我有多个CTE的以下查询。如果没有离开日期和到达日期CTE，查询将在大约12秒内完成。当我添加离开日期和到达日期CTE时，查询需要很长时间，因此我不得不取消它。我无法运行解释原因相同的分析。通过运行解释，它表示最昂贵的节点是末尾的连接a.arrival_date = r.arrival_date。从我的解释中可以看出，它使用的是日期CTE的索引。所以我的问题是，加上这两个，是什么会导致它减慢这么多，有什么办法可以优化/修复它？
WITH
relationships AS (
SELECT rt.from_location_code,
rt.to_location_code,
rt.departure_datetime AS departure_date,
rt.arrival_datetime AS arrival_date,
rt.ticketno,
rt.leg_number,
rt.leg_direction,
rt.service_direction,
rt.booking_reference,
fj.transaction_id,
fj.ticket_id,
fj.ticket_number,
rt.batch_id
FROM sch1.booked_travel rt
LEFT JOIN (
SELECT DISTINCT t.transaction_id, sdt.ticket_number, sdt.ticket_id
FROM sch2.ticket_transactions t
JOIN sch2.tickets sdt USING (ticket_id)
JOIN sch1.reserved_travels ert ON ert.ticketno = sdt.ticket_number
) fj ON fj.ticket_number = rt.ticketno
WHERE batch_id = 234
),
xaction AS (
SELECT DISTINCT t.transaction_id, sdt.ticket_number, sdt.ticket_id
FROM sch2.ticket_transactions t
JOIN sch2.tickets sdt USING (ticket_id)
JOIN relationships ert ON ert.ticketno = sdt.ticket_number
WHERE ert.batch_id = 234
),
from_location AS (
SELECT DISTINCT l.location_id AS from_location_id, rt.from_location_code
FROM sch2.locations l
JOIN relationships rt ON rt.from_location_code = l.code
WHERE rt.batch_id = 234
),
to_location AS (
SELECT DISTINCT d.location_id AS to_location_id, rt.to_location_code
FROM sch2.locations d
JOIN relationships rt ON rt.to_location_code = d.code
WHERE rt.batch_id = 234
),
departure_dates as (
select distinct on (d.date_id, d.the_date) d.date_id as departure_date_id, d.the_date as departure_date
from sch2.dates d
join relationships r on r.departure_date = d.the_date
where r.batch_id = 234
),
arrival_dates as (
select distinct on (d.date_id, d.the_date) d.date_id as arrival_date_id, d.the_date as arrival_date
from sch2.dates d
join relationships r on r.arrival_date = d.the_date
where r.batch_id = 234
)
INSERT
INTO sch2.travel_legs (transaction_id, ticket_id, leg_number, leg_direction,
from_location_id, to_location_id, service_direction,
departure_date_id, departure_date, arrival_date, arrival_date_id, booking_reference)
SELECT r.transaction_id,
r.ticket_id,
r.leg_number,
r.leg_direction,
f.from_location_id,
t.to_location_id,
r.service_direction,
d.departure_date_id,
r.departure_date,
r.arrival_date,
a.arrival_date_id,
r.booking_reference
FROM relationships r
LEFT JOIN xaction USING (transaction_id)
LEFT JOIN from_location f ON f.from_location_code = r.from_location_code
LEFT JOIN to_location t ON t.to_location_code = r.to_location_code
left join departure_dates d on r.departure_date = d.departure_date
left join arrival_dates a on a.arrival_date = r.arrival_date
RETURNING *;
计划：
"Insert on sch2.travle_legs (cost=6500820.62..19312607.17 rows=425901878 width=678)"
" Output: travle_legs.journey_leg_id, travle_legs.transaction_id, travle_legs.customer_id, travle_legs.ticket_id, travle_legs.brand_id, travle_legs.leg_number, travle_legs.leg_direction, travle_legs.from_location_id, travle_legs.to_location_id, travle_legs.service_id, travle_legs.service_direction, travle_legs.departure_date, travle_legs.arrival_date, travle_legs.departure_date_id, travle_legs.arrival_date_id, travle_legs.journey_type, travle_legs.flight_id, travle_legs.booking_reference, travle_legs.scheduled_depature_date, travle_legs.scheduled_departure_date_id, travle_legs.actual_departure_date, travle_legs.actual_departure_date_id, travle_legs.scheduled_arrival_date, travle_legs.scheduled_arrival_date_id, travle_legs.actual_arrival_date, travle_legs.actual_arrival_date_id, travle_legs.departure_offset_minutes, travle_legs.departure_offset_time, travle_legs.departure_late, travle_legs.arrival_offset_minutes, travle_legs.arrival_offset_time, travle_legs.arrival_late"
" CTE relationships"
" -> Hash Right Join (cost=17457.33..769694.82 rows=73016 width=90)"
" Output: rt.from_location_code, rt.to_location_code, rt.departure_datetime, rt.arrival_datetime, COALESCE($0, '-1'::integer), (SubPlan 2), rt.ticketno, rt.leg_number, rt.leg_direction, COALESCE($2, '-1'::integer), rt.service_direction, $3, rt.booking_reference, fj.transaction_id, fj.ticket_id, fj.ticket_number, rt.sch1_batch_file_id"
" Hash Cond: ((fj.ticket_number)::text = (rt.ticketno)::text)"
" InitPlan 1 (returns $0)"
" -> Limit (cost=1.02..59.51 rows=1 width=4)"
" Output: c.service_id"
" -> Hash Join (cost=1.02..11112.93 rows=190 width=4)"
" Output: c.service_id"
" Inner Unique: true"
" Hash Cond: ((e.service_number)::text = (c.code)::text)"
" -> Seq Scan on sch1.booked_travels e (cost=0.00..10989.21 rows=45937 width=3)"
" Output: e.id, e.sale_id, e.ticketno, e.transaction_date, e.leg_number, e.leg_direction, e.from_location_code, e.to_location_code, e.company_brand_code, e.service_number, e.service_direction, e.departure_datetime, e.arrival_datetime, e.flight_code, e.booking_reference, e.sch1_batch_file_id, e.imported, e.created_at, e.updated_at, e.customer_id"
" Filter: (e.sch1_batch_file_id = 234)"
" -> Hash (cost=1.01..1.01 rows=1 width=72)"
" Output: c.service_id, c.code"
" -> Seq Scan on sch2.services c (cost=0.00..1.01 rows=1 width=72)"
" Output: c.service_id, c.code"
" InitPlan 3 (returns $2)"
" -> Function Scan on public.find_brand (cost=0.25..10.25 rows=1000 width=4)"
" Output: find_brand.brand_id"
" Function Call: find_brand('sch1.booked_travels'::regclass, 152, 'company_brand_code'::text)"
" InitPlan 4 (returns $3)"
" -> Limit (cost=1.02..219.88 rows=1 width=4)"
" Output: c_1.flight_id"
" -> Hash Join (cost=1.02..11163.01 rows=51 width=4)"
" Output: c_1.flight_id"
" Hash Cond: ((e_1.flight_code)::text = (c_1.flight_code)::text)"
" -> Seq Scan on sch1.booked_travels e_1 (cost=0.00..10989.21 rows=45937 width=3)"
" Output: e_1.id, e_1.sale_id, e_1.ticketno, e_1.transaction_date, e_1.leg_number, e_1.leg_direction, e_1.from_location_code, e_1.to_location_code, e_1.company_brand_code, e_1.service_number, e_1.service_direction, e_1.departure_datetime, e_1.arrival_datetime, e_1.flight_code, e_1.booking_reference, e_1.sch1_batch_file_id, e_1.imported, e_1.created_at, e_1.updated_at, e_1.customer_id"
" Filter: (e_1.sch1_batch_file_id = 234)"
" -> Hash (cost=1.01..1.01 rows=1 width=520)"
" Output: c_1.flight_id, c_1.flight_code"
" -> Seq Scan on sch2.flights c_1 (cost=0.00..1.01 rows=1 width=520)"
" Output: c_1.flight_id, c_1.flight_code"
" -> Subquery Scan on fj (cost=5110.26..6047.10 rows=46842 width=17)"
" Output: fj.transaction_id, fj.ticket_id, fj.ticket_number"
" -> HashAggregate (cost=5110.26..5578.68 rows=46842 width=17)"
" Output: t_1.transaction_id, sdt.ticket_number, sdt.ticket_id"
" Group Key: t_1.transaction_id, sdt.ticket_number, sdt.ticket_id"
" -> Hash Join (cost=2505.21..4758.94 rows=46842 width=17)"
" Output: t_1.transaction_id, sdt.ticket_number, sdt.ticket_id"
" Hash Cond: ((ert.ticketno)::text = (sdt.ticket_number)::text)"
" -> Index Only Scan using idx_booked_travels_batch_id_ticketno on sch1.booked_travels ert (cost=0.41..1613.47 rows=45937 width=9)"
" Output: ert.ticketno, ert.sch1_batch_file_id"
" -> Hash (cost=2059.58..2059.58 rows=35617 width=17)"
" Output: t_1.transaction_id, sdt.ticket_number, sdt.ticket_id"
" -> Hash Join (cost=1077.90..2059.58 rows=35617 width=17)"
" Output: t_1.transaction_id, sdt.ticket_number, sdt.ticket_id"
" Inner Unique: true"
" Hash Cond: (t_1.ticket_id = sdt.ticket_id)"
" -> Seq Scan on sch2.fact_ticket_transactions t_1 (cost=0.00..888.17 rows=35617 width=8)"
" Output: t_1.transaction_id, t_1.customer_id, t_1.ticket_id, t_1.agent_id, t_1.sale_date, t_1.sale_date_id, t_1.sales_channel, t_1.transaction_type, t_1.ticket_type, t_1.ticket_queue, t_1.fare_type, t_1.fare_value, t_1.adults, t_1.children, t_1.concessionary, t_1.young_person_coach_card, t_1.eurolines_young_person, t_1.hm_forces, t_1.infants, t_1.eurolines_seniors, t_1.over_sixties, t_1.coach_card_id, t_1.coach_card_consumer_type_id, t_1.account_id, t_1.distribution_type, t_1.ticket_email_id"
" -> Hash (cost=641.29..641.29 rows=34929 width=13)"
" Output: sdt.ticket_number, sdt.ticket_id"
" -> Seq Scan on sch2.tickets sdt (cost=0.00..641.29 rows=34929 width=13)"
" Output: sdt.ticket_number, sdt.ticket_id"
" -> Hash (cost=10989.21..10989.21 rows=45937 width=61)"
" Output: rt.from_location_code, rt.to_location_code, rt.departure_datetime, rt.arrival_datetime, rt.customer_id, rt.ticketno, rt.leg_number, rt.leg_direction, rt.service_direction, rt.booking_reference, rt.sch1_batch_file_id"
" -> Seq Scan on sch1.booked_travels rt (cost=0.00..10989.21 rows=45937 width=61)"
" Output: rt.from_location_code, rt.to_location_code, rt.departure_datetime, rt.arrival_datetime, rt.customer_id, rt.ticketno, rt.leg_number, rt.leg_direction, rt.service_direction, rt.booking_reference, rt.sch1_batch_file_id"
" Filter: (rt.sch1_batch_file_id = 234)"
" SubPlan 2"
" -> Function Scan on public.find_customer (cost=0.25..10.25 rows=1000 width=4)"
" Output: rt.customer_id"
" Function Call: find_customer('sch1.booked_travels'::regclass, 152)"
" CTE xaction"
" -> Unique (cost=2879.91..2883.63 rows=372 width=17)"
" Output: t_2.transaction_id, sdt_1.ticket_number, sdt_1.ticket_id"
" -> Sort (cost=2879.91..2880.84 rows=372 width=17)"
" Output: t_2.transaction_id, sdt_1.ticket_number, sdt_1.ticket_id"
" Sort Key: t_2.transaction_id, sdt_1.ticket_number, sdt_1.ticket_id"
" -> Nested Loop (cost=1078.19..2864.03 rows=372 width=17)"
" Output: t_2.transaction_id, sdt_1.ticket_number, sdt_1.ticket_id"
" -> Hash Join (cost=1077.90..2721.72 rows=365 width=13)"
" Output: sdt_1.ticket_number, sdt_1.ticket_id"
" Inner Unique: true"
" Hash Cond: ((ert_1.ticketno)::text = (sdt_1.ticket_number)::text)"
" -> CTE Scan on relationships ert_1 (cost=0.00..1642.86 rows=365 width=32)"
" Output: ert_1.from_location_code, ert_1.to_location_code, ert_1.departure_date, ert_1.arrival_date, ert_1.service_id, ert_1.customer_id, ert_1.ticketno, ert_1.leg_number, ert_1.leg_direction, ert_1.brand_id, ert_1.service_direction, ert_1.flight_id, ert_1.booking_reference, ert_1.transaction_id, ert_1.ticket_id, ert_1.ticket_number, ert_1.sch1_batch_file_id"
" Filter: (ert_1.sch1_batch_file_id = 234)"
" -> Hash (cost=641.29..641.29 rows=34929 width=13)"
" Output: sdt_1.ticket_number, sdt_1.ticket_id"
" -> Seq Scan on sch2.tickets sdt_1 (cost=0.00..641.29 rows=34929 width=13)"
" Output: sdt_1.ticket_number, sdt_1.ticket_id"
" -> Index Only Scan using idx_ticket_xaction_ticket_id_transaction_id on sch2.fact_ticket_transactions t_2 (cost=0.29..0.38 rows=1 width=8)"
" Output: t_2.ticket_id, t_2.transaction_id"
" Index Cond: (t_2.ticket_id = sdt_1.ticket_id)"
" CTE from_location"
" -> Unique (cost=1676.67..1679.41 rows=365 width=36)"
" Output: l.location_id, rt_1.from_location_code"
" -> Sort (cost=1676.67..1677.58 rows=365 width=36)"
" Output: l.location_id, rt_1.from_location_code"
" Sort Key: l.location_id, rt_1.from_location_code"
" -> Hash Join (cost=17.31..1661.14 rows=365 width=36)"
" Output: l.location_id, rt_1.from_location_code"
" Inner Unique: true"
" Hash Cond: ((rt_1.from_location_code)::text = (l.code)::text)"
" -> CTE Scan on relationships rt_1 (cost=0.00..1642.86 rows=365 width=32)"
" Output: rt_1.from_location_code, rt_1.to_location_code, rt_1.departure_date, rt_1.arrival_date, rt_1.service_id, rt_1.customer_id, rt_1.ticketno, rt_1.leg_number, rt_1.leg_direction, rt_1.brand_id, rt_1.service_direction, rt_1.flight_id, rt_1.booking_reference, rt_1.transaction_id, rt_1.ticket_id, rt_1.ticket_number, rt_1.sch1_batch_file_id"
" Filter: (rt_1.sch1_batch_file_id = 234)"
" -> Hash (cost=10.47..10.47 rows=547 width=10)"
" Output: l.location_id, l.code"
" -> Seq Scan on sch2.locations l (cost=0.00..10.47 rows=547 width=10)"
" Output: l.location_id, l.code"
" CTE to_location"
" -> Unique (cost=1676.67..1679.41 rows=365 width=36)"
" Output: d_1.location_id, rt_2.to_location_code"
" -> Sort (cost=1676.67..1677.58 rows=365 width=36)"
" Output: d_1.location_id, rt_2.to_location_code"
" Sort Key: d_1.location_id, rt_2.to_location_code"
" -> Hash Join (cost=17.31..1661.14 rows=365 width=36)"
" Output: d_1.location_id, rt_2.to_location_code"
" Inner Unique: true"
" Hash Cond: ((rt_2.to_location_code)::text = (d_1.code)::text)"
" -> CTE Scan on relationships rt_2 (cost=0.00..1642.86 rows=365 width=32)"
" Output: rt_2.from_location_code, rt_2.to_location_code, rt_2.departure_date, rt_2.arrival_date, rt_2.service_id, rt_2.customer_id, rt_2.ticketno, rt_2.leg_number, rt_2.leg_direction, rt_2.brand_id, rt_2.service_direction, rt_2.flight_id, rt_2.booking_reference, rt_2.transaction_id, rt_2.ticket_id, rt_2.ticket_number, rt_2.sch1_batch_file_id"
" Filter: (rt_2.sch1_batch_file_id = 234)"
" -> Hash (cost=10.47..10.47 rows=547 width=10)"
" Output: d_1.location_id, d_1.code"
" -> Seq Scan on sch2.locations d_1 (cost=0.00..10.47 rows=547 width=10)"
" Output: d_1.location_id, d_1.code"
" CTE departure_dates"
" -> Unique (cost=8103.16..8149.19 rows=6137 width=12)"
" Output: d_2.date_id, d_2.the_date"
" -> Sort (cost=8103.16..8118.51 rows=6137 width=12)"
" Output: d_2.date_id, d_2.the_date"
" Sort Key: d_2.date_id, d_2.the_date"
" -> Nested Loop (cost=0.42..7717.04 rows=6137 width=12)"
" Output: d_2.date_id, d_2.the_date"
" -> CTE Scan on relationships r_1 (cost=0.00..1642.86 rows=365 width=8)"
" Output: r_1.from_location_code, r_1.to_location_code, r_1.departure_date, r_1.arrival_date, r_1.service_id, r_1.customer_id, r_1.ticketno, r_1.leg_number, r_1.leg_direction, r_1.brand_id, r_1.service_direction, r_1.flight_id, r_1.booking_reference, r_1.transaction_id, r_1.ticket_id, r_1.ticket_number, r_1.sch1_batch_file_id"
" Filter: (r_1.sch1_batch_file_id = 234)"
" -> Index Scan using idx_lkup_dates_date on sch2.lkup_dates d_2 (cost=0.42..16.47 rows=17 width=12)"
" Output: d_2.date_id, d_2.the_date, d_2.date_iso, d_2.date_text, d_2.date_abbreviation, d_2.day_of_week_number, d_2.day_of_week_name, d_2.day_of_week_short_name, d_2.first_date_of_week, d_2.last_date_of_week, d_2.day_of_month, d_2.day_of_month_number, d_2.month_name, d_2.month_name_with_year, d_2.month_short_name, d_2.month_short_name_with_year, d_2.day_of_month_name, d_2.first_date_of_month, d_2.last_date_of_month, d_2.calendar_week_number, d_2.calendar_week_name, d_2.calendar_week_name_with_year, d_2.calendar_week_short_name, d_2.calendar_week_short_name_with_year, d_2.calendar_week_yy_wk, d_2.calendar_month_number, d_2.calendar_month_yy_mm, d_2.calendar_year_month"
" Index Cond: (d_2.the_date = r_1.departure_date)"
" CTE arrival_dates"
" -> Unique (cost=8103.16..8149.19 rows=6137 width=12)"
" Output: d_3.date_id, d_3.the_date"
" -> Sort (cost=8103.16..8118.51 rows=6137 width=12)"
" Output: d_3.date_id, d_3.the_date"
" Sort Key: d_3.date_id, d_3.the_date"
" -> Nested Loop (cost=0.42..7717.04 rows=6137 width=12)"
" Output: d_3.date_id, d_3.the_date"
" -> CTE Scan on relationships r_2 (cost=0.00..1642.86 rows=365 width=8)"
" Output: r_2.from_location_code, r_2.to_location_code, r_2.departure_date, r_2.arrival_date, r_2.service_id, r_2.customer_id, r_2.ticketno, r_2.leg_number, r_2.leg_direction, r_2.brand_id, r_2.service_direction, r_2.flight_id, r_2.booking_reference, r_2.transaction_id, r_2.ticket_id, r_2.ticket_number, r_2.sch1_batch_file_id"
" Filter: (r_2.sch1_batch_file_id = 234)"
" -> Index Scan using idx_lkup_dates_date on sch2.lkup_dates d_3 (cost=0.42..16.47 rows=17 width=12)"
" Output: d_3.date_id, d_3.the_date, d_3.date_iso, d_3.date_text, d_3.date_abbreviation, d_3.day_of_week_number, d_3.day_of_week_name, d_3.day_of_week_short_name, d_3.first_date_of_week, d_3.last_date_of_week, d_3.day_of_month, d_3.day_of_month_number, d_3.month_name, d_3.month_name_with_year, d_3.month_short_name, d_3.month_short_name_with_year, d_3.day_of_month_name, d_3.first_date_of_month, d_3.last_date_of_month, d_3.calendar_week_number, d_3.calendar_week_name, d_3.calendar_week_name_with_year, d_3.calendar_week_short_name, d_3.calendar_week_short_name_with_year, d_3.calendar_week_yy_wk, d_3.calendar_month_number, d_3.calendar_month_yy_mm, d_3.calendar_year_month"
" Index Cond: (d_3.the_date = r_2.arrival_date)"
" -> Merge Right Join (cost=5708584.97..18520371.52 rows=425901878 width=678)"
" Output: nextval('sch2.travle_legs_journey_leg_id_seq'::regclass), r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, f.from_location_id, t.to_location_id, r.service_id, r.service_direction, r.departure_date, r.arrival_date, d.departure_date_id, a.arrival_date_id, NULL::integer, r.flight_id, r.booking_reference, NULL::timestamp without time zone, NULL::integer, NULL::timestamp without time zone, NULL::integer, NULL::timestamp without time zone, NULL::integer, NULL::timestamp without time zone, NULL::integer, NULL::integer, NULL::integer, NULL::boolean, NULL::integer, NULL::integer, NULL::boolean"
" Merge Cond: (a.arrival_date = r.arrival_date)"
" -> Sort (cost=508.86..524.20 rows=6137 width=12)"
" Output: a.arrival_date_id, a.arrival_date"
" Sort Key: a.arrival_date"
" -> CTE Scan on arrival_dates a (cost=0.00..122.74 rows=6137 width=12)"
" Output: a.arrival_date_id, a.arrival_date"
" -> Materialize (cost=5708076.12..5777475.15 rows=13879807 width=180)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id, d.departure_date_id"
" -> Sort (cost=5708076.12..5742775.63 rows=13879807 width=180)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id, d.departure_date_id"
" Sort Key: r.arrival_date"
" -> Merge Right Join (cost=151743.89..361102.51 rows=13879807 width=180)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id, d.departure_date_id"
" Merge Cond: (d.departure_date = r.departure_date)"
" -> Sort (cost=508.86..524.20 rows=6137 width=12)"
" Output: d.departure_date_id, d.departure_date"
" Sort Key: d.departure_date"
" -> CTE Scan on departure_dates d (cost=0.00..122.74 rows=6137 width=12)"
" Output: d.departure_date_id, d.departure_date"
" -> Materialize (cost=151235.03..153496.69 rows=452332 width=176)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id"
" -> Sort (cost=151235.03..152365.86 rows=452332 width=176)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id"
" Sort Key: r.departure_date"
" -> Hash Left Join (cost=35.82..31437.17 rows=452332 width=176)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id"
" Hash Cond: (r.transaction_id = xaction.transaction_id)"
" -> Hash Left Join (cost=23.73..15046.30 rows=243189 width=176)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, f.from_location_id, t.to_location_id"
" Hash Cond: ((r.to_location_code)::text = (t.to_location_code)::text)"
" -> Hash Left Join (cost=11.86..6272.98 rows=133254 width=204)"
" Output: r.transaction_id, r.customer_id, r.ticket_id, r.brand_id, r.leg_number, r.leg_direction, r.service_id, r.service_direction, r.departure_date, r.arrival_date, r.flight_id, r.booking_reference, r.to_location_code, f.from_location_id"
" Hash Cond: ((r.from_location_code)::text = (f.from_location_code)::text)"
" -> CTE Scan on relationships r (cost=0.00..1460.32 rows=73016 width=232)"
" Output: r.from_location_code, r.to_location_code, r.departure_date, r.arrival_date, r.service_id, r.customer_id, r.ticketno, r.leg_number, r.leg_direction, r.brand_id, r.service_direction, r.flight_id, r.booking_reference, r.transaction_id, r.ticket_id, r.ticket_number, r.sch1_batch_file_id"
" -> Hash (cost=7.30..7.30 rows=365 width=36)"
" Output: f.from_location_id, f.from_location_code"
" -> CTE Scan on from_location f (cost=0.00..7.30 rows=365 width=36)"
" Output: f.from_location_id, f.from_location_code"
" -> Hash (cost=7.30..7.30 rows=365 width=36)"
" Output: t.to_location_id, t.to_location_code"
" -> CTE Scan on to_location t (cost=0.00..7.30 rows=365 width=36)"
" Output: t.to_location_id, t.to_location_code"
" -> Hash (cost=7.44..7.44 rows=372 width=4)"
" Output: xaction.transaction_id"
" -> CTE Scan on xaction (cost=0.00..7.44 rows=372 width=4)"
" Output: xaction.transaction_id" Output: xaction.transaction_id"
很难说您可以采取一种确定的措施来解决运行时问题，但是我建议您尝试一些方法，看看它们是否可以改善查询的性能。
在relationships CTE中，您应该使用GROUP BY子句来确保返回的记录是唯一的。因为您的所有后续CTE都重新加入relationships，所以如果relationships包含重复的记录，则可能会给以后的CTE带来麻烦，具体取决于查询计划者选择的联接类型。
您的查询计划列出了三个嵌套循环联接；以下CTE中的每一个CTE：xaction，departure_dates和arrival_dates。我将检查嵌套循环联接（大概是sch2.lkup_dates，relationships sch2.fact_ticket_transactions]]和sch2 .tickets）。当查询计划者认为所涉及的记录总数很少时，通常会选择一个嵌套循环联接，但是在这种假设下，有时这是完全错误的，这可能导致指数运行时间增加，具体取决于嵌套循环在执行中的最终位置计划。
这更多的是实践问题，而不是性能提高，但是因为您正在过滤relationships
batch_id = 234的记录，所以您不需要在其中包含类似的WHERE子句已加入回到[[relationships CTE。的所有后续CTE。如果发现嵌套循环联接中涉及的表非常大，建议您创建一个临时表，其中包含执行此查询之前联接表的输出，以确保嵌套循环不会出现在表中。查询计划。