Problem Scenario 96 : Your spark application required extra Java options as below. -XX:+PrintGCDetails-XX:+PrintGCTimeStamps
Please replace the XXX values correctly
./bin/spark-submit --name "My app" --master local[4] --conf spark.eventLog.enabled=talse --conf XXX hadoopexam.jar
Problem Scenario 8 : You have been given following mysql database details as well as other info.
Please accomplish following.
1. Import joined result of orders and order_items table join on orders.order_id = order_items.order_item_order_id.
2. Also make sure each tables file is partitioned in 2 files e.g. part-00000, part-00002
3. Also make sure you use orderid columns for sqoop to use for boundary conditions.
Problem Scenario 52 : You have been given below code snippet.
val b = sc.parallelize(List(1,2,3,4,5,6,7,8,2,4,2,1,1,1,1,1))
Operation_xyz
Write a correct code snippet for Operation_xyz which will produce below output. scalaxollection.Map[lnt,Long] = Map(5 -> 1, 8 -> 1, 3 -> 1, 6 -> 1, 1 -> S, 2 -> 3, 4 -> 2, 7 -> 1)
Problem Scenario GG : You have been given below code snippet.
val a = sc.parallelize(List("dog", "tiger", "lion", "cat", "spider", "eagle"), 2)
val b = a.keyBy(_.length)
val c = sc.parallelize(List("ant", "falcon", "squid"), 2)
val d = c.keyBy(.length)
operation 1
Write a correct code snippet for operationl which will produce desired output, shown below. Array[(lnt, String)] = Array((4,lion))
Problem Scenario 40 : You have been given sample data as below in a file called spark15/file1.txt
3070811,1963,1096,,"US","CA",,1,
3022811,1963,1096,,"US","CA",,1,56
3033811,1963,1096,,"US","CA",,1,23
Below is the code snippet to process this tile.
val field= sc.textFile("spark15/f ilel.txt")
val mapper = field.map(x=> A)
mapper.map(x => x.map(x=> {B})).collect
Please fill in A and B so it can generate below final output
Array(Array(3070811,1963,109G, 0, "US", "CA", 0,1, 0)
,Array(3022811,1963,1096, 0, "US", "CA", 0,1, 56)
,Array(3033811,1963,1096, 0, "US", "CA", 0,1, 23)
)
Problem Scenario 24 : You have been given below comma separated employee information.
Data Set:
name,salary,sex,age
alok,100000,male,29
jatin,105000,male,32
yogesh,134000,male,39
ragini,112000,female,35
jyotsana,129000,female,39
valmiki,123000,male,29
Requirements:
Use the netcat service on port 44444, and nc above data line by line. Please do the following activities.
1. Create a flume conf file using fastest channel, which write data in hive warehouse directory, in a table called flumemaleemployee (Create hive table as well tor given data).
2. While importing, make sure only male employee data is stored.
Problem Scenario 41 : You have been given below code snippet.
val aul = sc.parallelize(List (("a" , Array(1,2)), ("b" , Array(1,2))))
val au2 = sc.parallelize(List (("a" , Array(3)), ("b" , Array(2))))
Apply the Spark method, which will generate below output.
Array[(String, Array[lnt])] = Array((a,Array(1, 2)), (b,Array(1, 2)), (a(Array(3)), (b,Array(2)))
Problem Scenario 22 : You have been given below comma separated employee information.
name,salary,sex,age
alok,100000,male,29
jatin,105000,male,32
yogesh,134000,male,39
ragini,112000,female,35
jyotsana,129000,female,39
valmiki,123000,male,29
Use the netcat service on port 44444, and nc above data line by line. Please do the following activities.
1. Create a flume conf file using fastest channel, which write data in hive warehouse directory, in a table called flumeemployee (Create hive table as well tor given data).
2. Write a hive query to read average salary of all employees.
Problem Scenario 5 : You have been given following mysql database details.
user=retail_dba
password=cloudera
database=retail_db
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following activities.
1. List all the tables using sqoop command from retail_db
2. Write simple sqoop eval command to check whether you have permission to read database tables or not.
3. Import all the tables as avro files in /user/hive/warehouse/retail cca174.db
4. Import departments table as a text file in /user/cloudera/departments.
Problem Scenario 57 : You have been given below code snippet.
val a = sc.parallelize(1 to 9, 3) operationl
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(String, Seq[lnt])] = Array((even,ArrayBuffer(2, 4, G, 8)), (odd,ArrayBuffer(1, 3, 5, 7, 9)))
Problem Scenario 28 : You need to implement near real time solutions for collecting information when submitted in file with below
Data
echo "IBM,100,20160104" >> /tmp/spooldir2/.bb.txt
echo "IBM,103,20160105" >> /tmp/spooldir2/.bb.txt
mv /tmp/spooldir2/.bb.txt /tmp/spooldir2/bb.txt
After few mins
echo "IBM,100.2,20160104" >> /tmp/spooldir2/.dr.txt
echo "IBM,103.1,20160105" >> /tmp/spooldir2/.dr.txt
mv /tmp/spooldir2/.dr.txt /tmp/spooldir2/dr.txt
You have been given below directory location (if not available than create it) /tmp/spooldir2 .
As soon as file committed in this directory that needs to be available in hdfs in /tmp/flume/primary as well as /tmp/flume/secondary location.
However, note that/tmp/flume/secondary is optional, if transaction failed which writes in this directory need not to be rollback.
Write a flume configuration file named flumeS.conf and use it to load data in hdfs with following additional properties .
1. Spool /tmp/spooldir2 directory
2. File prefix in hdfs sholuld be events
3. File suffix should be .log
4. If file is not committed and in use than it should have _ as prefix.
5. Data should be written as text to hdfs
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TESTED 17 May 2024
