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Transactions
RocksDB supports Transactions when using a (Pessimistic)TransactionDB
or OptimisticTransactionDB
. Transactions have a simple BEGIN/COMMIT/ROLLBACK API and allows applications to modify their data concurrently while letting RocksDB handle the conflict checking. RocksDB supports both pessimistic and optimistic concurrency control.
Note that RocksDB provides Atomicity by default when writing multiple keys via WriteBatch
. Transactions provide a way to guarantee that a batch of writes will only be written if there are no conflicts. Similar to a WriteBatch
, no other threads can see the changes in a transaction until it has been written (committed).
When using a TransactionDB
, all keys that are written are locked internally by RocksDB to perform conflict detection. If a key cannot be locked, the operation will return an error. When the transaction is committed, it is guaranteed to succeed as long as the database is able to be written to.
A TransactionDB
can be better for workloads with heavy concurrency compared to an OptimisticTransactionDB
. However, there is a small locking overhead when TransactionDB
is used. A TransactionDB
will do conflict checking for all write operations (Put
, Delete
and Merge
), including writes performed outside a Transaction.
Locking timeouts and limits can be tuned in the TransactionDBOptions
.
TransactionDB* txn_db;
Status s = TransactionDB::Open(options, path, &txn_db);
Transaction* txn = txn_db->BeginTransaction(write_options, txn_options);
s = txn->Put(“key”, “value”);
s = txn->Delete(“key2”);
s = txn->Merge(“key3”, “value”);
s = txn->Commit();
delete txn;
The default write policy is WriteCommitted
. The alternatives are WritePrepared
and WriteUnprepared
. Read more about them here.
Optimistic Transactions provide light-weight optimistic concurrency control for workloads that do not expect high contention/interference between multiple transactions.
Optimistic Transactions do not take any locks when preparing writes. Instead, they rely on doing conflict-detection at commit time to validate that no other writers have modified the keys being written by the current transaction. If there is a conflict with another write (or it cannot be determined), the commit will return an error and no keys will be written.
Optimistic concurrency control is useful for many workloads that need to protect against occasional write conflicts. However, this may not be a good solution for workloads where write-conflicts occur frequently due to many transactions constantly attempting to update the same keys. For these workloads, using a TransactionDB
may be a better fit. An OptimisticTransactionDB
may be more performant than a TransactionDB
for workloads that have many non-transactional writes and few transactions.
DB* db;
OptimisticTransactionDB* txn_db;
Status s = OptimisticTransactionDB::Open(options, path, &txn_db);
db = txn_db->GetBaseDB();
OptimisticTransaction* txn = txn_db->BeginTransaction(write_options, txn_options);
txn->Put(“key”, “value”);
txn->Delete(“key2”);
txn->Merge(“key3”, “value”);
s = txn->Commit();
delete txn;
Transactions also support easily reading the state of keys that are currently batched in a given transaction but not yet committed:
db->Put(write_options, “a”, “old”);
db->Put(write_options, “b”, “old”);
txn->Put(“a”, “new”);
vector<string> values;
vector<Status> results = txn->MultiGet(read_options, {“a”, “b”}, &values);
// The value returned for key “a” will be “new” since it was written by this transaction.
// The value returned for key “b” will be “old” since it is unchanged in this transaction.
You can also iterate through keys that exist in both the db and the current transaction by using Transaction::GetIterator()
.
Call GetForUpdate() to read a key and make the read value a precondition for transaction commit.
// Start a transaction
txn = txn_db->BeginTransaction(write_options);
// Read key1 in this transaction
Status s = txn->GetForUpdate(read_options, “key1”, &value);
// Write to key1 OUTSIDE of the transaction
s = db->Put(write_options, “key1”, “value0”);
If this transaction was created by a TransactionDB
, the Put
would either timeout or block until the transaction commits or aborts. If this transaction were created by an OptimisticTransactionDB
, then the Put
would succeed, but the transaction would fail when txn->Commit()
is called.
// Repeat the previous example but just do a Get() instead of a GetForUpdate()
txn = txn_db->BeginTransaction(write_options);
// Read key1 in this transaction
Status s = txn->Get(read_options, “key1”, &value);
// Write to key1 OUTSIDE of the transaction
s = db->Put(write_options, “key1”, “value0”);
// No conflict since transactions only do conflict checking for keys read using GetForUpdate().
s = txn->Commit();
Currently, GetForUpdate()
is the only way to establish Read-Write conflicts, so it can be used in combination with iterators, for example.
By default, Transaction conflict checking validates that no one else has written a key after the time the key was first written in this transaction. This isolation guarantee is sufficient for many use-cases. However, you may want to guarantee that no else has written a key since the start of the transaction. This can be accomplished by calling SetSnapshot()
after creating the transaction.
Default behavior:
// Create a txn using either a TransactionDB or OptimisticTransactionDB
txn = txn_db->BeginTransaction(write_options);
// Write to key1 OUTSIDE of the transaction
db->Put(write_options, “key1”, “value0”);
// Write to key1 IN transaction
s = txn->Put(“key1”, “value1”);
s = txn->Commit();
// There is no conflict since the write to key1 outside of the transaction
// happened before it was written in this transaction.
Using SetSnapshot()
:
txn = txn_db->BeginTransaction(write_options);
txn->SetSnapshot();
// Write to key1 OUTSIDE of the transaction
db->Put(write_options, “key1”, “value0”);
// Write to key1 IN transaction
s = txn->Put(“key1”, “value1”);
s = txn->Commit();
// Transaction will NOT commit since key1 was written outside of this transaction
// after SetSnapshot() was called (even though this write
// occurred before this key was written in this transaction).
Note that in the SetSnapshot()
case of the previous example, if this were a TransactionDB
, the Put()
would have failed. If this were an OptimisticTransactionDB
, the Commit()
would fail.
Similar to normal RocksDB reads, you can achieve repeatable reads when reading through a transaction by specifying a Snapshot
in the ReadOptions
.
read_options.snapshot = db->GetSnapshot();
s = txn->GetForUpdate(read_options, “key1”, &value);
…
s = txn->GetForUpdate(read_options, “key1”, &value);
db->ReleaseSnapshot(read_options.snapshot);
Note that Setting a Snapshot
in the ReadOptions
only affects the version of the data that is read. This does not have any affect on whether the transaction will be able to be committed.
If you have called SetSnapshot()
, you can read using the same snapshot that was set in the transaction:
read_options.snapshot = txn->GetSnapshot();
Status s = txn->GetForUpdate(read_options, “key1”, &value);
Internally, Transactions need to keep track of which keys have been written recently. The existing in-memory write buffers are re-used for this purpose. Transactions will still obey the existing max_write_buffer_number
option when deciding how many write buffers to keep in memory. In addition, using transactions will not affect flushes or compactions.
It is possible that switching to using a [Optimistic]TransactionDB
will use more memory than was used previously. If you have set a very large value for max_write_buffer_number
, a typical RocksDB instance will could never come close to this maximum memory limit. However, an [Optimistic]TransactionDB
will try to use as many write buffers as allowed. But, this can be tuned by either reducing max_write_buffer_number
or by setting max_write_buffer_size_to_maintain
. See memtable for more details about max_write_buffer_size_to_maintain
.
OptimisticTransactionDBs:
At commit time, optimistic transactions will use the in-memory write buffers for conflict detection. For this to be successful, the data buffered must be older than the changes in the transaction. If not, Commit will fail. To decrease the likelihood of Commit
failures due to insufficient buffer history, increase max_write_buffer_size_to_maintain
.
TransactionDBs:
If SetSnapshot()
is used, Put/Delete/Merge/GetForUpdate
operations will first check the in-memory buffers to do conflict detection. If there isn’t sufficient data history in the in-memory buffers, the SST files will then be checked. Increasing max_write_buffer_size_to_maintain
will reduce the chance that SST files must be read during conflict detection.
In addition to Rollback()
, Transactions can also be partially rolled back if SavePoints
are used.
s = txn->Put("A", "a");
txn->SetSavePoint();
s = txn->Put("B", "b");
txn->RollbackToSavePoint()
s = txn->Commit()
// Since RollbackToSavePoint() was called, this transaction will
// only write key A and not write key B.
A high-level, succinct overview of how transactions work under the hood.
Each update in RocksDB is done by inserting an entry tagged with a monotonically increasing sequence number. Assigning a seq to read_options.snapshot
will be used by (transactional or non-transactional) DB to read only values with seq smaller than that, i.e., read snapshots → DBImpl::GetImpl
That aside, transactions can call TransactionBaseImpl::SetSnapshot
which will invoke DBImpl::GetSnapshot
. It achieves two goals:
- Return the current seq: transactions will use the seq (instead of the seq of its written value) to check for write-write conflicts →
TransactionImpl::TryLock
→TransactionImpl::ValidateSnapshot
→TransactionUtil::CheckKeyForConflicts
- Makes sure that values with smaller seq will not be erased by compaction jobs, etc. (snapshots_.GetAll). Such marked snapshots must be released by the callee (
DBImpl::ReleaseSnapshot
)
Read-Write conflicts can be prevented by escalating them to write-write conflict: doing reads via GetForUpdate
(instead of Get
).
Write-write conflicts are detected at the write time using a lock table.
Non-transactional updates (Put
, Merge
and Delete
) are internally run under a transaction. So, every update is through transactions → TransactionDBImpl::Put
Every update acquires a lock beforehand → TransactionImpl::TryLock
TransactionLockMgr::TryLock
has only 16 locks per column family → size_t num_stripes = 16
Commit simply writes the write batch to WAL as well as to Memtable by calling DBImpl::Write
→ TransactionImpl::Commit
To support distributed transactions, the clients can call Prepare after performing the writes. It writes the value to WAL but not to the MemTable, which allows recovery in the case of machine crash → TransactionImpl::Prepare
If Prepare
is invoked, Commit
writes a commit marker to the WAL and writes values to MemTable. This is done by calling MarkWalTerminationPoint()
before adding value to the write batch.
Write-write conflicts are detected using seq of the latest values at the commit time.
Each update adds the key to an in-memory vector → TransactionDBImpl::Put
and OptimisticTransactionImpl::TryLock
Commit links OptimisticTransactionImpl::CheckTransactionForConflicts
as a callback to the write batch → OptimisticTransactionImpl::Commit
which will be invoked in DBImpl::WriteImpl
via write->CheckCallback
The conflict detection logic is implemented at TransactionUtil::CheckKeysForConflicts
- only checks for conflicts against keys present in memory and fails otherwise.
- conflict detection is done by checking the latest seq of each key (
DBImpl::GetLatestSequenceForKey
) against the seq used for writing it.
Contents
- RocksDB Wiki
- Overview
- RocksDB FAQ
- Terminology
- Requirements
- Contributors' Guide
- Release Methodology
- RocksDB Users and Use Cases
- RocksDB Public Communication and Information Channels
-
Basic Operations
- Iterator
- Prefix seek
- SeekForPrev
- Tailing Iterator
- Compaction Filter
- Multi Column Family Iterator (Experimental)
- Read-Modify-Write (Merge) Operator
- Column Families
- Creating and Ingesting SST files
- Single Delete
- Low Priority Write
- Time to Live (TTL) Support
- Transactions
- Snapshot
- DeleteRange
- Atomic flush
- Read-only and Secondary instances
- Approximate Size
- User-defined Timestamp
- Wide Columns
- BlobDB
- Online Verification
- Options
- MemTable
- Journal
- Cache
- Write Buffer Manager
- Compaction
- SST File Formats
- IO
- Compression
- Full File Checksum and Checksum Handoff
- Background Error Handling
- Huge Page TLB Support
- Tiered Storage (Experimental)
- Logging and Monitoring
- Known Issues
- Troubleshooting Guide
- Tests
- Tools / Utilities
-
Implementation Details
- Delete Stale Files
- Partitioned Index/Filters
- WritePrepared-Transactions
- WriteUnprepared-Transactions
- How we keep track of live SST files
- How we index SST
- Merge Operator Implementation
- RocksDB Repairer
- Write Batch With Index
- Two Phase Commit
- Iterator's Implementation
- Simulation Cache
- [To Be Deprecated] Persistent Read Cache
- DeleteRange Implementation
- unordered_write
- Extending RocksDB
- RocksJava
- Lua
- Performance
- Projects Being Developed
- Misc