PostgreSQL does not use a partial index - sql

Question

I have a table in PostgreSQL 9.2 that has a text column. Let's call this text_col. The values in this column are fairly unique (may contain 5-6 duplicates at the most). The table has ~5 million rows. About half these rows contain a null value for text_col. When I execute the following query I expect 1-5 rows. In most cases (>80%) I only expect 1 row.
Query
explain analyze SELECT col1,col2.. colN
FROM table
WHERE text_col = 'my_value';
A btree index exists on text_col. This index is never used by the query planner and I am not sure why. This is the output of the query.
Planner
Seq Scan on two (cost=0.000..459573.080 rows=93 width=339) (actual time=1392.864..3196.283 rows=2 loops=1)
Filter: (victor = 'foxtrot'::text)
Rows Removed by Filter: 4077384
I added another partial index to try to filter out those values that were not null, but that did not help (with or without text_pattern_ops. I do not need text_pattern_ops considering no LIKE conditions are expressed in my queries, but they also match equality).
CREATE INDEX name_idx
ON table
USING btree
(text_col COLLATE pg_catalog."default" text_pattern_ops)
WHERE text_col IS NOT NULL;
Disabling sequence scans using set enable_seqscan = off; makes the planner still pick the seqscan over an index_scan. In summary...
The number of rows returned by this query is small.
Given that the non-null rows are fairly unique, an index scan over the text should be faster.
Vacuuming and analyzing the table did not help the optimizer pick the index.
My questions
Why does the database pick the sequence scan over the index scan?
When a table has a text column whose equality condition should be checked, are there any best practices I can adhere to?
How do I reduce the time taken for this query?
[Edit - More information]
The index scan is picked up on my local database that houses about 10% of the data that is available in production.

Answer 1

A partial index is a good idea to exclude half the rows of the table which you obviously do not need. Simpler:
CREATE INDEX name_idx ON table (text_col)
WHERE text_col IS NOT NULL;
Be sure to run ANALYZE table after creating the index. (Autovacuum does that automatically after some time if you don't do it manually, but if you test right after creation, your test will fail.)
Then, to convince the query planner that a particular partial index can be used, repeat the WHERE condition in the query - even if it seems completely redundant:
SELECT col1,col2, .. colN
FROM table
WHERE text_col = 'my_value'
AND text_col IS NOT NULL; -- repeat condition
Voilá.
Per documentation:
However, keep in mind that the predicate must match the conditions
used in the queries that are supposed to benefit from the index. To be
precise, a partial index can be used in a query only if the system can
recognize that the WHERE condition of the query mathematically implies
the predicate of the index. PostgreSQL does not have a sophisticated
theorem prover that can recognize mathematically equivalent
expressions that are written in different forms. (Not only is such a
general theorem prover extremely difficult to create, it would
probably be too slow to be of any real use.) The system can recognize
simple inequality implications, for example "x < 1" implies "x < 2";
otherwise the predicate condition must exactly match part of the
query's WHERE condition or the index will not be recognized as usable.
Matching takes place at query planning time, not at run time. As a
result, parameterized query clauses do not work with a partial index.
As for parameterized queries: again, add the (redundant) predicate of the partial index as an additional, constant WHERE condition, and it works just fine.
An important update in Postgres 9.6 largely improves chances for index-only scans (which can make queries cheaper and the query planner will more readily chose such query plans). Related:
PostgreSQL not using index during count(*)

Answer 2

A partial index is only used if the WHERE conditions match. Thus an index with WHERE text_col IS NOT NULL can only be used if you use the same condition in your SELECT. Collation mismatch could also cause harm.
Try the following:
Make a simplest possible btree index CREATE INDEX foo ON table (text_col)
ANALYZE table
Query

Answer 3

I figured it out. Upon taking a closer look at the pg_stats view that analyze helps build, I came across this excerpt on the documentation.
Correlation
Statistical correlation between physical row ordering and logical
ordering of the column values. This ranges from -1 to +1. When the
value is near -1 or +1, an index scan on the column will be estimated
to be cheaper than when it is near zero, due to reduction of random
access to the disk. (This column is null if the column data type does
not have a < operator.)
On my local box the correlation number is 0.97 and on production it was 0.05. Thus the planner is estimating that it is easier to go through all those rows sequentially instead of looking up the index each time and diving into a random access on the disk block. This is the query I used to peek at the correlation number.
select * from pg_stats where tablename = 'table_name' and attname = 'text_col';
This table also has a few updates performed on its rows. The avg_width of the rows is estimated to be 20 bytes. If the update has a large value for a text column, it can exceed the average and also result in a slower update. My guess was that the physical and logical ordering are slowing moving apart with each update. To fix that I executed the following queries.
ALTER TABLE table_name SET (FILLFACTOR = 80);
VACUUM FULL table_name;
REINDEX TABLE table_name;
ANALYZE table_name;
The idea is that I could give each disk block a 20% buffer and vacuum full the table to reclaim lost space and maintain physical and logical order. After I did this the query picks up the index.
Query
explain analyze SELECT col1,col2... colN
FROM table_name
WHERE text_col is not null
AND
text_col = 'my_value';
Partial index scan - 1.5ms
Index Scan using tango on two (cost=0.000..165.290 rows=40 width=339) (actual time=0.083..0.086 rows=1 loops=1)
Index Cond: ((victor five NOT NULL) AND (victor = 'delta'::text))
Excluding the NULL condition picks up the other index with a bitmap heap scan.
Full index - 0.08ms
Bitmap Heap Scan on two (cost=5.380..392.150 rows=98 width=339) (actual time=0.038..0.039 rows=1 loops=1)
Recheck Cond: (victor = 'delta'::text)
-> Bitmap Index Scan on tango (cost=0.000..5.360 rows=98 width=0) (actual time=0.029..0.029 rows=1 loops=1)
Index Cond: (victor = 'delta'::text)
[EDIT]
While it initially looked like correlation plays a major role in choosing the index scan #Mike has observed that a correlation value that is close to 0 on his database still resulted in an index scan. Changing fill factor and vacuuming fully has helped but I'm unsure why.