ZhouXY108/hutool
1
0
Fork 0
mirror of https://gitee.com/chinabugotech/hutool.git synced 2025-05-09 23:51:34 +08:00
Code Issues Packages Projects Releases Wiki Activity

!1096 Snowflake增加方法：根据传入时间戳，计算ID起终点 (gitee/issues/I60M14)

Browse Source 
* Snowflake add method:根据传入时间戳-计算ID起终点 (gitee/issues/I60M14)
This commit is contained in:
晚安,地球 2023-10-25 03:21:40 +00:00 committed by Looly
parent 7d80f1aa14
commit fe37c1aa84
2 changed files with 83 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

34
hutool-core/src/main/java/cn/hutool/core/lang/Snowflake.java
View File

@ -198,6 +198,40 @@ public class Snowflake implements Serializable {
return (id >> TIMESTAMP_LEFT_SHIFT & ~(-1L << 41L)) + twepoch;
}
/**
* 根据传入时间戳-计算ID起终点
*
* @param timestampStart 开始时间戳
* @param timestampEnd 结束时间戳
* @return key-ID起点，Value-ID终点
* @since 5.8.24
*/
public Pair<Long, Long> getIdScopeByTimestamp(long timestampStart, long timestampEnd) {
return getIdScopeByTimestamp(timestampStart, timestampEnd, true);
}
/**
* 根据传入时间戳-计算ID起终点 Gitee/issues/I60M14
*
* @param timestampStart 开始时间戳
* @param timestampEnd 结束时间戳
* @param ignoreCenterAndWorker 是否忽略数据中心和机器节点的占位，忽略后可获得分布式环境全局可信赖的起终点。
* @return key-ID起点，Value-ID终点
* @since 5.8.24
*/
public Pair<Long, Long> getIdScopeByTimestamp(long timestampStart, long timestampEnd, boolean ignoreCenterAndWorker) {
long startTimeMinId = (timestampStart - twepoch) << TIMESTAMP_LEFT_SHIFT;
long endTimeMinId = (timestampEnd - twepoch) << TIMESTAMP_LEFT_SHIFT;
if (ignoreCenterAndWorker) {
long endId = endTimeMinId | ~(-1 << TIMESTAMP_LEFT_SHIFT);
return Pair.of(startTimeMinId, endId);
} else {
long startId = startTimeMinId | (dataCenterId << DATA_CENTER_ID_SHIFT) | (workerId << WORKER_ID_SHIFT);
long endId = endTimeMinId | (dataCenterId << DATA_CENTER_ID_SHIFT) | (workerId << WORKER_ID_SHIFT) | SEQUENCE_MASK;
return Pair.of(startId, endId);
}
}
/**
* 下一个ID
*

49
hutool-core/src/test/java/cn/hutool/core/lang/SnowflakeTest.java
View File

@ -4,6 +4,7 @@ import cn.hutool.core.collection.ConcurrentHashSet;
import cn.hutool.core.exceptions.UtilException;
import cn.hutool.core.thread.ThreadUtil;
import cn.hutool.core.util.IdUtil;
import cn.hutool.core.util.RandomUtil;
import cn.hutool.core.util.StrUtil;
import org.junit.Assert;
import org.junit.Ignore;
@ -19,6 +20,54 @@ import java.util.Set;
*/
public class SnowflakeTest {
/**
* 测试-根据传入时间戳-计算ID起终点
*/
@Test
public void snowflakeTestGetIdScope() {
long workerId = RandomUtil.randomLong(31);
long dataCenterId = RandomUtil.randomLong(31);
Snowflake idWorker = new Snowflake(workerId, dataCenterId);
long generatedId = idWorker.nextId();
// 随机忽略数据中心和工作机器的占位
boolean ignore = RandomUtil.randomBoolean();
long createTimestamp = idWorker.getGenerateDateTime(generatedId);
Pair<Long, Long> idScope = idWorker.getIdScopeByTimestamp(createTimestamp, createTimestamp, ignore);
long startId = idScope.getKey();
long endId = idScope.getValue();
System.out.println(longToBinaryReadable(generatedId) + " = generatedId longToBinaryReadable");
System.out.println(longToBinaryReadable(startId) + " = startId longToBinaryReadable");
System.out.println(longToBinaryReadable(endId) + " = endId longToBinaryReadable");
// 起点终点相差比较
long trueOffSet = endId - startId;
// 忽略数据中心和工作机器时差值为22个1，否则为12个1
long expectedOffSet = ignore ? ~(-1 << 22) : ~(-1 << 12);
System.out.println("计算差值 = " + trueOffSet + ", 预期差值 = " + expectedOffSet);
Assert.assertEquals(trueOffSet, expectedOffSet);
}
/**
* long转雪花格式的2进制字符串
*
* @param number long值
* @return 符号位（1bit）- 时间戳相对值（41bit）- 数据中心标志（5bit）- 机器标志（5bit）- 递增序号（12bit）
*/
private String longToBinaryReadable(long number) {
String binaryString = Long.toBinaryString(number);
StringBuilder sb = new StringBuilder(binaryString);
while (sb.length() < 64) {
sb.insert(0, '0'); // 在二进制字符串前面补零
}
sb
.insert(52, "-")
.insert(47, "-")
.insert(42, "-")
.insert(1, "-")
;
return sb.toString();
}
@Test
public void snowflakeTest1(){
//构建Snowflake，提供终端ID和数据中心ID