Thanks a lot, Sumit! I am a senior data engineer with 5 years of exp but since we don't work with dataframes or pyspark mostly I am not able to do these simple things.

Hi Sir,Waiting for the next videos on git branching

Really good videos sir

What is demons?

I want answersvideo from 11 to 20question pls urgent

who told secondaryname node becomes primary name node its wrong information Secondary NameNode helps the NameNode by periodically taking snapshots of its metadata and combining edits to reduce the size of the logs. It doesn't replace the NameNode if it goes down but assists in keeping things manageable by reducing the load on the NameNode.

Using Lead/Lag approach: WITH DownPeriods AS ( SELECT service_name, updated_time, status, LAG(status) OVER (ORDER BY updated_time) AS prev_status, LEAD(status) OVER (ORDER BY updated_time) AS next_status FROM service_status ) SELECT service_name, MIN(updated_time) AS start_updated_time, MAX(updated_time) AS end_updated_time, 'down' AS status FROM DownPeriods WHERE status = 'down' AND (prev_status = 'up' OR prev_status IS NULL) -- Identify where the "down" period starts OR (next_status = 'up' OR next_status IS NULL) -- Identify where the "down" period ends GROUP BY service_name, status ORDER BY start_updated_time; Not using Lead/lag approach: WITH StatusSequence AS ( SELECT service_name, updated_time, status, ROW_NUMBER() OVER (ORDER BY updated_time) - ROW_NUMBER() OVER (PARTITION BY status ORDER BY updated_time) AS grp FROM service_status WHERE status = 'down' ) SELECT service_name, MIN(updated_time) AS start_updated_time, MAX(updated_time) AS end_updated_time, 'down' AS status FROM StatusSequence GROUP BY service_name, grp ORDER BY start_updated_time;

at what time does he show how to download the MySQL??

Nice