{"id":66,"date":"2022-05-15T15:27:43","date_gmt":"2022-05-15T15:27:43","guid":{"rendered":"https:\/\/blog.topexamcollection.com\/?p=66"},"modified":"2022-05-15T15:27:43","modified_gmt":"2022-05-15T15:27:43","slug":"may-15-2022-cca175-exam-dumps-try-best-cca175-exam-questions-topexamcollection-q16-q40","status":"publish","type":"post","link":"https:\/\/blog.topexamcollection.com\/zh\/2022\/05\/may-15-2022-cca175-exam-dumps-try-best-cca175-exam-questions-topexamcollection-q16-q40\/","title":{"rendered":"[May 15, 2022] CCA175 Exam Dumps &#8211; Try Best CCA175 Exam Questions &#8211; TopExamCollection [Q16-Q40]"},"content":{"rendered":"\n\n<div class=\"kk-star-ratings kksr-auto kksr-align-left kksr-valign-top\"\n    data-payload='{&quot;align&quot;:&quot;left&quot;,&quot;id&quot;:&quot;66&quot;,&quot;slug&quot;:&quot;default&quot;,&quot;valign&quot;:&quot;top&quot;,&quot;ignore&quot;:&quot;&quot;,&quot;reference&quot;:&quot;auto&quot;,&quot;class&quot;:&quot;&quot;,&quot;count&quot;:&quot;1&quot;,&quot;legendonly&quot;:&quot;&quot;,&quot;readonly&quot;:&quot;&quot;,&quot;score&quot;:&quot;4&quot;,&quot;starsonly&quot;:&quot;&quot;,&quot;best&quot;:&quot;5&quot;,&quot;gap&quot;:&quot;5&quot;,&quot;greet&quot;:&quot;Rate this post&quot;,&quot;legend&quot;:&quot;4\\\/5 - (1 vote)&quot;,&quot;size&quot;:&quot;24&quot;,&quot;title&quot;:&quot;[May 15, 2022] CCA175 Exam Dumps - Try Best CCA175 Exam Questions - TopExamCollection [Q16-Q40]&quot;,&quot;width&quot;:&quot;113.5&quot;,&quot;_legend&quot;:&quot;{score}\\\/{best} - ({count} {votes})&quot;,&quot;font_factor&quot;:&quot;1.25&quot;}'>\n            \n<div class=\"kksr-stars\">\n    \n<div class=\"kksr-stars-inactive\">\n            <div class=\"kksr-star\" data-star=\"1\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"2\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"3\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"4\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"5\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n    <\/div>\n    \n<div class=\"kksr-stars-active\" style=\"width: 113.5px;\">\n            <div class=\"kksr-star\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-right: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 24px; height: 24px;\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n                \n\n<div class=\"kksr-legend\" style=\"font-size: 19.2px;\">\n            4\/5 - (1 vote)    <\/div>\n    <\/div>\n<p><span style=\"font-size: 18px\"><strong><span style=\"color: red\">[May 15, 2022] CCA175 Exam Dumps &#8211; Try Best CCA175 Exam Questions &#8211; TopExamCollection<\/span><\/strong><\/span><\/p>\n<p><strong><span style=\"color: red\">Verified CCA175 exam dumps Q&amp;As with Correct 96 Questions and Answers<\/span><\/strong><\/p>\n<p><\/p>\n<h3>Cloudera Certified Advanced Architect- Data Engineer Exam Technical review<\/h3>\n<p>Coding of CCA175 exam questions is sufficient to get success in the exam. Correct answers are being prepared in the most appropriate manner. Covers all the key points of CCA175 exam questions<\/p>\n<p><\/p>\n<h3>What are the steps involved in taking the CCA Spark and Hadoop Developer (CCA175) Exam<\/h3>\n<p>There are various steps involved in taking the CCA Spark and Hadoop Developer (CCA175) Exam. These steps will help you to know how the exam will be given to you. These steps will also guide you to your success in the test. Formats of the exam are Computer based testing (CBT), Performance-Based hands-on testing (PBT) and Web-based testing (WBT). All formats might be used in the exam. Your success is guaranteed if you choose PBT or WBT format. Started with preparation materials helps you for success for the exam. Application is also available for the preparation materials. Queries of candidates are answered through these materials. Solutions to these problems will be helpful for you to get more confidence in the exam. <strong>Cloudera CCA175 exam dumps<\/strong> questions can also help you. This is needed for better understanding of the test. Confidence will increase when you get good marks in the CCA Spark and Hadoop Developer (CCA175) Exam prep materials.<\/p>\n<p>Updated test materials are available in these preparation materials. Values and advantages of these materials will be helpful for you to get success in the exam. Check the requirements of the exam as per the Cloudera exam. Simulator for CCA Spark and Hadoop Developer (CCA175) Exam Prep Materials is available in these preparation materials. This simulator will be helpful to you to gain knowledge of the test. Loaded practices in the preparation materials will be helpful for you to gain knowledge of the test.<\/p>\n<p>&nbsp;<\/p>\n<div id=\"watu_quiz\" class=\"quiz-area single-page-quiz\">\n<form action=\"\" method=\"post\" class=\"quiz-form \" id=\"quiz-31\" >\n<div class='watu-question' id='question-1'><div class='question-content'><p><strong>NEW QUESTION 16<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 60 : You have been given below code snippet.<br \/>val a = sc.parallelize(List(&#8220;dog&#8221;, &#8220;salmon&#8221;, &#8220;salmon&#8221;, &#8220;rat&#8221;, &#8220;elephant&#8221;}, 3} val b = a.keyBy(_.length) val c = sc.parallelize(List(&#8220;dog&#8221;,&#8221;cat&#8221;,&#8221;gnu&#8221;,&#8221;salmon&#8221;,&#8221;rabbit&#8221;,&#8221;turkey&#8221;,&#8221;woif&#8221;,&#8221;bear&#8221;,&#8221;bee&#8221;), 3) val d = c.keyBy(_.length) operation1<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[(lnt, (String, String))] = Array((6,(salmon,salmon)), (6,(salmon,rabbit)),<br \/>(6,(salmon,turkey)), (6,(salmon,salmon)), (6,(salmon,rabbit)),<br \/>(6,(salmon,turkey)), (3,(dog,dog)), (3,(dog,cat)), (3,(dog,gnu)), (3,(dog,bee)), (3,(rat,dog)),<br \/>(3,(rat,cat)), (3,(rat,gnu)), (3,(rat,bee)))<\/p>\n<\/div><input type='hidden' name='question_id[]' value='599' \/><textarea name='answer-599[]' rows='5' cols='40' id='textarea_q_599' class='watu-textarea watu-textarea-1'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>solution:<br\/>b.join(d).collect<br\/>join [Pair]: Performs an inner join using two key-value RDDs. Please note that the keys must be generally comparable to make this work. keyBy : Constructs two-component tuples<br\/>(key-value pairs) by applying a function on each data item. The result of the function becomes the data item becomes the key and the original value of the newly created tuples.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(1,this)' id='btn-1' value='See Answer'  \/><input type='hidden' id='questionType1' value='textarea' class=''><\/div><div class='watu-question' id='question-2'><div class='question-content'><p><strong>NEW QUESTION 17<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 96 : Your spark application required extra Java options as below. &#8211;<br \/>XX:+PrintGCDetails-XX:+PrintGCTimeStamps<br \/>Please replace the XXX values correctly<br \/>.\/bin\/spark-submit &#8211;name &#8220;My app&#8221; &#8211;master local[4] &#8211;conf spark.eventLog.enabled=talse &#8211;<br \/>-conf XXX hadoopexam.jar<\/p>\n<\/div><input type='hidden' name='question_id[]' value='600' \/><textarea name='answer-600[]' rows='5' cols='40' id='textarea_q_600' class='watu-textarea watu-textarea-2'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution<br\/>XXX: Mspark.executoi\\extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps&#8221;<br\/>Notes: .\/bin\/spark-submit \\<br\/>&#8211;class &lt;maln-class&gt;<br\/>&#8211;master &lt;master-url&gt; \\<br\/>&#8211;deploy-mode &lt;deploy-mode&gt; \\<br\/>-conf &lt;key&gt;=&lt;value&gt; \\<br\/># other options<br\/>&lt; application-jar&gt; \\<br\/>[application-arguments]<br\/>Here, conf is used to pass the Spark related contigs which are required for the application to run like any specific property(executor memory) or if you want to override the default property which is set in Spark-default.conf.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(2,this)' id='btn-2' value='See Answer'  \/><input type='hidden' id='questionType2' value='textarea' class=''><\/div><div class='watu-question' id='question-3'><div class='question-content'><p><strong>NEW QUESTION 18<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 55 : You have been given below code snippet.<br \/>val pairRDDI = sc.parallelize(List( (&#8220;cat&#8221;,2), (&#8220;cat&#8221;, 5), (&#8220;book&#8221;, 4),(&#8220;cat&#8221;, 12))) val pairRDD2 = sc.parallelize(List( (&#8220;cat&#8221;,2), (&#8220;cup&#8221;, 5), (&#8220;mouse&#8221;, 4),(&#8220;cat&#8221;, 12))) operation1<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[(String, (Option[lnt], Option[lnt]))] = Array((book,(Some(4},None)),<br \/>(mouse,(None,Some(4))), (cup,(None,Some(5))), (cat,(Some(2),Some(2)),<br \/>(cat,(Some(2),Some(12))), (cat,(Some(5),Some(2))), (cat,(Some(5),Some(12))),<br \/>(cat,(Some(12),Some(2))), (cat,(Some(12),Some(12)))J<\/p>\n<\/div><input type='hidden' name='question_id[]' value='601' \/><textarea name='answer-601[]' rows='5' cols='40' id='textarea_q_601' class='watu-textarea watu-textarea-3'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution : pairRDD1.fullOuterJoin(pairRDD2).collect<br\/>fullOuterJoin [Pair]<br\/>Performs the full outer join between two paired RDDs.<br\/>Listing Variants<br\/>def fullOuterJoin[W](other: RDD[(K, W)], numPartitions: Int): RDD[(K, (Option[V],<br\/>OptionfW]))]<br\/>def fullOuterJoin[W](other: RDD[(K, W}]}: RDD[(K, (Option[V], OptionfW]))] def fullOuterJoin[W](other: RDD[(K, W)], partitioner: Partitioner): RDD[(K, (Option[V],<br\/>Option[W]))]<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(3,this)' id='btn-3' value='See Answer'  \/><input type='hidden' id='questionType3' value='textarea' class=''><\/div><div class='watu-question' id='question-4'><div class='question-content'><p><strong>NEW QUESTION 19<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 70 : Write down a Spark Application using Python, In which it read a file &#8220;Content.txt&#8221; (On hdfs) with following content. Do the word count and save the results in a directory called &#8220;problem85&#8221; (On hdfs)<br \/>Content.txt<br \/>Hello this is ABCTECH.com<br \/>This is XYZTECH.com<br \/>Apache Spark Training<br \/>This is Spark Learning Session<br \/>Spark is faster than MapReduce<\/p>\n<\/div><input type='hidden' name='question_id[]' value='602' \/><textarea name='answer-602[]' rows='5' cols='40' id='textarea_q_602' class='watu-textarea watu-textarea-4'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Create an application with following code and store it in problem84.py<br\/># Import SparkContext and SparkConf<br\/>from pyspark import SparkContext, SparkConf<br\/># Create configuration object and set App name<br\/>conf = SparkConf().setAppName(&#8220;CCA 175 Problem 85&#8221;) sc = sparkContext(conf=conf)<br\/>#load data from hdfs<br\/>contentRDD = sc.textFile(MContent.txt&#8221;)<br\/>#filter out non-empty lines<br\/>nonemptyjines = contentRDD.filter(lambda x: len(x) &gt; 0)<br\/>#Split line based on space<br\/>words = nonempty_lines.ffatMap(lambda x: x.split(&#8221;}}<br\/>#Do the word count<br\/>wordcounts = words.map(lambda x: (x, 1)) \\<br\/>reduceByKey(lambda x, y: x+y) \\<br\/>map(lambda x: (x[1], x[0]}}.sortByKey(False}<br\/>for word in wordcounts.collect(): print(word)<br\/>#Save final data &#8221; wordcounts.saveAsTextFile(&#8220;problem85&#8221;)<br\/>step 2 : Submit this application<br\/>spark-submit -master yarn problem85.py<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(4,this)' id='btn-4' value='See Answer'  \/><input type='hidden' id='questionType4' value='textarea' class=''><\/div><div class='watu-question' id='question-5'><div class='question-content'><p><strong>NEW QUESTION 20<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 19 : You have been given following mysql database details as well as other info.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Now accomplish following activities.<br \/>1. Import departments table from mysql to hdfs as textfile in departments_text directory.<br \/>2. Import departments table from mysql to hdfs as sequncefile in departments_sequence directory.<br \/>3. Import departments table from mysql to hdfs as avro file in departments avro directory.<br \/>4. Import departments table from mysql to hdfs as parquet file in departments_parquet directory.<\/p>\n<\/div><input type='hidden' name='question_id[]' value='603' \/><textarea name='answer-603[]' rows='5' cols='40' id='textarea_q_603' class='watu-textarea watu-textarea-5'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Import departments table from mysql to hdfs as textfile<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:3306\/retail_db \\<br\/>~ username=retail_dba \\<br\/>-password=cloudera \\<br\/>-table departments \\<br\/>-as-textfile \\<br\/>-target-dir=departments_text<br\/>verify imported data<br\/>hdfs dfs -cat departments_text\/part&#8221;<br\/>Step 2 : Import departments table from mysql to hdfs as sequncetlle<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:330G\/retaiI_db \\<br\/>~ username=retail_dba \\<br\/>-password=cloudera \\<br\/>&#8211;table departments \\<br\/>-as-sequencetlle \\<br\/>-~target-dir=departments sequence<br\/>verify imported data<br\/>hdfs dfs -cat departments_sequence\/part*<br\/>Step 3 : Import departments table from mysql to hdfs as sequncetlle<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:330G\/retaiI_db \\<br\/>~ username=retail_dba \\<br\/>&#8211;password=cloudera \\<br\/>&#8211;table departments \\<br\/>&#8211;as-avrodatafile \\<br\/>&#8211;target-dir=departments_avro<br\/>verify imported data<br\/>hdfs dfs -cat departments avro\/part*<br\/>Step 4 : Import departments table from mysql to hdfs as sequncetlle<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:330G\/retaiI_db \\<br\/>~ username=retail_dba \\<br\/>&#8211;password=cloudera \\<br\/>-table departments \\<br\/>-as-parquetfile \\<br\/>-target-dir=departments_parquet<br\/>verify imported data<br\/>hdfs dfs -cat departmentsparquet\/part*<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(5,this)' id='btn-5' value='See Answer'  \/><input type='hidden' id='questionType5' value='textarea' class=''><\/div><div class='watu-question' id='question-6'><div class='question-content'><p><strong>NEW QUESTION 21<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 30 : You have been given three csv files in hdfs as below.<br \/>EmployeeName.csv with the field (id, name)<br \/>EmployeeManager.csv (id, manager Name)<br \/>EmployeeSalary.csv (id, Salary)<br \/>Using Spark and its API you have to generate a joined output as below and save as a text tile (Separated by comma) for final distribution and output must be sorted by id.<br \/>ld,name,salary,managerName<br \/>EmployeeManager.csv<br \/>E01,Vishnu<br \/>E02,Satyam<br \/>E03,Shiv<br \/>E04,Sundar<br \/>E05,John<br \/>E06,Pallavi<br \/>E07,Tanvir<br \/>E08,Shekhar<br \/>E09,Vinod<br \/>E10,Jitendra<br \/>EmployeeName.csv<br \/>E01,Lokesh<br \/>E02,Bhupesh<br \/>E03,Amit<br \/>E04,Ratan<br \/>E05,Dinesh<br \/>E06,Pavan<br \/>E07,Tejas<br \/>E08,Sheela<br \/>E09,Kumar<br \/>E10,Venkat<br \/>EmployeeSalary.csv<br \/>E01,50000<br \/>E02,50000<br \/>E03,45000<br \/>E04,45000<br \/>E05,50000<br \/>E06,45000<br \/>E07,50000<br \/>E08,10000<br \/>E09,10000<br \/>E10,10000<\/p>\n<\/div><input type='hidden' name='question_id[]' value='604' \/><textarea name='answer-604[]' rows='5' cols='40' id='textarea_q_604' class='watu-textarea watu-textarea-6'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Create all three files in hdfs in directory called sparkl (We will do using Hue}.<br\/>However, you can first create in local filesystem and then<br\/>Step 2 : Load EmployeeManager.csv file from hdfs and create PairRDDs<br\/>val manager = sc.textFile(&#8220;spark1\/EmployeeManager.csv&#8221;)<br\/>val managerPairRDD = manager.map(x=&gt; (x.split(&#8220;,&#8221;)(0),x.split(&#8220;,&#8221;)(1)))<br\/>Step 3 : Load EmployeeName.csv file from hdfs and create PairRDDs<br\/>val name = sc.textFile(&#8220;spark1\/EmployeeName.csv&#8221;)<br\/>val namePairRDD = name.map(x=&gt; (x.split(&#8220;,&#8221;)(0),x.split(&#8216;\\&#8221;)(1)))<br\/>Step 4 : Load EmployeeSalary.csv file from hdfs and create PairRDDs<br\/>val salary = sc.textFile(&#8220;spark1\/EmployeeSalary.csv&#8221;)<br\/>val salaryPairRDD = salary.map(x=&gt; (x.split(&#8220;,&#8221;)(0),x.split(&#8220;,&#8221;)(1)))<br\/>Step 4 : Join all pairRDDS<br\/>val joined = namePairRDD.join(salaryPairRDD}.join(managerPairRDD}<br\/>Step 5 : Now sort the joined results, val joinedData = joined.sortByKey()<br\/>Step 6 : Now generate comma separated data.<br\/>val finalData = joinedData.map(v=&gt; (v._1, v._2._1._1, v._2._1._2, v._2._2))<br\/>Step 7 : Save this output in hdfs as text file.<br\/>finalData.saveAsTextFile(&#8220;spark1\/result.txt&#8221;)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(6,this)' id='btn-6' value='See Answer'  \/><input type='hidden' id='questionType6' value='textarea' class=''><\/div><div class='watu-question' id='question-7'><div class='question-content'><p><strong>NEW QUESTION 22<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 53 : You have been given below code snippet.<br \/>val a = sc.parallelize(1 to 10, 3)<br \/>operation1<br \/>b.collect<br \/>Output 1<br \/>Array[lnt] = Array(2, 4, 6, 8,10)<br \/>operation2<br \/>Output 2<br \/>Array[lnt] = Array(1,2, 3)<br \/>Write a correct code snippet for operation1 and operation2 which will produce desired output, shown above.<\/p>\n<\/div><input type='hidden' name='question_id[]' value='605' \/><textarea name='answer-605[]' rows='5' cols='40' id='textarea_q_605' class='watu-textarea watu-textarea-7'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>valb = a.filter(_%2==0)<br\/>a.filter(_ &lt; 4).collect<br\/>filter<br\/>Evaluates a boolean function for each data item of the RDD and puts the items for which the function returned true into the resulting RDD.<br\/>When you provide a filter function, it must be able to handle all data items contained in the<br\/>RDD. Scala provides so-called partial functions to deal with mixed data types (Tip: Partial functions to deal are very useful if you have some data which may be bad and you do not want to handle but for the good data (matching data) you want to apply some Kind of map function. The following article is good. It teaches you about partial functions in a very nice way and explains why case has to be used for partial functions:article)<br\/>Examples for mixed data without partial functions<br\/>val b = sc.parallelize(1 to 8)<br\/>b.filter(_ &lt; 4)xollect<br\/>res15: Arrayjlnt] = Array(1, 2, 3)<br\/>val a = sc.parallelize(List(&#8220;cat&#8217;\\ &#8220;horse&#8221;, 4.0, 3.5, 2, &#8220;dog&#8221;))<br\/>a.filter(_&lt;4).collect<br\/>error: value &lt; is not a member of Any<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(7,this)' id='btn-7' value='See Answer'  \/><input type='hidden' id='questionType7' value='textarea' class=''><\/div><div class='watu-question' id='question-8'><div class='question-content'><p><strong>NEW QUESTION 23<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 16 : You have been given following mysql database details as well as other info.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Please accomplish below assignment.<br \/>1. Create a table in hive as below.<br \/>create table departments_hive(department_id int, department_name string);<br \/>2. Now import data from mysql table departments to this hive table. Please make sure that data should be visible using below hive command, select&#8221; from departments_hive<\/p>\n<\/div><input type='hidden' name='question_id[]' value='606' \/><textarea name='answer-606[]' rows='5' cols='40' id='textarea_q_606' class='watu-textarea watu-textarea-8'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Create hive table as said.<br\/>hive<br\/>show tables;<br\/>create table departments_hive(department_id int, department_name string);<br\/>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.<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:3306\/retail_db \\<br\/>~ username=retail_dba \\<br\/>-password=cloudera \\<br\/>&#8211;table departments \\<br\/>&#8211;hive-home \/user\/hive\/warehouse \\<br\/>-hive-import \\<br\/>-hive-overwrite \\<br\/>&#8211;hive-table departments_hive \\<br\/>&#8211;fields-terminated-by &#8216;\\001&#8217;<br\/>Step 3 : Check-the data in directory.<br\/>hdfs dfs -Is \/user\/hive\/warehouse\/departments_hive<br\/>hdfs dfs -cat\/user\/hive\/warehouse\/departmentshive\/part&#8217;<br\/>Check data in hive table.<br\/>Select * from departments_hive;<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(8,this)' id='btn-8' value='See Answer'  \/><input type='hidden' id='questionType8' value='textarea' class=''><\/div><div class='watu-question' id='question-9'><div class='question-content'><p><strong>NEW QUESTION 24<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 15 : You have been given following mysql database details as well as other info.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Please accomplish following activities.<br \/>1. In mysql departments table please insert following record. Insert into departments values(9999, &#8216;&#8221;Data Science&#8221;1);<br \/>2. Now there is a downstream system which will process dumps of this file. However, system is designed the way that it can process only files if fields are enlcosed in(&#8216;) single quote and separate of the field should be (-} and line needs to be terminated by : (colon).<br \/>3. If data itself contains the &#8221; (double quote } than it should be escaped by .<br \/>4. Please import the departments table in a directory called departments_enclosedby and file should be able to process by downstream system.<\/p>\n<\/div><input type='hidden' name='question_id[]' value='607' \/><textarea name='answer-607[]' rows='5' cols='40' id='textarea_q_607' class='watu-textarea watu-textarea-9'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Connect to mysql database.<br\/>mysql &#8211;user=retail_dba -password=cloudera<br\/>show databases; use retail_db; show tables;<br\/>Insert record<br\/>Insert into departments values(9999, &#8216;&#8221;Data Science&#8221;&#8216;);<br\/>select&#8221; from departments;<br\/>Step 2 : Import data as per requirement.<br\/>sqoop import \\<br\/>-connect jdbc:mysql;\/\/quickstart:3306\/retail_db \\<br\/>~ username=retail_dba \\<br\/>&#8211;password=cloudera \\<br\/>-table departments \\<br\/>-target-dir \/user\/cloudera\/departments_enclosedby \\<br\/>-enclosed-by V -escaped-by \\\\ -fields-terminated-by&#8211;&#8216; -lines-terminated-by :<br\/>Step 3 : Check the result.<br\/>hdfs dfs -cat\/user\/cloudera\/departments_enclosedby\/part&#8221;<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(9,this)' id='btn-9' value='See Answer'  \/><input type='hidden' id='questionType9' value='textarea' class=''><\/div><div class='watu-question' id='question-10'><div class='question-content'><p><strong>NEW QUESTION 25<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 43 : You have been given following code snippet.<br \/>val grouped = sc.parallelize(Seq(((1,&#8221;twoM), List((3,4), (5,6)))))<br \/>val flattened = grouped.flatMap {A =&gt;<br \/>groupValues.map { value =&gt; B }<br \/>}<br \/>You need to generate following output.<br \/>Hence replace A and B<br \/>Array((1,two,3,4),(1,two,5,6))<\/p>\n<\/div><input type='hidden' name='question_id[]' value='608' \/><textarea name='answer-608[]' rows='5' cols='40' id='textarea_q_608' class='watu-textarea watu-textarea-10'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>A case (key, groupValues)<br\/>B (key._1, key._2, value._1, value._2)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(10,this)' id='btn-10' value='See Answer'  \/><input type='hidden' id='questionType10' value='textarea' class=''><\/div><div class='watu-question' id='question-11'><div class='question-content'><p><strong>NEW QUESTION 26<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 21 : You have been given log generating service as below.<br \/>startjogs (It will generate continuous logs)<br \/>tailjogs (You can check , what logs are being generated)<br \/>stopjogs (It will stop the log service)<br \/>Path where logs are generated using above service : \/opt\/gen_logs\/logs\/access.log<br \/>Now write a flume configuration file named flumel.conf , using that configuration file dumps logs in HDFS file system in a directory called flumel. Flume channel should have following property as well. After every 100 message it should be committed, use non-durable\/faster channel and it should be able to hold maximum 1000 events<br \/>Solution :<br \/>Step 1 : Create flume configuration file, with below configuration for source, sink and channel.<br \/>#Define source , sink , channel and agent,<br \/>agent1 .sources = source1<br \/>agent1 .sinks = sink1<br \/>agent1.channels = channel1<br \/># Describe\/configure source1<br \/>agent1 .sources.source1.type = exec<br \/>agent1.sources.source1.command = tail -F \/opt\/gen logs\/logs\/access.log<br \/>## Describe sinkl<br \/>agentl .sinks.sinkl.channel = memory-channel<br \/>agentl .sinks.sinkl .type = hdfs<br \/>agentl .sinks.sink1.hdfs.path = flumel<br \/>agentl .sinks.sinkl.hdfs.fileType = Data Stream<br \/># Now we need to define channell property.<br \/>agent1.channels.channel1.type = memory<br \/>agent1.channels.channell.capacity = 1000<br \/>agent1.channels.channell.transactionCapacity = 100<br \/># Bind the source and sink to the channel<br \/>agent1.sources.source1.channels = channel1<br \/>agent1.sinks.sink1.channel = channel1<br \/>Step 2 : Run below command which will use this configuration file and append data in hdfs.<br \/>Start log service using : startjogs<br \/>Start flume service:<br \/>flume-ng agent -conf \/home\/cloudera\/flumeconf -conf-file<br \/>\/home\/cloudera\/flumeconf\/flumel.conf-Dflume.root.logger=DEBUG,INFO,console<br \/>Wait for few mins and than stop log service.<br \/>Stop_logs<\/p>\n<\/div><input type='hidden' name='question_id[]' value='609' \/><textarea name='answer-609[]' rows='5' cols='40' id='textarea_q_609' class='watu-textarea watu-textarea-11'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(11,this)' id='btn-11' value='See Answer'  \/><input type='hidden' id='questionType11' value='textarea' class=''><\/div><div class='watu-question' id='question-12'><div class='question-content'><p><strong>NEW QUESTION 27<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 58 : You have been given below code snippet.<br \/>val a = sc.parallelize(List(&#8220;dog&#8221;, &#8220;tiger&#8221;, &#8220;lion&#8221;, &#8220;cat&#8221;, &#8220;spider&#8221;, &#8220;eagle&#8221;), 2) val b = a.keyBy(_.length) operation1<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[(lnt, Seq[String])] = Array((4,ArrayBuffer(lion)), (6,ArrayBuffer(spider)),<br \/>(3,ArrayBuffer(dog, cat)), (5,ArrayBuffer(tiger, eagle}}}<\/p>\n<\/div><input type='hidden' name='question_id[]' value='610' \/><textarea name='answer-610[]' rows='5' cols='40' id='textarea_q_610' class='watu-textarea watu-textarea-12'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>b.groupByKey.collect<br\/>groupByKey [Pair]<br\/>Very similar to groupBy, but instead of supplying a function, the key-component of each pair will automatically be presented to the partitioner.<br\/>Listing Variants<br\/>def groupByKeyQ: RDD[(K, lterable[V]}]<br\/>def groupByKey(numPartittons: Int): RDD[(K, lterable[V] )]<br\/>def groupByKey(partitioner: Partitioner): RDD[(K, lterable[V])]<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(12,this)' id='btn-12' value='See Answer'  \/><input type='hidden' id='questionType12' value='textarea' class=''><\/div><div class='watu-question' id='question-13'><div class='question-content'><p><strong>NEW QUESTION 28<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 61 : You have been given below code snippet.<br \/>val a = sc.parallelize(List(&#8220;dog&#8221;, &#8220;salmon&#8221;, &#8220;salmon&#8221;, &#8220;rat&#8221;, &#8220;elephant&#8221;), 3) val b = a.keyBy(_.length) val c = sc.parallelize(List(&#8220;dog&#8221;,&#8221;cat&#8221;,&#8221;gnu&#8221;,&#8221;salmon&#8221;,&#8221;rabbit&#8221;,&#8221;turkey&#8221;,&#8221;wolf&#8221;,&#8221;bear&#8221;,&#8221;bee&#8221;), 3) val d = c.keyBy(_.length) operationl<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[(lnt, (String, Option[String]}}] = Array((6,(salmon,Some(salmon))),<br \/>(6,(salmon,Some(rabbit))),<br \/>(6,(salmon,Some(turkey))), (6,(salmon,Some(salmon))), (6,(salmon,Some(rabbit))),<br \/>(6,(salmon,Some(turkey))), (3,(dog,Some(dog))), (3,(dog,Some(cat))),<br \/>(3,(dog,Some(dog))), (3,(dog,Some(bee))), (3,(rat,Some(dogg)), (3,(rat,Some(cat)j),<br \/>(3,(rat.Some(gnu))). (3,(rat,Some(bee))), (8,(elephant,None)))<\/p>\n<\/div><input type='hidden' name='question_id[]' value='611' \/><textarea name='answer-611[]' rows='5' cols='40' id='textarea_q_611' class='watu-textarea watu-textarea-13'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>b.leftOuterJoin(d}.collect<br\/>leftOuterJoin [Pair]: Performs an left outer join using two key-value RDDs. Please note that the keys must be generally comparable to make this work keyBy : Constructs two- component tuples (key-value pairs) by applying a function on each data item. Trie result of the function becomes the key and the original data item becomes the value of the newly created tuples.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(13,this)' id='btn-13' value='See Answer'  \/><input type='hidden' id='questionType13' value='textarea' class=''><\/div><div class='watu-question' id='question-14'><div class='question-content'><p><strong>NEW QUESTION 29<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 41 : You have been given below code snippet.<br \/>val aul = sc.parallelize(List ((&#8220;a&#8221; , Array(1,2)), (&#8220;b&#8221; , Array(1,2)))) val au2 = sc.parallelize(List ((&#8220;a&#8221; , Array(3)), (&#8220;b&#8221; , Array(2))))<br \/>Apply the Spark method, which will generate below output.<br \/>Array[(String, Array[lnt])] = Array((a,Array(1, 2)), (b,Array(1, 2)), (a(Array(3)), (b,Array(2)))<\/p>\n<\/div><input type='hidden' name='question_id[]' value='612' \/><textarea name='answer-612[]' rows='5' cols='40' id='textarea_q_612' class='watu-textarea watu-textarea-14'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution:<br\/>au1.union(au2)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(14,this)' id='btn-14' value='See Answer'  \/><input type='hidden' id='questionType14' value='textarea' class=''><\/div><div class='watu-question' id='question-15'><div class='question-content'><p><strong>NEW QUESTION 30<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 74 : You have been given MySQL DB with following details.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>table=retail_db.orders<br \/>table=retail_db.order_items<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Columns of order table : (orderjd , order_date , ordercustomerid, order status}<br \/>Columns of orderjtems table : (order_item_td , order_item_order_id ,<br \/>order_item_product_id,<br \/>order_item_quantity,order_item_subtotal,order_item_product_price)<br \/>Please accomplish following activities.<br \/>1. Copy &#8220;retaildb.orders&#8221; and &#8220;retaildb.orderjtems&#8221; table to hdfs in respective directory p89_orders and p89_order_items .<br \/>2. Join these data using orderjd in Spark and Python<br \/>3. Now fetch selected columns from joined data Orderld, Order date and amount collected on this order.<br \/>4. Calculate total order placed for each date, and produced the output sorted by date.<\/p>\n<\/div><input type='hidden' name='question_id[]' value='613' \/><textarea name='answer-613[]' rows='5' cols='40' id='textarea_q_613' class='watu-textarea watu-textarea-15'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution:<br\/>Step 1 : Import Single table .<br\/>sqoop import &#8211;connect jdbc:mysql:\/\/quickstart:3306\/retail_db -username=retail_dba &#8211; password=cloudera -table=orders &#8211;target-dir=p89_orders &#8211; -m1 sqoop import &#8211;connect jdbc:mysql:\/\/quickstart:3306\/retail_db -username=retail_dba &#8211; password=cloudera -table=order_items ~target-dir=p89_ order items -m 1<br\/>Note : Please check you dont have space between before or after &#8216;=&#8217; sign. Sqoop uses the<br\/>MapReduce framework to copy data from RDBMS to hdfs<br\/>Step 2 : Read the data from one of the partition, created using above command, hadoopfs<br\/>-cat p89_orders\/part-m-00000 hadoop fs -cat p89_order_items\/part-m-00000<br\/>Step 3 : Load these above two directory as RDD using Spark and Python (Open pyspark terminal and do following). orders = sc.textFile(&#8220;p89_orders&#8221;) orderitems = sc.textFile(&#8220;p89_order_items&#8221;)<br\/>Step 4 : Convert RDD into key value as (orderjd as a key and rest of the values as a value)<br\/>#First value is orderjd<br\/>ordersKeyValue = orders.map(lambda line: (int(line.split(&#8220;,&#8221;)[0]), line))<br\/>#Second value as an Orderjd<br\/>orderltemsKeyValue = orderltems.map(lambda line: (int(line.split(&#8220;,&#8221;)[1]), line))<br\/>Step 5 : Join both the RDD using orderjd<br\/>joinedData = orderltemsKeyValue.join(ordersKeyValue)<br\/>#print the joined data<br\/>tor line in joinedData.collect():<br\/>print(line)<br\/>Format of joinedData as below.<br\/>[Orderld, &#8216;All columns from orderltemsKeyValue&#8217;, &#8216;All columns from orders Key Value&#8217;]<br\/>Step 6 : Now fetch selected values Orderld, Order date and amount collected on this order.<br\/>revenuePerOrderPerDay = joinedData.map(lambda row: (row[0]( row[1][1].split(&#8220;,&#8221;)[1]( f!oat(row[1][0].split(&#8216;\\M}[4]}}}<br\/>#printthe result<br\/>for line in revenuePerOrderPerDay.collect():<br\/>print(line)<br\/>Step 7 : Select distinct order ids for each date.<br\/>#distinct(date,order_id)<br\/>distinctOrdersDate = joinedData.map(lambda row: row[1][1].split(&#8216;\\&#8221;)[1] + &#8220;,&#8221; + str(row[0])).distinct() for line in distinctOrdersDate.collect(): print(line)<br\/>Step 8 : Similar to word count, generate (date, 1) record for each row. newLineTuple = distinctOrdersDate.map(lambda line: (line.split(&#8220;,&#8221;)[0], 1))<br\/>Step 9 : Do the count for each key(date), to get total order per date. totalOrdersPerDate = newLineTuple.reduceByKey(lambda a, b: a + b}<br\/>#print results<br\/>for line in totalOrdersPerDate.collect():<br\/>print(line)<br\/>step 10 : Sort the results by date sortedData=totalOrdersPerDate.sortByKey().collect()<br\/>#print results<br\/>for line in sortedData:<br\/>print(line)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(15,this)' id='btn-15' value='See Answer'  \/><input type='hidden' id='questionType15' value='textarea' class=''><\/div><div class='watu-question' id='question-16'><div class='question-content'><p><strong>NEW QUESTION 31<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 9 : You have been given following mysql database details as well as other info.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Please accomplish following.<br \/>1. Import departments table in a directory.<br \/>2. Again import departments table same directory (However, directory already exist hence it should not overrride and append the results)<br \/>3. Also make sure your results fields are terminated by &#8216;|&#8217; and lines terminated by &#8216;n<\/p>\n<\/div><input type='hidden' name='question_id[]' value='614' \/><textarea name='answer-614[]' rows='5' cols='40' id='textarea_q_614' class='watu-textarea watu-textarea-16'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solutions :<br\/>Step 1 : Clean the hdfs file system, if they exists clean out.<br\/>hadoop fs -rm -R departments<br\/>hadoop fs -rm -R categories<br\/>hadoop fs -rm -R products<br\/>hadoop fs -rm -R orders<br\/>hadoop fs -rm -R order_items<br\/>hadoop fs -rm -R customers<br\/>Step 2 : Now import the department table as per requirement.<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:330G\/retaiI_db \\<br\/>&#8211;username=retail_dba \\<br\/>-password=cloudera \\<br\/>-table departments \\<br\/>-target-dir=departments \\<br\/>-fields-terminated-by &#8216;|&#8217; \\<br\/>-lines-terminated-by &#8216;\\n&#8217; \\<br\/>-ml<br\/>Step 3 : Check imported data.<br\/>hdfs dfs -Is departments<br\/>hdfs dfs -cat departments\/part-m-00000<br\/>Step 4 : Now again import data and needs to appended.<br\/>sqoop import \\<br\/>-connect jdbc:mysql:\/\/quickstart:3306\/retail_db \\<br\/>&#8211;username=retail_dba \\<br\/>-password=cloudera \\<br\/>-table departments \\<br\/>-target-dir departments \\<br\/>-append \\<br\/>-tields-terminated-by &#8216;|&#8217; \\<br\/>-lines-termtnated-by &#8216;\\n&#8217; \\<br\/>-ml<br\/>Step 5 : Again Check the results<br\/>hdfs dfs -Is departments<br\/>hdfs dfs -cat departments\/part-m-00001<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(16,this)' id='btn-16' value='See Answer'  \/><input type='hidden' id='questionType16' value='textarea' class=''><\/div><div class='watu-question' id='question-17'><div class='question-content'><p><strong>NEW QUESTION 32<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 59 : You have been given below code snippet.<br \/>val x = sc.parallelize(1 to 20)<br \/>val y = sc.parallelize(10 to 30) operationl<br \/>z.collect<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[lnt] = Array(16,12, 20,13,17,14,18,10,19,15,11)<\/p>\n<\/div><input type='hidden' name='question_id[]' value='615' \/><textarea name='answer-615[]' rows='5' cols='40' id='textarea_q_615' class='watu-textarea watu-textarea-17'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>val z = x.intersection(y)<br\/>intersection : Returns the elements in the two RDDs which are the same.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(17,this)' id='btn-17' value='See Answer'  \/><input type='hidden' id='questionType17' value='textarea' class=''><\/div><div class='watu-question' id='question-18'><div class='question-content'><p><strong>NEW QUESTION 33<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 62 : You have been given below code snippet.<br \/>val a = sc.parallelize(List(&#8220;dogM, &#8220;tiger&#8221;, &#8220;lion&#8221;, &#8220;cat&#8221;, &#8220;panther&#8221;, &#8220;eagle&#8221;), 2) val b = a.map(x =&gt; (x.length, x)) operation1<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[(lnt, String)] = Array((3,xdogx), (5,xtigerx), (4,xlionx), (3,xcatx), (7,xpantherx),<br \/>(5,xeaglex))<\/p>\n<\/div><input type='hidden' name='question_id[]' value='616' \/><textarea name='answer-616[]' rows='5' cols='40' id='textarea_q_616' class='watu-textarea watu-textarea-18'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>b.mapValuesf&#8217;x&#8221; + _ + &#8220;x&#8221;).collect<br\/>mapValues [Pair] : Takes the values of a RDD that consists of two-component tuples, and applies the provided function to transform each value. Tlien,.it.forms newtwo-componend tuples using the key and the transformed value and stores them in a new RDD.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(18,this)' id='btn-18' value='See Answer'  \/><input type='hidden' id='questionType18' value='textarea' class=''><\/div><div class='watu-question' id='question-19'><div class='question-content'><p><strong>NEW QUESTION 34<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 63 : You have been given below code snippet.<br \/>val a = sc.parallelize(List(&#8220;dog&#8221;, &#8220;tiger&#8221;, &#8220;lion&#8221;, &#8220;cat&#8221;, &#8220;panther&#8221;, &#8220;eagle&#8221;), 2) val b = a.map(x =&gt; (x.length, x)) operation1<br \/>Write a correct code snippet for operationl which will produce desired output, shown below.<br \/>Array[(lnt, String}] = Array((4,lion), (3,dogcat), (7,panther), (5,tigereagle))<\/p>\n<\/div><input type='hidden' name='question_id[]' value='617' \/><textarea name='answer-617[]' rows='5' cols='40' id='textarea_q_617' class='watu-textarea watu-textarea-19'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>b.reduceByKey(_ + _).collect<br\/>reduceByKey JPair] : This function provides the well-known reduce functionality in Spark.<br\/>Please note that any function f you provide, should be commutative in order to generate reproducible results.<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(19,this)' id='btn-19' value='See Answer'  \/><input type='hidden' id='questionType19' value='textarea' class=''><\/div><div class='watu-question' id='question-20'><div class='question-content'><p><strong>NEW QUESTION 35<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 4: You have been given MySQL DB with following details.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>table=retail_db.categories<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Please accomplish following activities.<br \/>Import Single table categories (Subset data} to hive managed table , where category_id between 1 and 22<\/p>\n<\/div><input type='hidden' name='question_id[]' value='618' \/><textarea name='answer-618[]' rows='5' cols='40' id='textarea_q_618' class='watu-textarea watu-textarea-20'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Import Single table (Subset data)<br\/>sqoop import &#8211;connect jdbc:mysql:\/\/quickstart:3306\/retail_db -username=retail_dba &#8211; password=cloudera -table=categories -where &#8220;\\&#8217;category_id\\&#8217; between 1 and 22&#8221; &#8211;hive- import &#8211;m 1<br\/>Note: Here the &#8216; is the same you find on ~ key<br\/>This command will create a managed table and content will be created in the following directory.<br\/>\/user\/hive\/warehouse\/categories<br\/>Step 2 : Check whether table is created or not (In Hive)<br\/>show tables;<br\/>select * from categories;<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(20,this)' id='btn-20' value='See Answer'  \/><input type='hidden' id='questionType20' value='textarea' class=''><\/div><div class='watu-question' id='question-21'><div class='question-content'><p><strong>NEW QUESTION 36<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 87 : You have been given below three files<br \/>product.csv (Create this file in hdfs)<br \/>productID,productCode,name,quantity,price,supplierid<br \/>1 001,PEN,Pen Red,5000,1.23,501<br \/>1 002,PEN,Pen Blue,8000,1.25,501<br \/>1003,PEN,Pen Black,2000,1.25,501<br \/>1004,PEC,Pencil 2B,10000,0.48,502<br \/>1005,PEC,Pencil 2H,8000,0.49,502<br \/>1006,PEC,Pencil HB,0,9999.99,502<br \/>2001,PEC,Pencil 3B,500,0.52,501<br \/>2002,PEC,Pencil 4B,200,0.62,501<br \/>2003,PEC,Pencil 5B,100,0.73,501<br \/>2004,PEC,Pencil 6B,500,0.47,502<br \/>supplier.csv<br \/>supplierid,name,phone<br \/>501,ABC Traders,88881111<br \/>502,XYZ Company,88882222<br \/>503,QQ Corp,88883333<br \/>products_suppliers.csv<br \/>productID,supplierID<br \/>2001,501<br \/>2002,501<br \/>2003,501<br \/>2004,502<br \/>2001,503<br \/>Now accomplish all the queries given in solution.<br \/>Select product, its price , its supplier name where product price is less than 0.6 using<br \/>SparkSQL<\/p>\n<\/div><input type='hidden' name='question_id[]' value='619' \/><textarea name='answer-619[]' rows='5' cols='40' id='textarea_q_619' class='watu-textarea watu-textarea-21'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1:<br\/>hdfs dfs -mkdir sparksql2<br\/>hdfs dfs -put product.csv sparksq!2\/<br\/>hdfs dfs -put supplier.csv sparksql2\/<br\/>hdfs dfs -put products_suppliers.csv sparksql2\/<br\/>Step 2 : Now in spark shell<br\/>\/\/ this Is used to Implicitly convert an RDD to a DataFrame.<br\/>import sqlContext.impIicits._<br\/>\/\/ Import Spark SQL data types and Row.<br\/>import org.apache.spark.sql._<br\/>\/\/ load the data into a new RDD<br\/>val products = sc.textFile(&#8220;sparksql2\/product.csv&#8221;)<br\/>val supplier = sc.textFileC&#8217;sparksq^supplier.csv&#8221;)<br\/>val prdsup = sc.textFile(&#8220;sparksql2\/products_suppliers.csv&#8221;}<br\/>\/\/ Return the first element in this RDD<br\/>products.fi rst()<br\/>supplier.first{).<br\/>prdsup.first()<br\/>\/\/define the schema using a case class<br\/>case class Product(productid: Integer, code: String, name: String, quantity:lnteger, price:<br\/>Float, supplierid:lnteger)<br\/>case class Suplier(supplierid: Integer, name: String, phone: String)<br\/>case class PRDSUP(productid: Integer.supplierid: Integer)<br\/>\/\/ create an RDD of Product objects<br\/>val prdRDD = products.map(_.split(&#8216;\\&#8221;)).map(p =&gt;<br\/>Product(p(0).tolnt,p(1),p(2),p(3).tolnt,p(4).toFloat,p(5).toint))<br\/>val supRDD = supplier.map(_.split(&#8220;,&#8221;)).map(p =&gt; Suplier(p(0).tolnt,p(1),p(2))) val prdsupRDD = prdsup.map(_.split(&#8220;,&#8221;)).map(p =&gt; PRDSUP(p(0).tolnt,p(1}.tolnt}} prdRDD.first() prdRDD.count() supRDD.first() supRDD.count()<br\/>prdsupRDD.first() prdsupRDD.count(}<br\/>\/\/ change RDD of Product objects to a DataFrame<br\/>val prdDF = prdRDD.toDF()<br\/>val supDF = supRDD.toDF()<br\/>val prdsupDF = prdsupRDD.toDF()<br\/>\/\/ register the DataFrame as a temp table prdDF.registerTempTablef&#8217;products&#8221;) supDF.registerTempTablef&#8217;suppliers&#8221;) prdsupDF.registerTempTablef&#8217;productssuppliers&#8221;}<br\/>\/\/Select product, its price , its supplier name where product price is less than 0.6 val results = sqlContext.sql(&#8230;&#8230;SELECT products.name, price, suppliers.name as sup_name FROM products JOIN suppliers ON products.supplierlD= suppliers.supplierlD<br\/>WHERE price &lt; 0.6&#8230;&#8230;]<br\/>results. show()<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(21,this)' id='btn-21' value='See Answer'  \/><input type='hidden' id='questionType21' value='textarea' class=''><\/div><div class='watu-question' id='question-22'><div class='question-content'><p><strong>NEW QUESTION 37<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 80 : You have been given MySQL DB with following details.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>table=retail_db.products<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Columns of products table : (product_id | product_category_id | product_name | product_description | product_price | product_image )<br \/>Please accomplish following activities.<br \/>1. Copy &#8220;retaildb.products&#8221; table to hdfs in a directory p93_products<br \/>2. Now sort the products data sorted by product price per category, use productcategoryid colunm to group by category<\/p>\n<\/div><input type='hidden' name='question_id[]' value='620' \/><textarea name='answer-620[]' rows='5' cols='40' id='textarea_q_620' class='watu-textarea watu-textarea-22'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Import Single table .<br\/>sqoop import &#8211;connect jdbc:mysql:\/\/quickstart:3306\/retail_db -username=retail_dba &#8211; password=cloudera -table=products &#8211;target-dir=p93<br\/>Note : Please check you dont have space between before or after &#8216;=&#8217; sign. Sqoop uses the<br\/>MapReduce framework to copy data from RDBMS to hdfs<br\/>Step 2 : Step 2 : Read the data from one of the partition, created using above command, hadoop fs -cat p93_products\/part-m-00000<br\/>Step 3 : Load this directory as RDD using Spark and Python (Open pyspark terminal and do following}. productsRDD = sc.textFile(Mp93_products&#8221;)<br\/>Step 4 : Filter empty prices, if exists<br\/>#filter out empty prices lines<br\/>Nonempty_lines = productsRDD.filter(lambda x: len(x.split(&#8220;,&#8221;)[4]) &gt; 0)<br\/>Step 5 : Create data set like (categroyld, (id,name,price)<br\/>mappedRDD = nonempty_lines.map(lambda line: (line.split(&#8220;,&#8221;)[1], (line.split(&#8220;,&#8221;)[0], line.split(&#8220;,&#8221;)[2], float(line.split(&#8220;,&#8221;)[4])))) tor line in mappedRDD.collect(): print(line)<br\/>Step 6 : Now groupBy the all records based on categoryld, which a key on mappedRDD it will produce output like (categoryld, iterable of all lines for a key\/categoryld) groupByCategroyld = mappedRDD.groupByKey() for line in groupByCategroyld.collect():<br\/>print(line)<br\/>step 7 : Now sort the data in each category based on price in ascending order.<br\/># sorted is a function to sort an iterable, we can also specify, what would be the Key on which we want to sort in this case we have price on which it needs to be sorted.<br\/>groupByCategroyld.map(lambda tuple: sorted(tuple[1], key=lambda tupleValue:<br\/>tupleValue[2])).take(5)<br\/>Step 8 : Now sort the data in each category based on price in descending order.<br\/># sorted is a function to sort an iterable, we can also specify, what would be the Key on which we want to sort in this case we have price which it needs to be sorted.<br\/>on groupByCategroyld.map(lambda tuple: sorted(tuple[1], key=lambda tupleValue:<br\/>tupleValue[2] , reverse=True)).take(5)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(22,this)' id='btn-22' value='See Answer'  \/><input type='hidden' id='questionType22' value='textarea' class=''><\/div><div class='watu-question' id='question-23'><div class='question-content'><p><strong>NEW QUESTION 38<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 69 : Write down a Spark Application using Python,<br \/>In which it read a file &#8220;Content.txt&#8221; (On hdfs) with following content.<br \/>And filter out the word which is less than 2 characters and ignore all empty lines.<br \/>Once doen store the filtered data in a directory called &#8220;problem84&#8221; (On hdfs)<br \/>Content.txt<br \/>Hello this is ABCTECH.com<br \/>This is ABYTECH.com<br \/>Apache Spark Training<br \/>This is Spark Learning Session<br \/>Spark is faster than MapReduce<\/p>\n<\/div><input type='hidden' name='question_id[]' value='621' \/><textarea name='answer-621[]' rows='5' cols='40' id='textarea_q_621' class='watu-textarea watu-textarea-23'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Create an application with following code and store it in problem84.py<br\/># Import SparkContext and SparkConf<br\/>from pyspark import SparkContext, SparkConf<br\/># Create configuration object and set App name<br\/>conf = SparkConf().setAppName(&#8220;CCA 175 Problem 84&#8221;) sc = sparkContext(conf=conf)<br\/>#load data from hdfs<br\/>contentRDD = sc.textFile(MContent.txt&#8221;)<br\/>#filter out non-empty lines<br\/>nonemptyjines = contentRDD.filter(lambda x: len(x) &gt; 0)<br\/>#Split line based on space<br\/>words = nonempty_lines.ffatMap(lambda x: x.split(&#8221;}}<br\/>#filter out all 2 letter words<br\/>finalRDD = words.filter(lambda x: len(x) &gt; 2)<br\/>for word in finalRDD.collect():<br\/>print(word)<br\/>#Save final data finalRDD.saveAsTextFile(&#8220;problem84M)<br\/>step 2 : Submit this application<br\/>spark-submit -master yarn problem84.py<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(23,this)' id='btn-23' value='See Answer'  \/><input type='hidden' id='questionType23' value='textarea' class=''><\/div><div class='watu-question' id='question-24'><div class='question-content'><p><strong>NEW QUESTION 39<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 78 : You have been given MySQL DB with following details.<br \/>user=retail_dba<br \/>password=cloudera<br \/>database=retail_db<br \/>table=retail_db.orders<br \/>table=retail_db.order_items<br \/>jdbc URL = jdbc:mysql:\/\/quickstart:3306\/retail_db<br \/>Columns of order table : (orderid , order_date , order_customer_id, order_status)<br \/>Columns of ordeMtems table : (order_item_td , order_item_order_id ,<br \/>order_item_product_id,<br \/>order_item_quantity,order_item_subtotal,order_item_product_price)<br \/>Please accomplish following activities.<br \/>1. Copy &#8220;retail_db.orders&#8221; and &#8220;retail_db.order_items&#8221; table to hdfs in respective directory p92_orders and p92_order_items .<br \/>2. Join these data using order_id in Spark and Python<br \/>3. Calculate total revenue perday and per customer<br \/>4. Calculate maximum revenue customer<\/p>\n<\/div><input type='hidden' name='question_id[]' value='622' \/><textarea name='answer-622[]' rows='5' cols='40' id='textarea_q_622' class='watu-textarea watu-textarea-24'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Import Single table .<br\/>sqoop import &#8211;connect jdbc:mysql:\/\/quickstart:3306\/retail_db -username=retail_dba &#8211; password=cloudera -table=orders &#8211;target-dir=p92_orders -m 1 sqoop import -connect jdbc:mysql:\/\/quickstart:3306\/retail_db -username=retail_dba &#8211; password=cloudera -table=order_items &#8211;target-dir=p92_order_orderitems &#8211;m 1<br\/>Note : Please check you dont have space between before or after &#8216;=&#8217; sign. Sqoop uses the<br\/>MapReduce framework to copy data from RDBMS to hdfs<br\/>Step 2 : Read the data from one of the partition, created using above command, hadoop fs<br\/>-cat p92_orders\/part-m-00000 hadoop fs -cat p92 orderitems\/part-m-00000<br\/>Step 3 : Load these above two directory as RDD using Spark and Python (Open pyspark terminal and do following). orders = sc.textFile(Mp92_orders&#8221;) orderitems = sc.textFile(&#8220;p92_order_items&#8221;)<br\/>Step 4 : Convert RDD into key value as (orderjd as a key and rest of the values as a value)<br\/>#First value is orderjd<br\/>orders Key Value = orders.map(lambda line: (int(line.split(&#8220;,&#8221;)[0]), line))<br\/>#Second value as an Orderjd<br\/>orderltemsKeyValue = orderltems.map(lambda line: (int(line.split(&#8220;,&#8221;)[1]), line))<br\/>Step 5 : Join both the RDD using orderjd<br\/>joinedData = orderltemsKeyValue.join(ordersKeyValue)<br\/>#print the joined data<br\/>for line in joinedData.collect():<br\/>print(line)<br\/>#Format of joinedData as below.<br\/>#[Orderld, &#8216;All columns from orderltemsKeyValue&#8217;, &#8216;All columns from ordersKeyValue&#8217;] ordersPerDatePerCustomer = joinedData.map(lambda line: ((line[1][1].split(&#8220;,&#8221;)[1], line[1][1].split(&#8220;,M)[2]), float(line[1][0].split(&#8220;,&#8221;)[4]))) amountCollectedPerDayPerCustomer = ordersPerDatePerCustomer.reduceByKey(lambda runningSum, amount: runningSum + amount}<br\/>#(Out record format will be ((date,customer_id), totalAmount} for line in amountCollectedPerDayPerCustomer.collect(): print(line)<br\/>#now change the format of record as (date,(customer_id,total_amount))<br\/>revenuePerDatePerCustomerRDD = amountCollectedPerDayPerCustomer.map(lambda threeElementTuple: (threeElementTuple[0][0],<br\/>(threeElementTuple[0][1],threeElementTuple[1])))<br\/>for line in revenuePerDatePerCustomerRDD.collect():<br\/>print(line)<br\/>#Calculate maximum amount collected by a customer for each day<br\/>perDateMaxAmountCollectedByCustomer =<br\/>revenuePerDatePerCustomerRDD.reduceByKey(lambda runningAmountTuple,<br\/>newAmountTuple: (runningAmountTuple if runningAmountTuple[1] &gt;=<br\/>newAmountTuple[1] else newAmountTuple})<br\/>for line in perDateMaxAmountCollectedByCustomer\\sortByKey().collect(): print(line)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(24,this)' id='btn-24' value='See Answer'  \/><input type='hidden' id='questionType24' value='textarea' class=''><\/div><div class='watu-question' id='question-25'><div class='question-content'><p><strong>NEW QUESTION 40<\/strong><br \/>CORRECT TEXT<br \/>Problem Scenario 39 : You have been given two files<br \/>spark16\/file1.txt<br \/>1,9,5<br \/>2,7,4<br \/>3,8,3<br \/>spark16\/file2.txt<br \/>1 ,g,h<br \/>2 ,i,j<br \/>3 ,k,l<br \/>Load these two tiles as Spark RDD and join them to produce the below results<br \/>(l,((9,5),(g,h)))<br \/>(2, ((7,4), (i,j))) (3, ((8,3), (k,l)))<br \/>And write code snippet which will sum the second columns of above joined results (5+4+3).<\/p>\n<\/div><input type='hidden' name='question_id[]' value='623' \/><textarea name='answer-623[]' rows='5' cols='40' id='textarea_q_623' class='watu-textarea watu-textarea-25'><\/textarea><div class='watu-questions-wrap '><\/div><div class='show-question-feedback' style='display:none;'>See the explanation for Step by Step Solution and configuration.<br\/>Explanation:<br\/>Solution :<br\/>Step 1 : Create tiles in hdfs using Hue.<br\/>Step 2 : Create pairRDD for both the files.<br\/>val one = sc.textFile(&#8220;spark16\/file1.txt&#8221;).map{<br\/>_.split(&#8220;,&#8221;,-1) match {<br\/>case Array(a, b, c) =&gt; (a, ( b, c))<br\/>} }<br\/>val two = sc.textFHe(Mspark16\/file2.txt&#8221;).map{<br\/>_ .split(&#8216;7\\-1) match {<br\/>case Array(a, b, c) =&gt; (a, (b, c))<br\/>} }<br\/>Step 3 : Join both the RDD. val joined = one.join(two)<br\/>Step 4 : Sum second column values.<br\/>val sum = joined.map {<br\/>case (_, ((_, num2), (_, _))) =&gt; num2.tolnt<br\/>}.reduce(_ + _)<\/div><input type='button' class='showchecked' style='margin: 10px 0;' onclick='showanswer1(25,this)' id='btn-25' value='See Answer'  \/><input type='hidden' id='questionType25' value='textarea' class=''><\/div><div style='display:none' id='question-26'><br \/><div class='question-content'><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/blog.topexamcollection.com\/wp-content\/plugins\/watu\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading ...\" title=\"Loading ...\" \/>&nbsp;Loading &#8230;<\/div><\/div><br \/>\n<input type=\"button\" name=\"action\" onclick=\"Watu.submitResult()\" id=\"action-button\" style=\"margin:0 auto 20px auto;\" value=\"View Results\"  class=\"watu-submit-button\" \/>\n<input type=\"hidden\" name=\"no_ajax\" value=\"0\"><input type=\"hidden\" name=\"quiz_id\" value=\"31\" \/>\n<input type=\"hidden\" id=\"watuStartTime\" name=\"start_time\" value=\"2026-09-23 23:48:29\" \/>\n<\/form>\n<\/div>\n<div id=\"watu-loading-result\" style=\"display:none;\">\n\t<p align=\"center\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/blog.topexamcollection.com\/wp-content\/plugins\/watu\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading\" title=\"Loading\" \/><\/p>\n<\/div>\t\n<script type=\"text\/javascript\">\nvar exam_id=0;\nvar question_ids='';\nvar watuURL='';\njQuery(function($){\nquestion_ids = \"599,600,601,602,603,604,605,606,607,608,609,610,611,612,613,614,615,616,617,618,619,620,621,622,623\";\nexam_id = 31;\nWatu.exam_id = exam_id;\nWatu.qArr = question_ids.split(',');\nWatu.post_id = 66;\nWatu.singlePage = '1';\nWatu.hAppID = \"0.64165800 1790207309\";\nwatuURL = \"https:\/\/blog.topexamcollection.com\/wp-admin\/admin-ajax.php\";\nWatu.noAlertUnanswered = 0;\n});\n\nfunction showanswer1(e,q) {\n\tvar check = new Array();\n\tjQuery('.answer-' + e).each(function (i) {\n\t\tcheck.push(this.checked)\n\t})\n\tlet textval = jQuery('.watu-textarea-' + e).val()\n\tif (jQuery.inArray(true, check) >= 0 || textval !== '' && textval !== undefined) {\n\t\tjQuery(q).stop().fadeOut(300)\n\t\tjQuery('.php-answer-label.label-' + e).addClass(\n\t\t\t'correct-answer'\n\t\t)\n\t\tjQuery('.answer-' + e).each(function (i) {\n\t\t\tif (this.checked && this.className.match(\/js\\-answer\/)) {\n\t\t\t\tvar number = this.id.toString().replace(\/\\D\/g, '')\n\t\t\t\tif (number) {\n\t\t\t\t\tjQuery('#answer-label-' + number).addClass('user-answer')\n\t\t\t\t}\n\t\t\t}\n\t\t})\n\t\tjQuery(q).siblings('.show-question-feedback').stop().fadeIn(300)\n\t\ttextval = ''\n\t} else if (textval == '' || textval == undefined){\n\t\t\/\/jQuery(\".hint\").stop().fadeIn(300)\n\t\talert('Please first answer the question');\n\t}\n}\nvar btnisshow = jQuery(\".php-answer-label\").length\nif (btnisshow > 0) {\n\tjQuery('.showchecked').show()\n} else {\n\tjQuery('.showchecked').hide()\n}\n<\/script>\n<p><strong>Cloudera CCA175 Test Engine PDF &#8211; 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