All stacks · Compute & processing
HDFS, YARN, Hive, and the on-prem stack still running in many banks.
HadoopNameNode small-file pauses, the Hive metastore as the real lock-in, and why distcp-plus-EMR keeps the same tables. Iceberg is the exit, not a new cluster.
DatabricksHow I structure Unity Catalog for real teams: three-level namespace design, group-based grants, lineage that works, and a hive_metastore migration that ships.
Hadoop is not dead in the places that matter for interviews: banks, telcos, and on-prem estates still run HDFS, YARN, Hive, and Sqoop. The cloud lakehouse is the migration story, not the starting point for those teams.
Learn Hive tables, partitioning, and why small files kill NameNodes — then learn Iceberg on object storage as the exit. Skipping Hadoop entirely is how you fail a legacy-platform screen.
No. New platforms start on object storage plus Iceberg or a warehouse. Hadoop skills still matter because migrations and interviews assume you can read a Hive table and a YARN queue.
Spark (or Trino) on Iceberg/Delta is the modern path. Hive-on-Tez is maintenance. If the metastore is Hive, you can still query it from engines that are not Hive.
Lift-and-shift of every small file and every cron Sqoop job into S3 + EMR with no table format. You moved the NameNode problem into LIST requests and a bigger bill.
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