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Problem Scenario 91 : You have been given data in json format as below.
{"first_name":"Ankit", "last_name":"Jain"}
{"first_name":"Amir", "last_name":"Khan"}
{"first_name":"Rajesh", "last_name":"Khanna"}
{"first_name":"Priynka", "last_name":"Chopra"}
{"first_name":"Kareena", "last_name":"Kapoor"}
{"first_name":"Lokesh", "last_name":"Yadav"}
Do the following activity
1. create employee.json tile locally.
2. Load this tile on hdfs
3. Register this data as a temp table in Spark using Python.
4. Write select query and print this data.
5. Now save back this selected data in json format.
Problem Scenario 86 : In Continuation of previous question, please accomplish following activities.
1. Select Maximum, minimum, average , Standard Deviation, and total quantity.
2. Select minimum and maximum price for each product code.
3. Select Maximum, minimum, average , Standard Deviation, and total quantity for each product code, hwoever make sure Average and Standarddeviation will have maximum two decimal values.
4. Select all the product code and average price only where product count is more than or equal to 3.
5. Select maximum, minimum , average and total of all the products for each code. Also produce the same across all the products.
Problem Scenario 85 : In Continuation of previous question, please accomplish following activities.
1. Select all the columns from product table with output header as below. productID AS ID
code AS Code name AS Description price AS 'Unit Price'
2. Select code and name both separated by ' -' and header name should be Product Description'.
3. Select all distinct prices.
4. Select distinct price and name combination.
5. Select all price data sorted by both code and productID combination.
6. count number of products.
7. Count number of products for each code.
Problem Scenario 69 : Write down a Spark Application using Python,
In which it read a file "Content.txt" (On hdfs) with following content.
And filter out the word which is less than 2 characters and ignore all empty lines.
Once doen store the filtered data in a directory called "problem84" (On hdfs)
Content.txt
Apache Spark Training
This is Spark Learning Session
Spark is faster than MapReduce
Problem Scenario 29 : Please accomplish the following exercises using HDFS command line options.
1. Create a directory in hdfs named hdfs_commands.
2. Create a file in hdfs named data.txt in hdfs_commands.
3. Now copy this data.txt file on local filesystem, however while copying file please make sure file properties are not changed e.g.file permissions.
4. Now create a file in local directory named data_local.txt and move this file to hdfs in hdfs_commands directory.
5. Create a file data_hdfs.txt in hdfs_commands directory and copy it to local file system.
6. Create a file in local filesystem named file1.txt and put it to hdfs
