Write an application using HBase and HiveQL for OnlineRetail Dataset which will include
i. Create and Load table with Online Retail data in Hive.
j. Create Index on Online Retail Table in Hive.
k. Find the total, average sales in Hive
l. Find Order details with maximum cost.
m. Find Customer details with maximum order total.
n. Find the Country with maximum and minimum sale.
o. Creating an external Hive table to connect to the HBase for OnlineRetail.
p. Display records of OnlineRetail Table in Hbase.










[cloudera@quickstart ~]$ hive

Logging initialized using configuration in file:/etc/hive/conf.dist/hive-log4j.properties
WARNING: Hive CLI is deprecated and migration to Beeline is recommended.

i. Create and Load table with Online Retail data in Hive.

hive> create table OnlineRetail(
    > InvoiceNo string,
    > StockCode string,
    > Description string,
    > Quantity int
    > , UnitPrice double,
    > CustomerID int,
    > Country string)
    > row format delimited
    > fields terminated by ','
    > stored as textfile;
OK
Time taken: 2.465 seconds
hive> load data local inpath '/home/cloudera/onlineRetail.csv' into table OnlineRetail
    > ;
Loading data to table default.onlineretail
Table default.onlineretail stats: [numFiles=1, totalSize=522]
OK
Time taken: 2.355 seconds
hive> select * from OnlineRetail;
OK
536365	A452	Abracadabra Bag	5	2.99	17850	United Kingdom
536366	B123	Bubblegum Bracelet	3	1.5	17851	United Kingdom
536367	C789	Crystal Crown	1	9.99	17852	France
536368	D987	Dragon Earrings	2	4.75	17853	Germany
536369	E654	Enchanted Necklace	1	12.99	17854	France
536370	F321	Fairy Dust Powder	4	3.25	17855	Germany
536371	G111	Golden Ring	2	15.5	17856	United Kingdom
536372	H222	Harmony Pendant	1	8.49	17857	France
536373	I333	Infinity Bangle	3	6.75	17858	United Kingdom
536374	J444	Jewel Box	1	18.99	17859	Germany
Time taken: 2.041 seconds, Fetched: 10 row(s)


j. Create Index on Online Retail Table in Hive.


hive> create index olindex on table OnlineRetail(InvoiceNo) as 'compact' with deferred rebuild;
OK
Time taken: 0.79 seconds


hive> show index on OnlineRetail;
OK
olindex             	onlineretail        	invoiceno           	default__onlineretail_olindex__	compact             	
Time taken: 0.209 seconds, Fetched: 1 row(s)


k. Find the total, average sales in Hive


hive> select sum(Quantity * UnitPrice) as total, avg(Quantity*UnitPrice) as average from Onlineretail;

Query ID = cloudera_20240508085454_43f57c68-d234-4d5d-bb51-2e22adab46be
Total jobs = 1
Launching Job 1 out of 1
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_1715074264747_0035, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0035/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0035
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2024-05-08 08:54:35,740 Stage-1 map = 0%,  reduce = 0%
2024-05-08 08:54:55,231 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 5.52 sec
2024-05-08 08:55:13,899 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 10.25 sec
MapReduce Total cumulative CPU time: 10 seconds 250 msec
Ended Job = job_1715074264747_0035
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 10.25 sec   HDFS Read: 9891 HDFS Write: 14 SUCCESS
Total MapReduce CPU Time Spent: 10 seconds 250 msec
OK
143.66	14.366
Time taken: 69.659 seconds, Fetched: 1 row(s)



l. Find Order details with maximum cost.


hive> select * from
    > (select InvoiceNo, sum(Quantity*UnitPrice) as totalcost from OnlineRetail group by InvoiceNo)
    > as ordercost
    > order by totalcost desc
    > limit 1;
Query ID = cloudera_20240508090404_7d5888d9-f87b-49f6-b423-f4e71493b406
Total jobs = 2
Launching Job 1 out of 2
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_1715074264747_0037, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0037/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0037
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2024-05-08 09:04:50,409 Stage-1 map = 0%,  reduce = 0%
2024-05-08 09:05:11,188 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 5.61 sec
2024-05-08 09:05:30,084 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 10.3 sec
MapReduce Total cumulative CPU time: 10 seconds 300 msec
Ended Job = job_1715074264747_0037
Launching Job 2 out of 2
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_1715074264747_0038, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0038/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0038
Hadoop job information for Stage-2: number of mappers: 1; number of reducers: 1
2024-05-08 09:05:51,639 Stage-2 map = 0%,  reduce = 0%
2024-05-08 09:06:08,128 Stage-2 map = 100%,  reduce = 0%, Cumulative CPU 2.2 sec
2024-05-08 09:06:24,029 Stage-2 map = 100%,  reduce = 100%, Cumulative CPU 6.28 sec
MapReduce Total cumulative CPU time: 6 seconds 280 msec
Ended Job = job_1715074264747_0038
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 10.3 sec   HDFS Read: 8442 HDFS Write: 416 SUCCESS
Stage-Stage-2: Map: 1  Reduce: 1   Cumulative CPU: 6.28 sec   HDFS Read: 4930 HDFS Write: 12 SUCCESS
Total MapReduce CPU Time Spent: 16 seconds 580 msec
OK
536371	31.0
Time taken: 124.986 seconds, Fetched: 1 row(s)



m. Find Customer details with maximum order total.


hive> select CustomerID, sum(Quantity*UnitPrice) as totalcost
    > from OnlineRetail
    > group by CustomerID
    > order by totalcost desc
    > limit 1;
Query ID = cloudera_20240508091111_549bc540-37c6-467d-a85e-573f8dff8040
Total jobs = 2
Launching Job 1 out of 2
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_1715074264747_0039, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0039/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0039
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2024-05-08 09:11:32,760 Stage-1 map = 0%,  reduce = 0%
2024-05-08 09:11:49,979 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 4.52 sec
2024-05-08 09:12:08,572 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 8.7 sec
MapReduce Total cumulative CPU time: 8 seconds 700 msec
Ended Job = job_1715074264747_0039
Launching Job 2 out of 2
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_1715074264747_0040, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0040/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0040
Hadoop job information for Stage-2: number of mappers: 1; number of reducers: 1
2024-05-08 09:12:28,230 Stage-2 map = 0%,  reduce = 0%
2024-05-08 09:12:44,335 Stage-2 map = 100%,  reduce = 0%, Cumulative CPU 2.89 sec
2024-05-08 09:13:00,546 Stage-2 map = 100%,  reduce = 100%, Cumulative CPU 6.71 sec
MapReduce Total cumulative CPU time: 6 seconds 710 msec
Ended Job = job_1715074264747_0040
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 8.7 sec   HDFS Read: 8444 HDFS Write: 376 SUCCESS
Stage-Stage-2: Map: 1  Reduce: 1   Cumulative CPU: 6.71 sec   HDFS Read: 4854 HDFS Write: 11 SUCCESS
Total MapReduce CPU Time Spent: 15 seconds 410 msec
OK
17856	31.0
Time taken: 111.778 seconds, Fetched: 1 row(s)


n. Find the Country with maximum and minimum sale.


maximum:

hive> select country, sum(Quantity * UnitPrice) as totalsale
    > from OnlineRetail
    > group by Country
    > order by totalsale desc
    > limit 1;
Query ID = cloudera_20240508091616_90fb1520-9802-4d0c-ac49-d57d9a9c03f9
Total jobs = 2
Launching Job 1 out of 2
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_1715074264747_0041, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0041/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0041
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2024-05-08 09:17:17,795 Stage-1 map = 0%,  reduce = 0%
2024-05-08 09:17:36,627 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 5.73 sec
2024-05-08 09:17:57,036 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 9.75 sec
MapReduce Total cumulative CPU time: 9 seconds 750 msec
Ended Job = job_1715074264747_0041
Launching Job 2 out of 2
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_1715074264747_0042, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0042/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0042
Hadoop job information for Stage-2: number of mappers: 1; number of reducers: 1
2024-05-08 09:18:18,080 Stage-2 map = 0%,  reduce = 0%
2024-05-08 09:18:34,071 Stage-2 map = 100%,  reduce = 0%, Cumulative CPU 3.15 sec
2024-05-08 09:18:54,376 Stage-2 map = 100%,  reduce = 100%, Cumulative CPU 7.14 sec
MapReduce Total cumulative CPU time: 7 seconds 140 msec
Ended Job = job_1715074264747_0042
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 9.75 sec   HDFS Read: 8439 HDFS Write: 201 SUCCESS
Stage-Stage-2: Map: 1  Reduce: 1   Cumulative CPU: 7.14 sec   HDFS Read: 4694 HDFS Write: 20 SUCCESS
Total MapReduce CPU Time Spent: 16 seconds 890 msec
OK
United Kingdom	70.7
Time taken: 119.42 seconds, Fetched: 1 row(s)



minimum:

hive> select country, sum(Quantity * UnitPrice) as totalsale
    > from OnlineRetail
    > group by Country
    > order by totalsale asc
    > limit 1;
Query ID = cloudera_20240508092020_1462005e-e33d-491e-9157-a17a6fb013e9
Total jobs = 2
Launching Job 1 out of 2
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_1715074264747_0043, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0043/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0043
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2024-05-08 09:20:33,229 Stage-1 map = 0%,  reduce = 0%
2024-05-08 09:20:51,658 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 5.35 sec
2024-05-08 09:21:13,155 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 10.05 sec
MapReduce Total cumulative CPU time: 10 seconds 50 msec
Ended Job = job_1715074264747_0043
Launching Job 2 out of 2
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_1715074264747_0044, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0044/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0044
Hadoop job information for Stage-2: number of mappers: 1; number of reducers: 1
2024-05-08 09:21:41,131 Stage-2 map = 0%,  reduce = 0%
2024-05-08 09:22:07,286 Stage-2 map = 100%,  reduce = 0%, Cumulative CPU 4.4 sec
2024-05-08 09:22:32,281 Stage-2 map = 100%,  reduce = 100%, Cumulative CPU 8.94 sec
MapReduce Total cumulative CPU time: 8 seconds 940 msec
Ended Job = job_1715074264747_0044
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1  Reduce: 1   Cumulative CPU: 10.05 sec   HDFS Read: 8439 HDFS Write: 201 SUCCESS
Stage-Stage-2: Map: 1  Reduce: 1   Cumulative CPU: 8.94 sec   HDFS Read: 4694 HDFS Write: 13 SUCCESS
Total MapReduce CPU Time Spent: 18 seconds 990 msec
OK
France	31.47
Time taken: 146.091 seconds, Fetched: 1 row(s)









Creating an external Hive table to connect to the HBase for OnlineRetail.


hive> create external table OnlineRetailHbase(
    > InvoiceNo string,
    > StockCode string,
    > Description string,
    > Quantity int,
    > UnitPrice double,
    > CustomerID int,
    > Country string)
    > stored by 'org.apache.hadoop.hive.hbase.HBaseStorageHandler'
    > with serdeproperties(
    > "hbase.columns.mapping" = "
    > :key,OnlineRetail:stock_code,OnlineRetail:description,OnlineRetail:quantity,OnlineRetail:unitprice,OnlineRetail:custID,OnlineRetail:country")
    > tblproperties("hbase.table.name"="OnlineRetailRecords");
OK
Time taken: 3.481 seconds
hive> insert into OnlineRetailHbase 
    > select * from OnlineRetail;
Query ID = cloudera_20240508092929_553763c6-2bd0-43ca-aa25-faac42255956
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1715074264747_0045, Tracking URL = http://quickstart.cloudera:8088/proxy/application_1715074264747_0045/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1715074264747_0045
Hadoop job information for Stage-0: number of mappers: 1; number of reducers: 0
2024-05-08 09:29:42,983 Stage-0 map = 0%,  reduce = 0%
2024-05-08 09:30:09,130 Stage-0 map = 100%,  reduce = 0%, Cumulative CPU 4.9 sec
MapReduce Total cumulative CPU time: 4 seconds 900 msec
Ended Job = job_1715074264747_0045
MapReduce Jobs Launched: 
Stage-Stage-0: Map: 1   Cumulative CPU: 5.77 sec   HDFS Read: 12053 HDFS Write: 0 SUCCESS
Total MapReduce CPU Time Spent: 5 seconds 770 msec
OK
Time taken: 54.055 seconds
hive> select * from OnlineRetailHbase;
OK
536365	A452	Abracadabra Bag	5	2.99	17850	United Kingdom
536366	B123	Bubblegum Bracelet	3	1.5	17851	United Kingdom
536367	C789	Crystal Crown	1	9.99	17852	France
536368	D987	Dragon Earrings	2	4.75	17853	Germany
536369	E654	Enchanted Necklace	1	12.99	17854	France
536370	F321	Fairy Dust Powder	4	3.25	17855	Germany
536371	G111	Golden Ring	2	15.5	17856	United Kingdom
536372	H222	Harmony Pendant	1	8.49	17857	France
536373	I333	Infinity Bangle	3	6.75	17858	United Kingdom
536374	J444	Jewel Box	1	18.99	17859	Germany
Time taken: 0.293 seconds, Fetched: 10 row(s)






p. Display records of OnlineRetail Table in Hbase.


hbase(main):001:0> create 'OnlineRetailRecords','OnlineRetail'
0 row(s) in 3.0470 seconds

=> Hbase::Table - OnlineRetailRecords
hbase(main):002:0> list
TABLE                                                                                                                                  
CustomerInfo                                                                                                                           
OnlineRetailRecords                                                                                                                    
flight                                                                                                                                 
3 row(s) in 0.1020 seconds

=> ["CustomerInfo", "OnlineRetailRecords", "flight"]
hbase(main):003:0> scan 'OnlineRetailRecords'
ROW                                COLUMN+CELL                                                                                         
 536365                            column=OnlineRetail:country, timestamp=1715185808954, value=United Kingdom                          
 536365                            column=OnlineRetail:custID, timestamp=1715185808954, value=17850                                    
 536365                            column=OnlineRetail:description, timestamp=1715185808954, value=Abracadabra Bag                     
 536365                            column=OnlineRetail:quantity, timestamp=1715185808954, value=5                                      
 536365                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=A452                                 
 536365                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=2.99                                  
 536366                            column=OnlineRetail:country, timestamp=1715185808954, value=United Kingdom                          
 536366                            column=OnlineRetail:custID, timestamp=1715185808954, value=17851                                    
 536366                            column=OnlineRetail:description, timestamp=1715185808954, value=Bubblegum Bracelet                  
 536366                            column=OnlineRetail:quantity, timestamp=1715185808954, value=3                                      
 536366                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=B123                                 
 536366                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=1.5                                   
 536367                            column=OnlineRetail:country, timestamp=1715185808954, value=France                                  
 536367                            column=OnlineRetail:custID, timestamp=1715185808954, value=17852                                    
 536367                            column=OnlineRetail:description, timestamp=1715185808954, value=Crystal Crown                       
 536367                            column=OnlineRetail:quantity, timestamp=1715185808954, value=1                                      
 536367                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=C789                                 
 536367                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=9.99                                  
 536368                            column=OnlineRetail:country, timestamp=1715185808954, value=Germany                                 
 536368                            column=OnlineRetail:custID, timestamp=1715185808954, value=17853                                    
 536368                            column=OnlineRetail:description, timestamp=1715185808954, value=Dragon Earrings                     
 536368                            column=OnlineRetail:quantity, timestamp=1715185808954, value=2                                      
 536368                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=D987                                 
 536368                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=4.75                                  
 536369                            column=OnlineRetail:country, timestamp=1715185808954, value=France                                  
 536369                            column=OnlineRetail:custID, timestamp=1715185808954, value=17854                                    
 536369                            column=OnlineRetail:description, timestamp=1715185808954, value=Enchanted Necklace                  
 536369                            column=OnlineRetail:quantity, timestamp=1715185808954, value=1                                      
 536369                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=E654                                 
 536369                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=12.99                                 
 536370                            column=OnlineRetail:country, timestamp=1715185808954, value=Germany                                 
 536370                            column=OnlineRetail:custID, timestamp=1715185808954, value=17855                                    
 536370                            column=OnlineRetail:description, timestamp=1715185808954, value=Fairy Dust Powder                   
 536370                            column=OnlineRetail:quantity, timestamp=1715185808954, value=4                                      
 536370                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=F321                                 
 536370                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=3.25                                  
 536371                            column=OnlineRetail:country, timestamp=1715185808954, value=United Kingdom                          
 536371                            column=OnlineRetail:custID, timestamp=1715185808954, value=17856                                    
 536371                            column=OnlineRetail:description, timestamp=1715185808954, value=Golden Ring                         
 536371                            column=OnlineRetail:quantity, timestamp=1715185808954, value=2                                      
 536371                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=G111                                 
 536371                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=15.5                                  
 536372                            column=OnlineRetail:country, timestamp=1715185808954, value=France                                  
 536372                            column=OnlineRetail:custID, timestamp=1715185808954, value=17857                                    
 536372                            column=OnlineRetail:description, timestamp=1715185808954, value=Harmony Pendant                     
 536372                            column=OnlineRetail:quantity, timestamp=1715185808954, value=1                                      
 536372                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=H222                                 
 536372                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=8.49                                  
 536373                            column=OnlineRetail:country, timestamp=1715185808954, value=United Kingdom                          
 536373                            column=OnlineRetail:custID, timestamp=1715185808954, value=17858                                    
 536373                            column=OnlineRetail:description, timestamp=1715185808954, value=Infinity Bangle                     
 536373                            column=OnlineRetail:quantity, timestamp=1715185808954, value=3                                      
 536373                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=I333                                 
 536373                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=6.75                                  
 536374                            column=OnlineRetail:country, timestamp=1715185808954, value=Germany                                 
 536374                            column=OnlineRetail:custID, timestamp=1715185808954, value=17859                                    
 536374                            column=OnlineRetail:description, timestamp=1715185808954, value=Jewel Box                           
 536374                            column=OnlineRetail:quantity, timestamp=1715185808954, value=1                                      
 536374                            column=OnlineRetail:stock_code, timestamp=1715185808954, value=J444                                 
 536374                            column=OnlineRetail:unitprice, timestamp=1715185808954, value=18.99                                 
10 row(s) in 0.4870 seconds
