我有这个非常长的查询,我将在这里总结并在底部粘贴:
select * from
a
left join b t1 on a.x = b.x
left join b t2 on a.y = b.x
left join b t3 on a.z = b.x
left join c on a.1 = c.1 and a.2 = c.2 and a.3 = c.3 --call this predicate 1
where c.z is null
a和c有主键1,2,3 unclustered a.x y或z可以为null 您将在下面链接的内容中看到a是40k行,c是500k行,b是7k行。此查询需要10分钟。手动执行excel更快。我的行计数估计都是错误的,即使我运行真空全分析并且它有嵌套循环,它不应该
这是完整的 https://explain.depesz.com/s/w2uN
当我删除谓词1时,所有嵌套循环都消失了,行估计仍然是错误的。在我重置postgre之后运行还需要不到一秒的时间,因此没有缓存
https://explain.depesz.com/s/O7R
有关如何强制散列连接的任何想法?或者我可以在40k表上构建3个索引,我会截断并加载到所有时间,因为这实际上是一个每周都刷新的临时表。看起来像矫枉过正,但可能不会伤害任何人。除了真空分析之外,如何在计划器中获得正确的行数也很少。关于这个的任何想法?
最后,这是完整的代码
SELECT
ar.cocd,
ar.customer,
ar.sales_doc,
ar.documentno,
ar.headertext,
ar.clrng_doc,
ar.typ,
ar.net_due_dt,
ar.amt,
ar.lcurr,
ar.amount_in_dc,
ar.curr,
ar.text,
ar.doc_date,
ar.clearing,
ar.po_number,
ar.payt,
ar.st,
ar.arrear,
ar.gl,
ar.user_name,
ar.tcod,
ar.itm,
ar.inv_ref,
ar.amount_in_loccurr2,
ar.pmnt_date,
ar.pk,
ar.pstng_date,
ar.account,
ar.accty,
ar.aging_bucket,
ar.billdoc,
ar.ftyp,
ar.general_ledger_amt,
ar.offstacct,
ar.pmtmthsu,
ar.purchdoc,
ar.rcd,
ar.transtype,
ar.ym,
COALESCE(ar_f2.branch, ar_f2.subbranch, ar_f2.account) AS forecast_company,
ar_f.customer_name AS paying_company,
ar_f3.customer_name AS shipping_company
FROM h_ar_open ar
LEFT JOIN h_ar_forecast ar_f ON ar.customer = ar_f.customer
LEFT JOIN h_ar_forecast ar_f2 ON ar.soldto::double precision = ar_f2.customer
LEFT JOIN h_ar_forecast ar_f3 ON ar.shipto::double precision = ar_f3.customer
LEFT JOIN h_ar_hist hist ON ar.cocd = hist.cocd AND ar.itm = hist.itm AND ar.documentno = hist.documentno
WHERE hist.documentno IS NULL;
答案 0 :(得分:0)
评论中的索引有很多帮助,因为它使嵌套循环连接更快。超过7000行的46417次连续扫描很糟糕。
你的问题是错误的。
也许您可以通过以下方法强制加入订单:
SELECT ...
FROM (SELECT ...
FROM a
LEFT JOIN b t1 ...
LEFT JOIN b t3 ...
LEFT JOIN b t3 ...
OFFSET 0) x
LEFT JOIN c ...;
如果c
最后加入,则错误估计不会造成伤害。