explain.depesz.com

PostgreSQL's explain analyze made readable

Result: wQqB

Settings
# exclusive inclusive rows x rows loops node
1. 0.003 77.137 ↓ 2.0 2 1

Unique (cost=19,624.06..19,624.07 rows=1 width=9) (actual time=77.134..77.137 rows=2 loops=1)

  • Output: productto.article_number, (((NOT ((productfrom.width)::text IS DISTINCT FROM (productto.width)::text)) AND (NOT ((productfrom.depth)::text IS DISTINCT FROM (productto.depth)::text)) AND (NOT ((productfrom.length)::text IS DISTINCT FROM (productto.length)::text)) AND (NOT ((productfrom.height)::text IS DISTINCT FROM (productto.height)::text)) AND (NOT ((productfrom.diameter)::text IS DISTINCT FROM (productto.diameter)::text)))), (((productto.custom_program IS NULL) = (productfrom.custom_program IS NULL)))
  • Buffers: shared hit=155,331
2. 0.015 77.134 ↓ 8.0 8 1

Sort (cost=19,624.06..19,624.06 rows=1 width=9) (actual time=77.134..77.134 rows=8 loops=1)

  • Output: productto.article_number, (((NOT ((productfrom.width)::text IS DISTINCT FROM (productto.width)::text)) AND (NOT ((productfrom.depth)::text IS DISTINCT FROM (productto.depth)::text)) AND (NOT ((productfrom.length)::text IS DISTINCT FROM (productto.length)::text)) AND (NOT ((productfrom.height)::text IS DISTINCT FROM (productto.height)::text)) AND (NOT ((productfrom.diameter)::text IS DISTINCT FROM (productto.diameter)::text)))), (((productto.custom_program IS NULL) = (productfrom.custom_program IS NULL)))
  • Sort Key: (((NOT ((productfrom.width)::text IS DISTINCT FROM (productto.width)::text)) AND (NOT ((productfrom.depth)::text IS DISTINCT FROM (productto.depth)::text)) AND (NOT ((productfrom.length)::text IS DISTINCT FROM (productto.length)::text)) AND (NOT ((productfrom.height)::text IS DISTINCT FROM (productto.height)::text)) AND (NOT ((productfrom.diameter)::text IS DISTINCT FROM (productto.diameter)::text)))) DESC, (((productto.custom_program IS NULL) = (productfrom.custom_program IS NULL))) DESC, productto.article_number
  • Sort Method: quicksort Memory: 25kB
  • Buffers: shared hit=155,331
3. 0.010 77.119 ↓ 8.0 8 1

Nested Loop Left Join (cost=1,006.32..19,624.05 rows=1 width=9) (actual time=35.305..77.119 rows=8 loops=1)

  • Output: productto.article_number, ((NOT ((productfrom.width)::text IS DISTINCT FROM (productto.width)::text)) AND (NOT ((productfrom.depth)::text IS DISTINCT FROM (productto.depth)::text)) AND (NOT ((productfrom.length)::text IS DISTINCT FROM (productto.length)::text)) AND (NOT ((productfrom.height)::text IS DISTINCT FROM (productto.height)::text)) AND (NOT ((productfrom.diameter)::text IS DISTINCT FROM (productto.diameter)::text))), ((productto.custom_program IS NULL) = (productfrom.custom_program IS NULL))
  • Inner Unique: true
  • Filter: ((fromisleather.name)::text IS DISTINCT FROM (toisleather.name)::text)
  • Rows Removed by Filter: 12
  • Buffers: shared hit=155,331
4. 0.016 77.049 ↓ 20.0 20 1

Nested Loop Left Join (cost=1,005.89..19,615.57 rows=1 width=83) (actual time=35.296..77.049 rows=20 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, toisleather.name
  • Inner Unique: true
  • Buffers: shared hit=155,271
5. 0.008 76.973 ↓ 20.0 20 1

Nested Loop (cost=1,005.46..19,612.22 rows=1 width=87) (actual time=35.283..76.973 rows=20 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id
  • Inner Unique: true
  • Join Filter: ((rls.valid_from >= c.valid_from) AND (rls.valid_from <= c.valid_to))
  • Buffers: shared hit=155,203
6. 0.010 76.925 ↓ 20.0 20 1

Nested Loop (cost=1,005.19..19,610.06 rows=1 width=111) (actual time=35.276..76.925 rows=20 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, rls.valid_from, cs.release_id, cs.category_id
  • Buffers: shared hit=155,143
7. 0.024 76.790 ↓ 25.0 25 1

Nested Loop (cost=1,004.90..19,600.79 rows=1 width=119) (actual time=35.266..76.790 rows=25 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, rls.valid_from, ss.subcategory_id, s.id, s.release_id
  • Inner Unique: true
  • Join Filter: ((rls.valid_from >= s.valid_from) AND (rls.valid_from <= s.valid_to))
  • Buffers: shared hit=154,943
8. 0.003 76.716 ↓ 6.2 25 1

Nested Loop (cost=1,004.61..19,588.71 rows=4 width=111) (actual time=35.258..76.716 rows=25 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, rls.valid_from, ss.release_id, ss.subcategory_id
  • Inner Unique: true
  • Buffers: shared hit=154,868
9. 0.023 76.638 ↓ 6.2 25 1

Nested Loop (cost=1,004.32..19,578.74 rows=4 width=111) (actual time=35.249..76.638 rows=25 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, rls.valid_from, sspg.release_id, sspg.subcategory_set_id
  • Buffers: shared hit=154,793
10. 0.111 76.445 ↓ 5.0 5 1

Nested Loop Left Join (cost=1,002.52..19,537.84 rows=1 width=119) (actual time=35.210..76.445 rows=5 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, pgp.product_group_id, pg.id, pg.release_id, rls.valid_from
  • Inner Unique: true
  • Filter: (NOT ((subsetto.characteristic_value_key)::text IS DISTINCT FROM (subsetfrom.characteristic_value_key)::text))
  • Rows Removed by Filter: 256
  • Buffers: shared hit=154,625
11. 0.000 75.029 ↓ 6.7 261 1

Nested Loop (cost=1,001.96..19,255.66 rows=39 width=123) (actual time=5.969..75.029 rows=261 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, subsetfrom.characteristic_value_key, pgp.product_group_id, pg.id, pg.release_id, rls.valid_from
  • Join Filter: ((productto.product_id <> productfrom.product_id) AND (NOT ((productto.collection)::text IS DISTINCT FROM (productfrom.collection)::text)))
  • Rows Removed by Join Filter: 24,412
  • Buffers: shared hit=153,320
12. 0.004 0.038 ↑ 1.0 1 1

Nested Loop Left Join (cost=0.98..17.03 rows=1 width=48) (actual time=0.036..0.038 rows=1 loops=1)

  • Output: productfrom.width, productfrom.depth, productfrom.length, productfrom.height, productfrom.diameter, productfrom.custom_program, productfrom.product_id, productfrom.release_id, productfrom.collection, subsetfrom.characteristic_value_key
  • Inner Unique: true
  • Buffers: shared hit=9
13. 0.022 0.022 ↑ 1.0 1 1

Index Scan using web_product_article_num_uk on public.web_product productfrom (cost=0.42..8.44 rows=1 width=44) (actual time=0.021..0.022 rows=1 loops=1)

  • Output: productfrom.product_id, productfrom.release_id, productfrom.article_number, productfrom.material_id, productfrom.image_type, productfrom.configurable_flag, productfrom.max_quantity, productfrom.sap_type, productfrom.merch_category_code, productfrom.collection_name, productfrom.leg_finish, productfrom.foot_finish, productfrom.base_finish, productfrom.steel_thickness, productfrom.upholstered_frame_finish, productfrom.rationale, productfrom.top_quantity, productfrom.material_description, productfrom.fabric_style, productfrom.fabric_type, productfrom.sap_category, productfrom.bedding_type, productfrom.bedding_type_display_text, productfrom.shipping_method, productfrom.delivery_time_frame, productfrom.delivery_time, productfrom.width, productfrom.height, productfrom.depth, productfrom.length, productfrom.diameter, productfrom.top_shape, productfrom.footboard_height, productfrom.extension_width, productfrom.vendor_name, productfrom.primary_material, productfrom.primary_material_value, productfrom.secondary_material, productfrom.secondary_material_value, productfrom.material_type, productfrom.primary_color, productfrom.primary_color_value, productfrom.secondary_color, productfrom.secondary_color_value, productfrom.subset_name, productfrom.subset_display_text, productfrom.collection, productfrom.custom_program, productfrom.discount_price, productfrom.promotional_valid_thru, productfrom.price_range_flag, productfrom.max_custom_upcharge, productfrom.default_sales_text, productfrom.default_short_sales_text, productfrom.sap_sales_text, productfrom.pdf_metadata_json, productfrom.sap_sales_text_flag, productfrom.style, productfrom.date_created, productfrom.hash, productfrom.showable_flag, productfrom.full_price, productfrom.product_detail_json
  • Index Cond: (((productfrom.article_number)::text = '10009994'::text) AND (productfrom.release_id = 389))
  • Buffers: shared hit=4
14. 0.012 0.012 ↑ 1.0 1 1

Index Scan using web_product_attribute_pk on public.web_product_attribute subsetfrom (cost=0.56..8.58 rows=1 width=20) (actual time=0.011..0.012 rows=1 loops=1)

  • Output: subsetfrom.product_id, subsetfrom.release_id, subsetfrom.characteristic_key, subsetfrom.characteristic_name, subsetfrom.characteristic_desc, subsetfrom.characteristic_value_key, subsetfrom.characteristic_value_name, subsetfrom.characteristic_value_desc, subsetfrom.characteristic_value_stocked, subsetfrom.characteristic_value_sort, subsetfrom.date_created, subsetfrom.characteristic_label, subsetfrom.valid_from
  • Index Cond: ((productfrom.product_id = subsetfrom.product_id) AND (productfrom.release_id = subsetfrom.release_id) AND (subsetfrom.release_id = 389) AND ((subsetfrom.characteristic_key)::text = 'EPM_SUBSET'::text))
  • Buffers: shared hit=5
15. 17.675 81.459 ↓ 7.0 24,673 1

Gather (cost=1,000.98..19,186.10 rows=3,502 width=83) (actual time=1.282..81.459 rows=24,673 loops=1)

  • Output: productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, productto.collection, pgp.product_group_id, pg.id, pg.release_id, rls.valid_from
  • Workers Planned: 2
  • Workers Launched: 2
  • Buffers: shared hit=153,311
16. 7.667 63.784 ↓ 5.6 8,224 3 / 3

Nested Loop (cost=0.98..17,835.90 rows=1,459 width=83) (actual time=0.147..63.784 rows=8,224 loops=3)

  • Output: productto.article_number, productto.width, productto.depth, productto.length, productto.height, productto.diameter, productto.custom_program, productto.product_id, productto.release_id, productto.collection, pgp.product_group_id, pg.id, pg.release_id, rls.valid_from
  • Inner Unique: true
  • Buffers: shared hit=153,311
  • Worker 0: actual time=0.249..64.592 rows=7,219 loops=1
  • Buffers: shared hit=43,989
  • Worker 1: actual time=0.128..63.560 rows=7,502 loops=1
  • Buffers: shared hit=46,893
17. 1.263 31.381 ↓ 5.5 8,245 3 / 3

Nested Loop (cost=0.55..11,601.56 rows=1,503 width=48) (actual time=0.106..31.381 rows=8,245 loops=3)

  • Output: pgp.product_id, pgp.release_id, pgp.product_group_id, pg.id, pg.release_id, rls.valid_from
  • Buffers: shared hit=54,333
  • Worker 0: actual time=0.179..30.624 rows=7,257 loops=1
  • Buffers: shared hit=14,970
  • Worker 1: actual time=0.083..32.167 rows=7,512 loops=1
  • Buffers: shared hit=16,829
18. 0.671 9.960 ↓ 2.7 806 3 / 3

Nested Loop (cost=0.13..4,817.43 rows=299 width=24) (actual time=0.061..9.960 rows=806 loops=3)

  • Output: pg.id, pg.release_id, rls.valid_from
  • Inner Unique: true
  • Buffers: shared hit=12,965
  • Worker 0: actual time=0.116..8.663 rows=647 loops=1
  • Buffers: shared hit=3,033
  • Worker 1: actual time=0.033..10.099 rows=759 loops=1
  • Buffers: shared hit=3,976
19. 7.156 7.156 ↑ 1.3 2,133 3 / 3

Parallel Seq Scan on public.product_group pg (cost=0.00..4,391.87 rows=2,694 width=32) (actual time=0.016..7.156 rows=2,133 loops=3)

  • Output: pg.id, pg.release_id, pg.product_group_key, pg.name, pg.long_name, pg.editorial_description, pg.static_url, pg.s7_image_type, pg.meta_description, pg.pattern_guide_image_name, pg.sec_designer_title, pg.sec_designer_copy, pg.sec_designer_image_filename, pg.sec_connector_line_length, pg.show_style_selector, pg.show_review_selector, pg.type, pg.summary_sales_text_override, pg.friendly_url, pg.modified_flag, pg.relationship_modified_flag, pg.deleted_flag, pg.valid_from, pg.valid_to, pg.updated_by, pg.date_updated, pg.date_created, pg.medium_name, pg.page_title, pg.main_image_override_filename, pg.main_image_caption, pg.static_main_image, pg.product_page_template, pg.show_comfort_spectrum, pg.hide_customer_images_flag, pg.default_category_id, pg.default_subcategory_id, pg.size_guideline_key, pg.customer_image_pg_key_override, pg.show_price_guarantee_flag, pg.custom_options_text, pg.custom_cabinet_options_text, pg.selector_question_group_to_aggregate, pg.subcategory_image_override_filename, pg.hide_collection_search_segment
  • Filter: ((pg.release_id = 389) AND (pg.deleted_flag = 0))
  • Rows Removed by Filter: 11,407
  • Buffers: shared hit=4,138
  • Worker 0: actual time=0.027..6.083 rows=1,627 loops=1
  • Buffers: shared hit=754
  • Worker 1: actual time=0.008..7.695 rows=1,866 loops=1
  • Buffers: shared hit=1,349
20. 2.133 2.133 ↓ 0.0 0 6,399 / 3

Index Scan using release_valid_from_uk on public.release rls (cost=0.13..0.16 rows=1 width=16) (actual time=0.001..0.001 rows=0 loops=6,399)

  • Output: rls.id, rls.name, rls.type, rls.description, rls.refresh_date, rls.launch_date, rls.valid_from, rls.updated_by, rls.date_updated, rls.date_created
  • Index Cond: ((rls.valid_from >= pg.valid_from) AND (rls.valid_from <= pg.valid_to))
  • Filter: (rls.id = 389)
  • Rows Removed by Filter: 0
  • Buffers: shared hit=8,827
  • Worker 0: actual time=0.001..0.001 rows=0 loops=1,627
  • Buffers: shared hit=2,279
  • Worker 1: actual time=0.001..0.001 rows=0 loops=1,866
  • Buffers: shared hit=2,627
21. 20.158 20.158 ↓ 1.4 10 2,419 / 3

Index Scan using product_group_product_pk on public.product_group_product pgp (cost=0.42..22.62 rows=7 width=24) (actual time=0.012..0.025 rows=10 loops=2,419)

  • Output: pgp.product_group_id, pgp.product_id, pgp.release_id, pgp.default_flag, pgp.default_navigation_flag, pgp.product_config_id, pgp.default_sectional_drapeable, pgp.family_flag, pgp.hidden_flag, pgp.modified_flag, pgp.deleted_flag, pgp.updated_by, pgp.date_updated, pgp.date_created, pgp.selector_image_filename_override, pgp.sort
  • Index Cond: ((pgp.product_group_id = pg.id) AND (pgp.release_id = 389))
  • Filter: (pgp.deleted_flag = 0)
  • Rows Removed by Filter: 10
  • Buffers: shared hit=41,368
  • Worker 0: actual time=0.015..0.031 rows=11 loops=647
  • Buffers: shared hit=11,937
  • Worker 1: actual time=0.013..0.027 rows=10 loops=759
  • Buffers: shared hit=12,853
22. 24.736 24.736 ↑ 1.0 1 24,736 / 3

Index Scan using web_product_pk on public.web_product productto (cost=0.42..4.15 rows=1 width=51) (actual time=0.003..0.003 rows=1 loops=24,736)

  • Output: productto.product_id, productto.release_id, productto.article_number, productto.material_id, productto.image_type, productto.configurable_flag, productto.max_quantity, productto.sap_type, productto.merch_category_code, productto.collection_name, productto.leg_finish, productto.foot_finish, productto.base_finish, productto.steel_thickness, productto.upholstered_frame_finish, productto.rationale, productto.top_quantity, productto.material_description, productto.fabric_style, productto.fabric_type, productto.sap_category, productto.bedding_type, productto.bedding_type_display_text, productto.shipping_method, productto.delivery_time_frame, productto.delivery_time, productto.width, productto.height, productto.depth, productto.length, productto.diameter, productto.top_shape, productto.footboard_height, productto.extension_width, productto.vendor_name, productto.primary_material, productto.primary_material_value, productto.secondary_material, productto.secondary_material_value, productto.material_type, productto.primary_color, productto.primary_color_value, productto.secondary_color, productto.secondary_color_value, productto.subset_name, productto.subset_display_text, productto.collection, productto.custom_program, productto.discount_price, productto.promotional_valid_thru, productto.price_range_flag, productto.max_custom_upcharge, productto.default_sales_text, productto.default_short_sales_text, productto.sap_sales_text, productto.pdf_metadata_json, productto.sap_sales_text_flag, productto.style, productto.date_created, productto.hash, productto.showable_flag, productto.full_price, productto.product_detail_json
  • Index Cond: ((productto.product_id = pgp.product_id) AND (productto.release_id = 389))
  • Buffers: shared hit=98,978
  • Worker 0: actual time=0.004..0.004 rows=1 loops=7,257
  • Buffers: shared hit=29,019
  • Worker 1: actual time=0.003..0.003 rows=1 loops=7,512
  • Buffers: shared hit=30,064
23. 1.305 1.305 ↑ 1.0 1 261

Index Scan using web_product_attribute_pk on public.web_product_attribute subsetto (cost=0.56..7.22 rows=1 width=20) (actual time=0.005..0.005 rows=1 loops=261)

  • Output: subsetto.product_id, subsetto.release_id, subsetto.characteristic_key, subsetto.characteristic_name, subsetto.characteristic_desc, subsetto.characteristic_value_key, subsetto.characteristic_value_name, subsetto.characteristic_value_desc, subsetto.characteristic_value_stocked, subsetto.characteristic_value_sort, subsetto.date_created, subsetto.characteristic_label, subsetto.valid_from
  • Index Cond: ((productto.product_id = subsetto.product_id) AND (productto.release_id = subsetto.release_id) AND (subsetto.release_id = 389) AND ((subsetto.characteristic_key)::text = 'EPM_SUBSET'::text))
  • Buffers: shared hit=1,305
24. 0.140 0.170 ↓ 1.2 5 5

Bitmap Heap Scan on public.subcategory_set_product_group sspg (cost=1.80..40.86 rows=4 width=24) (actual time=0.020..0.034 rows=5 loops=5)

  • Output: sspg.id, sspg.release_id, sspg.sort, sspg.subcategory_set_id, sspg.product_group_id, sspg.article_number, sspg.default_navigation_flag, sspg.modified_flag, sspg.deleted_flag, sspg.date_created, sspg.date_updated, sspg.updated_by, sspg.subcategory_image_override, sspg.product_config_id
  • Recheck Cond: (sspg.product_group_id = pgp.product_group_id)
  • Filter: ((sspg.release_id = 389) AND (sspg.deleted_flag = 0))
  • Rows Removed by Filter: 27
  • Heap Blocks: exact=153
  • Buffers: shared hit=168
25. 0.030 0.030 ↑ 1.1 32 5

Bitmap Index Scan on subcategory_set_product_group_product_group_id_idx (cost=0.00..1.80 rows=36 width=0) (actual time=0.006..0.006 rows=32 loops=5)

  • Index Cond: (sspg.product_group_id = pgp.product_group_id)
  • Buffers: shared hit=15
26. 0.075 0.075 ↑ 1.0 1 25

Index Scan using subcategory_set_pk on public.subcategory_set ss (cost=0.29..2.49 rows=1 width=24) (actual time=0.002..0.003 rows=1 loops=25)

  • Output: ss.id, ss.release_id, ss.subcategory_id, ss.sort, ss.name, ss.button1_text, ss.button1_url, ss.button2_text, ss.button2_url, ss.modified_flag, ss.deleted_flag, ss.date_created, ss.date_updated, ss.updated_by, ss.copy
  • Index Cond: ((ss.id = sspg.subcategory_set_id) AND (ss.release_id = 389))
  • Filter: (ss.deleted_flag = 0)
  • Buffers: shared hit=75
27. 0.050 0.050 ↑ 1.0 1 25

Index Scan using subcategory_pk on public.subcategory s (cost=0.29..3.01 rows=1 width=32) (actual time=0.002..0.002 rows=1 loops=25)

  • Output: s.id, s.release_id, s.subcategory_key, s.editorial_description, s.static_url, s.type, s.meta_description, s.notes, s.friendly_url, s.hidden_from_feeds_flag, s.modified_flag, s.relationship_modified_flag, s.deleted_flag, s.valid_from, s.valid_to, s.updated_by, s.date_updated, s.date_created, s.google_category_id, s.page_title, s.brand_statement, s.recommendation_code, s.recommendation_title, s.shop_this_room_image, s.shop_this_room_image_caption, s.shop_this_room_text1, s.shop_this_room_text2, s.shop_this_room_text3, s.short_name, s.long_name, s.show_swatch_summary, s.column_layout
  • Index Cond: ((s.id = ss.subcategory_id) AND (s.release_id = 389))
  • Filter: (s.deleted_flag = 0)
  • Buffers: shared hit=75
28. 0.125 0.125 ↑ 1.0 1 25

Index Scan using category_subcategory_subcategory_id_idx on public.category_subcategory cs (cost=0.29..9.26 rows=1 width=24) (actual time=0.003..0.005 rows=1 loops=25)

  • Output: cs.category_id, cs.subcategory_id, cs.release_id, cs.name, cs.sort, cs.default_navigation_flag, cs.modified_flag, cs.deleted_flag, cs.updated_by, cs.date_updated, cs.date_created
  • Index Cond: (cs.subcategory_id = s.id)
  • Filter: ((cs.release_id = 389) AND (cs.deleted_flag = 0))
  • Rows Removed by Filter: 5
  • Buffers: shared hit=200
29. 0.040 0.040 ↑ 1.0 1 20

Index Scan using category_pk on public.category c (cost=0.28..2.15 rows=1 width=32) (actual time=0.002..0.002 rows=1 loops=20)

  • Output: c.id, c.release_id, c.category_key, c.name, c.editorial_description, c.static_url, c.catalog_id, c.sort, c.meta_description, c.friendly_url, c.modified_flag, c.relationship_modified_flag, c.deleted_flag, c.valid_from, c.valid_to, c.updated_by, c.date_updated, c.date_created, c.recommendation_code, c.recommendation_title, c.page_title, c.brand_statement, c.breadcrumb_override
  • Index Cond: ((c.id = cs.category_id) AND (c.release_id = 389))
  • Filter: (c.deleted_flag = 0)
  • Buffers: shared hit=60
30. 0.060 0.060 ↓ 0.0 0 20

Index Only Scan using web_product_type_pk on public.web_product_type toisleather (cost=0.43..3.34 rows=1 width=28) (actual time=0.003..0.003 rows=0 loops=20)

  • Output: toisleather.product_id, toisleather.release_id, toisleather.name
  • Index Cond: ((toisleather.product_id = productto.product_id) AND (toisleather.release_id = productto.release_id) AND (toisleather.release_id = 389) AND (toisleather.name = 'LEATHER'::text))
  • Heap Fetches: 8
  • Buffers: shared hit=68
31. 0.060 0.060 ↓ 0.0 0 20

Index Only Scan using web_product_type_pk on public.web_product_type fromisleather (cost=0.43..8.45 rows=1 width=28) (actual time=0.003..0.003 rows=0 loops=20)

  • Output: fromisleather.product_id, fromisleather.release_id, fromisleather.name
  • Index Cond: ((fromisleather.product_id = productfrom.product_id) AND (fromisleather.release_id = productfrom.release_id) AND (fromisleather.release_id = 389) AND (fromisleather.name = 'LEATHER'::text))
  • Heap Fetches: 0
  • Buffers: shared hit=60
Planning time : 24.535 ms
Execution time : 86.476 ms