I am with a_horse on this: Upgrade to Postgres 9.6 to have new options at your disposal (and for other reasons).
While stuck with 9.4, it might help to simplify like this:
CREATE OR REPLACE FUNCTION jsonb_merge2(jsonb1 JSONB, jsonb2 JSONB)
RETURNS JSONB LANGUAGE sql IMMUTABLE AS
$func$
SELECT
CASE
WHEN jsonb_typeof($1) = 'object' AND jsonb_typeof($2) = 'object' THEN
(
SELECT jsonb_object_agg(merged.key, merged.value)
FROM (
SELECT key
, CASE WHEN p1.value <> p2.value -- implies both are NOT NULL
THEN jsonb_merge2(p1.value, p2.value)
ELSE COALESCE(p2.value, p1.value) -- p2 trumps p1
END AS value
FROM jsonb_each($1) p1
FULL JOIN jsonb_each($2) p2 USING (key) -- USING helps to simplify
) AS merged
WHERE merged.value IS NOT NULL -- simpler, might help query planner
AND merged.value NOT IN ( '[]', 'null', '{}' )
)
WHEN $2 IN ( '[]', 'null', '{}' ) THEN -- just as simple as above
NULL
ELSE
$2
END
$func$;
Currently (version 9.6), Postgres does not have any statistics about the internals of document types like json, jsonb, xml or hstore. (There has been discussion whether and how to change that.) Instead, the Postgres query planner uses constant default frequency estimates (like you observed).
However, there are separate statistics for functional indexes like your idx_test_btree. The manual has this tip for you:
Tip: Although per-column tweaking of ANALYZE frequency might not be
very productive, you might find it worthwhile to do per-column
adjustment of the level of detail of the statistics collected by
ANALYZE. Columns that are heavily used in WHERE clauses and have
highly irregular data distributions might require a finer-grain data
histogram than other columns. See ALTER TABLE SET STATISTICS, or
change the database-wide default using the default_statistics_target
configuration parameter.
Also, by default there is limited information available about the
selectivity of functions. However, if you create an expression index
that uses a function call, useful statistics will be gathered about
the function, which can greatly improve query plans that use the
expression index.
The volume of statistics gathered depends on general setting of default_statistics_target, which can be overruled with a per-column setting. The setting for the column automatically covers depending indexes.
The default setting of 100 is conservative. For your test with 1M rows, if data distribution is uneven, it may help to increase it substantially. Checking on this once more I found you can actually tweak the statistics target per index column with ALTER INDEX, which is currently not documented. See related discussion on pgsql-docs.
ALTER TABLE idx_test_btree ALTER int4 SET STATISTICS 2000; -- max 10000, default 100
Default names for index columns are not exactly intuitive, but you can look it up with:
SELECT attname FROM pg_attribute WHERE attrelid = 'idx_test_btree'::regclass
Should result in the type name int4 as index column name for your case.
The best setting for STATISTICS depends on several factors: data distribution, data type, update frequency, characteristics of typical queries, ...
Internally, this sets the value of pg_attribute.attstattarget, and the exact meaning of this is (per documentation):
For scalar data types, attstattarget is both the target number of
"most common values" to collect, and the target number of histogram
bins to create.
Then run ANALYZE if you don't want to wait for autovacuum to kick in:
ANALYZE test_data;
You must ANALYZE the table, since you cannot ANALYZE indexes directly. Check with (before and after if you want to verify the effect):
SELECT * FROM pg_statistic WHERE starelid = 'idx_test_btree'::regclass;
Try your query again ...
Related:
Best Answer
The answer is: in pgadmin you have to escape every quotation mark before and after key/value definition. What a sophisticated solution.