怎样按一定时间间隔跳跃查询数据？

对于PostgreSQL数据库来说，这个需求很简单，写个函数就可以搞定。
例子：

digoal=# create table test(id serial, crt_time timestamp);
CREATE TABLE
digoal=# insert into test (crt_time) select generate_series(now(),now()+interval '10 min', interval '30 sec');
INSERT 0 21
digoal=# select * from test;
 id |          crt_time          
----+----------------------------
  1 | 2016-04-12 10:25:08.696388
  2 | 2016-04-12 10:25:38.696388
  3 | 2016-04-12 10:26:08.696388
  4 | 2016-04-12 10:26:38.696388
  5 | 2016-04-12 10:27:08.696388
  6 | 2016-04-12 10:27:38.696388
  7 | 2016-04-12 10:28:08.696388
  8 | 2016-04-12 10:28:38.696388
  9 | 2016-04-12 10:29:08.696388
 10 | 2016-04-12 10:29:38.696388
 11 | 2016-04-12 10:30:08.696388
 12 | 2016-04-12 10:30:38.696388
 13 | 2016-04-12 10:31:08.696388
 14 | 2016-04-12 10:31:38.696388
 15 | 2016-04-12 10:32:08.696388
 16 | 2016-04-12 10:32:38.696388
 17 | 2016-04-12 10:33:08.696388
 18 | 2016-04-12 10:33:38.696388
 19 | 2016-04-12 10:34:08.696388
 20 | 2016-04-12 10:34:38.696388
 21 | 2016-04-12 10:35:08.696388
(21 rows)

create or replace function get_sparse_data(b timestamp, e timestamp, sparse interval, lmt int) returns setof test as 
$$

declare
  res test;
  rec test;
  cn int := 0;
begin
  for rec in select * from test where crt_time between b and e order by crt_time loop
    if res is null or rec.crt_time - res.crt_time >= sparse then
      res := rec;
      cn := cn+1;
      return next res;
    end if;

    if cn >= lmt then
      return;
    end if;
  end loop;
end;

$$
 language plpgsql;

digoal=# select get_sparse_data('2016-04-12 10:26:38.696388', '2016-04-12 10:34:08.696388', '1 min', 5);
          get_sparse_data          
-----------------------------------
 (4,"2016-04-12 10:26:38.696388")
 (6,"2016-04-12 10:27:38.696388")
 (8,"2016-04-12 10:28:38.696388")
 (10,"2016-04-12 10:29:38.696388")
 (12,"2016-04-12 10:30:38.696388")
(5 rows)

digoal=# select get_sparse_data('2016-04-12 10:26:38.696388', '2016-04-12 10:34:08.696388', '2 min', 5);
          get_sparse_data          
-----------------------------------
 (4,"2016-04-12 10:26:38.696388")
 (8,"2016-04-12 10:28:38.696388")
 (12,"2016-04-12 10:30:38.696388")
 (16,"2016-04-12 10:32:38.696388")
(4 rows)

另外，您的场景非常像物联网，建议可以考虑使用PostgreSQL, 有几篇文章建议你可以看看：
一个简单算法可以帮助物联网,金融 用户 节约98%的数据存储成本 (PostgreSQL,Greenplum帮你做到)
https://yq.aliyun.com/articles/18042
PostgreSQL 如何潇洒的处理每天上百TB的数据增量
https://yq.aliyun.com/articles/8528
PostgreSQL 1000亿数据量 正则匹配 速度与激情
https://yq.aliyun.com/articles/7549
PostgreSQL 百亿地理位置数据 近邻查询性能
https://yq.aliyun.com/articles/2999
PostgreSQL "物联网"应用 - 1 实时流式数据处理案例(万亿每天)
https://yq.aliyun.com/articles/166