sql - Best way to handle multiple table query linked to "main" table -

i tracking visitor sessions , have "master" table contains session start, end , visitor info.

create table "sessions" (     session_id bigserial primary key,     session_start timestamp not null,     session_end timestamp not null     user_ip text not null,     user_agent text not null ) 

for each session have 3 metrics - pageviews, downloads , video plays. each table follows formula

create table "sessions_<x>" (     session_id bigint references sessions (session_id),     data_1 text not null,     data_2 text not null,     ... ) 

the 3 tables not identical, data not important - thing share session_id reference sessions table.

data inserted so, in single transaction, relevant pageview/download/video play record added , session_start / session_end updated.

for code, wish extract each session associated pageviews, downloads , video plays. in effort minimize number of queries figured i'd following:

1. do query on sessions table identifying information + session_id each session.
2. for each of 3 metric tables, select * table session_id in (<sessions>)
3. in code, "collect" data each result set #2 , associate base session information.

i wondering if best approach. have worries large data sets might bad idea (lots of in-memory data @ time), there alternative can in 1 query session information + associated metrics (for 3 tables) easily? or @ least in way can iterate through in program 1 session @ time?

this not user-facing web service, super-fast, sub-second replies not goal, performance factor. service being built in python if matters , using postgresql 9.2.

try:

select * session s left outer join session_<x> sx on s.session_id = sx.session_id left outer join session_<y> sy on s.session_id = sy.session_id;