Spark and hadoop architectural difference , DAG, What is stage boundaries , Partitioning and bucketing in hive

Question

Accepted Answer

Spark and Hadoop have different architectures. DAG is a directed acyclic graph. Stage boundaries are logical divisions in a Spark job. Hive has partitioning and bucketing.

Spark is an in-memory processing engine while Hadoop is a distributed file system.
DAG is a graph of stages in a Spark job.
Stage boundaries are logical divisions in a Spark job that help optimize execution.
Partitioning in Hive is a way to divide a table into smaller, more manageable parts based on a column.
Bucketing in Hive is a way to group data into more manageable parts based on a hash function.

Spark and hadoop architectural difference , DAG, What is stage boundaries , Partitioning and bucketing in hive

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