This document summarizes a lightning talk about using JSONB in PostgreSQL. It discusses how JSONB stores data in a decomposed binary format for faster processing compared to JSON, supports indexing for faster lookups, and strips extra whitespace. Examples show JSONB performing 5x faster than JSON for a text search and 2-3x faster for converting to GeoJSON. JSONB works well for selective queries on indexed fields and computations involving large JSON documents.

1. You, Me, and JSONB
(a lightning talk)
3.15.17

2. You
• Are you doing a lot of JSON manipulation inside PostgreSQL?
• Do you need indexed lookups for arbitrary key searches?
• …if “yes”, have you looked at JSONB?
• http://stackoverflow.com/questions/22654170/explanation-of-jsonb-
introduced-by-postgresql

3. Me
• Work for Tableau
• Have a lot of crufty old code laying around…particularly conversion
formulas for JSON to GeoJSON
• Discovered JSONB while trying to optimize a very selective SELECT
from a table I had created using auditing triggers…

4. JSONB

5. JSONB vs JSON
JSON
• Stores data in text format
• Input is as fast, as no conversions are required
• Processing functions must re-parse the data on each execution
• Indexing is not supported
• All white space and line feeds in the input are preserved as-is
• Duplicate keys are retained, processing functions only consider the last value
• Order of the keys is preserved
JSONB
• Stores data in decomposed binary format
• Input is slightly slower, as there is conversion overhead involved
• Re-parsing is not needed, making data processing significantly faster
• Indexing is supported
• Extra white space and line feeds are stripped
• Duplicate keys are purged at input, only the last value is stored
• Order is not preserved

6. INSERT w/ JSON
• Query returned successfully:
• 111396 rows affected,
• 10.6 secs execution time.
INSERT w/ JSONB
• Query returned successfully:
• 111396 rows affected,
• 17.4 secs execution time.
https://datahub.io/dataset/william-shakespeare-plays/resource/f357200a-d71c-44f4-8271-
b00348a6f9c4
INSERT INTO … (SELECT * SHAKESPEARE)

7. ..But wait!!! There is INDEXING!
CREATE TABLE public.will_play_text_raw_idx (
row_id SERIAL PRIMARY KEY,
data jsonb);
CREATE INDEX idxgin ON will_play_text_raw_idx USING gin (data);
Query returned successfully: 111396 rows affected,
19.2 secs execution time.

8. Find out what type of json objects there are…
SELECT json(b)_object_keys(data) FROM
public.will_play_text_raw
GROUP BY json(b)_object_keys(data);
JSON
• 1 secs execution time.
JSONB
• 6.1 secs execution time.
JSONB + INDEX (*just slightly faster then JSONB)
• 6.1 secs execution time.

9. Running with EXPLAIN ANALYZE VERBOSE…
JSON (1 sec)
"HashAggregate (cost=87267.47..87368.97 rows=20000 width=173)
(actual time=1051.083..1051.087 rows=6 loops=1)"
" Output: (json_object_keys(data))"
" Group Key: json_object_keys(will_play_text_raw.data)"
" -> Seq Scan on public.will_play_text_raw (cost=0.00..59418.47 rows=11139600 width=173)
(actual time=0.045..808.669 rows=668376 loops=1)"
" Output: json_object_keys(data)"
"Planning time: 0.175 ms"
"Execution time: 1051.170 ms"

10. Running with EXPLAIN ANALYZE VERBOSE…
JSONB (6.1 sec)
"Group (cost=4676148.26..4787265.77 rows=11139600 width=202)
(actual time=5242.724..6106.799 rows=6 loops=1)"
" Output: (jsonb_object_keys(data))"
" Group Key: (jsonb_object_keys(will_play_text_raw.data))"
" -> Sort (cost=4676148.26..4703997.26 rows=11139600 width=202)
(actual time=5242.719..6004.605 rows=668376 loops=1)"
" Output: (jsonb_object_keys(data))"
" Sort Key: (jsonb_object_keys(will_play_text_raw.data))"
" Sort Method: external merge Disk: 13352kB"
" -> Seq Scan on public.will_play_text_raw (cost=0.00..59794.47 rows=11139600 width=202)
(actual time=0.038..431.132 rows=668376 loops=1)"
" Output: jsonb_object_keys(data)"
"Planning time: 0.180 ms"
"Execution time: 6120.343 ms"
Doing a sort + sequential scan.
Notice that the cost of the sort on
the first row is very similar to the
all row costs. Usually when you a
step with very similar first row
and all row costs, that operation
requires all the data from all the
preceding steps.

11. Running with EXPLAIN ANALYZE VERBOSE…
JSONB + IDX (6.1 secs…slightly faster then just JSONB)
"Group (cost=4676148.26..4787265.77 rows=11139600 width=202)
(actual time=5231.472..6090.149 rows=6 loops=1)"
" Output: (jsonb_object_keys(data))"
" Group Key: (jsonb_object_keys(will_play_text_raw_idx.data))"
" -> Sort (cost=4676148.26..4703997.26 rows=11139600 width=202)
(actual time=5231.466..5987.161 rows=668376 loops=1)"
" Output: (jsonb_object_keys(data))"
" Sort Key: (jsonb_object_keys(will_play_text_raw_idx.data))"
" Sort Method: external merge Disk: 13352kB"
" -> Seq Scan on public.will_play_text_raw_idx (cost=0.00..59794.47 rows=11139600 width=202)
(actual time=0.034..424.509 rows=668376 loops=1)"
" Output: jsonb_object_keys(data)"
"Planning time: 0.182 ms"
"Execution time: 6103.038 ms"

12. When To Avoid JSONB in a PostgreSQL
Schema
https://blog.heapanalytics.com/when-to-avoid-jsonb-in-a-postgresql-schema/
- Slow queries due to a lack of table statistics (in other words, reconsider if you are
doing a lot of aggregate and grouping functions)
- Larger table footprint
(note: read this if you want to think more about “working around JSONB’s lack of
stats”)
https://www.postgresql.org/message-id/54C738E1.8080405@agliodbs.com

13. So…when does using JSONB **WORK?!**

14. Where doeth Shakespeare use the phrase
‘thou art’?
JSON
• 594 msecs execution time.
JSONB
• 133 msecs execution time.
JSONB + INDEX
• 125 msecs execution time.

15. ALMOST
5x’s
faster!!!

16. Where and Who said “To be, or not to be”
SELECT * FROM public.will_play_text_raw
Where data @> '{"text_entry" : "To be, or not to be: that is the
question:"}';
JSONB
• 78 msecs execution time.
JSONB + INDEX
• 31 msecs execution time.
https://www.postgresql.org/docs/9.4/static/functions-json.html#FUNCTIONS-JSONB-OP-TABLE
Note: ‘@>’ operator only
available with JSONB

18. Creating GeoJSON using JSON operations on a
regular PostGIS enabled spatial table
JSON (16 msecs)
SELECT row_to_json(fc)
FROM ( SELECT 'FeatureCollection' As type, array_to_json(array_agg(f)) As features
FROM (SELECT 'Feature' As type
, ST_AsGeoJSON(lg.geom, 4)::json As geometry
, row_to_json((SELECT l FROM (SELECT gid) As l
)) As properties
FROM public.smallworld As lg ) As f ) As fc;

19. Creating GeoJSON using JSONB operations on
a regular PostGIS enabled spatial table
JSONB (31 msecs)
SELECT to_jsonb(fc)
FROM ( SELECT 'FeatureCollection' As type, array_to_json(array_agg(f)) As features
FROM (SELECT 'Feature' As type
, ST_AsGeoJSON(lg.geom, 4)::jsonb As geometry
, to_jsonb((SELECT l FROM (SELECT gid) As l
)) As properties
FROM public.smallworld As lg ) As f ) As fc;
http://geojsonlint.com/
Is it valid GeoJSON?
Check here….

20. Weather Data – JSON to GeoJSON
http://openweathermap.org/api