I'm running a job like this:
raw_large = LOAD 'lots_of_files' AS (...);
raw_filtered = FILTER raw_large BY ...;
large_table = FOREACH raw_filtered GENERATE f1, f2, f3,....;
joined_1 = JOIN large_table BY (key1) LEFT, config_table_1 BY (key2) USING
joined_2 = JOIN join1 BY (key3) LEFT, config_table_2 BY (key4)
joined_3 = JOIN join2 BY (key5) LEFT, config_table_3 BY (key6)
joined_4 = JOIN join4 BY (key7) LEFT, config_table_3 BY (key8)
basically left join a large table with 4 relatively small tables using the
I see a first load job has 120 mapper tasks and no reducer, and this job
seems to be doing the load and filtering. And there is another job
following that has 26 mapper tasks that seem to be doing the joins.
Shouldn't there be only one job and the joins being done in the mapper
phase of the first job?
The 4 config tables (files) have these sizes respectively:
these are running on AWS EMR Pig 0.92 on xlarge instances which has 15GB