In a stream data structure, the XCLAIM command is used when a consumer group needs to take over pending messages from another consumer. This is needed when the original consumer that fetched the message failed to acknowledge it within a specified timeout or crashed.
Here's an example of how you might use XCLAIM
with the Go go-redis
client. In this case, we're going to claim messages that have not been acknowledged for at least 5000 milliseconds (5 seconds).
package main import ( "fmt" "github.com/go-redis/redis/v7" ) func main() { client := redis.NewClient(&redis.Options{ Addr: "localhost:6379", Password: "", DB: 0, }) streams := []string{"mystream"} group := "mygroup" consumer := "consumer1" msgs, err := client.XPendingExt(&redis.XPendingExtArgs{ Stream: streams[0], Group: group, Start: "-", End: "+", Count: 10, }).Result() if err != nil { panic(err) } for _, msg := range msgs { xclaimArgs := &redis.XClaimArgs{ Stream: streams[0], Group: group, Consumer: consumer, MinIdle: 5000, Messages: []string{msg.ID}, } msgs, err := client.XClaim(xclaimArgs).Result() if err != nil { panic(err) } for _, msg := range msgs { fmt.Println("Claimed message ID: ", msg.ID) } } }
In the above code, we first check for all pending messages of the mystream
stream and mygroup
group. We then claim any messages that have been idle for more than 5000 milliseconds.
XCLAIM
is not setting an appropriate min-idle-time. If you set this value too low, consumers might step on each other's toes by claiming messages that are still being processed by other consumers.Q1: What happens if a message is claimed by two different consumers?
A1: The message gets assigned to the consumer that issued the XCLAIM
command most recently. However, itโs considered good practice to avoid such situations as much as possible, because it can lead to duplicate processing of messages.
Q2: Can a consumer claim a message that has already been acknowledged?
A2: No, once a message has been acknowledged with XACK
, it cannot be claimed again. It is removed from the pending entries list.
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.