2) Difference between partitioning and Bucketing

Question

Accepted Answer

Partitioning is dividing data into smaller chunks based on a column value. Bucketing is dividing data into equal-sized buckets based on a hash function.

Partitioning is used for organizing data for efficient querying and processing.
Bucketing is used for evenly distributing data across nodes in a cluster.
Partitioning is done based on a column value, such as date or region.
Bucketing is done based on a hash function, such as MD5 or SHA-1.
Partitioning can improve query performance by reducing the amount of data that needs to be scanned.
Bucketing can improve join performance by reducing the amount of data that needs to be shuffled.
Example: Partitioning data by date can improve performance for time-based queries.
Example: Bucketing data by customer ID can improve join performance for customer-related queries.

Accepted Answer

Partition and bucketing both are performance increase techniques in hive

If any table having large no of records and we want fetch any particular that time the time consuming process to avoid this do the partition partition means further division of data have two types

Static partition. In this partition loaded bulk ammount of data at a time we create different files import this files into the hive

In dynamic partition. When table having different city records and we apply partition based on city column that time we use dynamic partition here

Dynamic partition load the one by one records

Bucketing

Bucket used when the table having more distinct values in one of the column and unequal partition that time we use bucketing

2) Difference between partitioning and Bucketing

Top IBM Data Engineer interview questions & answers

Popular interview questions of Data Engineer

Top HR questions asked in IBM Data Engineer