Performance issue with postgres_fdw

Hello,

I use Postgres version 9.3.5 and spot a performance issue
with postgres_fdw.

I have a table object_003_xyz with 275000 lines and is
exported to the master node as master_object_003_xyz.

( The following query is only a part of an automatically
generated complex query. )

On the master:

SELECT * FROM master_object_003_xyz AS o1, master_object_003_xyz AS o2 WHERE
o1.objectid <> o2.objectid AND cos(radians(o1.ra_PS)) *
cos(radians(o1.decl_PS)) BETWEEN cos(radians(o2.ra_PS)) *
cos(radians(o2.decl_PS)) - sin(radians(1.5e-5 / 2)) * 2 AND
cos(radians(o2.ra_PS)) * cos(radians(o2.decl_PS)) + sin(radians(1.5e-5 / 2))
* 2 AND sin(radians(o1.ra_PS)) * cos(radians(o1.decl_PS)) BETWEEN
sin(radians(o2.ra_PS)) * cos(radians(o2.decl_PS)) - sin(radians(1.5e-5 / 2))
* 2 AND sin(radians(o2.ra_PS)) * cos(radians(o2.decl_PS)) +
sin(radians(1.5e-5 / 2)) * 2 AND sin(radians(o1.decl_PS)) BETWEEN
sin(radians(o2.decl_PS)) - sin(radians(1.5e-5 / 2)) * 2 AND
sin(radians(o2.decl_PS)) + sin(radians(1.5e-5 / 2)) * 2 AND
degrees(asin(sqrt(power(sin(radians((o2.decl_PS - o1.decl_PS) / 2)), 2) +
power(sin(radians((o2.ra_PS - o1.ra_PS) / 2)), 2) * cos(radians(o1.decl_PS))
* cos(radians(o2.decl_PS)))) * 2) <= 1.5e-5
(4 rows)
Time: 513711.684 ms

Here is the plan used:

Nested Loop (cost=200.70..44187032.64 rows=34518880 width=2168)
-> Foreign Scan on master_object_003_xyz o2 (cost=100.00..24294.47
rows=275449 width=1084)
-> Foreign Scan on master_object_003_xyz o1 (cost=100.70..160.32 rows=1
width=1084)

On the pool:

SELECT * FROM object_003_xyz AS o1, object_003_xyz AS o2 WHERE o1.objectid <>
o2.objectid AND cos(radians(o1.ra_PS)) * cos(radians(o1.decl_PS)) BETWEEN
cos(radians(o2.ra_PS)) * cos(radians(o2.decl_PS)) - sin(radians(1.5e-5 / 2))
* 2 AND cos(radians(o2.ra_PS)) * cos(radians(o2.decl_PS)) +
sin(radians(1.5e-5 / 2)) * 2 AND sin(radians(o1.ra_PS)) *
cos(radians(o1.decl_PS)) BETWEEN sin(radians(o2.ra_PS)) *
cos(radians(o2.decl_PS)) - sin(radians(1.5e-5 / 2)) * 2 AND
sin(radians(o2.ra_PS)) * cos(radians(o2.decl_PS)) + sin(radians(1.5e-5 / 2))
* 2 AND sin(radians(o1.decl_PS)) BETWEEN sin(radians(o2.decl_PS)) -
sin(radians(1.5e-5 / 2)) * 2 AND sin(radians(o2.decl_PS)) +
sin(radians(1.5e-5 / 2)) * 2 AND
degrees(asin(sqrt(power(sin(radians((o2.decl_PS - o1.decl_PS) / 2)), 2) +
power(sin(radians((o2.ra_PS - o1.ra_PS) / 2)), 2) * cos(radians(o1.decl_PS))
* cos(radians(o2.decl_PS)))) * 2) <= 1.5e-5
(4 rows)
Time: 2738.217 ms

It is much faster because it uses available index :

Nested Loop (cost=0.56..360279717.93 rows=34692216 width=2168)
-> Seq Scan on object_003_xyz o2 (cost=0.00..18685.49 rows=275449 width=1084)
-> Index Scan using object_003_xyz_idx_xyz on object_003_xyz o1
(cost=0.56..1306.64 rows=126 width=1084)
Index Cond: (((cos(radians(ra_ps)) * cos(radians(decl_ps))) >=
((cos(radians(o2.ra_ps)) * cos(radians(o2.decl_ps))) -
2.61799387799149e-07::double precision)) AND ((cos(radians(ra_ps)) *
cos(radians(decl_ps))) <= ((cos(radians(o2.ra_ps)) * cos(radians(o2.decl_ps))) +
2.61799387799149e-07::double precision)) AND ((sin(radians(ra_ps)) *
cos(radians(decl_ps))) >= ((sin(radians(o2.ra_ps)) * cos(radians(o2.decl_ps))) -
2.61799387799149e-07::double precision)) AND ((sin(radians(ra_ps)) *
cos(radians(decl_ps))) <= ((sin(radians(o2.ra_ps)) * cos(radians(o2.decl_ps))) +
2.61799387799149e-07::double precision)) AND (sin(radians(decl_ps)) >=
(sin(radians(o2.decl_ps)) - 2.61799387799149e-07::double precision)) AND
(sin(radians(decl_ps)) <= (sin(radians(o2.decl_ps)) +
2.61799387799149e-07::double precision)))
Filter: ((objectid <> o2.objectid) AND
(degrees((asin(sqrt((power(sin(radians(((o2.decl_ps - decl_ps) / 2::double
precision))), 2::double precision) + ((power(sin(radians(((o2.ra_ps - ra_ps) /
2::double precision))), 2::double precision) * cos(radians(decl_ps))) *
cos(radians(o2.decl_ps)))))) * 2::double precision)) <= 1.5e-05::double precision))

Would it be possible to avoid doing a nested loop of foreign
scans when dealing with tables on the same pool ? And to
automatically export the query directly in that case ?

What may I do for now ?

Thanks for your help and best regards,
--
Emmanuel Medernach