Types of partitioning in hive, bucketing in hive, hoq to dedup data, what RDDs and dataframes, difference between spark session and context, prwtty json format

Question

Accepted Answer

Answering questions related to Hive, Spark, and JSON format.

Types of partitioning in Hive: static and dynamic
Bucketing in Hive: used for efficient sampling and joins
Deduplication in Hive: using DISTINCT keyword or GROUP BY clause
RDDs and DataFrames: both are distributed collections in Spark, but DataFrames have a schema
Difference between Spark Session and Context: Session is a higher-level API that includes Context
Pretty JSON format: using indentation and line breaks for readability

Types of partitioning in hive, bucketing in hive, hoq to dedup data, what RDDs and dataframes, difference between spark session and context, prwtty json format

Popular interview questions of Software Engineer