Sqoop version: 1.4.4.2.1.7.0-784 The following is the sqoop command that i used to export simple(comma separated) records . sqoop-export --connect jdbc:oracle:thin:@ipaddress:1521:orcl --username user --password password --table EMP --columns EMPNO,ENAME,JOB,MGR --export-dir /sqooptest/export -m 1 --batch The above command stucks at 95% and doesn't get completed. ... View more

select t1.student_id, t2.course_name from table_one t1 join table_two t2 on (t1.course_id=t2.course_id); The above one is the basic query i am dealing with.Where t1 and t2 are less in size 160 bytes and 50 bytes. When i run the above query ,Map only join is running as usual as "hive.auto.convert.join=true" by default in 0.14. Now, I made "set hive.auto.convert.join=false;".I run the query .Then query chooses "Default or map reduce join " as i taught. Now i changed query like select /*+ MAPJOIN(t2) */ t1.student_id,t2.course_name from table_one t1 join table_two t2 on (t1.course_id=t2.course_id); i.e I am giving hint through query.But In this case also,query chooses default join only.So i have 2 queries(still auto conversion set false) 1) How to give hint through query,so that query should select map only join.(when auto conversion set false). 2)What is the configuration parameter to know size where tables can fit it.So that map only join run. or How to know the size where tables can fit with in to run map only join. ... View more

I know some of the admin commands to check cluster detail.I am planning to write HDP practical as well as real exam.Other than admin commands ,Is there any way to check AWS ??? ... View more

Upto now, I am thinking like Normal join is simple map/reduce job where two tables are two inputs .Based on columns given in equality expression ,Key and values will be decided in map side and they are grouped when comes to reducer side. But when i read following lines, i confused a little bit about "Difference between Map side join and Normal join". In every map/reduce stage of the join, the last table in the sequence is streamed through the reducers where as the others are buffered. Therefore, it helps to reduce the memory needed in the reducer for buffering the rows for a particular value of the join key by organizing the tables such that the largest tables appear last in the sequence. e.g. in SELECT a.val, b.val, c.val FROM a JOIN b ON (a.key = b.key1) JOIN c ON (c.key = b.key1) Can any one explain above lines in normal join in details??? Once explain stream table and buffering in normal join?? ... View more