Partition vs Bucketing | Data Engineer interview

#dataengineer #dataengineering #interviewquestions #spark #hive

Hive, Spark provides different methods to optimize the performance of queries. So As part of this video, we are covering the following
What is Partitioning
How does partitioning help to improve performance
What is Bucketing
How does bucketing helps to improve performance
Difference between Partitioning and Bucketing

we will see most asked data engineer interview question

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what we have covered in this video:

Both Partitioning and Bucketing in Hive are used to improve performance by eliminating table scans when dealing with a large set of data on a Hadoop file system (HDFS). The major difference between Partitioning vs Bucketing lives in the way how they split the data

Partition is a way to organize large tables into smaller logical tables based on values of columns; one logical table (partition) for each distinct value. In Hive, tables are created as a directory on HDFS. A table can have one or more partitions that correspond to a sub-directory for each partition inside a table directory.

Bucketing a.k.a (Clustering) is a technique to split the data into more manageable files, (By specifying the number of buckets to create). The value of the bucketing column will be hashed by a user-defined number into buckets.

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Hope you liked this video and learned something new :)
See you in next video, until then Bye-Bye!

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#apachespark #sparktutorial #bigdata #hive #dataengineer
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[devendrag]

Bro, your way of explanation very well. could you pls make Oracle SQL and PLSQL concept videos one by one?

[anjibabumakkena]

Kindly make a video about the below topics
Shuffle hash join
Sort merge join
Data skew
OOM

[anirudhrayapudi]

I have one bucketing concept...hash technique is used for storing the data or for retrieving the data?