#	exclusive	inclusive	rows x	rows	loops	node
1.	0.006	1.978	↑ 1.0	30	1	→ Limit (cost=1,432.18..1,432.25 rows=30 width=92) (actual time=1.971..1.978 rows=30 loops=1) Output: product_variant.title, inventory_item.product_variant_id, brand.title, category.title, (min(inventory_item.price)), (max(inventory_item.price)), product.showcase_order, product_variant.id, brand.id, category.id, product.id Buffers: shared hit=907
2.	0.031	1.972	↑ 5.1	30	1	→ Sort (cost=1,432.18..1,432.56 rows=152 width=92) (actual time=1.971..1.972 rows=30 loops=1) Output: product_variant.title, inventory_item.product_variant_id, brand.title, category.title, (min(inventory_item.price)), (max(inventory_item.price)), product.showcase_order, product_variant.id, brand.id, category.id, product.id Sort Key: product.showcase_order Sort Method: quicksort Memory: 33kB Buffers: shared hit=907
3.	0.022	1.941	↑ 2.5	60	1	→ GroupAggregate (cost=1,423.13..1,427.69 rows=152 width=92) (actual time=1.919..1.941 rows=60 loops=1) Output: product_variant.title, inventory_item.product_variant_id, brand.title, category.title, min(inventory_item.price), max(inventory_item.price), product.showcase_order, product_variant.id, brand.id, category.id, product.id Group Key: inventory_item.product_variant_id, product_variant.id, brand.id, category.id, product.id Buffers: shared hit=907
4.	0.033	1.919	↑ 2.5	60	1	→ Sort (cost=1,423.13..1,423.51 rows=152 width=84) (actual time=1.916..1.919 rows=60 loops=1) Output: inventory_item.product_variant_id, product_variant.id, brand.id, category.id, product.id, product_variant.title, brand.title, category.title, inventory_item.price, product.showcase_order Sort Key: inventory_item.product_variant_id, brand.id, category.id, product.id Sort Method: quicksort Memory: 33kB Buffers: shared hit=907
5.	0.032	1.886	↑ 2.5	60	1	→ Hash Join (cost=1,275.30..1,417.62 rows=152 width=84) (actual time=1.174..1.886 rows=60 loops=1) Output: inventory_item.product_variant_id, product_variant.id, brand.id, category.id, product.id, product_variant.title, brand.title, category.title, inventory_item.price, product.showcase_order Inner Unique: true Hash Cond: (product.brand_id = brand.id) Buffers: shared hit=907
6.	0.042	1.841	↓ 1.1	174	1	→ Hash Join (cost=1,273.74..1,415.63 rows=152 width=75) (actual time=1.132..1.841 rows=174 loops=1) Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product.showcase_order, product.id, product.brand_id, category.title, category.id Inner Unique: true Hash Cond: (product_category.category_id = category.id) Buffers: shared hit=906
7.	0.160	1.794	↓ 1.1	174	1	→ Nested Loop (cost=1,272.60..1,413.82 rows=152 width=66) (actual time=1.121..1.794 rows=174 loops=1) Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product.showcase_order, product.id, product.brand_id, product_category.category_id Inner Unique: true Join Filter: (product_variant.product_id = product.id) Buffers: shared hit=905
8.	0.205	1.460	↑ 1.3	174	1	→ Hash Join (cost=1,272.32..1,318.64 rows=219 width=62) (actual time=1.110..1.460 rows=174 loops=1) Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product_variant.product_id, product_category.product_id, product_category.category_id Hash Cond: (product_category.product_id = product_variant.product_id) Buffers: shared hit=383
9.	0.160	0.160	↑ 1.0	2,058	1	→ Seq Scan on public.product_category (cost=0.00..36.18 rows=2,118 width=8) (actual time=0.004..0.160 rows=2,058 loops=1) Output: product_category.created_date, product_category.updated_date, product_category.id, product_category.product_id, product_category.category_id, product_category."order Buffers: shared hit=15
10.	0.041	1.095	↑ 1.3	174	1	→ Hash (cost=1,269.59..1,269.59 rows=219 width=54) (actual time=1.095..1.095 rows=174 loops=1) Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product_variant.product_id Buckets: 1024 Batches: 1 Memory Usage: 23kB Buffers: shared hit=368
11.	0.048	1.054	↑ 1.3	174	1	→ Hash Join (cost=74.26..1,269.59 rows=219 width=54) (actual time=0.547..1.054 rows=174 loops=1) Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product_variant.product_id Inner Unique: true Hash Cond: (inventory_item.product_variant_id = product_variant.id) Buffers: shared hit=368
12.	0.503	0.576	↑ 1.3	174	1	→ Bitmap Heap Scan on public.inventory_item (cost=26.00..1,220.75 rows=219 width=12) (actual time=0.111..0.576 rows=174 loops=1) Output: inventory_item.created_date, inventory_item.updated_date, inventory_item.id, inventory_item.poc_id, inventory_item.product_variant_id, inventory_item.quantity, inventory_item.price, inventory_item.published_date, inventory_item.available_date Recheck Cond: (inventory_item.poc_id = 21) Filter: ((inventory_item.available_date IS NOT NULL) AND (inventory_item.price > '0'::double precision)) Rows Removed by Filter: 527 Heap Blocks: exact=337 Buffers: shared hit=346
13.	0.073	0.073	↓ 1.1	811	1	→ Bitmap Index Scan on poc_product_variant (cost=0.00..25.95 rows=737 width=0) (actual time=0.073..0.073 rows=811 loops=1) Index Cond: (inventory_item.poc_id = 21) Buffers: shared hit=9
14.	0.220	0.430	↓ 1.0	1,176	1	→ Hash (cost=33.67..33.67 rows=1,167 width=42) (actual time=0.430..0.430 rows=1,176 loops=1) Output: product_variant.title, product_variant.id, product_variant.product_id Buckets: 2048 Batches: 1 Memory Usage: 104kB Buffers: shared hit=22
15.	0.210	0.210	↓ 1.0	1,176	1	→ Seq Scan on public.product_variant (cost=0.00..33.67 rows=1,167 width=42) (actual time=0.004..0.210 rows=1,176 loops=1) Output: product_variant.title, product_variant.id, product_variant.product_id Buffers: shared hit=22
16.	0.174	0.174	↑ 1.0	1	174	→ Index Scan using product_pkey on public.product (cost=0.28..0.42 rows=1 width=12) (actual time=0.001..0.001 rows=1 loops=174) Output: product.created_date, product.updated_date, product.id, product.title, product.tags, product.labels, product.abi_product, product.brand_id, product.rgb, product.showcase_order, product.attachment, product.description, product.short_description, product.type, product.has_fixed_price Index Cond: (product.id = product_category.product_id) Buffers: shared hit=522
17.	0.003	0.005	↑ 1.0	6	1	→ Hash (cost=1.06..1.06 rows=6 width=13) (actual time=0.005..0.005 rows=6 loops=1) Output: category.title, category.id Buckets: 1024 Batches: 1 Memory Usage: 9kB Buffers: shared hit=1
18.	0.002	0.002	↑ 1.0	6	1	→ Seq Scan on public.category (cost=0.00..1.06 rows=6 width=13) (actual time=0.001..0.002 rows=6 loops=1) Output: category.title, category.id Buffers: shared hit=1
19.	0.007	0.013	↑ 1.0	25	1	→ Hash (cost=1.25..1.25 rows=25 width=13) (actual time=0.013..0.013 rows=25 loops=1) Output: brand.title, brand.id Buckets: 1024 Batches: 1 Memory Usage: 10kB Buffers: shared hit=1
20.	0.006	0.006	↑ 1.0	25	1	→ Seq Scan on public.brand (cost=0.00..1.25 rows=25 width=13) (actual time=0.004..0.006 rows=25 loops=1) Output: brand.title, brand.id Buffers: shared hit=1

Planning time	:	2.150 ms
Execution time	:	2.101 ms

Limit  (cost=1432.18..1432.25 rows=30 width=92) (actual time=1.971..1.978 rows=30 loops=1)
  Output: product_variant.title, inventory_item.product_variant_id, brand.title, category.title, (min(inventory_item.price)), (max(inventory_item.price)), product.showcase_order, product_variant.id, brand.id, category.id, product.id
  Buffers: shared hit=907
  ->  Sort  (cost=1432.18..1432.56 rows=152 width=92) (actual time=1.971..1.972 rows=30 loops=1)
        Output: product_variant.title, inventory_item.product_variant_id, brand.title, category.title, (min(inventory_item.price)), (max(inventory_item.price)), product.showcase_order, product_variant.id, brand.id, category.id, product.id
        Sort Key: product.showcase_order
        Sort Method: quicksort  Memory: 33kB
        Buffers: shared hit=907
        ->  GroupAggregate  (cost=1423.13..1427.69 rows=152 width=92) (actual time=1.919..1.941 rows=60 loops=1)
              Output: product_variant.title, inventory_item.product_variant_id, brand.title, category.title, min(inventory_item.price), max(inventory_item.price), product.showcase_order, product_variant.id, brand.id, category.id, product.id
              Group Key: inventory_item.product_variant_id, product_variant.id, brand.id, category.id, product.id
              Buffers: shared hit=907
              ->  Sort  (cost=1423.13..1423.51 rows=152 width=84) (actual time=1.916..1.919 rows=60 loops=1)
                    Output: inventory_item.product_variant_id, product_variant.id, brand.id, category.id, product.id, product_variant.title, brand.title, category.title, inventory_item.price, product.showcase_order
                    Sort Key: inventory_item.product_variant_id, brand.id, category.id, product.id
                    Sort Method: quicksort  Memory: 33kB
                    Buffers: shared hit=907
                    ->  Hash Join  (cost=1275.30..1417.62 rows=152 width=84) (actual time=1.174..1.886 rows=60 loops=1)
                          Output: inventory_item.product_variant_id, product_variant.id, brand.id, category.id, product.id, product_variant.title, brand.title, category.title, inventory_item.price, product.showcase_order
                          Inner Unique: true
                          Hash Cond: (product.brand_id = brand.id)
                          Buffers: shared hit=907
                          ->  Hash Join  (cost=1273.74..1415.63 rows=152 width=75) (actual time=1.132..1.841 rows=174 loops=1)
                                Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product.showcase_order, product.id, product.brand_id, category.title, category.id
                                Inner Unique: true
                                Hash Cond: (product_category.category_id = category.id)
                                Buffers: shared hit=906
                                ->  Nested Loop  (cost=1272.60..1413.82 rows=152 width=66) (actual time=1.121..1.794 rows=174 loops=1)
                                      Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product.showcase_order, product.id, product.brand_id, product_category.category_id
                                      Inner Unique: true
                                      Join Filter: (product_variant.product_id = product.id)
                                      Buffers: shared hit=905
                                      ->  Hash Join  (cost=1272.32..1318.64 rows=219 width=62) (actual time=1.110..1.460 rows=174 loops=1)
                                            Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product_variant.product_id, product_category.product_id, product_category.category_id
                                            Hash Cond: (product_category.product_id = product_variant.product_id)
                                            Buffers: shared hit=383
                                            ->  Seq Scan on public.product_category  (cost=0.00..36.18 rows=2118 width=8) (actual time=0.004..0.160 rows=2058 loops=1)
                                                  Output: product_category.created_date, product_category.updated_date, product_category.id, product_category.product_id, product_category.category_id, product_category."order"
                                                  Buffers: shared hit=15
                                            ->  Hash  (cost=1269.59..1269.59 rows=219 width=54) (actual time=1.095..1.095 rows=174 loops=1)
                                                  Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product_variant.product_id
                                                  Buckets: 1024  Batches: 1  Memory Usage: 23kB
                                                  Buffers: shared hit=368
                                                  ->  Hash Join  (cost=74.26..1269.59 rows=219 width=54) (actual time=0.547..1.054 rows=174 loops=1)
                                                        Output: inventory_item.product_variant_id, inventory_item.price, product_variant.title, product_variant.id, product_variant.product_id
                                                        Inner Unique: true
                                                        Hash Cond: (inventory_item.product_variant_id = product_variant.id)
                                                        Buffers: shared hit=368
                                                        ->  Bitmap Heap Scan on public.inventory_item  (cost=26.00..1220.75 rows=219 width=12) (actual time=0.111..0.576 rows=174 loops=1)
                                                              Output: inventory_item.created_date, inventory_item.updated_date, inventory_item.id, inventory_item.poc_id, inventory_item.product_variant_id, inventory_item.quantity, inventory_item.price, inventory_item.published_date, inventory_item.available_date
                                                              Recheck Cond: (inventory_item.poc_id = 21)
                                                              Filter: ((inventory_item.available_date IS NOT NULL) AND (inventory_item.price > '0'::double precision))
                                                              Rows Removed by Filter: 527
                                                              Heap Blocks: exact=337
                                                              Buffers: shared hit=346
                                                              ->  Bitmap Index Scan on poc_product_variant  (cost=0.00..25.95 rows=737 width=0) (actual time=0.073..0.073 rows=811 loops=1)
                                                                    Index Cond: (inventory_item.poc_id = 21)
                                                                    Buffers: shared hit=9
                                                        ->  Hash  (cost=33.67..33.67 rows=1167 width=42) (actual time=0.430..0.430 rows=1176 loops=1)
                                                              Output: product_variant.title, product_variant.id, product_variant.product_id
                                                              Buckets: 2048  Batches: 1  Memory Usage: 104kB
                                                              Buffers: shared hit=22
                                                              ->  Seq Scan on public.product_variant  (cost=0.00..33.67 rows=1167 width=42) (actual time=0.004..0.210 rows=1176 loops=1)
                                                                    Output: product_variant.title, product_variant.id, product_variant.product_id
                                                                    Buffers: shared hit=22
                                      ->  Index Scan using product_pkey on public.product  (cost=0.28..0.42 rows=1 width=12) (actual time=0.001..0.001 rows=1 loops=174)
                                            Output: product.created_date, product.updated_date, product.id, product.title, product.tags, product.labels, product.abi_product, product.brand_id, product.rgb, product.showcase_order, product.attachment, product.description, product.short_description, product.type, product.has_fixed_price
                                            Index Cond: (product.id = product_category.product_id)
                                            Buffers: shared hit=522
                                ->  Hash  (cost=1.06..1.06 rows=6 width=13) (actual time=0.005..0.005 rows=6 loops=1)
                                      Output: category.title, category.id
                                      Buckets: 1024  Batches: 1  Memory Usage: 9kB
                                      Buffers: shared hit=1
                                      ->  Seq Scan on public.category  (cost=0.00..1.06 rows=6 width=13) (actual time=0.001..0.002 rows=6 loops=1)
                                            Output: category.title, category.id
                                            Buffers: shared hit=1
                          ->  Hash  (cost=1.25..1.25 rows=25 width=13) (actual time=0.013..0.013 rows=25 loops=1)
                                Output: brand.title, brand.id
                                Buckets: 1024  Batches: 1  Memory Usage: 10kB
                                Buffers: shared hit=1
                                ->  Seq Scan on public.brand  (cost=0.00..1.25 rows=25 width=13) (actual time=0.004..0.006 rows=25 loops=1)
                                      Output: brand.title, brand.id
                                      Buffers: shared hit=1
Planning time: 2.150 ms
Execution time: 2.101 ms

Per node type stats

node type	count	sum of times	% of query
Bitmap Heap Scan	1	0.503 ms	25.4 %
Bitmap Index Scan	1	0.073 ms	3.7 %
GroupAggregate	1	0.022 ms	1.1 %
Hash	4	0.271 ms	13.7 %
Hash Join	4	0.327 ms	16.5 %
Index Scan	1	0.174 ms	8.8 %
Limit	1	0.006 ms	0.3 %
Nested Loop	1	0.160 ms	8.1 %
Seq Scan	4	0.378 ms	19.1 %
Sort	2	0.064 ms	3.2 %

Per table stats

Table name	Scan count	Total time	% of query
scan type	count	sum of times	% of table
public.brand	1	0.006 ms	0.3 %
Seq Scan	1	0.006 ms	100.0 %
public.category	1	0.002 ms	0.1 %
Seq Scan	1	0.002 ms	100.0 %
public.inventory_item	1	0.503 ms	25.4 %
Bitmap Heap Scan	1	0.503 ms	100.0 %
public.product	1	0.174 ms	8.8 %
Index Scan	1	0.174 ms	100.0 %
public.product_category	1	0.160 ms	8.1 %
Seq Scan	1	0.160 ms	100.0 %
public.product_variant	1	0.210 ms	10.6 %
Seq Scan	1	0.210 ms	100.0 %

explain.depesz.com

PostgreSQL's explain analyze made readable

Result: HncS

Color mode:

Visible columns:

Per node type stats

Per table stats