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Bigdata, Semantic IoT, Hadoop, NoSQL

Bigdata, Hadoop ecosystem, Semantic IoT등의 프로젝트를 진행중에 습득한 내용을 정리하는 곳입니다.
필요한 분을 위해서 공개하고 있습니다. 문의사항은 gooper@gooper.com로 메일을 보내주세요.


*출처1 : https://www.cloudera.com/more/training/certification/cca-spark.html




*출처2 : http://www.hadoopexam.com/Cloudera_Certification/CCA175/CCA175_Cloudera_Hadoop_and_Spark_Developer_Tips_and_Tricks.pdf

1. Preparation: I have gone through all the CCA175 Questions and practice the code provided by
http://www.HadoopExam.com Thanks for your questions and code content. The content was
excellent and it helped me a lot. (Especially I have gone through all the Spark Professional
training module as well)
2. No. Of Questions: Generally you will get 10 questions in real exam: Topic will be coverings are
Sqoop, Hive, Pyspark and Scala and avro-tools to extract schema (All questions are covered in
CCA175 Certification Simulator).
3. Code Snippets: will be provided for Pyspark and Scala. You have to edit the snippets accordingly
as per the problem statement.
4. Real Exam Environment: Gateway node will be accessible for execution of the problems during
the exam. Keep in mind there will not be any on-screen timer available during the exam. You
have to keep asking for the time left. There are three sections for each problem i.e.
· Instructions
· Data Set
· Output Requirements.
Please go through all the three sections carefully before start developing the code.
Note: If you started developing code right after looking at the Instruction part of the question,
then later you will realized the exact details of the table like name of the table and HDFS
directory are also mentioned. This can waste your time if have to redo the code or might as well
cost you a question.
5. Editor: nano, gedit are not available. So if you have to edit any code snippets, you have to use vi
alone. Please make yourself familiar with vi editor if you are not.
6. Fill in blanks: You dont have to write entire code for Python and Scala for Apache Spark,
generally they will ask you to do fill in the blanks.
7. Flume: Very few questions on flume.
8. Difficulty Level: If you have enough knowledge, you will feel exam is quite easy. The questions
were logically easy and can be answered in the first attempt if you read the question carefully
(all three sections).
9. Common mistake in Sqoop: People use connector as localhost which is wrong, you have to use
full name instead of localhost (Avoid wasting your time). Use given hostname
10. Hive: Have initial knowledge of hive as well.
11. Spark: Using basic transform functions to get desired output. For instance filter according
particular scenario, sorting and ranking etc.
12. Avro-tool : avro-tool to get schema of avro file. (Very  nicely covered in CCA175
HadoopExam.com Simulator)
13. Big Mistake: Avoid accidently deleting your data: good practice is necessary to avoid such
mistakes. (Once you delete or drop hive table, you have to create it entirely once again.) Same is
instructed by www.HadoopExam.com during their videos  session provided at
http://cca175cloudera.training4exam.com/ (Please go through sample sessions)
14. Spark-sql: They will not ask questions based on Spark Sql learn importantly aggregate, reduce,
sort.
15. Time management: It is very important, (That’s the reason you need too much practice, use
CCA175 simulator to practice all the questions at least a week or two before your real exam).
16. Data sets in real exam is quite larger, hence it will take 2 to 5 mins for execution.

17. Attempts: try to attempt all questions at least 9/10, hence you must be able to score 70%.
18. File format: In most of questions there was tab delimited file to process.
19. Python or Scala: You will get a preloaded python or scala file to work with, so you don't have a
choice whether you want to attempt a question via scala or pyspark. (I have gone through all the
Video sessions provided by www.HadoopExam.com here
20. Connection Issue: If you got disconnected during exam, you may need to contact the proctor
immediately. If he/she is not available log back into examslocal.com and use their online help.
21. Shell scripts: Have good experience to use shell scripts.
22. Question types as mentioned in syllabus : Questions were from Sqoop(import and export),
Hive(table creation and dynamic partitioning), Pyspark and Scala(Joining, sorting and filtering
data), avro-tools. Snippets of code will be provided for Pyspark and Scala. You have to edit the
snippets accordingly as per the problem statement and can the script file(which is another file
apart from snippet) to get the results.
23. Overall exam is easy, but require lot of practice to complete on time and for accurate
solutions of the problem. Hence go through the all below material for CCA175 (It will not take
more than a month, if you are new and already know the Spark and Hadoop then 2-3 weeks
are good enough.
· CCA175 : Hadoop and Spark Developer Certification practice questions
· Hadoop professional training
· Spark professional training.

Wish you all the best

번호 제목 글쓴이 날짜 조회 수
260 spark2.0.0에서 hive 2.0.1 table을 읽어 출력하는 예제 소스(HiveContext, SparkSession, SQLContext) 총관리자 2017.03.09 163
259 It is indirectly referenced from required .class files 오류 발생시 조치방법 총관리자 2017.03.09 93
258 spark 2.0.0의 api를 이용하는 예제 프로그램 총관리자 2017.03.15 199
257 kafka-manager 1.3.3.4 설정및 실행하기 총관리자 2017.03.20 617
256 JavaStreamingContext를 이용하여 스트림으로 들어오는 문자열 카운트 소스 총관리자 2017.03.30 129
255 streaming작업시 입력된 값에 대한 사본을 만들게 되는데 이것이 실패했을때 발생하는 경고메세지 총관리자 2017.04.03 126
254 Container killed by the ApplicationMaster. Container killed on request. Exit code is 143 Container exited with a non-zero exit code 143 TaskAttempt killed because it ran on unusable node 오류시 조치방법 총관리자 2017.04.06 325
253 Caused by: java.lang.ClassNotFoundException: org.apache.spark.Logging 발생시 조치사항 총관리자 2017.04.19 284
252 Spark에서 Serializable관련 오류및 조치사항 총관리자 2017.04.21 4901
251 Hbase API를 이용하여 scan시 페이징을 고려하여 목록을 가져올때 사용할 수 있는 로직의 예시를 보여줌 총관리자 2017.04.26 239
250 Spark에서 KafkaUtils.createStream()를 이용하여 이용하여 kafka topic에 접근하여 객채로 저장된 값을 가져오고 처리하는 예제 소스 총관리자 2017.04.26 292
249 Kafka의 API중 Consumer.createJavaConsumerConnector()를 이용하고 다수의 thread를 생성하여 Kafka broker의 topic에 접근하여 데이타를 가져오고 처리하는 예제 소스 총관리자 2017.04.26 226
248 Ubuntu 16.04 LTS에 4대에 Hadoop 2.8.0설치 총관리자 2017.05.01 521
247 Ubuntu 16.04 LTS에 MariaDB 10.1설치 및 포트변경 및 원격접속 허용 총관리자 2017.05.01 1081
246 Cleaning up the staging area file시 'cannot access' 혹은 'Directory is not writable' 발생시 조치사항 총관리자 2017.05.02 336
245 hadoop에서 yarn jar ..를 이용하여 appliction을 실행하여 정상적으로 수행되었으나 yarn UI의 어플리케이션 목록에 나타나지 않는 문제 총관리자 2017.05.02 24
244 hadoop에서 yarn jar ..를 이용하여 appliction을 실행하여 정상적으로 수행되었으나 yarn UI의 어플리케이션 목록에 나타나지 않는 문제 총관리자 2017.05.02 51
243 hadoop에서 yarn jar ..를 이용하여 appliction을 실행하여 정상적으로 수행되었으나 yarn UI의 어플리케이션 목록에 나타나지 않는 문제 총관리자 2017.05.02 117
242 hadoop에서 yarn jar ..를 이용하여 appliction을 실행하여 정상적(?)으로 수행되었으나 yarn UI의 어플리케이션 목록에 나타나지 않는 문제 총관리자 2017.05.02 77
241 Ubuntu 16.04 LTS에 Hive 2.1.1설치하면서 "Version information not found in metastore"발생하는 오류원인및 조치사항 총관리자 2017.05.03 471

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