今天，我在做kudu的分区测试，那个结果让我很困惑
首先，我用presto创建两个kudu表
表1

CREATE TABLE events_one (
  id integer WITH (primary_key = true),
  event_time timestamp,
  score Decimal(8,2),
  message varchar
) WITH (
  partition_by_hash_columns = ARRAY['id'],
  partition_by_hash_buckets = 36 ,
number_of_replicas  =  1 

);

表二

CREATE TABLE events_two (
  id integer WITH (primary_key = true),
  event_time timestamp WITH (primary_key = true),
score Decimal(8,2),
  message varchar
) WITH (
  partition_by_hash_columns = ARRAY['id'],
  partition_by_hash_buckets = 36,
  partition_by_range_columns = ARRAY['event_time'],
  range_partitions = '[
{"lower": "2015-01-01T00:00:00", "upper": "2015-03-01T00:00:00"},
{"lower": "2015-03-01T00:00:00", "upper": "2015-06-01T00:00:00"},
{"lower": "2015-06-01T00:00:00", "upper": "2015-09-01T00:00:00"},
{"lower": "2015-09-01T00:00:00", "upper": "2016-01-01T00:00:00"},
{"lower": "2016-01-01T00:00:00", "upper": "2016-03-01T00:00:00"},
{"lower": "2016-03-01T00:00:00", "upper": "2016-06-01T00:00:00"},
{"lower": "2016-06-01T00:00:00", "upper": "2016-09-01T00:00:00"},
{"lower": "2016-09-01T00:00:00", "upper": "2017-01-01T00:00:00"},
{"lower": "2017-01-01T00:00:00", "upper": "2017-03-01T00:00:00"},
{"lower": "2017-03-01T00:00:00", "upper": "2017-06-01T00:00:00"},
{"lower": "2017-06-01T00:00:00", "upper": "2017-09-01T00:00:00"},
{"lower": "2017-09-01T00:00:00", "upper": "2018-01-01T00:00:00"}
]',number_of_replicas  =  1 );

在每个表中插入10000000行数据

List<Date> eventsTime = getDateTimes("2015-01-01","2018-01-01");
       List<TestTableTwo> entitys = new ArrayList<>();
       for(int i=1;i<10000000;i++){
           TestTableTwo entity = new TestTableTwo() ;
           entity.setId(i);
           entity.setEvent_time(eventsTime.get(new Random().nextInt(eventsTime.size())));
           entity.setScore(score);
           entity.setMessage(msg);
           entitys.add(entity);
           if(i%3000==0){
              KuduUtil.save(entitys);
              entitys = new ArrayList<>();
               System.out.println(i);
           }
       }

最后，我测试了查询速度

public static void main(String[] args) throws Exception{
        Class.forName("com.facebook.presto.jdbc.PrestoDriver");
        Connection conn=  DriverManager.getConnection("jdbc:presto://10.100.218.110:8090/kudu/tcdb", "root", null);
        Statement sm = conn.createStatement();
        String sql1 = "select count(1) from events_two where  event_time < timestamp '2017-01-03 00:00:00'";
        Long AllTime = 0L ;
        int per = 100 ;
        for(int i=0;i<per;i++) {
            long startTime = System.currentTimeMillis();
            ResultSet sets = sm.executeQuery(sql1);
            while (sets.next()) {
                String id = sets.getString(1);
                System.out.println(id);

            }
            long endTime = System.currentTimeMillis();
            AllTime += (endTime-startTime);
        }
        System.out.println("testSql:"+sql1);
        System.out.println("per cost :"+AllTime/per+"ms");
    }

结果是：

---
testSql:select * from events_one where id = 200
per cost :61ms

testSql:select * from events_two where id = 200
per cost :54ms
---
testSql:select sum(score) from events_one where event_time < timestamp '2017-01-03 00:00:00'
per cost :448ms

testSql:select sum(score) from events_two where event_time < timestamp '2017-01-03 00:00:00'
per cost :736ms
---
testSql:select sum(score) from events_one where id<5000000 and event_time < timestamp '2017-01-03 00:00:00'
per cost :281ms

testSql:select sum(score) from events_two where id<5000000 and event_time < timestamp '2017-01-03 00:00:00'
per cost :745ms

所有数据在“2015-01-01”-“2018-01-01”中是随机的
为什么kudu表按hash和range分区比按hash分区慢？