redis-cli, the Redis command line interface
redis-cli is the Redis command line interface, a simple program that allows
to send commands to Redis, and read the replies sent by the server, directly
from the terminal.
It has two main modes: an interactive mode where there is a REPL (Read
Eval Print Loop) where the user types commands and get replies; and another
mode where the command is sent as arguments of
redis-cli, executed, and
printed on the standard output.
In interactive mode,
redis-cli has basic line editing capabilities to provide
a good typing experience.
redis-cli is not just that. There are options you can use to launch
the program in order to put it into special modes, so that
definitely do more complex tasks, like simulate a slave and print the
replication stream it receives from the master, check the latency of a Redis
server and show statistics or even an ASCII-art spectrogram of latency
samples and frequencies, and many other things.
This guide will cover the different aspects of
redis-cli, starting from the
simplest and ending with the more advanced ones.
If you are going to use Redis extensively, or if you already do, chances are
you happen to use
redis-cli a lot. Spending some time to familiarize with
it is likely a very good idea, you’ll see that you’ll work more effectively
with Redis once you know all the tricks of its command line interface.
Command line usage
To just run a command and have its reply printed on the standard output is as
simple as typing the command to execute as separated arguments of
$ redis-cli incr mycounter (integer) 7
The reply of the command is “7”. Since Redis replies are typed (they can be
strings, arrays, integers, NULL, errors and so forth), you see the type
of the reply between brackets. However that would be not exactly a great idea
when the output of
redis-cli must be used as input of another command, or when
we want to redirect it into a file.
redis-cli only shows additional information which improves
readability for humans when it detects the standard output is a tty (a terminal
basically). Otherwise it will auto-enable the raw output mode, like in the
$ redis-cli incr mycounter > /tmp/output.txt $ cat /tmp/output.txt 8
(integer) was omitted from the output since the CLI detected
the output was no longer written to the terminal. You can force raw output
even on the terminal with the
$ redis-cli --raw incr mycounter 9
Similarly, you can force human readable output when writing to a file or in
pipe to other commands by using
Host, port, password and database
redis-cli connects to the server at 127.0.0.1 port 6379.
As you can guess, you can easily change this using command line options.
To specify a different host name or an IP address, use
-h. In order
to set a different port, use
$ redis-cli -h redis15.localnet.org -p 6390 ping PONG
If your instance is password protected, the
-a <password> option will
preform authentication saving the need of explicitly using the
$ redis-cli -a myUnguessablePazzzzzword123 ping PONG
Finally, it’s possible to send a command that operates a on a database number
other than the default number zero by using the
-n <dbnum> option:
$ redis-cli flushall OK $ redis-cli -n 1 incr a (integer) 1 $ redis-cli -n 1 incr a (integer) 2 $ redis-cli -n 2 incr a (integer) 1
Getting input from other programs
There are two ways you can use
redis-cli in order to get the input from other
commands (from the standard input, basically). One is to use as last argument
the payload we read from stdin. For example, in order to set a Redis key
to the content of the file
/etc/services if my computer, I can use the
$ redis-cli -x set foo < /etc/services OK $ redis-cli getrange foo 0 50 "#\n# Network services, Internet style\n#\n# Note that "
As you can see in the first line of the above session, the last argument of the
SET command was not specified. The arguments are just
SET foo without the
actual value I want my key to be set to.
-x option was specified and a file was redirected to the CLI’s
standard input. So the input was read, and was used as the final argument for
the command. This is useful for scripting.
A different approach is to feed
redis-cli a sequence of commands written in a
$ cat /tmp/commands.txt set foo 100 incr foo append foo xxx get foo $ cat /tmp/commands.txt | redis-cli OK (integer) 101 (integer) 6 "101xxx"
All the commands in
commands.txt are executed one after the other by
redis-cli as if they were typed by the user interactive. Strings can be
quoted inside the file if needed, so that it’s possible to have single
arguments with spaces or newlines or other special chars inside:
$ cat /tmp/commands.txt set foo "This is a single argument" strlen foo $ cat /tmp/commands.txt | redis-cli OK (integer) 25
Continuously run the same command
It is possible to execute the same command a specified number of times
with a user selected pause between the executions. This is useful in
different contexts, for example when we want to continuously monitor some
key content or
INFO field output, or when we want to simulate some
recurring write event (like pushing a new item into a list every 5 seconds).
This feature is controlled by two options:
-r <count> and
The first states how many times to run a command, the second configures
the delay between the different command calls, in seconds (with the ability
to specify decimal numbers like 0.1 in order to mean 100 milliseconds).
By default the interval (or delay) is set to 0, so commands are just executed ASAP:
$ redis-cli -r 5 incr foo (integer) 1 (integer) 2 (integer) 3 (integer) 4 (integer) 5
To run the same command forever, use
-1 as count.
So, in order to monitor over time the RSS memory size it’s possible
to use a command like the following:
$ redis-cli -r -1 -i 1 INFO | grep rss_human used_memory_rss_human:1.38M used_memory_rss_human:1.38M used_memory_rss_human:1.38M ... a new line will be printed each second ...
Mass insertion of data using
Mass insert using
redis-cli is covered in a separated page since it’s a
worthwhile topic itself. Please refer to our
mass insertion guide.
Sometimes you may want to use
redis-cli in order to quickly export data from
Redis to an external program. This can be accomplished using the CSV (Comma
Separated Values) output feature:
$ redis-cli lpush mylist a b c d (integer) 4 $ redis-cli --csv lrange mylist 0 -1 "d","c","b","a"
Currently it’s not possible to export the whole DB like that, but only to run single commands with CSV output.
Running Lua scripts
redis-cli has extensive support for using the new Lua debugging facility
of Lua scripting, available starting with Redis 3.2. For this feature, please
refer to the Redis Lua debugger documentation.
However, even without using the debugger, you can use
run scripts from a file in a way more comfortable compared to typing
the script interactively into the shell or as an argument:
$ cat /tmp/script.lua return redis.call('set',KEYS,ARGV) $ redis-cli --eval /tmp/script.lua foo , bar OK
EVAL command takes the list of keys the script uses, and the
other non key arguments, as different arrays. When calling
provide the number of keys as a number. However with
redis-cli and using
--eval option above, there is no need to specify the number of keys
explicitly. Instead it uses the convention of separating keys and arguments
with a comma. This is why in the above call you see
foo , bar as arguments.
foo will populate the
KEYS array, and
--eval option is useful when writing simple scripts. For more
complex work, using the Lua debugger is definitely more comfortable. It’s
possible to mix the two approaches, since the debugger also uses executing
scripts from an external file.
So far we explored how to use the Redis CLI as a command line program.
This is very useful for scripts and certain types of testing, however most
people will spend the majority of time in
redis-cli using its interactive
In interactive mode the user types Redis commands at the prompt. The command is sent to the server, processed, and the reply is parsed back and rendered into a simpler form to read.
Nothing special is needed for running the CLI in interactive mode - just lunch it without any arguments and you are in:
$ redis-cli 127.0.0.1:6379> ping PONG
127.0.0.1:6379> is the prompt. It reminds you that you are
connected to a given Redis instance.
The prompt changes as the server you are connected to changes, or when you are operating on a database different than the database number zero:
127.0.0.1:6379> select 2 OK 127.0.0.1:6379> dbsize (integer) 1 127.0.0.1:6379> select 0 OK 127.0.0.1:6379> dbsize (integer) 503
Handling connections and reconnections
connect command in interactive mode makes it possible to connect
to a different instance, by specifying the hostname and port we want
to connect to:
127.0.0.1:6379> connect metal 6379 metal:6379> ping PONG
As you can see the prompt changes accordingly. If the user attempts to connect
to an instance that is unreachable, the
redis-cli goes into disconnected
mode and attempts to reconnect with each new command:
127.0.0.1:6379> connect 127.0.0.1 9999 Could not connect to Redis at 127.0.0.1:9999: Connection refused not connected> ping Could not connect to Redis at 127.0.0.1:9999: Connection refused not connected> ping Could not connect to Redis at 127.0.0.1:9999: Connection refused
Generally after a disconnection is detected, the CLI always attempts to reconnect transparently: if the attempt fails, it shows the error and enters the disconnected state. The following is an example of disconnection and reconnection:
127.0.0.1:6379> debug restart Could not connect to Redis at 127.0.0.1:6379: Connection refused not connected> ping PONG 127.0.0.1:6379> (now we are connected again)
When a reconnection is performed,
redis-cli automatically re-select the
last database number selected. However, all the other state about the
connection is lost, such as the state of a transaction if we
were in the middle of it:
$ redis-cli 127.0.0.1:6379> multi OK 127.0.0.1:6379> ping QUEUED ( here the server is manually restarted ) 127.0.0.1:6379> exec (error) ERR EXEC without MULTI
This is usually not an issue when using the CLI in interactive mode for testing, but you should be aware of this limitation.
Editing, history and completion
redis-cli uses the
linenoise line editing library, it
always has line editing capabilities, without depending on
other optional libraries.
You can access an history of commands executed, in order to avoid retyping
them again and again, by pressing the arrow keys (up and down).
The history is preserved between restarts of the CLI, in a file called
.rediscli_history inside the user home directory, as specified
HOME environment variable. It is possible to use a different
history filename by setting the
REDISCLI_HISTFILE environment variable,
and disable it by setting it to
The CLI is also able to perform command names completion by pressing the TAB key, like in the following example:
127.0.0.1:6379> Z<TAB> 127.0.0.1:6379> ZADD<TAB> 127.0.0.1:6379> ZCARD<TAB>
Running the same command N times
It’s possible to run the same command multiple times by prefixing the command name by a number:
127.0.0.1:6379> 5 incr mycounter (integer) 1 (integer) 2 (integer) 3 (integer) 4 (integer) 5
Showing help about Redis commands
Redis has a number of commands and sometimes, as you test things,
you may not remember the exact order of arguments.
redis-cli provides online
help for most Redis commands, using the
help command. The command can be used
in two forms:
help @<category>shows all the commands about a given category. The categories are:
help <commandname>shows specific help for the command given as argument.
For example in order to show help for the
PFADD command, use:
127.0.0.1:6379> help PFADD
PFADD key element [element …] summary: Adds the specified elements to the specified HyperLogLog. since: 2.8.9
help supports TAB completion as well.
Clearing the terminal screen
clear command in interactive mode clears the terminal’s screen.
Special modes of operation
So far we saw two main modes of
- Command line execution of Redis commands.
- Interactive “REPL-like” usage.
However the CLI performs other auxiliary tasks related to Redis that are explained in the next sections:
- Monitoring tool to show continuous stats about a Redis server.
- Scanning a Redis database for very large keys.
- Key space scanner with pattern matching.
- Acting as a Pub/Sub client to subscribe to channels.
- Monitoring the commands executed into a Redis instance.
- Checking the latency of a Redis server in different ways.
- Checking the scheduler latency of the local computer.
- Transferring RDB backups from a remote Redis server locally.
- Acting as a Redis slave for showing what a slave receives.
- Simulating LRU workloads for showing stats about keys hits.
- A client for the Lua debugger.
Continuous stats mode
This is probably one of the lesser known features of
redis-cli, and one
very useful in order to monitor Redis instances in real time.
To enable this mode, the
--stat option is used.
The output is very clear about the behavior of the CLI in this mode:
$ redis-cli --stat ------- data ------ --------------------- load -------------------- - child - keys mem clients blocked requests connections 506 1015.00K 1 0 24 (+0) 7 506 1015.00K 1 0 25 (+1) 7 506 3.40M 51 0 60461 (+60436) 57 506 3.40M 51 0 146425 (+85964) 107 507 3.40M 51 0 233844 (+87419) 157 507 3.40M 51 0 321715 (+87871) 207 508 3.40M 51 0 408642 (+86927) 257 508 3.40M 51 0 497038 (+88396) 257
In this mode a new line is printed every second with useful information and the difference between the old data point. You can easily understand what’s happening with memory usage, clients connected, and so forth.
-i <interval> option in this case works as a modifier in order to
change the frequency at which new lines are emitted. The default is one
Scanning for big keys
In this special mode,
redis-cli works as a key space analyzer. It scans the
dataset for big keys, but also provides information about the data types
that the data set consists of. This mode is enabled with the
and produces quite a verbose output:
$ redis-cli --bigkeys # Scanning the entire keyspace to find biggest keys as well as # average sizes per key type. You can use -i 0.1 to sleep 0.1 sec # per 100 SCAN commands (not usually needed). [00.00%] Biggest string found so far 'key-419' with 3 bytes [05.14%] Biggest list found so far 'mylist' with 100004 items [35.77%] Biggest string found so far 'counter:__rand_int__' with 6 bytes [73.91%] Biggest hash found so far 'myobject' with 3 fields -------- summary ------- Sampled 506 keys in the keyspace! Total key length in bytes is 3452 (avg len 6.82) Biggest string found 'counter:__rand_int__' has 6 bytes Biggest list found 'mylist' has 100004 items Biggest hash found 'myobject' has 3 fields 504 strings with 1403 bytes (99.60% of keys, avg size 2.78) 1 lists with 100004 items (00.20% of keys, avg size 100004.00) 0 sets with 0 members (00.00% of keys, avg size 0.00) 1 hashs with 3 fields (00.20% of keys, avg size 3.00) 0 zsets with 0 members (00.00% of keys, avg size 0.00)
In the first part of the output, each new key larger than the previous larger key (of the same type) encountered is reported. The summary section provides general stats about the data inside the Redis instance.
The program uses the
SCAN command, so it can be executed against a busy
server without impacting the operations, however the
-i option can be
used in order to throttle the scanning process of the specified fraction
of second for each 100 keys requested. For example,
-i 0.1 will slow down
the program execution a lot, but will also reduce the load on the server
to a tiny amount.
Note that the summary also reports in a cleaner form the biggest keys found for each time. The initial output is just to provide some interesting info ASAP if running against a very large data set.
Getting a list of keys
It is also possible to scan the key space, again in a way that does not
block the Redis server (which does happen when you use a command
KEYS *), and print all the key names, or filter them for specific
patterns. This mode, like the
--bigkeys option, uses the
so keys may be reported multiple times if the dataset is changing, but no
key would ever be missing, if that key was present since the start of the
iteration. Because of the command that it uses this option is called
$ redis-cli --scan | head -10 key-419 key-71 key-236 key-50 key-38 key-458 key-453 key-499 key-446 key-371
head -10 is used in order to print only the first lines of the
Scanning is able to use the underlying pattern matching capability of
SCAN command with the
$ redis-cli --scan --pattern '*-11*' key-114 key-117 key-118 key-113 key-115 key-112 key-119 key-11 key-111 key-110 key-116
Piping the output through the
wc command can be used to count specific
kind of objects, by key name:
$ redis-cli --scan --pattern 'user:*' | wc -l 3829433
The CLI is able to publish messages in Redis Pub/Sub channels just using
PUBLISH command. This is expected since the
PUBLISH command is very
similar to any other command. Subscribing to channels in order to receive
messages is different - in this case we need to block and wait for
messages, so this is implemented as a special mode in
other special modes this mode is not enabled by using a special option,
but simply by using the
PSUBSCRIBE command, both in
interactive or non interactive mode:
$ redis-cli psubscribe '*' Reading messages... (press Ctrl-C to quit) 1) "psubscribe" 2) "*" 3) (integer) 1
The reading messages message shows that we entered Pub/Sub mode.
When another client publishes some message in some channel, like you
can do using
redis-cli PUBLISH mychannel mymessage, the CLI in Pub/Sub
mode will show something such as:
1) "pmessage" 2) "*" 3) "mychannel" 4) "mymessage"
This is very useful for debugging Pub/Sub issues.
To exit the Pub/Sub mode just process
Monitoring commands executed in Redis
Similarly to the Pub/Sub mode, the monitoring mode is entered automatically
once you use the
MONITOR mode. It will print all the commands received
by a Redis instance:
$ redis-cli monitor OK 1460100081.165665 [0 127.0.0.1:51706] "set" "foo" "bar" 1460100083.053365 [0 127.0.0.1:51707] "get" "foo"
Note that it is possible to use to pipe the output, so you can monitor
for specific patterns using tools such as
Monitoring the latency of Redis instances
Redis is often used in contexts where latency is very critical. Latency involves multiple moving parts within the application, from the client library to the network stack, to the Redis instance itself.
The CLI has multiple facilities for studying the latency of a Redis instance and understanding the latency’s maximum, average and distribution.
The basic latency checking tool is the
--latency option. Using this
option the CLI runs a loop where the
PING command is sent to the Redis
instance, and the time to get a reply is measured. This happens 100
times per second, and stats are updated in a real time in the console:
$ redis-cli --latency min: 0, max: 1, avg: 0.19 (427 samples)
The stats are provided in milliseconds. Usually, the average latency of
a very fast instance tends to be overestimated a bit because of the
latency due to the kernel scheduler of the system running
itself, so the average latency of 0.19 above may easily be 0.01 or less.
However this is usually not a big problem, since we are interested in
events of a few millisecond or more.
Sometimes it is useful to study how the maximum and average latencies
evolve during time. The
--latency-history option is used for that
purpose: it works exactly like
--latency, but every 15 seconds (by
default) a new sampling session is started from scratch:
$ redis-cli --latency-history min: 0, max: 1, avg: 0.14 (1314 samples) -- 15.01 seconds range min: 0, max: 1, avg: 0.18 (1299 samples) -- 15.00 seconds range min: 0, max: 1, avg: 0.20 (113 samples)^C
You can change the sampling sessions’ length with the
-i <interval> option.
The most advanced latency study tool, but also a bit harder to
interpret for non experienced users, is the ability to use color terminals
to show a spectrum of latencies. You’ll see a colored output that indicate the
different percentages of samples, and different ASCII characters that indicate
different latency figures. This mode is enabled using the
$ redis-cli --latency-dist (output not displayed, requires a color terminal, try it!)
There is another pretty unusual latency tool implemented inside
It does not check the latency of a Redis instance, but the latency of the
computer you are running
redis-cli on. What latency you may ask?
The latency that’s intrinsic to the kernel scheduler, the hypervisor in case
of virtualized instances, and so forth.
We call it intrinsic latency because it’s opaque to the programmer, mostly.
If your Redis instance has bad latency regardless of all the obvious things
that may be the source cause, it’s worth to check what’s the best your system
can do by running
redis-cli in this special mode directly in the system you
are running Redis servers on.
By measuring the intrinsic latency, you know that this is the baseline,
and Redis cannot outdo your system. In order to run the CLI
in this mode, use the
--intrinsic-latency <test-time>. The test’s time
is in seconds, and specifies how many seconds
redis-cli should check the
latency of the system it’s currently running on.
$ ./redis-cli --intrinsic-latency 5 Max latency so far: 1 microseconds. Max latency so far: 7 microseconds. Max latency so far: 9 microseconds. Max latency so far: 11 microseconds. Max latency so far: 13 microseconds. Max latency so far: 15 microseconds. Max latency so far: 34 microseconds. Max latency so far: 82 microseconds. Max latency so far: 586 microseconds. Max latency so far: 739 microseconds. 65433042 total runs (avg latency: 0.0764 microseconds / 764.14 nanoseconds per run). Worst run took 9671x longer than the average latency.
IMPORTANT: this command must be executed on the computer you want to run Redis server on, not on a different host. It does not even connect to a Redis instance and performs the test only locally.
In the above case, my system cannot do better than 739 microseconds of worst case latency, so I can expect certain queries to run in a bit less than 1 millisecond from time to time.
Remote backups of RDB files
During Redis replication’s first synchronization, the master and the slave
exchange the whole data set in form of an RDB file. This feature is exploited
redis-cli in order to provide a remote backup facility, that allows to
transfer an RDB file from any Redis instance to the local computer running
redis-cli. To use this mode, call the CLI with the
$ redis-cli --rdb /tmp/dump.rdb SYNC sent to master, writing 13256 bytes to '/tmp/dump.rdb' Transfer finished with success.
This is a simple but effective way to make sure you have disaster recovery
RDB backups of your Redis instance. However when using this options in
cron jobs, make sure to check the return value of the command.
If it is non zero, an error occurred like in the following example:
$ redis-cli --rdb /tmp/dump.rdb SYNC with master failed: -ERR Can't SYNC while not connected with my master $ echo $? 1
The slave mode of the CLI is an advanced feature useful for
Redis developers and for debugging operations.
It allows to inspect what a master sends to its slaves in the replication
stream in order to propagate the writes to its replicas. The option
name is simply
--slave. This is how it works:
$ redis-cli --slave SYNC with master, discarding 13256 bytes of bulk transfer... SYNC done. Logging commands from master. "PING" "SELECT","0" "set","foo","bar" "PING" "incr","myconuter"
The command begins by discarding the RDB file of the first synchronization and then logs each command received as in CSV format.
If you think some of the commands are not replicated correctly in your slaves this is a good way to check what’s happening, and also useful information in order to improve the bug report.
Performing an LRU simulation
Redis is often used as a cache with LRU eviction.
Depending on the number of keys and the amount of memory allocated for the
cache (specified via the
maxmemory directive), the amount of cache hits
and misses will change. Sometimes, simulating the rate of hits is very
useful to correctly provision your cache.
The CLI has a special mode where it performs a simulation of GET and SET operations, using an 80-20% power law distribution in the requests pattern. This means that 20% of keys will be requested 80% of times, which is a common distribution in caching scenarios.
Theoretically, given the distribution of the requests and the Redis memory overhead, it should be possible to compute the hit rate analytically with with a mathematical formula. However, Redis can be configured with different LRU settings (number of samples) and LRU’s implementation, which is approximated in Redis, changes a lot between different versions. Similarly the amount of memory per key may change between versions. That is why this tool was built: its main motivation was for testing the quality of Redis’ LRU implementation, but now is also useful in for testing how a given version behaves with the settings you had in mind for your deployment.
In order to use this mode, you need to specify the amount of keys
in the test. You also need to configure a
maxmemory setting that
makes sense as a first try.
IMPORTANT NOTE: Configuring the
maxmemory setting in the Redis configuration
is crucial: if there is no cap to the maximum memory usage, the hit will
eventually be 100% since all the keys can be stored in memory. Or if you
specify too many keys and no maximum memory, eventually all the computer
RAM will be used. It is also needed to configure an appropriate
maxmemory policy, most of the times what you want is
In the following example I configured a memory limit of 100MB, and an LRU simulation using 10 million keys.
WARNING: the test uses pipelining and will stress the server, don’t use it with production instances.
$ ./redis-cli --lru-test 10000000 156000 Gets/sec | Hits: 4552 (2.92%) | Misses: 151448 (97.08%) 153750 Gets/sec | Hits: 12906 (8.39%) | Misses: 140844 (91.61%) 159250 Gets/sec | Hits: 21811 (13.70%) | Misses: 137439 (86.30%) 151000 Gets/sec | Hits: 27615 (18.29%) | Misses: 123385 (81.71%) 145000 Gets/sec | Hits: 32791 (22.61%) | Misses: 112209 (77.39%) 157750 Gets/sec | Hits: 42178 (26.74%) | Misses: 115572 (73.26%) 154500 Gets/sec | Hits: 47418 (30.69%) | Misses: 107082 (69.31%) 151250 Gets/sec | Hits: 51636 (34.14%) | Misses: 99614 (65.86%)
The program shows stats every second. As you see, in the first seconds the cache starts to be populated. The misses rate later stabilizes into the actual figure we can expect in the long time:
120750 Gets/sec | Hits: 48774 (40.39%) | Misses: 71976 (59.61%) 122500 Gets/sec | Hits: 49052 (40.04%) | Misses: 73448 (59.96%) 127000 Gets/sec | Hits: 50870 (40.06%) | Misses: 76130 (59.94%) 124250 Gets/sec | Hits: 50147 (40.36%) | Misses: 74103 (59.64%)
A miss rage of 59% may not be acceptable for our use case. So we know that 100MB of memory are no enough. Let’s try with half gigabyte. After a few minutes we’ll see the output to stabilize to the following figures:
140000 Gets/sec | Hits: 135376 (96.70%) | Misses: 4624 (3.30%) 141250 Gets/sec | Hits: 136523 (96.65%) | Misses: 4727 (3.35%) 140250 Gets/sec | Hits: 135457 (96.58%) | Misses: 4793 (3.42%) 140500 Gets/sec | Hits: 135947 (96.76%) | Misses: 4553 (3.24%)
So we know that with 500MB we are going well enough for our number of keys (10 millions) and distribution (80-20 style).