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NEW QUESTION: 1
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.
Answer:
Explanation:
See the explanation for Step by Step Solution and configuration.
Explanation:
Solution :
Step 1 : Create all three files in hdfs (We will do using Hue). However, you can first create in local filesystem and then upload it to hdfs.
Step 2 : Load content from all files.
val content =
sc.textFile("spark3/sparkdir1/file1.txt,spark3/sparkdir2/file2.txt,spark3/sparkdir3/file3.
txt") //Load the text file
Step 3 : Now create split each line and create RDD of words.
val flatContent = content.flatMap(word=>word.split(" "))
step 4 : Remove space after each word (trim it)
val trimmedContent = f1atContent.map(word=>word.trim)
Step 5 : Create an RDD from remove, all the words that needs to be removed.
val removeRDD = sc.parallelize(List("a","theM,ManM, "as",
"a","with","this","these","is","are'\"in'\ "for", "to","and","The","of"))
Step 6 : Filter the RDD, so it can have only content which are not present in removeRDD.
val filtered = trimmedContent.subtract(removeRDD}
Step 7 : Create a PairRDD, so we can have (word,1) tuple or PairRDD. val pairRDD = filtered.map(word => (word,1))
Step 8 : Now do the word count on PairRDD. val wordCount = pairRDD.reduceByKey(_ +
_)
Step 9 : Now swap PairRDD.
val swapped = wordCount.map(item => item.swap)
Step 10 : Now revers order the content. val sortedOutput = swapped.sortByKey(false)
Step 11 : Save the output as a Text file. sortedOutput.saveAsTextFile("spark3/result")
Step 12 : Save compressed output.
import org.apache.hadoop.io.compress.GzipCodec
sortedOutput.saveAsTextFile("spark3/compressedresult", classOf[GzipCodec])

NEW QUESTION: 2
An LTM Specialist configures an HTTP monitor as follows:
ltm monitor http stats_http_monitor {
defaults-from http
destination *:*
interval 5
recv "Health check: OK"
send "GET /stats/stats.html HTTP/1.1\\r\\nHost: www.example.com\\r\\nAccept-EncodinG. gzip, deflate\
\r\\nConnection: close\\r\\n\\r\\n"
time-until-up 0
timeout 16
}
The monitor is marking all nodes as down. A trace of the HTTP conversation shows the following:
GET /stats/stats.html HTTP/1.1
Host: www.example.com
Accept-EncodinG. gzip, deflate
Connection: close
HTTP/1.1 401 Authorization Required
DatE. Tue, 23 Oct 2012 19:38:56 GMT
Server: Apache/2.2.15 (Unix)
WWW-AuthenticatE. Basic realm="Please enter your credentials"
Content-LengtH. 480
Connection: close
Content-TypE. text/html; charset=iso-8859-1
Which action will resolve the problem?
A. Add a valid username and password to the monitor.
B. Use an HTTPS monitor with a valid certificate instead.
C. Add a backslash before the colon in the receive string.
D. Add an NTLM profile to the virtual server.
Answer: A

NEW QUESTION: 3
ContosoAppという名前のASP.NETCoreアプリケーションを実行するDockerイメージを作成することを計画しています。 setupScript.ps1という名前のセットアップスクリプトと、ContosoApp.dllを含む一連のアプリケーションファイルがあります。
次の要件を満たすDockerfileドキュメントを作成する必要があります。
*コンテナのビルド時にsetupScripts.ps1を呼び出します。
*コンテナの起動時にContosoApp.dllを実行します。
Dockerfileドキュメントは、ContosoApp.dllとsetupScript.ps1が保存されているのと同じフォルダーに作成する必要があります。
ソリューションを開発するために使用する必要がある5つのコマンドはどれですか？回答するには、適切なコマンドをコマンドのリストから回答領域に移動し、正しい順序で配置します。

Answer:
Explanation:

Explanation

Box 1: CMD [..]
Cmd starts a new instance of the command interpreter, Cmd.exe.
Syntax: CMD <string>
Specifies the command you want to carry out.
Box 2: FROM microsoft/aspnetcore-build:latest
Box 3: WORKDIR /apps/ContosoApp
Bxo 4: COPY ./ .
Box 5: RUN powershell ./setupScript.ps1