hive调优实例分析

hive distribute by分组应用调优

以表中字段分组

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = false; --MR操作结束时，不合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
SELECT
      a.item_sku_id 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            distribute by item_sku_id -- 大表以表中字段分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL;

结果：

2022-02-16 23:03:47 INFO Table tmp.tmp_ljjtest02 stats: [numFiles=23, numRows=23, totalSize=5894, rawDataSize=2252]
2022-02-16 23:03:47 INFO Stage-1: Map: 18024  Reduce: 1009   Cumulative CPU: 377078.2 sec   HDFS Read: 193.287 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 4m18s539ms job_5690061100801_32622232
2022-02-16 23:03:47 INFO Stage-10: Map: 920   Cumulative CPU: 5431.21 sec   HDFS Read: 0.008 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 52s336ms job_5690061100801_32622707
2022-02-16 23:03:47 INFO Stage-4: Map: 832   Cumulative CPU: 1078.67 sec   HDFS Read: 0.001 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 31s273ms job_8766029101801_36250210
2022-02-16 23:03:47 INFO Total MapReduce CPU Time Spent: 4d10h33m8s80ms
2022-02-16 23:03:47 INFO Total Map: 19776  Total Reduce: 1009
2022-02-16 23:03:47 INFO Total HDFS Read: 193.296 GB  Written: 0.000 GB

结果分析：

以随机数分组

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = false; --MR操作结束时，不合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
SELECT
      a.item_sku_id 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            distribute by item_sku_id -- 大表以随机数分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL;

结果：

2022-02-16 22:53:00 INFO Table tmp.tmp_01 stats: [numFiles=3, numRows=23, totalSize=958, rawDataSize=2235]
2022-02-16 22:53:00 INFO Stage-1: Map: 18024  Reduce: 1009   Cumulative CPU: 372613.35 sec   HDFS Read: 193.289 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 5m32s865ms job_5690061100801_32621522
2022-02-16 22:53:00 INFO Stage-10: Map: 924   Cumulative CPU: 5424.53 sec   HDFS Read: 0.008 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 41s846ms job_5690061100801_32621870
2022-02-16 22:53:00 INFO Stage-4: Map: 858   Cumulative CPU: 1374.95 sec   HDFS Read: 0.001 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 43s592ms job_5690061100801_32621913
2022-02-16 22:53:00 INFO Total MapReduce CPU Time Spent: 4d9h23m32s830ms
2022-02-16 22:53:00 INFO Total Map: 19806  Total Reduce: 1009
2022-02-16 22:53:00 INFO Total HDFS Read: 193.298 GB  Written: 0.000 GB

结果分析：

总结：

distribute by rand()的风险具体原理如下：

• 部分reduce shuffle失败导致上游个别map task重新生成数据，如果shuffle分片逻辑包含随机因子，会导致新生成的数据shuffle分片与之前不完全一致，进而导致部分数据重复读取或者数据丢失

• reduce task从每个map task的结果文件中拉取对应分区的数据。数据在map阶段已经是分好区了，并且会有一个额外的索引文件记录每个分区的起始偏移量。所以reducetask取数的时候直接根据偏移量去拉取数据。

• 新生成的shuffle分片内数据会丢数据，同时也会包含分发到其他reducer的数据。

map-only 和 mapReduce job输出小文件合并调优

map-only操作结束时小文件合并

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true; -- map-only结束时小文件合并
set hive.merge.mapredfiles = false; -- MR操作结束时，不合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
create table tmp.tmp_01 as
SELECT
      item_sku_id
FROM
      cdm.cdm_goods_360buy_act_basic_da
WHERE
      dt = '2022-02-15'
      AND barndname_cn = '汾酒'

结果：

2022-02-17 14:45:37 INFO Table tmp.tmp_ljjtest021 stats: [numFiles=1, numRows=18415, totalSize=110953, rawDataSize=1762456]

结果分析：

mapReduce操作结束时小文件合并

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = false; -- map-only结束时小文件不合并
set hive.merge.mapredfiles = true; -- MR操作结束时，合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
SELECT
      a.item_sku_id 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL;

结果：

2022-02-16 23:12:45 INFO Table tmp.tmp_01 stats: [numFiles=1, numRows=23, totalSize=426, rawDataSize=2235]

结果分析：

总结：

hive输出结果小文件问题调优

执行mapjoin,不合并小文件，不分组

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = false; --MR操作结束时，不合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
SELECT
      a.item_sku_id 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            --distribute by rand(1) -- 不分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL;

结果：

2022-02-17 16:53:18 INFO Table tmp.tmp_01 stats: [numFiles=18020, numRows=23, totalSize=887747, rawDataSize=2252]
2022-02-17 16:53:18 INFO MapReduce Jobs Launched:
2022-02-17 16:53:19 INFO Stage-4: Map: 18020   Cumulative CPU: 205038.93 sec   HDFS Read: 193.386 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 3m28s419ms job_8766029101801_36451400
2022-02-17 16:53:19 INFO 
2022-02-17 16:53:19 INFO Total MapReduce CPU Time Spent: 2d8h57m18s930ms
2022-02-17 16:53:19 INFO Total Map: 18020  Total Reduce: 0
2022-02-17 16:53:19 INFO Total HDFS Read: 193.386 GB  Written: 0.000 GB

结果分析：

执行mapjoin,不合并小文件,大表分组

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = false; --MR操作结束时，不合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
SELECT
      a.item_sku_id 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            --distribute by rand(1) -- 大表分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL;

结果：

2022-02-16 22:53:00 INFO Table tmp.tmp_01 stats: [numFiles=3, numRows=23, totalSize=958, rawDataSize=2235]
2022-02-16 22:53:00 INFO Stage-1: Map: 18024  Reduce: 1009   Cumulative CPU: 372613.35 sec   HDFS Read: 193.289 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 5m32s865ms job_5690061100801_32621522
2022-02-16 22:53:00 INFO Stage-10: Map: 924   Cumulative CPU: 5424.53 sec   HDFS Read: 0.008 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 41s846ms job_5690061100801_32621870
2022-02-16 22:53:00 INFO Stage-4: Map: 858   Cumulative CPU: 1374.95 sec   HDFS Read: 0.001 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 43s592ms job_5690061100801_32621913
2022-02-16 22:53:00 INFO Total MapReduce CPU Time Spent: 4d9h23m32s830ms
2022-02-16 22:53:00 INFO Total Map: 19806  Total Reduce: 1009
2022-02-16 22:53:00 INFO Total HDFS Read: 193.298 GB  Written: 0.000 GB

结果分析：

执行mapjoin,合并小文件

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = true; --MR操作结束时，合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

--指定tmp.tmp_01的文件存储格式，默认为textfile
set hive.default.fileformat = orc;

drop table if exists tmp.tmp_01;
create table tmp.tmp_01 
--STORED AS orc
as
SELECT
      a.item_sku_id 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            --distribute by rand(1) -- 不分组,因为此时分组毫无意义，只会徒增任务开销
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL;

结果：

2022-02-16 23:12:45 INFO Table tmp.tmp_01 stats: [numFiles=1, numRows=23, totalSize=426, rawDataSize=2235]
2022-02-16 23:12:45 INFO Stage-1: Map: 18024  Reduce: 1009   Cumulative CPU: 365693.05 sec   HDFS Read: 193.289 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 3m21s803ms job_5690061100801_32623163
2022-02-16 23:12:45 INFO Stage-10: Map: 918   Cumulative CPU: 5232.29 sec   HDFS Read: 0.008 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 40s544ms job_8766029101801_36250732
2022-02-16 23:12:45 INFO Stage-4: Map: 1   Cumulative CPU: 13.95 sec   HDFS Read: 0.000 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 43s762ms job_8766029101801_36250769
2022-02-16 23:12:45 INFO Total MapReduce CPU Time Spent: 4d7h2m19s290ms
2022-02-16 23:12:45 INFO Total Map: 18943  Total Reduce: 1009
2022-02-16 23:12:45 INFO Total HDFS Read: 193.297 GB  Written: 0.000 GB

结果分析：

总结：

开启输出结果小文件合并:
rcfile和orc需要特殊设置才能进行文级别的合并，parquet、textfile、sequencefile默认进行文件级别的合并

set hive.merge.mapfiles = true;--开启只有map（map-only）操作结束时小文件输出合并
set hive.merge.mapredfiles = true;--开启有map和reduce操作结束时小文件输出合并
set hive.merge.size.per.task = 256000000;--合并后每个文件的大小
set hive.merge.smallfiles.avgsize=256000000;--当输出文件的平均大小小于256000000时，启动一个独立的MR任务进行文件合并，触发小文件合并的阀值
set hive.merge.orcfile.stripe.level=false; --当这个参数设置为true,orc文件进行stripe Level级别的合并,当设置为false,orc文件进行文件级别的合并。
set hive.merge.rcfile.block.level=false;--当这个参数设置为true,rcfile文件进行block Level级别的合并,当设置为false,rcfile文件进行文件级别的合并。

hive中间过程(两个job之间)大量小文件的调优

不分组，不合并小文件

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = false;
set hive.merge.mapredfiles = false; --MR操作结束时，不合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

WITH tmp as 
(
SELECT
      a.* 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            --distribute by rand(1) -- 不分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL
)
create table tmp.tmp_01 
as
SELECT
c.item_sku_id
FROM tmp c
join small_table d
on c.item_sku_id=d.item_sku_id

结果：

2022-02-17 20:49:21 INFO Stage-8: Map: 18026   Cumulative CPU: 210204.23 sec   HDFS Read: 193.388 GB HDFS Write: 0.001 GB SUCCESS  Elapsed : 2m55s772ms job_5690061100801_32863650
2022-02-17 20:49:21 INFO Stage-6: Map: 472   Cumulative CPU: 3330.08 sec   HDFS Read: 0.334 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 50s42ms job_5690061100801_32865433
2022-02-17 20:49:21 INFO Total MapReduce CPU Time Spent: 2d11h18m54s310ms
2022-02-17 20:49:21 INFO Total Map: 18498  Total Reduce: 0
2022-02-17 20:49:21 INFO Total HDFS Read: 193.722 GB  Written: 0.001 GB

2022-02-17 20:49:22 INFO Time taken: 1045.892 seconds, Fetched: 46 row(s)
2022-02-17 20:49:23 INFO 任务结束! sql执行耗时 0 hour 17 mins 38 s

结果分析：

不分组，合并小文件

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = true; --MR操作结束时，合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

WITH tmp as 
(
SELECT
      a.* 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            --distribute by rand(1) -- 不分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL
)
create table tmp.tmp_01 
as
SELECT
c.item_sku_id
FROM tmp c
join small_table d
on c.item_sku_id=d.item_sku_id

结果：

2022-02-17 20:45:25 INFO Stage-8: Map: 18026   Cumulative CPU: 214628.08 sec   HDFS Read: 193.388 GB HDFS Write: 0.001 GB SUCCESS  Elapsed : 3m41s147ms job_8766029101801_36477823
2022-02-17 20:45:25 INFO Stage-6: Map: 472   Cumulative CPU: 3995.4 sec   HDFS Read: 0.334 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 59s677ms job_5690061100801_32865009
2022-02-17 20:45:25 INFO Total MapReduce CPU Time Spent: 2d12h43m43s480ms
2022-02-17 20:45:25 INFO Total Map: 18498  Total Reduce: 0
2022-02-17 20:45:25 INFO Total HDFS Read: 193.722 GB  Written: 0.001 GB

2022-02-17 20:45:27 INFO Time taken: 1074.534 seconds, Fetched: 46 row(s)
2022-02-17 20:45:27 INFO 任务结束! sql执行耗时 0 hour 18 mins 10 s

结果分析：

分组，合并小文件

set hive.auto.convert.join=true;
set hive.auto.convert.join.noconditionaltask=true;
set hive.auto.convert.join.noconditionaltask.size=10000000;
set hive.mapjoin.smalltable.filesize=200000000;

set hive.merge.mapfiles = true;
set hive.merge.mapredfiles = true; --MR操作结束时，合并小文件
set hive.merge.size.per.task = 256000000;
set hive.merge.smallfiles.avgsize = 256000000;
set hive.merge.orcfile.stripe.level=false;
set hive.merge.rcfile.block.level=false;

WITH tmp as 
(
SELECT
      a.* 
FROM  (
            SELECT
                    item_sku_id,sku_name,brandname_cn,data_type
            FROM big_table 
            WHERE dt = '2022-02-15' AND brandname_cn = '汾酒'
            distribute by rand(1) -- 分组
      ) a --数据量大小2T左右
LEFT OUTER JOIN
      (     SELECT item_sku_id 
            FROM small_table 
            WHERE version = '1' AND normal_brandname_en = 'fenjiu' AND dt = '2022-02-15'
      ) b --数据量大小小于10M
ON a.item_sku_id = b.item_sku_id
WHERE b.item_sku_id IS NULL
)
create table tmp.tmp_01 
as
SELECT
c.item_sku_id
FROM tmp c
join small_table d
on c.item_sku_id=d.item_sku_id

结果：

2022-02-17 19:57:57 INFO Stage-1: Map: 18026  Reduce: 1009   Cumulative CPU: 362544.56 sec   HDFS Read: 193.290 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 4m55s871ms job_5690061100801_32857972
2022-02-17 19:57:57 INFO Stage-9: Map: 928   Cumulative CPU: 5520.28 sec   HDFS Read: 0.008 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 2m33s752ms job_5690061100801_32858541
2022-02-17 19:57:57 INFO Stage-7: Map: 472   Cumulative CPU: 3638.63 sec   HDFS Read: 0.334 GB HDFS Write: 0.000 GB SUCCESS  Elapsed : 1m42s589ms job_5690061100801_32858927
2022-02-17 19:57:57 INFO Total MapReduce CPU Time Spent: 4d7h15m3s470ms
2022-02-17 19:57:57 INFO Total Map: 19426  Total Reduce: 1009
2022-02-17 19:57:57 INFO Total HDFS Read: 193.634 GB  Written: 0.000 GB

2022-02-17 19:57:58 INFO Time taken: 690.782 seconds, Fetched: 46 row(s)
2022-02-17 19:57:58 INFO 任务结束! sql执行耗时 0 hour 11 mins 44 s

结果分析：

总结：