XREAD [COUNT count] [BLOCK milliseconds] STREAMS key [key ...] id [id ...]

Available since: 5.0.0

Time complexity: For each stream mentioned: O(N) with N being the number of elements being returned, it means that XREAD-ing with a fixed COUNT is O(1). Note that when the BLOCK option is used, XADD will pay O(M) time in order to serve the M clients blocked on the stream getting new data.

ACL categories: @read @stream @slow @blocking

Read data from one or multiple streams, only returning entries with an ID greater than the last received ID reported by the caller. This command has an option to block if items are not available, in a similar fashion to BRPOP or BZPOPMIN and others.

Please note that before reading this page, if you are new to streams, we recommend to read our introduction to Redis Streams.

Non-blocking usage

If the BLOCK option is not used, the command is synchronous, and can be considered somewhat related to XRANGE: it will return a range of items inside streams, however it has two fundamental differences compared to XRANGE even if we just consider the synchronous usage:

This command can be called with multiple streams if we want to read at the same time from a number of keys. This is a key feature of XREAD because especially when blocking with BLOCK, to be able to listen with a single connection to multiple keys is a vital feature.
While XRANGE returns items in a range of IDs, XREAD is more suited in order to consume the stream starting from the first entry which is greater than any other entry we saw so far. So what we pass to XREAD is, for each stream, the ID of the last element that we received from that stream.

For example, if I have two streams mystream and writers, and I want to read data from both the streams starting from the first element they contain, I could call XREAD like in the following example.

Note: we use the COUNT option in the example, so that for each stream the call will return at maximum two elements per stream.

> XREAD COUNT 2 STREAMS mystream writers 0-0 0-0
1) 1) "mystream"
   2) 1) 1) 1526984818136-0
         2) 1) "duration"
            2) "1532"
            3) "event-id"
            4) "5"
            5) "user-id"
            6) "7782813"
      2) 1) 1526999352406-0
         2) 1) "duration"
            2) "812"
            3) "event-id"
            4) "9"
            5) "user-id"
            6) "388234"
2) 1) "writers"
   2) 1) 1) 1526985676425-0
         2) 1) "name"
            2) "Virginia"
            3) "surname"
            4) "Woolf"
      2) 1) 1526985685298-0
         2) 1) "name"
            2) "Jane"
            3) "surname"
            4) "Austen"

The STREAMS option is mandatory and MUST be the final option because such option gets a variable length of argument in the following format:

STREAMS key_1 key_2 key_3 ... key_N ID_1 ID_2 ID_3 ... ID_N

So we start with a list of keys, and later continue with all the associated IDs, representing the last ID we received for that stream, so that the call will serve us only greater IDs from the same stream.

For instance in the above example, the last items that we received for the stream mystream has ID 1526999352406-0, while for the stream writers has the ID 1526985685298-0.

To continue iterating the two streams I’ll call:

> XREAD COUNT 2 STREAMS mystream writers 1526999352406-0 1526985685298-0
1) 1) "mystream"
   2) 1) 1) 1526999626221-0
         2) 1) "duration"
            2) "911"
            3) "event-id"
            4) "7"
            5) "user-id"
            6) "9488232"
2) 1) "writers"
   2) 1) 1) 1526985691746-0
         2) 1) "name"
            2) "Toni"
            3) "surname"
            4) "Morrison"
      2) 1) 1526985712947-0
         2) 1) "name"
            2) "Agatha"
            3) "surname"
            4) "Christie"

And so forth. Eventually, the call will not return any item, but just an empty array, then we know that there is nothing more to fetch from our stream (and we would have to retry the operation, hence this command also supports a blocking mode).

Incomplete IDs

To use incomplete IDs is valid, like it is valid for XRANGE. However here the sequence part of the ID, if missing, is always interpreted as zero, so the command:

> XREAD COUNT 2 STREAMS mystream writers 0 0

is exactly equivalent to

> XREAD COUNT 2 STREAMS mystream writers 0-0 0-0

Blocking for data

In its synchronous form, the command can get new data as long as there are more items available. However, at some point, we’ll have to wait for producers of data to use XADD to push new entries inside the streams we are consuming. In order to avoid polling at a fixed or adaptive interval the command is able to block if it could not return any data, according to the specified streams and IDs, and automatically unblock once one of the requested keys accept data.

It is important to understand that this command fans out to all the clients that are waiting for the same range of IDs, so every consumer will get a copy of the data, unlike to what happens when blocking list pop operations are used.

In order to block, the BLOCK option is used, together with the number of milliseconds we want to block before timing out. Normally Redis blocking commands take timeouts in seconds, however this command takes a millisecond timeout, even if normally the server will have a timeout resolution near to 0.1 seconds. This time it is possible to block for a shorter time in certain use cases, and if the server internals will improve over time, it is possible that the resolution of timeouts will improve.

When the BLOCK command is passed, but there is data to return at least in one of the streams passed, the command is executed synchronously exactly like if the BLOCK option would be missing.

This is an example of blocking invocation, where the command later returns a null reply because the timeout has elapsed without new data arriving:

> XREAD BLOCK 1000 STREAMS mystream 1526999626221-0
(nil)

The special `$` ID.

When blocking sometimes we want to receive just entries that are added to the stream via XADD starting from the moment we block. In such a case we are not interested in the history of already added entries. For this use case, we would have to check the stream top element ID, and use such ID in the XREAD command line. This is not clean and requires to call other commands, so instead it is possible to use the special $ ID to signal the stream that we want only the new things.

It is very important to understand that you should use the $ ID only for the first call to XREAD. Later the ID should be the one of the last reported item in the stream, otherwise you could miss all the entries that are added in between.

This is how a typical XREAD call looks like in the first iteration of a consumer willing to consume only new entries:

> XREAD BLOCK 5000 COUNT 100 STREAMS mystream $

Once we get some replies, the next call will be something like:

> XREAD BLOCK 5000 COUNT 100 STREAMS mystream 1526999644174-3

And so forth.

How multiple clients blocked on a single stream are served

Blocking list operations on lists or sorted sets have a pop behavior. Basically, the element is removed from the list or sorted set in order to be returned to the client. In this scenario you want the items to be consumed in a fair way, depending on the moment clients blocked on a given key arrived. Normally Redis uses the FIFO semantics in this use cases.

However note that with streams this is not a problem: stream entries are not removed from the stream when clients are served, so every client waiting will be served as soon as an XADD command provides data to the stream.

@return

@array-reply, specifically:

The command returns an array of results: each element of the returned array is an array composed of a two element containing the key name and the entries reported for that key. The entries reported are full stream entries, having IDs and the list of all the fields and values. Field and values are guaranteed to be reported in the same order they were added by XADD.

When BLOCK is used, on timeout a null reply is returned.

Reading the Redis Streams introduction is highly suggested in order to understand more about the streams overall behavior and semantics.