I really don't understand how to improve the performance of my query using index. db.Vendite.aggregate([{$group: { _id: { anno: "$anno", mese: "$mese", cod_age: "$cod_age", cod_int: "$cod_int", cod_cli: "$cod_cli", cod_linea_comm: "$cod_linea_comm", cod_sett_comm: "$cod_sett_comm", _art: "$cod_art"}, vendite_quantita: { $sum: { $add: […
I've been investigating an issue with one of our application queries running very slowly and it seems to be related to a particular view we're using. Here is the full query with the selected columns omitted (there are 408 columns…
A parallel sequential scan is chosen, although an index exists on the column cpv.value. The value column has data type `text. This is the most costly step of the query plan. How do I tune this to reduce the cost/time…
I have the following query: SELECT DISTINCT FIRST_VALUE(business_id) OVER (PARTITION BY b.sub_category_id ORDER BY AVG(stars) desc, COUNT(*) DESC) business_id, sub_category_id FROM purchase_experience pe JOIN businesses b ON b.id = pe.business_id AND b.status = 'active' AND b.sub_category_id IN (1010 ,1007 ,1034…
I have the following MSQL query, that is very slow SELECT a.id, a.date, a.Title, a.Text, a.Text2, a.Text3, b.xxx, b.yyyy, c.aaaa, c.bbbb FROM table_a a JOIN table_b b on a.Id = b.Id JOIN table_c c on a.eeee = c.id ORDER BY…
I have one query that is taking too long(> 5 minutes) and creating deadlocks virt_assist_bandwidth_incoming has 1115501 rows virt_assist_bandwidth_incoming_media has 25752 rows I do not think these are supper big tables. The query: SELECT * FROM virt_assist_bandwidth_incoming i LEFT JOIN…
I have a collection of data like this: { "items": [ { "product": { "name": "prod1", "price": { "pledge": 1, "cost": 19 } } }, { "product": { "name": "prod2", "price": { "pledge": 2, "cost": 10 } } } ]…
We have Postgres DB design that in simplified form looks like this: CREATE TABLE products ( id varchar, version bigint, profile varchar, PRIMARY KEY(id, profile, version) ); CREATE TABLE product_attributes ( productId varchar, key varchar, value varchar, profile varchar, version…
In our DB we have tables, that have 6-8 M records, this data is static and in order of performance optimization we decided to store some data from this tables in separate table, and for predefined filters use the values…
I have a huge dataset on two tables (users, pos_transactions), and I need to execute a join on them. I wrote the query both with join and subquery approches. Both looks Non-optimal: explain SELECT pt.card_number FROM pos_transactions pt where user_id…