explain.depesz.com

PostgreSQL's explain analyze made readable

Result: ALAn

Settings

Optimization(s) for this plan:

# exclusive inclusive rows x rows loops node
1. 0.000 0.000 ↓ 0.0

Unique (cost=25,957,607.83..27,161,155.85 rows=6,977,090 width=1,375) (actual rows= loops=)

2. 0.000 0.000 ↓ 0.0

Sort (cost=25,957,607.83..25,975,050.55 rows=6,977,090 width=1,375) (actual rows= loops=)

  • Sort Key: p.global_ultimate_duns_number, p.global_ultimate_business_name, p.domestic_ultimate_duns_number, p.hq_duns_number, p.parent_duns_number, p.duns_number, p.business_name, p.global_ultimate_country, p.global_ultimate_indicator, p.domestic_ultimate_indicator, p.domestic_ultimate_country, p.country_name, p.number_of_family_members, p.hierarchy_code, p.major_industry_category, p.primary_sic_2_digit, p.primary_sic_4_digit, p.emp_here, p.emp_total, p.sales_volume_us, p.percent_growth_emp_3yr, p.percent_growth_emp_5yr, p.percent_growth_sales_3yr, p.percent_growth_sales_5yr, p.trend_year_sales, p.trend_year_emp, p.emp_base_3yr, p.emp_base_5yr, p.sales_base_3yr, p.sales_base_5yr, p.population, p.division_indicator, p.import_export, p.manufacturing_indicator, p.small_business_indicator, p.subsidiary_indicator, p.legal_status, p.owns_rents, p.public_private, p.location_type, p.year_started, p.square_footage, p.marketability_indicator, p.url, p.sic8_0, p.sic8_1, p.sic8_2, p.sic8_3, p.sic8_4, p.sic8_5, p.sales_volume_code, p.emp_total_code, p.emp_here_code, p.domestic_ultimate_name, p.domestic_ultimate_country2, p.parent_hq_name, p.primary_sic_8_digit, p.url_status_ind, p.fortune_1000_rank, p.global_500_rank, p.fortune_1000_indicator, p.global_500_flag, p.tradestyle, p.second_tradestyle, p.state_name, p.accounting_firm_name, m.akam_account_id
3. 0.000 0.000 ↓ 0.0

Merge Join (cost=1,075,005.31..20,991,206.24 rows=6,977,090 width=1,375) (actual rows= loops=)

  • Merge Cond: ((p.duns_number)::text = m.duns_key)
4. 0.000 0.000 ↓ 0.0

Index Scan using idx_pop_duns_number on pop p (cost=0.57..19,463,517.51 rows=139,211,056 width=1,333) (actual rows= loops=)

5. 0.000 0.000 ↓ 0.0

Sort (cost=1,075,004.74..1,092,447.46 rows=6,977,090 width=42) (actual rows= loops=)

  • Sort Key: m.duns_key
6. 0.000 0.000 ↓ 0.0

Subquery Scan on m (cost=142,370.35..281,912.15 rows=6,977,090 width=42) (actual rows= loops=)

7. 0.000 0.000 ↓ 0.0

HashAggregate (cost=142,370.35..212,141.25 rows=6,977,090 width=42) (actual rows= loops=)

8. 0.000 0.000 ↓ 0.0

Seq Scan on temp_anskumar (cost=0.00..107,484.90 rows=6,977,090 width=42) (actual rows= loops=)