I have taken CCA 175 on 06-Oct-2019(8 correct out of 9)
just want to share my personal experience with you, so it may useful who are planning take CC175.
Preparation : if you want to give exam, minimum 1 to 2 months preparation is required with seriousness
I wanted to give exam almost 10months back, but did not prepare seriously, but prepared Python well, that help me, while I started seriously 3months
Materials : Gone through lot of Youtube tutorials on HDFS, Python and Pyspark2…etc, but finally stick with following ITVersity materials.
I have registered “ITVersity Labs” and setup “Cloudera quickstart vm” in my laptop, practiced on both environments and understood the environments better.
Once I ready with preparation, booked the CCA 175 exam date then practiced few mock tests to understand time management
Exam Experience : 1 sqoop import, 1 sqoop export, remain 7 spark questions got in exam.
I had camera issues initially, took extra 15mins to fix.
completed all 9 questions and verified results once again and thought all answers were right.
Tried spark questions in pyspark2 with spark sql, one question had issues with spark sql and DF, so left that question and completed all remain at last I completed that question in RDD(thought to left this question as I completed remain 8), but results saying one was not correct out of remain 8. so we should finish all questions in any format Spark SQL or DF or RDD.
**Some important points **
- Read question twice before start, then choose Spark sql or DF or RDD, which is good to finish
- Don’t spend time on failed question, first finish remain all questions and come back to failed one. 10mins per question.
- use Sublime text, open tab per question(9 tabs for 9 questions), this way you can review your answers before close exam.
- Open multiple command prompts like for hive, sql, spark and hdfs
- Check the target paths and sample data from target
- Before close/submit exam, review questions and your answers once again
Thanks ITVersity and material and Labs
Prepare for certifications on our state of the art labs which have Hadoop, Spark, Kafka, Hive and other Big Data technologies
- Click here for signing up for our state of the art 13 node Hadoop and Spark Cluster