本節博主分享一個在工做中常常遇到的級聯求和出報表的案例。需求以下:centos
(1)有以下訪客訪問次數統計表 t_access_times服務器
訪客app |
月份ide |
訪問次數oop |
A大數據 |
2015-01url |
5spa |
Acode |
2015-01orm |
15 |
B |
2015-01 |
5 |
A |
2015-01 |
8 |
B |
2015-01 |
25 |
A |
2015-01 |
5 |
A |
2015-02 |
4 |
A |
2015-02 |
6 |
B |
2015-02 |
10 |
B |
2015-02 |
5 |
…… |
…… |
…… |
(2)須要輸出報表:t_access_times_accumulate
訪客 |
月份 |
月訪問總計 |
累計訪問總計 |
A |
2015-01 |
33 |
33 |
A |
2015-02 |
10 |
43 |
……. |
……. |
……. |
……. |
B |
2015-01 |
30 |
30 |
B |
2015-02 |
15 |
45 |
……. |
……. |
……. |
……. |
(3)實現步驟
create table t_access_times(username string,month string,salary int) row format delimited fields terminated by ','; load data local inpath '/home/hadoop/t_access_times.dat' into table t_access_times; A,2015-01,5 A,2015-01,15 B,2015-01,5 A,2015-01,8 B,2015-01,25 A,2015-01,5 A,2015-02,4 A,2015-02,6 B,2015-02,10 B,2015-02,5 一、第一步,先求個用戶的月總金額 select username,month,sum(salary) as salary from t_access_times group by username,month +-----------+----------+---------+--+ | username | month | salary | +-----------+----------+---------+--+ | A | 2015-01 | 33 | | A | 2015-02 | 10 | | B | 2015-01 | 30 | | B | 2015-02 | 15 | +-----------+----------+---------+--+ 二、第二步,將月總金額表 本身鏈接 本身鏈接 select * from (select username,month,sum(salary) as salary from t_access_times group by username,month) A inner join (select username,month,sum(salary) as salary from t_access_times group by username,month) B on A.username=B.username +-------------+----------+-----------+-------------+----------+-----------+--+ | a.username | a.month | a.salary | b.username | b.month | b.salary | +-------------+----------+-----------+-------------+----------+-----------+--+ | A | 2015-01 | 33 | A | 2015-01 | 33 | | A | 2015-01 | 33 | A | 2015-02 | 10 | | A | 2015-02 | 10 | A | 2015-01 | 33 | | A | 2015-02 | 10 | A | 2015-02 | 10 | | B | 2015-01 | 30 | B | 2015-01 | 30 | | B | 2015-01 | 30 | B | 2015-02 | 15 | | B | 2015-02 | 15 | B | 2015-01 | 30 | | B | 2015-02 | 15 | B | 2015-02 | 15 | +-------------+----------+-----------+-------------+----------+-----------+--+ 三、第三步,從上一步的結果中 進行分組查詢,分組的字段是a.username a.month 求月累計值: 將b.month <= a.month的全部b.salary求和便可 select A.username,A.month,max(A.salary) as salary,sum(B.salary) as accumulate from (select username,month,sum(salary) as salary from t_access_times group by username,month) A inner join (select username,month,sum(salary) as salary from t_access_times group by username,month) B on A.username=B.username where B.month <= A.month group by A.username,A.month order by A.username,A.month;
(4)操做效果
0: jdbc:hive2://centos-aaron-h1:10000> create table t_access_times(username string,month string,salary int) 0: jdbc:hive2://centos-aaron-h1:10000> row format delimited fields terminated by ','; OK No rows affected (0.908 seconds) 0: jdbc:hive2://centos-aaron-h1:10000> load data local inpath '/home/hadoop/t_access_times.dat' into table t_access_times; Loading data to table default.t_access_times Table default.t_access_times stats: [numFiles=1, totalSize=123] OK INFO : Loading data to table default.t_access_times from file:/home/hadoop/t_access_times.dat INFO : Table default.t_access_times stats: [numFiles=1, totalSize=123] No rows affected (2.88 seconds) 0: jdbc:hive2://centos-aaron-h1:10000> select username,month,sum(salary) as salary from t_access_times group by username,month; Query ID = hadoop_20190212052316_64866ab3-25a5-4f1e-8ae4-7b2dcfcc1c1f Total jobs = 1 Launching Job 1 out of 1 Number of reduce tasks not specified. Estimated from input data size: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> INFO : Number of reduce tasks not specified. Estimated from input data size: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0001, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0001/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0001 INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0001 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0001/ INFO : Starting Job = job_1549919838832_0001, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0001/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0001 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 2019-02-12 05:23:38,459 Stage-1 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:23:38,459 Stage-1 map = 0%, reduce = 0% 2019-02-12 05:23:55,144 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.51 sec INFO : 2019-02-12 05:23:55,144 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.51 sec 2019-02-12 05:24:01,293 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.37 sec INFO : 2019-02-12 05:24:01,293 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.37 sec MapReduce Total cumulative CPU time: 3 seconds 370 msec Ended Job = job_1549919838832_0001 MapReduce Jobs Launched: Stage-Stage-1: Map: 1 Reduce: 1 Cumulative CPU: 3.37 sec HDFS Read: 7681 HDFS Write: 52 SUCCESS Total MapReduce CPU Time Spent: 3 seconds 370 msec OK INFO : MapReduce Total cumulative CPU time: 3 seconds 370 msec INFO : Ended Job = job_1549919838832_0001 +-----------+----------+---------+--+ | username | month | salary | +-----------+----------+---------+--+ | A | 2015-01 | 33 | | A | 2015-02 | 10 | | B | 2015-01 | 30 | | B | 2015-02 | 15 | +-----------+----------+---------+--+ 4 rows selected (46.143 seconds) 0: jdbc:hive2://centos-aaron-h1:10000> select * 0: jdbc:hive2://centos-aaron-h1:10000> from 0: jdbc:hive2://centos-aaron-h1:10000> (select username,month,sum(salary) as salary from t_access_times group by username,month) A 0: jdbc:hive2://centos-aaron-h1:10000> inner join 0: jdbc:hive2://centos-aaron-h1:10000> (select username,month,sum(salary) as salary from t_access_times group by username,month) B 0: jdbc:hive2://centos-aaron-h1:10000> on 0: jdbc:hive2://centos-aaron-h1:10000> A.username=B.username; Query ID = hadoop_20190212052542_208d2ee5-d122-4a12-a0d6-aa6ec90e031a Total jobs = 5 Launching Job 1 out of 5 Number of reduce tasks not specified. Estimated from input data size: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0002, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0002/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0002 INFO : Number of reduce tasks not specified. Estimated from input data size: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0002 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0002/ INFO : Starting Job = job_1549919838832_0002, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0002/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0002 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 2019-02-12 05:25:55,359 Stage-1 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:25:55,359 Stage-1 map = 0%, reduce = 0% 2019-02-12 05:26:05,614 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.61 sec INFO : 2019-02-12 05:26:05,614 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 2.61 sec 2019-02-12 05:26:11,762 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.39 sec INFO : 2019-02-12 05:26:11,762 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.39 sec MapReduce Total cumulative CPU time: 3 seconds 390 msec Ended Job = job_1549919838832_0002 Launching Job 2 out of 5 Number of reduce tasks not specified. Estimated from input data size: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> INFO : MapReduce Total cumulative CPU time: 3 seconds 390 msec INFO : Ended Job = job_1549919838832_0002 INFO : Number of reduce tasks not specified. Estimated from input data size: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0003, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0003/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0003 INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0003 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0003/ INFO : Starting Job = job_1549919838832_0003, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0003/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0003 Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 1 2019-02-12 05:26:34,772 Stage-3 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:26:34,772 Stage-3 map = 0%, reduce = 0% 2019-02-12 05:26:43,958 Stage-3 map = 100%, reduce = 0%, Cumulative CPU 0.86 sec INFO : 2019-02-12 05:26:43,958 Stage-3 map = 100%, reduce = 0%, Cumulative CPU 0.86 sec 2019-02-12 05:26:52,127 Stage-3 map = 100%, reduce = 100%, Cumulative CPU 1.73 sec INFO : 2019-02-12 05:26:52,127 Stage-3 map = 100%, reduce = 100%, Cumulative CPU 1.73 sec MapReduce Total cumulative CPU time: 1 seconds 730 msec Ended Job = job_1549919838832_0003 Stage-7 is selected by condition resolver. Stage-8 is filtered out by condition resolver. Stage-2 is filtered out by condition resolver. Execution log at: /tmp/hadoop/hadoop_20190212052542_208d2ee5-d122-4a12-a0d6-aa6ec90e031a.log INFO : MapReduce Total cumulative CPU time: 1 seconds 730 msec INFO : Ended Job = job_1549919838832_0003 INFO : Stage-7 is selected by condition resolver. INFO : Stage-8 is filtered out by condition resolver. INFO : Stage-2 is filtered out by condition resolver. 2019-02-12 05:26:58 Starting to launch local task to process map join; maximum memory = 518979584 2019-02-12 05:26:59 Dump the side-table for tag: 1 with group count: 2 into file: file:/tmp/hadoop/2d536889-8e64-4ece-91b9-6ae10c4ff631/hive_2019-02-12_05-25-42_429_4168125726438328049-1/-local-10005/HashTable-Stage-4/MapJoin-mapfile01--.hashtable 2019-02-12 05:26:59 Uploaded 1 File to: file:/tmp/hadoop/2d536889-8e64-4ece-91b9-6ae10c4ff631/hive_2019-02-12_05-25-42_429_4168125726438328049-1/-local-10005/HashTable-Stage-4/MapJoin-mapfile01--.hashtable (346 bytes) 2019-02-12 05:26:59 End of local task; Time Taken: 1.103 sec. Execution completed successfully MapredLocal task succeeded Launching Job 4 out of 5 Number of reduce tasks is set to 0 since there's no reduce operator INFO : Execution completed successfully INFO : MapredLocal task succeeded INFO : Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1549919838832_0004, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0004/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0004 INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0004 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0004/ INFO : Starting Job = job_1549919838832_0004, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0004/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0004 Hadoop job information for Stage-4: number of mappers: 1; number of reducers: 0 2019-02-12 05:27:14,062 Stage-4 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-4: number of mappers: 1; number of reducers: 0 INFO : 2019-02-12 05:27:14,062 Stage-4 map = 0%, reduce = 0% 2019-02-12 05:27:22,362 Stage-4 map = 100%, reduce = 0%, Cumulative CPU 0.83 sec INFO : 2019-02-12 05:27:22,362 Stage-4 map = 100%, reduce = 0%, Cumulative CPU 0.83 sec MapReduce Total cumulative CPU time: 830 msec Ended Job = job_1549919838832_0004 MapReduce Jobs Launched: Stage-Stage-1: Map: 1 Reduce: 1 Cumulative CPU: 3.39 sec HDFS Read: 7283 HDFS Write: 208 SUCCESS Stage-Stage-3: Map: 1 Reduce: 1 Cumulative CPU: 1.73 sec HDFS Read: 7285 HDFS Write: 208 SUCCESS Stage-Stage-4: Map: 1 Cumulative CPU: 0.83 sec HDFS Read: 5188 HDFS Write: 208 SUCCESS Total MapReduce CPU Time Spent: 5 seconds 950 msec OK INFO : MapReduce Total cumulative CPU time: 830 msec INFO : Ended Job = job_1549919838832_0004 +-------------+----------+-----------+-------------+----------+-----------+--+ | a.username | a.month | a.salary | b.username | b.month | b.salary | +-------------+----------+-----------+-------------+----------+-----------+--+ | A | 2015-01 | 33 | A | 2015-01 | 33 | | A | 2015-01 | 33 | A | 2015-02 | 10 | | A | 2015-02 | 10 | A | 2015-01 | 33 | | A | 2015-02 | 10 | A | 2015-02 | 10 | | B | 2015-01 | 30 | B | 2015-01 | 30 | | B | 2015-01 | 30 | B | 2015-02 | 15 | | B | 2015-02 | 15 | B | 2015-01 | 30 | | B | 2015-02 | 15 | B | 2015-02 | 15 | +-------------+----------+-----------+-------------+----------+-----------+--+ 8 rows selected (101.008 seconds) 0: jdbc:hive2://centos-aaron-h1:10000> 0: jdbc:hive2://centos-aaron-h1:10000> select A.username,A.month,max(A.salary) as salary,sum(B.salary) as accumulate 0: jdbc:hive2://centos-aaron-h1:10000> from 0: jdbc:hive2://centos-aaron-h1:10000> (select username,month,sum(salary) as salary from t_access_times group by username,month) A 0: jdbc:hive2://centos-aaron-h1:10000> inner join 0: jdbc:hive2://centos-aaron-h1:10000> (select username,month,sum(salary) as salary from t_access_times group by username,month) B 0: jdbc:hive2://centos-aaron-h1:10000> on 0: jdbc:hive2://centos-aaron-h1:10000> A.username=B.username 0: jdbc:hive2://centos-aaron-h1:10000> where B.month <= A.month 0: jdbc:hive2://centos-aaron-h1:10000> group by A.username,A.month 0: jdbc:hive2://centos-aaron-h1:10000> order by A.username,A.month; Query ID = hadoop_20190212053047_a2bcb673-b252-4277-85dd-8085248520aa Total jobs = 7 Launching Job 1 out of 7 Number of reduce tasks not specified. Estimated from input data size: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0005, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0005/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0005 INFO : Number of reduce tasks not specified. Estimated from input data size: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0005 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0005/ INFO : Starting Job = job_1549919838832_0005, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0005/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0005 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 2019-02-12 05:30:59,370 Stage-1 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:30:59,370 Stage-1 map = 0%, reduce = 0% 2019-02-12 05:31:06,540 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.49 sec INFO : 2019-02-12 05:31:06,540 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.49 sec 2019-02-12 05:31:12,653 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 2.29 sec INFO : 2019-02-12 05:31:12,653 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 2.29 sec MapReduce Total cumulative CPU time: 2 seconds 290 msec Ended Job = job_1549919838832_0005 Launching Job 2 out of 7 Number of reduce tasks not specified. Estimated from input data size: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0006, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0006/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0006 INFO : MapReduce Total cumulative CPU time: 2 seconds 290 msec INFO : Ended Job = job_1549919838832_0005 INFO : Number of reduce tasks not specified. Estimated from input data size: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0006 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0006/ INFO : Starting Job = job_1549919838832_0006, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0006/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0006 Hadoop job information for Stage-5: number of mappers: 1; number of reducers: 1 2019-02-12 05:31:37,597 Stage-5 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-5: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:31:37,597 Stage-5 map = 0%, reduce = 0% 2019-02-12 05:31:49,323 Stage-5 map = 100%, reduce = 0%, Cumulative CPU 3.24 sec INFO : 2019-02-12 05:31:49,323 Stage-5 map = 100%, reduce = 0%, Cumulative CPU 3.24 sec 2019-02-12 05:31:55,512 Stage-5 map = 100%, reduce = 100%, Cumulative CPU 4.02 sec MapReduce Total cumulative CPU time: 4 seconds 20 msec Ended Job = job_1549919838832_0006 Stage-9 is selected by condition resolver. Stage-10 is filtered out by condition resolver. Stage-2 is filtered out by condition resolver. INFO : 2019-02-12 05:31:55,512 Stage-5 map = 100%, reduce = 100%, Cumulative CPU 4.02 sec INFO : MapReduce Total cumulative CPU time: 4 seconds 20 msec INFO : Ended Job = job_1549919838832_0006 INFO : Stage-9 is selected by condition resolver. INFO : Stage-10 is filtered out by condition resolver. INFO : Stage-2 is filtered out by condition resolver. Execution log at: /tmp/hadoop/hadoop_20190212053047_a2bcb673-b252-4277-85dd-8085248520aa.log 2019-02-12 05:32:00 Starting to launch local task to process map join; maximum memory = 518979584 2019-02-12 05:32:01 Dump the side-table for tag: 1 with group count: 2 into file: file:/tmp/hadoop/e8520f79-8d60-4b0e-a593-b9cfbad8463e/hive_2019-02-12_05-30-47_300_154987026293528311-4/-local-10007/HashTable-Stage-6/MapJoin-mapfile21--.hashtable 2019-02-12 05:32:01 Uploaded 1 File to: file:/tmp/hadoop/e8520f79-8d60-4b0e-a593-b9cfbad8463e/hive_2019-02-12_05-30-47_300_154987026293528311-4/-local-10007/HashTable-Stage-6/MapJoin-mapfile21--.hashtable (346 bytes) 2019-02-12 05:32:01 End of local task; Time Taken: 0.824 sec. Execution completed successfully MapredLocal task succeeded Launching Job 4 out of 7 Number of reduce tasks is set to 0 since there's no reduce operator INFO : Execution completed successfully INFO : MapredLocal task succeeded INFO : Number of reduce tasks is set to 0 since there's no reduce operator Starting Job = job_1549919838832_0007, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0007/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0007 INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0007 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0007/ INFO : Starting Job = job_1549919838832_0007, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0007/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0007 Hadoop job information for Stage-6: number of mappers: 1; number of reducers: 0 2019-02-12 05:32:16,644 Stage-6 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-6: number of mappers: 1; number of reducers: 0 INFO : 2019-02-12 05:32:16,644 Stage-6 map = 0%, reduce = 0% 2019-02-12 05:32:27,075 Stage-6 map = 100%, reduce = 0%, Cumulative CPU 1.06 sec INFO : 2019-02-12 05:32:27,075 Stage-6 map = 100%, reduce = 0%, Cumulative CPU 1.06 sec MapReduce Total cumulative CPU time: 1 seconds 60 msec Ended Job = job_1549919838832_0007 Launching Job 5 out of 7 Number of reduce tasks not specified. Estimated from input data size: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0008, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0008/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0008 INFO : MapReduce Total cumulative CPU time: 1 seconds 60 msec INFO : Ended Job = job_1549919838832_0007 INFO : Number of reduce tasks not specified. Estimated from input data size: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0008 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0008/ INFO : Starting Job = job_1549919838832_0008, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0008/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0008 Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 1 2019-02-12 05:32:44,584 Stage-3 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:32:44,584 Stage-3 map = 0%, reduce = 0% 2019-02-12 05:32:56,191 Stage-3 map = 100%, reduce = 0%, Cumulative CPU 2.87 sec INFO : 2019-02-12 05:32:56,191 Stage-3 map = 100%, reduce = 0%, Cumulative CPU 2.87 sec 2019-02-12 05:33:02,318 Stage-3 map = 100%, reduce = 100%, Cumulative CPU 3.62 sec INFO : 2019-02-12 05:33:02,318 Stage-3 map = 100%, reduce = 100%, Cumulative CPU 3.62 sec MapReduce Total cumulative CPU time: 3 seconds 620 msec Ended Job = job_1549919838832_0008 Launching Job 6 out of 7 Number of reduce tasks determined at compile time: 1 In order to change the average load for a reducer (in bytes): set hive.exec.reducers.bytes.per.reducer=<number> In order to limit the maximum number of reducers: set hive.exec.reducers.max=<number> In order to set a constant number of reducers: set mapreduce.job.reduces=<number> Starting Job = job_1549919838832_0009, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0009/ Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0009 INFO : MapReduce Total cumulative CPU time: 3 seconds 620 msec INFO : Ended Job = job_1549919838832_0008 INFO : Number of reduce tasks determined at compile time: 1 INFO : In order to change the average load for a reducer (in bytes): INFO : set hive.exec.reducers.bytes.per.reducer=<number> INFO : In order to limit the maximum number of reducers: INFO : set hive.exec.reducers.max=<number> INFO : In order to set a constant number of reducers: INFO : set mapreduce.job.reduces=<number> INFO : number of splits:1 INFO : Submitting tokens for job: job_1549919838832_0009 INFO : The url to track the job: http://centos-aaron-h1:8088/proxy/application_1549919838832_0009/ INFO : Starting Job = job_1549919838832_0009, Tracking URL = http://centos-aaron-h1:8088/proxy/application_1549919838832_0009/ INFO : Kill Command = /home/hadoop/apps/hadoop-2.9.1/bin/hadoop job -kill job_1549919838832_0009 Hadoop job information for Stage-4: number of mappers: 1; number of reducers: 1 2019-02-12 05:33:15,716 Stage-4 map = 0%, reduce = 0% INFO : Hadoop job information for Stage-4: number of mappers: 1; number of reducers: 1 INFO : 2019-02-12 05:33:15,716 Stage-4 map = 0%, reduce = 0% 2019-02-12 05:33:22,868 Stage-4 map = 100%, reduce = 0%, Cumulative CPU 0.75 sec INFO : 2019-02-12 05:33:22,868 Stage-4 map = 100%, reduce = 0%, Cumulative CPU 0.75 sec 2019-02-12 05:33:28,985 Stage-4 map = 100%, reduce = 100%, Cumulative CPU 1.59 sec MapReduce Total cumulative CPU time: 1 seconds 590 msec Ended Job = job_1549919838832_0009 MapReduce Jobs Launched: Stage-Stage-1: Map: 1 Reduce: 1 Cumulative CPU: 2.29 sec HDFS Read: 7284 HDFS Write: 208 SUCCESS Stage-Stage-5: Map: 1 Reduce: 1 Cumulative CPU: 4.02 sec HDFS Read: 7284 HDFS Write: 208 SUCCESS Stage-Stage-6: Map: 1 Cumulative CPU: 1.06 sec HDFS Read: 5638 HDFS Write: 212 SUCCESS Stage-Stage-3: Map: 1 Reduce: 1 Cumulative CPU: 3.62 sec HDFS Read: 5420 HDFS Write: 212 SUCCESS Stage-Stage-4: Map: 1 Reduce: 1 Cumulative CPU: 1.59 sec HDFS Read: 5597 HDFS Write: 64 SUCCESS Total MapReduce CPU Time Spent: 12 seconds 580 msec OK INFO : 2019-02-12 05:33:28,985 Stage-4 map = 100%, reduce = 100%, Cumulative CPU 1.59 sec INFO : MapReduce Total cumulative CPU time: 1 seconds 590 msec INFO : Ended Job = job_1549919838832_0009 +-------------+----------+---------+-------------+--+ | a.username | a.month | salary | accumulate | +-------------+----------+---------+-------------+--+ | A | 2015-01 | 33 | 33 | | A | 2015-02 | 10 | 43 | | B | 2015-01 | 30 | 30 | | B | 2015-02 | 15 | 45 | +-------------+----------+---------+-------------+--+ 4 rows selected (162.792 seconds) 0: jdbc:hive2://centos-aaron-h1:10000>
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