最も有効な CCA175 試験参考書

CCA175試験は出題範囲が広く、独学だけでは不安を感じる方も少なくありません。ShikenPASSのCloudera CCA Spark and Hadoop Developer問題集は96問の練習問題で出題傾向を網羅しており、弱点分野の克服をしっかりサポートします。

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CCA175試験に関するQ&Aまとめ

Cloudera CCA Spark and Hadoop Developer 認定 CCA175 試験問題：

問題 #1

CORRECT TEXT
Problem Scenario 65 : You have been given below code snippet.
val a = sc.parallelize(List("dog", "cat", "owl", "gnu", "ant"), 2)
val b = sc.parallelize(1 to a.count.tolnt, 2)
val c = a.zip(b)
operation1
Write a correct code snippet for operationl which will produce desired output, shown below.
Array[(String, Int)] = Array((owl,3), (gnu,4), (dog,1), (cat,2>, (ant,5))

問題 #2

CORRECT TEXT
Problem Scenario 82 : You have been given table in Hive with following structure (Which you have created in previous exercise).
productid int code string name string quantity int price float
Using SparkSQL accomplish following activities.
1 . Select all the products name and quantity having quantity <= 2000
2 . Select name and price of the product having code as 'PEN'
3 . Select all the products, which name starts with PENCIL
4 . Select all products which "name" begins with 'P\ followed by any two characters, followed by space, followed by zero or more characters

問題 #3

CORRECT TEXT
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

問題 #4

CORRECT TEXT
Problem Scenario 32 : You have given three files as below.
spark3/sparkdir1/file1.txt
spark3/sparkd ir2ffile2.txt
spark3/sparkd ir3Zfile3.txt
Each file contain some text.
spark3/sparkdir1/file1.txt
Apache Hadoop is an open-source software framework written in Java for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware. All the modules in Hadoop are designed with a fundamental assumption that hardware failures are common and should be automatically handled by the framework spark3/sparkdir2/file2.txt
The core of Apache Hadoop consists of a storage part known as Hadoop Distributed File
System (HDFS) and a processing part called MapReduce. Hadoop splits files into large blocks and distributes them across nodes in a cluster. To process data, Hadoop transfers packaged code for nodes to process in parallel based on the data that needs to be processed.
spark3/sparkdir3/file3.txt
his approach takes advantage of data locality nodes manipulating the data they have access to to allow the dataset to be processed faster and more efficiently than it would be in a more conventional supercomputer architecture that relies on a parallel file system where computation and data are distributed via high-speed networking
Now write a Spark code in scala which will load all these three files from hdfs and do the word count by filtering following words. And result should be sorted by word count in reverse order.
Filter words ("a","the","an", "as", "a","with","this","these","is","are","in", "for",
"to","and","The","of")
Also please make sure you load all three files as a Single RDD (All three files must be loaded using single API call).
You have also been given following codec
import org.apache.hadoop.io.compress.GzipCodec
Please use above codec to compress file, while saving in hdfs.

問題 #5

CORRECT TEXT
Problem Scenario 7 : You have been given following mysql database details as well as other info.
user=retail_dba
password=cloudera
database=retail_db
jdbc URL = jdbc:mysql://quickstart:3306/retail_db
Please accomplish following.
1. Import department tables using your custom boundary query, which import departments between 1 to 25.
2 . Also make sure each tables file is partitioned in 2 files e.g. part-00000, part-00002
3 . Also make sure you have imported only two columns from table, which are department_id,department_name

解説：