May 20, at 4: Finally I have found something which helped me. Marcelino Egge May 26, at 9:
January 09, We know that Hadoop helps to store mass data, process and analyze the same very fast. It is not easy for non java developers to extract and analyze the data from Hadoop framework but with the development of Hive any non java database developers can easily do the data analysis quickly.
Pig which I have explained in my previous post can consider as alternative to Hive.
Pig was developed at Yahoo! To illustrate the Hive syntax and use, I thought it is best to load the data from Adventureworks DW database.
I followed below steps to load data from Adventureworks database to file and to Hadoop eco system. Pull the records from required tables to xlsx files 2.
Browse the csv file from Hadoop as shown in Fig 1 Fig 1 3. Select the file that need to be uploaded Fig 2 4. This will load the xls file into Hadoop Fig 3 5. Now we need to create metadata for this loaded data into Hadoop using HCatalog. Click on the create table option in left side of the HCatalog.
This will open the below window where you can select the already loaded file Fig 5 7. Once you enter, you can see below screen where you can provide the column name and the data type for each field. HCatalog automatically fixes data type for each field based on the data but we can change it based on our requirement.
Finally you can hit create table button to generate the final table.
Fig 7 Once the file is uploaded in Hadoop and created metadata using HCatalog, you can browse or analyze the data using hive.At the time, Thesis was one of the few themes to offer built-in SEO options, and it created an industry standard with those features.
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