I have a PostgreSQL table with 7.9GB of JSON data. My goal is to perform aggregations on the whole table on a daily basis, the aggregation results will later be used for analytical reports in Google Data Studio.
One of the queries I'm trying to run looks as follows:
explain analyze
select tender->>'procurementMethodType' as procurement_method,
tender->>'status' as tender_status,
sum(cast(tender->'value'->>'amount' as decimal)) as total_expected_value
from tenders
group by 1,2
The query plan and execution time are the following:
The problem is that the database has to scan through all the 7.9GB of data, even though the query uses only 3 field values out of approximately 100. So I decided to create the following index:
create index on tenders((tender->>'procurementMethodType'), (tender->>'status'), (cast(tender->'value'->>'amount' as decimal)))
The size of the index is 44MB, which is much smaller than the size of the entire table, so I expect that the query should be much faster. However, when I run the same query with the index created, I get the following result:
The query with index is slower! How can this be possible?
EDIT: the table itself contains two columns: the ID column and the jsonb data column:
create table tenders (
id uuid primary key,
tender jsonb
)

