ partitioned_store<Store, Hash, Mutex, N>     # one lock per partition, one shared commit order

  transaction_group<Stores...>  → One 2-phase commit spanning several stores

§ Choosing a Container for a Concurrency Shape

The Writers column of the table in What’s Inside names how many threads may write, and the reader rule follows from it rather than standing beside it: a core’s const methods are safe from any number of threads only while no thread is writing, since a probe reads slot metadata and node links a write is midway through changing. The shape that gets this wrong most often is a cache behind a mutable member, filled on what its caller calls a read — a reader-writer lock held in shared mode admits several such calls at once, and each of them is a writer as far as the container is concerned.

Growth is the other half of the rule. A core that can grow repoints the regions every live slot reference and every node pointer has already cached, so a container a second thread can reach must either be pinned at a capacity nobody exceeds, or reached through a wrapper that excludes. basic_growing_pool is the one core whose growth repoints nothing: it adds chunks and never moves a record, so readers by index or handle need no claim while its one writer takes, vacates and grows.

Both wrappers take their mutex as a template parameter, and that mutex takes two of its own: the reference its word is owned through, and the policy a waiting core follows. The pinned table takes the same two directly, since its slot lock is the mutex it has. A deployment that knows its hardware names both: a reference whose conditional add decides an acquire in one instruction, and a stall its cores actually have. One that does not pays nothing for the question.

Transactions and thread-safety are two independent axes, not one ladder. A wrapper takes its mutex per call, not across a transaction: stage and commit each take it and drop it in between, and only a group holds it from its validation to its publication. What carries the inner store’s level across that gap is the reservation staging made, since no other transaction can claim those keys until this one publishes or unwinds. A store in no order gives its reader no stamp to hold, so a monotonic reader spanning partitions can catch a commit half-applied and only Read Committed survives — but a snapshot reader answers at its own stamp, and every partition belongs to one order, so it keeps Snapshot across all sixteen. Every container publishes what it promises as isolation_k, so the level is checkable rather than folklore. atomic_hash_table has no transactions at all — it offers per-operation atomicity, which is a different product, and is why it is not a *_store.

status_t reports out_of_memory_heap_k == ENOMEM, invalid_argument_k == EINVAL, key_not_found_k == ENOENT and others, and is [[nodiscard]] on every mutating API.

§ Making std::set Transactional

smashtable/reference_store.hpp

The baseline reference design, and the yardstick the tree containers are held against — it runs the same test suites they do. Updates group into transactions that stage and roll back before committing, which is what lets inter-dependent updates span several stores.

Reads are consistent at the Monotonic Atomic View level, so a transaction never sees another’s partial update. That is weaker than Snapshot Isolation: there is no guarantee that every read within one transaction sees the same snapshot. It keeps a version per key all the same, dated by a generation rather than by a shared commit stamp, which is why a watch is re-resolved at commit instead of compared against one. snapshot_store is the sibling that does make that guarantee, and the section below states what it costs.

§ Adelson-Velsky and Landis Trees

smashtable/basic_avl_tree.hpp

Rarely called by its full name, the AVL tree is the simplest clean self-balancing binary search tree, from 1962. basic_avl_tree<value, comparator, allocator> is an ordered store in the shape of std::set or std::map. Standard libraries usually pick Red-Black trees; AVL balances more rigidly, trading slightly slower updates for faster lookups.

Its API differs from the STL where exception-free reporting demands it:

• insert() returns std::pair<iterator, bool>, as the STL does.
• erase(iterator) returns erase_result_t { iterator next; status_t status; }.
• Range insert(first, last) returns status_t.
• Hint-based insert(hint, value) and emplace_hint() are deleted, since AVL trees gain nothing from a hint.

§ Weight-Balanced Trees

smashtable/basic_wb_tree.hpp

basic_wb_tree balances on subtree sizes rather than heights, using Δ=3 and Γ=2 — the only proven integer solution, per Hirai and Yamamoto. Storing sizes buys order statistics: select(k) finds the k-th smallest and rank(x) finds a key’s position, both in O(log n). That is what pagination, percentiles and quantiles need, and it is the one thing the AVL tree cannot offer.

Expect depth around 1.88 log₂(n) against AVL’s 1.44, in exchange for O(1) amortized rotations per update.

§ Flat Sets & Rings

smashtable/basic_flat_set.hpp · smashtable/basic_ring.hpp

basic_flat_set is an ordered set in one contiguous allocation, growable and allocator-aware like basic_avl_tree, differing only in where elements live. Inserting and erasing shift the tail, so it suits a few hundred elements rather than millions, in exchange for a search that reads adjacent memory and allocates nothing. That search is the same row search the immutable trees below use, wherever the element is a row_searchable_key ordered by less_t, and a plain binary search otherwise — basic_flat_set takes the kit as its third template argument. It answers the same ordered_collection surface the trees do — bounds, ranges and half-open erasure — so the shared suites hold it to the same contract.

basic_ring is a first-in first-out queue over one allocation whose capacity is a power of two fixed at make, for batching and read-ahead. Two 32-bit counters of pushes and pops wrap together, so their difference is the size and a full ring is told from an empty one without a spare slot.

§ Immutable B & S+ Trees

smashtable/immutable_b_tree.hpp · smashtable/immutable_splus_tree.hpp · smashtable/row_layout.hpp · smashtable/row_search.hpp

Both are built once from a sorted span and never written again, so any number of threads may read one at once with no synchronization at all. Both search a row at a time rather than a key at a time — a row being a span wide enough to be worth one vectorized pass, 512 bytes by default, which is default_row_bytes_k. row_layout.hpp says what a key may be and where each one sits in a row; row_search.hpp says how a row is searched.

immutable_b_tree stores nodes breadth-first with implicit children: node i holds one row of B keys and its children are nodes i*(B+1)+j+1. A lookup reads one row per level and the rank adds up as the descent goes, with no subtree sizes stored.

immutable_splus_tree keeps every key in sorted leaves and copies separators onto the levels above. A lookup lands on the leaf whose position is the rank, so select is an index into the leaves.

Every kit the compiler can emit is compiled into the same artifact, each under its own target attributes, so no global instruction-set flag is needed. detect_row_kit() probes the processor once and visit_row_kit hands the answer over as a type, so a tree instantiated over it calls its kit with no table and no branch per key.

visit_row_kit(detect_row_kit(), [&](auto kit) {
    using tree_t = immutable_b_tree<std::uint64_t, 64, decltype(kit)>;
    // …built once, then read from any number of threads
});

Keys may be 32- or 64-bit of either signedness, or 16 bytes ordered as memcmp. A 16-byte key is stored either interleaved or split into a column of high words and a column of low words, the low column read only where a high word ties.

immutable_b_set and immutable_splus_set hold bare keys; immutable_b_map and immutable_splus_map pair each key with a value. A map keeps the rows byte-identical to its set twin and puts the values in one array the rank indexes, so every kit still loads a row of nothing but keys, and mapped_at(rank) costs one further cache line.

§ Elias-Fano Sequences

smashtable/immutable_elias_fano.hpp

immutable_elias_fano keeps non-decreasing integers - the offsets of variable-length rows, say - in at most 2 + ⌈log₂(universe / count)⌉ bits apiece, and select(i) reads the i-th one back in constant time. The low bits of every value are packed side by side and the high bits are stored in unary, with every 256th set bit’s position sampled, so a select jumps to a sample and counts a handful of words. make takes the values whole, or pulls them in order through a callback, so a column of offsets streams in from storage without ever sitting in memory at full width.

std::uint64_t const offsets[] = {0, 3, 3, 10, 42};
auto sequence = immutable_elias_fano<>::make(std::span<std::uint64_t const>(offsets));
std::uint64_t const row_bytes = sequence->select(3) - sequence->select(2); // 7

§ Packed Arrays

smashtable/immutable_packed_array.hpp

immutable_packed_array keeps unsigned integers between a base and a maximum as their distance from the base, in bit_width(maximum - base) bits apiece, and array[i] reads the i-th one back in constant time. Values that all equal the base cost no words at all, so a column of commit stamps coded against the oldest live snapshot is free once nobody reads below it. immutable_elias_fano keeps its low parts in one, based at zero. save writes a three-word header and the packed words, and immutable_packed_array_view reads them in place from borrowed bytes at any alignment, so a memory-mapped file is read without a copy.

std::uint64_t const stamps[] = {1000, 1003, 1001, 1007};
auto packed = immutable_packed_array<>::make(std::span<std::uint64_t const>(stamps)); // base 1000, 3 bits apiece
std::vector<std::byte> bytes(packed->saved_bytes());
_ = packed->save(bytes);
auto view = immutable_packed_array_view<>::make(bytes);
std::uint64_t const third = (*view)[2]; // 1001

§ Transactional Stores

smashtable/monotonic_store.hpp

monotonic_store<Core> adds two-phase commit, watches and CAS on top of any key-addressable core. monotonic_avl_set, monotonic_avl_map, monotonic_wb_set and monotonic_wb_map are the aliases you’ll name directly. monotonic_hash_set and monotonic_hash_map back the same store with the open-addressed table, which supplies no ordering, so bounds, ranges and order statistics are gated out of those instantiations at compile time.

Which version a reader sees is decided by one number, stamped when a transaction commits. A version that has not committed carries no stamp, so it is invisible to readers and cannot make anyone else’s validation fail — a transaction that stages and then rolls back costs its peers nothing. Two writers on one key are ordered by their stamps, and the later one wins. That is a lost update, which this level permits: Monotonic Atomic View constrains what a reader observes, not what two writers do to each other, and a level that is available under partition provably cannot prevent it. A writer that needs the first commit to win must watch() the key, or use a snapshot container, where the write set is validated whether you ask or not.

find never records what it read, here. A read set is memory, and a read that allocates is a read that can fail, so on this engine the recording variant is a different name:

_ = transaction.find(key, on_found, on_missing);             // answers, and records nothing
_ = transaction.find_and_watch(key, on_found, on_missing);   // records, and can report out of memory

Both return status_t, because a read that cannot write down what it read has to say so where it happened rather than poisoning the transaction silently until commit. snapshot_store at serializable_k and above needs no second name: every read records, and every read reports.

An erase leaves a tombstone that readers skip, and vacuum() is what returns that space:

expected<std::size_t> const reclaimed = store.vacuum();          // everything no reader can name
expected<std::size_t> const window = store.vacuum(lower, upper); // ordered cores, one slice at a time

§ Snapshot Isolation

smashtable/snapshot_store.hpp

snapshot_store<Core> is the sibling that fixes a transaction’s reads to one instant, and it is where multi-version concurrency control is at its most literal here: a transaction draws a snapshot when it opens, every read is answered from the newest version at or below that snapshot, and a writer never overwrites what a reader can still name. It rebinds the same cores, exports snapshot_avl_set, _avl_map, _wb_set, _wb_map, _hash_set and _hash_map, and publishes isolation_k == snapshot_k. A repeated read returns what it first saw, a repeated range admits no phantoms, and neither holds in its sibling.

The same template answers at three levels, selected by a second parameter rather than by a second implementation, and each has aliases of its own:

snapshot_store<Core>                        // isolation_k == snapshot_k
serializable_store<Core>                    // reads validated too
strict_serializable_store<Core>             // and a commit waits for its own publication

serializable_avl_map<Key, Value>            // and `_avl_set`, `_wb_*`, `_hash_*`
strict_serializable_avl_map<Key, Value>     // the same six for the top rung

Versions are kept as ordinary entries keyed by (key, generation) rather than chained off one entry, on ordered and unordered cores alike. The hash core still hashes the bare key, so every version of a key shares one probe run and a lookup walks that run instead of stopping at the first match.

Reclamation is the other half of multi-version concurrency control, and the whole of it here: old versions are freed against a low-water mark that sits at the oldest open snapshot, so it can never pass a snapshot somebody still holds, and it advances as soon as the oldest reader leaves rather than waiting for the last. Pruning happens on every commit, and vacuum() reaches the keys nobody writes again. There is no background thread and no epoch registry. clear() refuses while a reader is open rather than dropping versions out from under it.

Range writes publish under one stamp, so a reader on an older snapshot sees all of a range erase or none of it. update_range builds new versions rather than rewriting the visible one, which is what open readers make unsound. select and rank descend on the weight-balanced tree’s augmented count, exact at the newest commit — a reader at an older snapshot gets the merged walk instead, because one number per node cannot answer for an unbounded parameter.

What it costs, on an AVL core over mapping<key, int>:

At rest it is the cheaper of the two, because a key carries no chain-head pointer and no per-entry allocator. It becomes the more expensive one exactly when a long-lived reader pins history — and on the hash core a pinned version occupies a real slot, so it lengthens the probe runs of its neighbours as well. With no transaction open the low-water mark sits at the newest commit and the whole version tail is freed on the next write, so a store nobody is reading costs what its sibling costs.

§ Hash Tables

smashtable/basic_hash_table.hpp

hash_set<key> and hash_map<key, value> are open-addressing containers with linear probing. They differ from google::dense_hash_map and tsl::robin_map by not reserving sentinel key values for tombstones, by unpacking keys and values into disjoint arrays, and by carrying two bits of metadata per slot rather than a byte.

Keys and values live in separate regions, so a lookup that only compares keys never pulls values into cache — which is most of them, since a miss touches no value at all. Thirty-two slots share one 64-bit header holding two parallel bitmasks, encoding free, deleted, populated and locked in two bits each. Sixty-four bits is the widest atomic every target supports, which is what lets a whole bucket header move in one instruction.

Growing repoints the key, value and header regions that every live slot reference has cached, so a table that can grow can never be read concurrently. The type system enforces that rather than a sentence: two types, neither of which includes the other’s header. basic_hash_table grows, iterates and rehashes; atomic_hash_table is pinned and atomic over the slot each operation touches. What passes between them is the allocation itself — a hash_storage — so the hand-off is a move of a value rather than one table reaching into the other:

_ = growable.reserve(1u << 20);                                          // pin the capacity first
auto pinned = atomic_hash_map<key_t, value_t>::adopt(std::move(growable).release());

_ = pinned.find(key, [](auto const &slot) noexcept { use(slot.value()); });
if (failed(pinned.emplace(key, value))) report_full();                   // a pinned table can fill up

auto compacted = hash_map<key_t, value_t>::adopt(std::move(pinned).release());   // iterators return

Every operation on the pinned table is atomic over the slot it touches: it takes that slot by setting both its bits with a fetch_or and releases it by posting the xor of the difference to the desired state, which reads nothing back, so neither path needs a compare-and-swap loop. It is not lock-free, though — fetch_or spins until it wins the slot, so a thread descheduled while holding one blocks every other prober that walks onto it. No global lock and no reallocation is what the pinning buys; a stalled thread stalling its neighbours is what it does not. Reads take a callback rather than returning a reference or an iterator, since both would dangle the moment another thread erased the slot. Tombstones only accumulate while pinned, because compaction needs a rehash — deleted_count() is what says it is time to hand the storage back.

Readers take the slot lock like writers do. A reader that merely loaded the header would be unsound, and measurably so: the two bits per slot cannot distinguish “untouched” from “locked, rewritten and unlocked”, because a completed write cycle restores exactly the bits the reader first saw. Adding a per-bucket version counter would fix it and would cost half the slots per bucket, which is not worth breaking the one-warp-per-bucket geometry for.

Order-dependent operations are absent by construction: there is no range, erase_range, lower_bound or select.

smashtable/basic_hash_index.hpp

basic_hash_index is the same layout serving another job: a fixed-capacity map from 4-, 8- or 16-byte keys to the positions of records kept elsewhere, such as a fixed pool’s. Its keys sit in the keys region, so a probe compares a window of them without loading a record, and a key may repeat, since it is often a hash of something longer: find takes a check that reads the record behind each match, and erase names the exact position. A tombstone would make every later probe walk past the erased slot until a rehash, which a fixed-capacity index never runs, so an erase shifts the rest of its run back over the hole instead. Every key stays reachable from its home, the deletion bits stay zero, and capacity is at most half the slots, so a run always ends at a free one and a table under constant churn probes no further than a fresh one.