WATCH are the foundation of
transactions in Redis. They allow the execution of a group of commands
in a single step, with two important guarantees:
All the commands in a transaction are serialized and executed sequentially. It can never happen that a request issued by another client is served in the middle of the execution of a Redis transaction. This guarantees that the commands are executed as a single isolated operation.
Either all of the commands or none are processed, so a Redis transaction is also atomic. The
EXECcommand triggers the execution of all the commands in the transaction, so if a client loses the connection to the server in the context of a transaction before calling the
MULTIcommand none of the operations are performed, instead if the
EXECcommand is called, all the operations are performed. When using the append-only file Redis makes sure to use a single write(2) syscall to write the transaction on disk. However if the Redis server crashes or is killed by the system administrator in some hard way it is possible that only a partial number of operations are registered. Redis will detect this condition at restart, and will exit with an error. Using the
redis-check-aoftool it is possible to fix the append only file that will remove the partial transaction so that the server can start again.
Starting with version 2.2, Redis allows for an extra guarantee to the above two, in the form of optimistic locking in a way very similar to a check-and-set (CAS) operation. This is documented later on this page.
A Redis transaction is entered using the
MULTI command. The command
always replies with
OK. At this point the user can issue multiple
commands. Instead of executing these commands, Redis will queue
them. All the commands are executed once
EXEC is called.
DISCARD instead will flush the transaction queue and will exit
The following example increments keys
> MULTI OK > INCR foo QUEUED > INCR bar QUEUED > EXEC 1) (integer) 1 2) (integer) 1
As it is possible to see from the session above,
EXEC returns an
array of replies, where every element is the reply of a single command
in the transaction, in the same order the commands were issued.
When a Redis connection is in the context of a
all commands will reply with the string
QUEUED (sent as a Status Reply
from the point of view of the Redis protocol). A queued command is
simply scheduled for execution when
EXEC is called.
Errors inside a transaction
During a transaction it is possible to encounter two kind of command errors:
- A command may fail to be queued, so there may be an error before
EXECis called. For instance the command may be syntactically wrong (wrong number of arguments, wrong command name, ...), or there may be some critical condition like an out of memory condition (if the server is configured to have a memory limit using the
- A command may fail after
EXECis called, for instance since we performed an operation against a key with the wrong value (like calling a list operation against a string value).
Clients used to sense the first kind of errors, happening before the
EXEC call, by checking the return value of the queued command: if the command replies with QUEUED it was queued correctly, otherwise Redis returns an error. If there is an error while queueing a command, most clients will abort the transaction discarding it.
However starting with Redis 2.6.5, the server will remember that there was an error during the accumulation of commands, and will refuse to execute the transaction returning also an error during
EXEC, and discarding the transaction automatically.
Before Redis 2.6.5 the behavior was to execute the transaction with just the subset of commands queued successfully in case the client called
EXEC regardless of previous errors. The new behavior makes it much more simple to mix transactions with pipelining, so that the whole transaction can be sent at once, reading all the replies later at once.
Errors happening after
EXEC instead are not handled in a special way: all the other commands will be executed even if some command fails during the transaction.
This is more clear on the protocol level. In the following example one command will fail when executed even if the syntax is right:
Trying 127.0.0.1... Connected to localhost. Escape character is '^]'. MULTI +OK SET a 3 abc +QUEUED LPOP a +QUEUED EXEC *2 +OK -ERR Operation against a key holding the wrong kind of value
EXEC returned two-element @bulk-string-reply where one is an
OK code and
the other an
-ERR reply. It's up to the client library to find a
sensible way to provide the error to the user.
It's important to note that even when a command fails, all the other commands in the queue are processed – Redis will not stop the processing of commands.
Another example, again using the wire protocol with
telnet, shows how
syntax errors are reported ASAP instead:
MULTI +OK INCR a b c -ERR wrong number of arguments for 'incr' command
This time due to the syntax error the bad
INCR command is not queued
Why Redis does not support roll backs?
If you have a relational databases background, the fact that Redis commands can fail during a transaction, but still Redis will execute the rest of the transaction instead of rolling back, may look odd to you.
However there are good opinions for this behavior:
- Redis commands can fail only if called with a wrong syntax (and the problem is not detectable during the command queueing), or against keys holding the wrong data type: this means that in practical terms a failing command is the result of a programming errors, and a kind of error that is very likely to be detected during development, and not in production.
- Redis is internally simplified and faster because it does not need the ability to roll back.
An argument against Redis point of view is that bugs happen, however it should be noted that in general the roll back does not save you from programming errors. For instance if a query increments a key by 2 instead of 1, or increments the wrong key, there is no way for a rollback mechanism to help. Given that no one can save the programmer from his or her errors, and that the kind of errors required for a Redis command to fail are unlikely to enter in production, we selected the simpler and faster approach of not supporting roll backs on errors.
Discarding the command queue
DISCARD can be used in order to abort a transaction. In this case, no
commands are executed and the state of the connection is restored to
> SET foo 1 OK > MULTI OK > INCR foo QUEUED > DISCARD OK > GET foo "1"
Optimistic locking using check-and-set
WATCH is used to provide a check-and-set (CAS) behavior to Redis
WATCHed keys are monitored in order to detect changes against them. If
at least one watched key is modified before the
EXEC command, the
whole transaction aborts, and
EXEC returns a @nil-reply to notify that
the transaction failed.
For example, imagine we have the need to atomically increment the value
of a key by 1 (let's suppose Redis doesn't have
The first try may be the following:
val = GET mykey val = val + 1 SET mykey $val
This will work reliably only if we have a single client performing the
operation in a given time. If multiple clients try to increment the key
at about the same time there will be a race condition. For instance,
client A and B will read the old value, for instance, 10. The value will
be incremented to 11 by both the clients, and finally
SET as the value
of the key. So the final value will be 11 instead of 12.
WATCH we are able to model the problem very well:
WATCH mykey val = GET mykey val = val + 1 MULTI SET mykey $val EXEC
Using the above code, if there are race conditions and another client
modifies the result of
val in the time between our call to
our call to
EXEC, the transaction will fail.
We just have to repeat the operation hoping this time we'll not get a new race. This form of locking is called optimistic locking and is a very powerful form of locking. In many use cases, multiple clients will be accessing different keys, so collisions are unlikely – usually there's no need to repeat the operation.
So what is
WATCH really about? It is a command that will
EXEC conditional: we are asking Redis to perform
the transaction only if none of the
WATCHed keys were modified.
(But they might be changed by the same client inside the transaction
without aborting it. More on this.)
Otherwise the transaction is not entered at
all. (Note that if you
WATCH a volatile key and Redis expires
the key after you
EXEC will still work. More on
WATCH can be called multiple times. Simply all the
WATCH calls will
have the effects to watch for changes starting from the call, up to
EXEC is called. You can also send any number of keys to a
EXEC is called, all keys are
UNWATCHed, regardless of whether
the transaction was aborted or not. Also when a client connection is
closed, everything gets
It is also possible to use the
UNWATCH command (without arguments)
in order to flush all the watched keys. Sometimes this is useful as we
optimistically lock a few keys, since possibly we need to perform a
transaction to alter those keys, but after reading the current content
of the keys we don't want to proceed. When this happens we just call
UNWATCH so that the connection can already be used freely for new
WATCH to implement ZPOP
A good example to illustrate how
WATCH can be used to create new
atomic operations otherwise not supported by Redis is to implement ZPOP,
that is a command that pops the element with the lower score from a
sorted set in an atomic way. This is the simplest implementation:
WATCH zset element = ZRANGE zset 0 0 MULTI ZREM zset element EXEC
EXEC fails (i.e. returns a @nil-reply) we just repeat the operation.
Redis scripting and transactions
A Redis script is transactional by definition, so everything you can do with a Redis transaction, you can also do with a script, and usually the script will be both simpler and faster.
This duplication is due to the fact that scripting was introduced in Redis 2.6 while transactions already existed long before. However we are unlikely to remove the support for transactions in the short time because it seems semantically opportune that even without resorting to Redis scripting it is still possible to avoid race conditions, especially since the implementation complexity of Redis transactions is minimal.
However it is not impossible that in a non immediate future we'll see that the whole user base is just using scripts. If this happens we may deprecate and finally remove transactions.