Hello @K_K Once you run a query in beeline pick the queryID and trace the queryID in Hiveserver2 logs to figure out how much time it takes in the HTTP handler thread and the background thread to figure out any slowness in this part. Once the job goes through this it reaches YARN so you need to check the YARN application log of the query about where it is getting slow whether at AM level/container assigning level or task level. In this way, you can see where it is taking time. If it is a managed table you can run major compaction in the table to compress all the delta files into a single base file, in this way you can eliminate multiple HDFS scanning while running the query. You can also run explain plan against the query to figure out the flow and how much data it is processing. You can also run analyze query against the table to collect the column stats and table stats that will increase the query performance. All the jobs cannot be completed in lesser than 4 seconds. Reference: https://cwiki.apache.org/confluence/display/Hive/StatsDev#StatsDev-ANALYZETABLE%3Ctable1%3ECACHEMETADATA https://docs.cloudera.com/HDPDocuments/HDP3/HDP-3.0.1/performance-tuning/content/hive_query_result_cache_ms_cache.html https://docs.cloudera.com/HDPDocuments/HDP3/HDP-3.1.5/using-hiveql/content/hive_hive_3_tables.html
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