CCA175 Exam Dumps : CCA Spark and Hadoop Developer Exam

Solution :

Step 1 : Create directory mkdir /tmp/spooldir/bb mkdir /tmp/spooldir/dr

Step 2 : Create flume configuration file, with below configuration for

agent1.sources = source1 source2

agent1 .sinks = sink1

agent1.channels = channel1

agent1 .sources.source1.channels = channel1

agentl .sources.source2.channels = channell agent1 .sinks.sinkl.channel = channell

agent1 .sources.source1.type = spooldir

agent1 .sources.sourcel.spoolDir = /tmp/spooldir/bb

agent1 .sources.source2.type = spooldir

agent1 .sources.source2.spoolDir = /tmp/spooldir/dr

agent1 .sinks.sink1.type = hdfs

agent1 .sinks.sink1.hdfs.path = /tmp/flume/finance

agent1-sinks.sink1.hdfs.filePrefix = events

agent1.sinks.sink1.hdfs.fileSuffix = .log

agent1 .sinks.sink1.hdfs.inUsePrefix = _

agent1 .sinks.sink1.hdfs.fileType = Data Stream

agent1.channels.channel1.type = file

Step 4 : Run below command which will use this configuration file and append data in hdfs.

Start flume service:

flume-ng agent -conf /home/cloudera/flumeconf -conf-file /home/cloudera/fIumeconf/fIume7.conf --name agent1

Step 5 : Open another terminal and create a file in /tmp/spooldir/

echo "IBM,100,20160104" » /tmp/spooldir/bb/.bb.txt

echo "IBM,103,20160105" » /tmp/spooldir/bb/.bb.txt mv /tmp/spooldir/bb/.bb.txt /tmp/spooldir/bb/bb.txt

After few mins

echo "IBM,100.2,20160104" » /tmp/spooldir/dr/.dr.txt

echo "IBM,103.1,20160105" »/tmp/spooldir/dr/.dr.txt mv /tmp/spooldir/dr/.dr.txt /tmp/spooldir/dr/dr.txt

Solution :

Step 1 : Create hive table as said.

hive

show tables;

create table departments_hive(department_id int, department_name string);

Step 2 : The important here is, when we create a table without delimiter fields. Then default delimiter for hive is ^A (\001). Hence, while importing data we have to provide proper delimiter.

sqoop import \

-connect jdbc:mysql://quickstart:3306/retail_db \

~username=retail_dba \

-password=cloudera \

--table departments \

--hive-home /user/hive/warehouse \

-hive-import \

-hive-overwrite \

--hive-table departments_hive \

--fields-terminated-by '\001'

Step 3 : Check-the data in directory.

hdfs dfs -Is /user/hive/warehouse/departments_hive

hdfs dfs -cat/user/hive/warehouse/departmentshive/part'

Check data in hive table.

Select * from departments_hive;

Solution :

Step 1 : Create 2 files first using Hue in hdfs.

Step 2 : Load all file as an RDD

val technology = sc.textFile(Msparkl2/technology.txt").map(e => e.splitf',"))

val salary = sc.textFile("spark12/salary.txt").map(e => e.split("."))

Step 3 : Now create Key.value pair of data and join them.

val joined = technology.map(e=>((e(0),e(1)),e(2))).join(salary.map(e=>((e(0),e(1)),e(2))))

Step 4 : Save the results in a text file as below.

joined.repartition(1).saveAsTextFile("spark12/multiColumn Joined.txt")