Help with view performance problem

I am having a problem with a view on one of my db's.  This view is
trying to sequentially can the 2 tables it is accessing.  However,
when I explain the view on most of my other db's (all have the same
schema's), it is using the indexes.  Can anyone please help me
understand why postgres is choosing to sequenially scan both tables?

Both tables in the view have a primary key defined on inv_nbr,
inv_qfr.  Vacuum and analyze have been run on the tables in question
to try and make sure stats are up to date.

Thanks,

Chris
PG - 7.3.4
RH 2.1


Here is the view definition:
SELECT DISTINCT clmcom1.inv_nbr AS inventory_number,
                              clmcom1.inv_qfr AS inventory_qualifier,
                              clmcom1.pat_addr_1 AS patient_address_1,
                              clmcom1.pat_addr_2 AS patient_address_2,
                              clmcom1.pat_city AS patient_city,
                              clmcom1.pat_cntry AS patient_country,
                              clmcom1.pat_dob AS patient_date_of_birth,
                              clmcom1.pat_gender_cd AS patient_gender_code,
                              clmcom1.pat_info_pregnancy_ind AS pregnancy_ind,
                              clmcom1.pat_state AS patient_state,
                              clmcom1.pat_suffix AS patient_suffix,
                              clmcom1.pat_zip AS patient_zip_code,
                              clmcom1.payto_addr_1 AS payto_address_1,
                              clmcom1.payto_addr_2 AS payto_address_2,
                              clmcom1.payto_city,
                              clmcom1.payto_cntry AS payto_country,
                              clmcom1.payto_f_name AS payto_first_name,
                              clmcom1.payto_m_name AS payto_middle_name,
                              clmcom1.payto_state,
                              clmcom1.payto_zip AS payto_zip_code,
                              clmcom1.clm_tot_clm_chgs AS total_claim_charge,
                              clmcom1.bill_l_name_org AS
billing_last_name_or_org,
                              clmcom1.clm_delay_rsn_cd AS
claim_delay_reason_code,
                              clmcom1.clm_submit_rsn_cd AS
claim_submit_reason_code,
                              clmcom1.payto_l_name_org AS
payto_last_name_or_org,
                              clmcom1.payto_prim_id AS payto_primary_id,
                              clmcom1.bill_prim_id AS billing_prov_primary_id,
                              clmcom1.clm_tot_ncov_chgs AS total_ncov_charge,
                              clmcom2.contract_amt AS contract_amount,
                              clmcom2.svc_fac_or_lab_name,
                              clmcom2.svc_fac_addr_1 AS svc_fac_address_1,
                              clmcom2.svc_fac_addr_2 AS svc_fac_address_2,
                              clmcom2.svc_fac_city,
                              clmcom2.svc_fac_zip AS svc_fac_zip_code
FROM (clmcom1 LEFT JOIN clmcom2 ON (((clmcom1.inv_nbr =
clmcom2.inv_nbr) AND

(clmcom1.inv_qfr = clmcom2.inv_qfr))))
ORDER BY clmcom1.inv_nbr,
                  clmcom1.inv_qfr,
                  clmcom1.pat_addr_1,
                  clmcom1.pat_addr_2,
                  clmcom1.pat_city,
                  clmcom1.pat_cntry,
                  clmcom1.pat_dob,
                  clmcom1.pat_gender_cd,
                  clmcom1.pat_info_pregnancy_ind,
                  clmcom1.pat_state,
                  clmcom1.pat_suffix,
                  clmcom1.pat_zip,
                  clmcom1.payto_addr_1,
                  clmcom1.payto_addr_2,
                  clmcom1.payto_city,
                  clmcom1.payto_cntry,
                  clmcom1.payto_f_name,
                  clmcom1.payto_m_name,
                  clmcom1.payto_state,
                  clmcom1.payto_zip,
                  clmcom1.clm_tot_clm_chgs,
                  clmcom1.bill_l_name_org,
                  clmcom1.clm_delay_rsn_cd,
                  clmcom1.clm_submit_rsn_cd,
                  clmcom1.payto_l_name_org,
                  clmcom1.payto_prim_id,
                  clmcom1.bill_prim_id,
                  clmcom1.clm_tot_ncov_chgs,
                  clmcom2.contract_amt,
                  clmcom2.svc_fac_or_lab_name,
                  clmcom2.svc_fac_addr_1,
                  clmcom2.svc_fac_addr_2,
                  clmcom2.svc_fac_city,
                  clmcom2.svc_fac_zip;


Here is the explain analyze from the problem db:
prob_db=# explain analyze select * from clm_com;



                          QUERY PLAN




--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Subquery Scan clm_com  (cost=1039824.35..1150697.61 rows=126712
width=367) (actual time=311792.78..405819.03 rows=1266114 loops=1)
   ->  Unique  (cost=1039824.35..1150697.61 rows=126712 width=367)
(actual time=311792.74..386313.14 rows=1266114 loops=1)
         ->  Sort  (cost=1039824.35..1042992.16 rows=1267123
width=367) (actual time=311792.74..338189.48 rows=1266114 loops=1)
               Sort Key: clmcom1.inv_nbr, clmcom1.inv_qfr,
clmcom1.pat_addr_1, clmcom1.pat_addr_2, clmcom1.pat_city,
clmcom1.pat_cntry, clmcom1.pat_dob, clmcom1.pat_gender_cd,
clmcom1.pat_info_pregnancy_ind, clmcom1.pat_state, clmcom1.pat_suffix,
clmcom1.pat_zip, clmcom1.payto_addr_1,
clmcom1.payto_addr_2, clmcom1.payto_city, clmcom1.payto_cntry,
clmcom1.payto_f_name, clmcom1.payto_m_name, clmcom1.payto_state,
clmcom1.payto_zip, clmcom1.clm_tot_clm_chgs, clmcom1.bill_l_name_org,
clmcom1.clm_delay_rsn_cd, clmcom1.clm_submit_rsn_cd,
clmcom1.payto_l_name_org, clmcom1.payto_prim_id, clmcom1.bill_prim_id,
clmcom1.clm_tot_ncov_chgs, clmcom2.contract_amt,
clmcom2.svc_fac_or_lab_name, clmcom2.svc_fac_addr_1,
clmcom2.svc_fac_addr_2, clmcom2.svc_fac_city, clmcom2.svc_fac_zip
               ->  Hash Join  (cost=132972.78..548171.70 rows=1267123
width=367) (actual time=16999.32..179359.43 rows=1266114 loops=1)
                     Hash Cond: ("outer".inv_nbr = "inner".inv_nbr)
                     Join Filter: ("outer".inv_qfr = "inner".inv_qfr)
                     ->  Seq Scan on clmcom1  (cost=0.00..267017.23
rows=1267123 width=271) (actual time=0.11..84711.83 rows=1266114
loops=1)
                     ->  Hash  (cost=111200.82..111200.82 rows=1269582
width=96) (actual time=16987.45..16987.45 rows=0 loops=1)
                           ->  Seq Scan on clmcom2
(cost=0.00..111200.82 rows=1269582 width=96) (actual
time=0.07..12164.81 rows=1266108 loops=1)
 Total runtime: 407317.47 msec
(11 rows)
~



Here is the explain analyze from a good db (on the same postgres cluster);
good_db=# explain analyze select * from clm_com;





                            QUERY PLAN

--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
 Subquery Scan clm_com  (cost=78780.59..89498.29 rows=12249 width=359)
(actual time=73045.36..79974.37 rows=122494 loops=1)
   ->  Unique  (cost=78780.59..89498.29 rows=12249 width=359) (actual
time=73045.28..78031.99 rows=122494 loops=1)
         ->  Sort  (cost=78780.59..79086.81 rows=122488 width=359)
(actual time=73045.28..73362.94 rows=122494 loops=1)
               Sort Key: clmcom1.inv_nbr, clmcom1.inv_qfr,
clmcom1.pat_addr_1, clmcom1.pat_addr_2, clmcom1.pat_city,
clmcom1.pat_cntry, clmcom1.pat_dob, clmcom1.pat_gender_cd,
clmcom1.pat_info_pregnancy_ind, clmcom1.pat_state, clmcom1.pat_suffix,
clmcom1.pat_zip, clmcom1.payto_addr_1, clmcom1.payto_addr_2,
clmcom1.payto_city, clmcom1.payto_cntry, clmcom1.payto_f_name,
clmcom1.payto_m_name, clmcom1.payto_state, clmcom1.payto_zip,
clmcom1.clm_tot_clm_chgs, clmcom1.bill_l_name_org,
clmcom1.clm_delay_rsn_cd, clmcom1.clm_submit_rsn_cd,
clmcom1.payto_l_name_org, clmcom1.payto_prim_id, clmcom1.bill_prim_id,
clmcom1.clm_tot_ncov_chgs, clmcom2.contract_amt,
clmcom2.svc_fac_or_lab_name, clmcom2.svc_fac_addr_1,
clmcom2.svc_fac_addr_2, clmcom2.svc_fac_city, clmcom2.svc_fac_zip
               ->  Merge Join  (cost=0.00..56945.12 rows=122488
width=359) (actual time=54.76..71635.65 rows=122494 loops=1)
                     Merge Cond: (("outer".inv_nbr = "inner".inv_nbr)
AND ("outer".inv_qfr = "inner".inv_qfr))
                     ->  Index Scan using clmcom1_pkey on clmcom1
(cost=0.00..38645.61 rows=122488 width=267) (actual
time=25.60..49142.16 rows=122494 loops=1)
                     ->  Index Scan using clmcom2_pkey on clmcom2
(cost=0.00..16004.08 rows=122488 width=92) (actual
time=29.09..19418.94 rows=122494 loops=1)
 Total runtime: 80162.26 msec
(9 rows)