Partitioning vs Bucketing By Example | Spark | big data interview questions #13 | TeKnowledGeek

Partitioning vs Bucketing By Example | Spark | big data interview questions and answers #13 | TeKnowledGeek

Hello and Welcome to Big Data and Hadoop Tutorial by TeKnowledGeek. This tutorial is based on top Hadoop Interview questions and answers that can help anyone to get a job in Big Data Career. This is the latest video with the collections of big data interview questions from the subject matter experts in the big data field will help you pass interview questions.

Let’s know the questions that are explained in this video. In this video, the interview questions are based on Spark and the questions as follows,

1. Why you need partition?
2. Why you need bucketing?
3. What is the benifit of using bucket?
4. What is the upper limit of number of buckets?

Watch the entire video, learn and understand the answers for the above big data interview questions and learn how to clear the big data interview and get a job in job in Big Data stream.
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[banty]

Hi,
Thanks for your information 👍 it was clear and crisp but here I've two queries to your explanation
1)how to decide number of buckets, kindly demonstrate by taking some sample data or file

2)so we can implement bucketing using spark and save it to the hive table, but the challenge is when we check back for the table on hive it throws an error as java.io.error .. and failed to access the records of that table
If possible please demonstrate the same as well in one video.
I'm proliferating your channel link in our data engineering fraternity.
Thanks 😊

[bhavaniv]

I want to learn spark and scala can please share your experience