Hive - Is there a way to further optimize a HiveQL query?

Question

I have written a query to find 10 most busy airports in the USA from March to April. It produces the desired output however I want to try to further optimize it.

Ar

Answer 1

Filter by airport(inner join) and do aggregation before UNION ALL to reduce dataset passed to the final aggregation reducer. UNION ALL subqueries with joins should run in parallel and faster than join with bigger dataset after UNION ALL.

SELECT f.airport, SUM(cnt) AS Total_Flights
FROM (
      SELECT a.airport, COUNT(*) as cnt 
       FROM flights_stats f
            INNER JOIN airports a ON f.Origin=a.iata AND a.country='USA'
       WHERE Cancelled = 0 AND Month IN (3,4)
       GROUP BY a.airport
       UNION ALL
      SELECT a.airport, COUNT(*) as cnt
       FROM flights_stats f
            INNER JOIN airports a ON f.Dest=a.iata AND a.country='USA'
       WHERE Cancelled = 0 AND Month IN (3,4)
       GROUP BY a.airport
     ) f 
GROUP BY f.airport
ORDER BY Total_Flights DESC
LIMIT 10
;

Tune mapjoins and enable parallel execution:

set hive.exec.parallel=true;
set hive.auto.convert.join=true; --this enables map-join
set hive.mapjoin.smalltable.filesize=25000000; --size of table to fit in memory

Use Tez and vectorizing, tune mappers and reducers parallelism: https://stackoverflow.com/a/48487306/2700344