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Big Data
Processing
Training,
R&DPower by Data Cloud Lab
[Bigdata isa fieldthattreats ways to analyze, systematically extract
informationfrom,orotherwisedeal withdata sets that are too large
or complex to be dealt with by traditional data-processing
application software. Big data was originally associated with three
key concepts: volume, variety, and velocity.]
Data Set – 1M Data:
1. Healthcare_ [Record – 46935]
2. Weather-history - [Record – 4573]
3. World Demography - [Record – 5000]
4. Census Tracts 2010 - [Record -21
5. Animal_Services_Intake_Data - [Record -187594]
6. Average_Daily_Traffic_Counts - [Record -1280]
7. Acciental_Durg_Related_Death - [Record -5106]
8. Retails Store - [Record – 182728]
customer12435,category_59,Departments_7,orders_68883,products_1345,order_items_99999
9. Popular_Baby_Names - [Record – 46935]
10. SAT__College_Board__2010_School_Level_Results - Total Data [Record -461]
11. Sales_Tax_Rates - [Record -1911]
12. Restaurants [Record -1328]
13. Transportation : 34_drivers , 17076_truck_event_text_partition , 1768_timesheet - [Record -
18878]
14. Acciental_Durg_Related_Death - [Record -5106]
15. Census Tracts 2010 - [Record -216]
16. Employees_Salary - [Record – 824]
17. Customer_transactional_spending - [Record – 60000]
18. Customer_Order - [Record – 1000]
19. Employees_Salary - [Record – 824]
Power by: Software Linux, Hadoop Big Data, Hive & Power BI)
Case Study 01: Healthcare [Record – 46935]
Raw Data (Date, Sex, Diseases, Age) :
12/10/1950,M,Diabetes,78
12/10/1984,F,PCOS,67
712/11/1940,M,Fever,90
12/12/1950,F,Cold,88
12/13/1960,M,Blood Pressure,76
Result :
Blood Pressure,5215
Cold,5215
Diabetes,5215
Fever,15645
Malaria,5215
PCOS,5215
Swine Flu,5215
Data Visualizations:
Backend Data Process by HiveQL command:
select diseases, count(*) from healthgroupby diseases;
WARNING: Hive-on-MR is deprecated inHive2 and may not beavailableinthefuture versions. Considerusing a different execution engine(i.e.
spark, tez) or using Hive 1.X releases.
Query ID =hduser_20200125220715_338a065f-f176-4464-b03e-28fb18dc66f5
Total jobs =1
Launching Job 1 outof1
Number ofreducetasks not specified. Estimated frominputdata size: 1
In order to changethe average load for a reducer (inbytes): , set hive.exec.reducers.bytes.per.reducer=<number>
In order to limitthemaximum number ofreducers: , sethive.exec.reducers.max=<number>
In order to set a constant numberofreducers: , setmapreduce.job.reduces=<number>
Job running in-process (localHadoop) , 2020-01-25 22:07:18,630Stage-1 map =100%, reduce=100%
Ended Job =job_local171670995_0001, Moving data to localdirectory /home/hduser/Dataset
MapReduceJobs Launched: , Stage-Stage-1: HDFS Read:2336322 HDFS Write: 0 SUCCESS, TotalMapReduce CPU TimeSpent:0 msec, OK
Time taken: 3.617seconds

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Data cloud-lab-version-v0012020

  • 1. Big Data Processing Training, R&DPower by Data Cloud Lab [Bigdata isa fieldthattreats ways to analyze, systematically extract informationfrom,orotherwisedeal withdata sets that are too large or complex to be dealt with by traditional data-processing application software. Big data was originally associated with three key concepts: volume, variety, and velocity.]
  • 2. Data Set – 1M Data: 1. Healthcare_ [Record – 46935] 2. Weather-history - [Record – 4573] 3. World Demography - [Record – 5000] 4. Census Tracts 2010 - [Record -21 5. Animal_Services_Intake_Data - [Record -187594] 6. Average_Daily_Traffic_Counts - [Record -1280] 7. Acciental_Durg_Related_Death - [Record -5106] 8. Retails Store - [Record – 182728] customer12435,category_59,Departments_7,orders_68883,products_1345,order_items_99999 9. Popular_Baby_Names - [Record – 46935] 10. SAT__College_Board__2010_School_Level_Results - Total Data [Record -461] 11. Sales_Tax_Rates - [Record -1911] 12. Restaurants [Record -1328] 13. Transportation : 34_drivers , 17076_truck_event_text_partition , 1768_timesheet - [Record - 18878] 14. Acciental_Durg_Related_Death - [Record -5106] 15. Census Tracts 2010 - [Record -216] 16. Employees_Salary - [Record – 824] 17. Customer_transactional_spending - [Record – 60000] 18. Customer_Order - [Record – 1000] 19. Employees_Salary - [Record – 824]
  • 3. Power by: Software Linux, Hadoop Big Data, Hive & Power BI) Case Study 01: Healthcare [Record – 46935] Raw Data (Date, Sex, Diseases, Age) : 12/10/1950,M,Diabetes,78 12/10/1984,F,PCOS,67 712/11/1940,M,Fever,90 12/12/1950,F,Cold,88 12/13/1960,M,Blood Pressure,76 Result : Blood Pressure,5215 Cold,5215 Diabetes,5215 Fever,15645 Malaria,5215 PCOS,5215 Swine Flu,5215 Data Visualizations: Backend Data Process by HiveQL command: select diseases, count(*) from healthgroupby diseases; WARNING: Hive-on-MR is deprecated inHive2 and may not beavailableinthefuture versions. Considerusing a different execution engine(i.e. spark, tez) or using Hive 1.X releases. Query ID =hduser_20200125220715_338a065f-f176-4464-b03e-28fb18dc66f5 Total jobs =1 Launching Job 1 outof1 Number ofreducetasks not specified. Estimated frominputdata size: 1 In order to changethe average load for a reducer (inbytes): , set hive.exec.reducers.bytes.per.reducer=<number> In order to limitthemaximum number ofreducers: , sethive.exec.reducers.max=<number> In order to set a constant numberofreducers: , setmapreduce.job.reduces=<number> Job running in-process (localHadoop) , 2020-01-25 22:07:18,630Stage-1 map =100%, reduce=100% Ended Job =job_local171670995_0001, Moving data to localdirectory /home/hduser/Dataset MapReduceJobs Launched: , Stage-Stage-1: HDFS Read:2336322 HDFS Write: 0 SUCCESS, TotalMapReduce CPU TimeSpent:0 msec, OK Time taken: 3.617seconds