import org.apache.commons.lang.math.RandomUtils;
import redis.clients.jedis.Jedis;
import redis.clients.jedis.Pipeline;
public class RedisEasyTest {
private static Jedis jedis = new Jedis("xx.xx.xx.xx");
private static Pipeline p = jedis.pipelined();
private static int KEY_COUNT = 10000;
private static int FIELD_COUNT = 10;
public void single() {
for (int i = 0; i < KEY_COUNT; i++) {
String key = RandomUtils.nextInt(5) + "";
for (int j = 0; j < FIELD_COUNT; j++) {
jedis.hset(key, j + "", i + j + "");
jedis.expire(key, 3600);
}
}
}
public void batch() {
int index = 0;
for (int i = 0; i < KEY_COUNT; i++) {
String key = RandomUtils.nextInt(5) + "";
for (int j = 0; j < FIELD_COUNT; j++) {
p.hset(key, j + "", i + j + "");
p.expire(key, 3600);
}
if (++index % 1000 == 0) {
p.sync();
}
}
p.sync();
}
public static void main(String[] args) {
long start = System.currentTimeMillis();
RedisEasyTest r = new RedisEasyTest();
r.single();
System.out.printf("single use %d sec \n", (System.currentTimeMillis() - start) / 1000);
start = System.currentTimeMillis();
r.batch();
System.out.printf("batch use %d sec \n", (System.currentTimeMillis() - start) / 1000);
}
}
输出结果：
single use 30 sec
batch use 0 sec
可以看到通过pipeline批量插入数据性能是非常不错的。