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In Go language, you can use the snowflake algorithm to generate unique ids. The Snowflake algorithm is a distributed ID generation algorithm open sourced by Twitter. It can generate unique IDs in a distributed system, ensuring the global uniqueness of the ID, and the generated IDs increase in time.
The following is a sample code that uses the Go language to implement the Snowflake algorithm to generate a unique ID, running online:
package main import ( "fmt" "time" ) const ( workerBits uint8 = 10 seqBits uint8 = 12 maxWorkerNum int64 = -1 ^ (-1 << workerBits) maxSeqNum int64 = -1 ^ (-1 << seqBits) timeShift uint8 = workerBits + seqBits workerShift uint8 = seqBits ) type snowflake struct { lastTimestamp int64 workerId int64 sequence int64 } func newSnowflake(workerId int64) *snowflake { if workerId < 0 || workerId > maxWorkerNum { panic("workerId out of range") } return &snowflake{ lastTimestamp: 0, workerId: workerId, sequence: 0, } } func (sf *snowflake) NextId() int64 { timestamp := time.Now().UnixNano() / 1000000 if timestamp < sf.lastTimestamp { panic("clock is moving backwards") } if timestamp == sf.lastTimestamp { sf.sequence = (sf.sequence + 1) & maxSeqNum if sf.sequence == 0 { for timestamp <= sf.lastTimestamp { timestamp = time.Now().UnixNano() / 1000000 } } } else { sf.sequence = 0 } sf.lastTimestamp = timestamp return (timestamp << timeShift) | (sf.workerId << workerShift) | sf.sequence } func main() { sf := newSnowflake(1) fmt.Println(sf.NextId()) }
In the above code, we define a snowflake structure, which contains the last generated The three attributes of timestamp, workerId and sequence. In the newSnowflake function, we check whether the passed-in workerId is within a reasonable range, and then initialize the properties of the snowflake structure. In the NextId function, we first obtain the current timestamp. If the current timestamp is less than the last generated timestamp, it means that the clock has been set back, and an exception needs to be thrown.
If the current timestamp is equal to the last generated timestamp, it means that multiple IDs were generated in the same millisecond. At this time, the sequence needs to be incremented. If the sequence reaches the maximum value, you need to wait until the next millisecond. If the current timestamp is greater than the last generated timestamp, it means that it has entered the next millisecond. At this time, the sequence needs to be reset to 0 and lastTimestamp updated. Finally, a unique ID is generated based on the timestamp, workerId, and sequence.
In this example, we set workerId=1 to generate a unique ID. You can use different workerIds according to the actual situation.
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