Postgresql doesn't use index

Question

I have large table crumbs (about 100M+ rows, 100GB). It's just collection of json stored as text. It has index on column run_id that has about 10K unique values. So each run is small (1K - 1M rows).

For simple query:

explain analyze verbose select * from crumbs c 
where c.run_id='2016-04-26T19_02_01_015Z' limit 10

Plan is good:

Limit  (cost=0.56..36.89 rows=10 width=2262) (actual time=1.978..2.016 rows=10 loops=1)
  Output: id, robot_id, run_id, content, created_at, updated_at, table_id, fork_id, log, err
  ->  Index Scan using index_crumbs_on_run_id on public.crumbs c  (cost=0.56..5533685.73 rows=1523397 width=2262) (actual time=1.975..1.996 rows=10 loops=1)
        Output: id, robot_id, run_id, content, created_at, updated_at, table_id, fork_id, log, err
        Index Cond: ((c.run_id)::text = '2016-04-26T19_02_01_015Z'::text)
Planning time: 0.117 ms
Execution time: 2.048 ms

But if I try to look inside json stored in one of the columns it then wants to do full scan:

explain verbose select x from crumbs c, 
lateral json_array_elements(c.content::json) x
where c.run_id='2016-04-26T19_02_01_015Z' 
limit 10

Plan:

Limit  (cost=0.01..0.69 rows=10 width=32)
  Output: x.value
  ->  Nested Loop  (cost=0.01..10332878.67 rows=152343800 width=32)
        Output: x.value
        ->  Seq Scan on public.crumbs c  (cost=0.00..7286002.66 rows=1523438 width=895)
              Output: c.id, c.robot_id, c.run_id, c.content, c.created_at, c.updated_at, c.table_id, c.fork_id, c.log, c.err
              Filter: ((c.run_id)::text = '2016-04-26T19_02_01_015Z'::text)
        ->  Function Scan on pg_catalog.json_array_elements x  (cost=0.01..1.01 rows=100 width=32)
              Output: x.value
              Function Call: json_array_elements((c.content)::json)

Tried:

analyze crumbs

But made no difference.

Update 1 Disabling sequential scanning for whole database works, but this is not an option in our application. In many other places seq scan should stay:

set enable_seqscan=false;

Plan:

Limit  (cost=0.57..1.14 rows=10 width=32) (actual time=0.120..0.294 rows=10 loops=1)
  Output: x.value
  ->  Nested Loop  (cost=0.57..8580698.45 rows=152343400 width=32) (actual time=0.118..0.273 rows=10 loops=1)
        Output: x.value
        ->  Index Scan using index_crumbs_on_run_id on public.crumbs c  (cost=0.56..5533830.45 rows=1523434 width=895) (actual time=0.087..0.107 rows=10 loops=1)
              Output: c.id, c.robot_id, c.run_id, c.content, c.created_at, c.updated_at, c.table_id, c.fork_id, c.log, c.err
              Index Cond: ((c.run_id)::text = '2016-04-26T19_02_01_015Z'::text)
        ->  Function Scan on pg_catalog.json_array_elements x  (cost=0.01..1.01 rows=100 width=32) (actual time=0.011..0.011 rows=1 loops=10)
              Output: x.value
              Function Call: json_array_elements((c.content)::json)
Planning time: 0.124 ms
Execution time: 0.337 ms

Update 2:

Schema is:

CREATE TABLE crumbs
(
  id serial NOT NULL,
  run_id character varying(255),
  content text,
  created_at timestamp without time zone,
  updated_at timestamp without time zone,
  CONSTRAINT crumbs_pkey PRIMARY KEY (id)
);

CREATE INDEX index_crumbs_on_run_id
  ON crumbs
  USING btree
  (run_id COLLATE pg_catalog."default");

Update 3

Rewriting query like so:

select json_array_elements(c.content::json) x
from crumbs c
where c.run_id='2016-04-26T19_02_01_015Z' 
limit 10

Gets correct plan. Still unclear why wrong plan is chosen for second query.

Answer 1

Rewriting the query so that the limit is applied first and then the cross join against the function should make Postgres use the index:

Using a derived table:

select x 
from (
    select *
    from crumbs 
    where run_id='2016-04-26T19_02_01_015Z' 
    limit 10
) c 
  cross join lateral json_array_elements(c.content::json) x

Alternatively using a CTE:

with c as (
  select *
  from crumbs 
  where run_id='2016-04-26T19_02_01_015Z' 
  limit 10
)
select x
from c 
  cross join lateral json_array_elements(c.content::json) x

Or use json_array_elements() directly in the select list:

select json_array_elements(c.content::json) 
from crumbs c
where c.run_id='2016-04-26T19_02_01_015Z' 
limit 10

However this is something different then the other two queries because it applies the limit after "unnesting" the json array, not on the number of rows returned from the crumbs table (which is what your first query is doing).

Answer 2

You've got three different problems going on. First, the limit 10 in the first query is tipping the planner in favor of the index scan, which would otherwise be pretty expensive to get all rows matching that run_id. For the sake of comparison you might want to see what the first (un-joined) query plan looks like if you remove the limit. My guess is the planner switches to a table scan.

Second, that lateral join is unnecessary and throwing off the planner. You can expand the elements of the content array in your select clause like so:

select json_array_elements(content::json)
from crumbs
where run_id = '2016-04-26T19_02_01_015Z'
;

This is more likely to use the index scan to pick off rows for that run_id, then "unnest" the array elements for you.

But the third hidden problem is what you're actually trying to get. If you run this last query as is then you're in the same boat as the first (un-joined) query without a limit, which means you'll likely not get an index scan (not that that's inherently bad if you're reading such a large chunk of the table).

Do you want just the first few arbitrary array elements from all content arrays in that run? If so then tacking on a limit clause here should be the end of the story. If you want all array elements for this particular run then you may just have to accept a table scan, although without the lateral join you're potentially in a much better situation than the original query.

Answer 3

Data modelling suggestions:

        -- Suggest replacing the column run_id (low cardinality, and rather fat)
        -- by a reference to a domain table, like:
        -- ------------------------------------------------------------------
CREATE TABLE runs
        ( run_seq serial NOT NULL PRIMARY KEY
        , run_id character varying UNIQUE
        );

        -- Grab all the distinct values occuring in crumbs.run_id
        -- -------------------------------------------------------
INSERT INTO runs (run_id)
SELECT DISTINCT run_id FROM crumbs;

        -- Add an FK column
        -- -----------------
ALTER TABLE crumbs
        ADD COLUMN run_seq integer REFERENCES runs(run_seq)
        ;

UPDATE crumbs c
SET run_seq = r.run_seq
FROM runs r
WHERE r.run_id = c.run_id
        ;
VACUUM ANALYZE runs;

        -- Drop old column and set new column to not nullable
        -- ---------------------------------------------------
ALTER TABLE crumbs
        DROP COLUMN run_id
        ;
ALTER TABLE crumbs
        ALTER COLUMN run_seq SET NOT NULL
        ;

        -- Recreate the supporting index for the FK
        -- adding id to support index-only lookups
        -- (and enforce uniqueness)
        -- -------------------------------------
CREATE UNIQUE INDEX index_crumbs_run_seq_id ON crumbs (run_seq,id)
        ;

        -- Refresh statistics
        -- ------------------
VACUUM ANALYZE crumbs; -- this may take some time ...

-- and then: join the runs table to your original crumbs table
-- -----------------------------------------------------------
-- explain analyze 
SELECT x FROM crumbs c
JOIN runs r ON r.run_seq = c.run_seq
        , lateral json_array_elements(c.content::json) x
WHERE r.run_id='2016-04-26T19_02_01_015Z'
LIMIT 10
        ;

Or: use the other answerers's suggestion with a similar join.

---

But possibly even better: replace the ugly run_id text string by an actual timestamp.