查詢計劃範例 - Amazon Redshift

本文為英文版的機器翻譯版本,如內容有任何歧義或不一致之處,概以英文版為準。

查詢計劃範例

此範例顯示如何評估查詢計劃來找出最佳化分佈的機會。

搭配 EXPLAIN 命令執行下列查詢來產生查詢計劃。

explain select lastname, catname, venuename, venuecity, venuestate, eventname, month, sum(pricepaid) as buyercost, max(totalprice) as maxtotalprice from category join event on category.catid = event.catid join venue on venue.venueid = event.venueid join sales on sales.eventid = event.eventid join listing on sales.listid = listing.listid join date on sales.dateid = date.dateid join users on users.userid = sales.buyerid group by lastname, catname, venuename, venuecity, venuestate, eventname, month having sum(pricepaid)>9999 order by catname, buyercost desc;

在 TICKIT 資料庫中,SALES 是事實資料表,而 LISTING 是最大維度。為了共置資料表,SALES 會分佈在 LISTID (即 LISTING 的外部索引鍵) 上,而 LISTING 會分佈在其主要索引鍵 LISTID 上。下列範例顯示 SALES 和 LISTID 的 CREATE TABLE 命令。

create table sales( salesid integer not null, listid integer not null distkey, sellerid integer not null, buyerid integer not null, eventid integer not null encode mostly16, dateid smallint not null, qtysold smallint not null encode mostly8, pricepaid decimal(8,2) encode delta32k, commission decimal(8,2) encode delta32k, saletime timestamp, primary key(salesid), foreign key(listid) references listing(listid), foreign key(sellerid) references users(userid), foreign key(buyerid) references users(userid), foreign key(dateid) references date(dateid)) sortkey(listid,sellerid); create table listing( listid integer not null distkey sortkey, sellerid integer not null, eventid integer not null encode mostly16, dateid smallint not null, numtickets smallint not null encode mostly8, priceperticket decimal(8,2) encode bytedict, totalprice decimal(8,2) encode mostly32, listtime timestamp, primary key(listid), foreign key(sellerid) references users(userid), foreign key(eventid) references event(eventid), foreign key(dateid) references date(dateid));

在下列查詢計劃中,SALES 和 LISTING 上聯結的合併聯結步驟顯示 DS_DIST_NONE,這指出步驟不需要重新分佈。不過,往上移動查詢計劃時,其他內部資料表顯示 DS_BCAST_INNER,這指出內部資料表將播送,做為查詢執行的一部分。因為只有一對資料表可以使用索引鍵分佈來進行共置,所以五個資料表需要重新播送。

QUERY PLAN XN Merge (cost=1015345167117.54..1015345167544.46 rows=1000 width=103) Merge Key: category.catname, sum(sales.pricepaid) -> XN Network (cost=1015345167117.54..1015345167544.46 rows=170771 width=103) Send to leader -> XN Sort (cost=1015345167117.54..1015345167544.46 rows=170771 width=103) Sort Key: category.catname, sum(sales.pricepaid) -> XN HashAggregate (cost=15345150568.37..15345152276.08 rows=170771 width=103) Filter: (sum(pricepaid) > 9999.00) -> XN Hash Join DS_BCAST_INNER (cost=742.08..15345146299.10 rows=170771 width=103) Hash Cond: ("outer".catid = "inner".catid) -> XN Hash Join DS_BCAST_INNER (cost=741.94..15342942456.61 rows=170771 width=97) Hash Cond: ("outer".dateid = "inner".dateid) -> XN Hash Join DS_BCAST_INNER (cost=737.38..15269938609.81 rows=170766 width=90) Hash Cond: ("outer".buyerid = "inner".userid) -> XN Hash Join DS_BCAST_INNER (cost=112.50..3272334142.59 rows=170771 width=84) Hash Cond: ("outer".venueid = "inner".venueid) -> XN Hash Join DS_BCAST_INNER (cost=109.98..3167290276.71 rows=172456 width=47) Hash Cond: ("outer".eventid = "inner".eventid) -> XN Merge Join DS_DIST_NONE (cost=0.00..6286.47 rows=172456 width=30) Merge Cond: ("outer".listid = "inner".listid) -> XN Seq Scan on listing (cost=0.00..1924.97 rows=192497 width=14) -> XN Seq Scan on sales (cost=0.00..1724.56 rows=172456 width=24) -> XN Hash (cost=87.98..87.98 rows=8798 width=25) -> XN Seq Scan on event (cost=0.00..87.98 rows=8798 width=25) -> XN Hash (cost=2.02..2.02 rows=202 width=41) -> XN Seq Scan on venue (cost=0.00..2.02 rows=202 width=41) -> XN Hash (cost=499.90..499.90 rows=49990 width=14) -> XN Seq Scan on users (cost=0.00..499.90 rows=49990 width=14) -> XN Hash (cost=3.65..3.65 rows=365 width=11) -> XN Seq Scan on date (cost=0.00..3.65 rows=365 width=11) -> XN Hash (cost=0.11..0.11 rows=11 width=10) -> XN Seq Scan on category (cost=0.00..0.11 rows=11 width=10)

解決方案為使用 DISTSTYLE ALL 重建資料表。建立資料表的分佈樣式之後,您便無法變更該分佈樣式。若要使用不同的分佈樣式來重建資料表,請使用深層複製。

首先,重新命名資料表。

alter table users rename to userscopy; alter table venue rename to venuecopy; alter table category rename to categorycopy; alter table date rename to datecopy; alter table event rename to eventcopy;

執行下列指令碼來重建 USERS、VENUE、CATEGORY、DATE、EVENT。請勿對 SALES 和 LISTING 進行任何變更。

create table users( userid integer not null sortkey, username char(8), firstname varchar(30), lastname varchar(30), city varchar(30), state char(2), email varchar(100), phone char(14), likesports boolean, liketheatre boolean, likeconcerts boolean, likejazz boolean, likeclassical boolean, likeopera boolean, likerock boolean, likevegas boolean, likebroadway boolean, likemusicals boolean, primary key(userid)) diststyle all; create table venue( venueid smallint not null sortkey, venuename varchar(100), venuecity varchar(30), venuestate char(2), venueseats integer, primary key(venueid)) diststyle all; create table category( catid smallint not null, catgroup varchar(10), catname varchar(10), catdesc varchar(50), primary key(catid)) diststyle all; create table date( dateid smallint not null sortkey, caldate date not null, day character(3) not null, week smallint not null, month character(5) not null, qtr character(5) not null, year smallint not null, holiday boolean default('N'), primary key (dateid)) diststyle all; create table event( eventid integer not null sortkey, venueid smallint not null, catid smallint not null, dateid smallint not null, eventname varchar(200), starttime timestamp, primary key(eventid), foreign key(venueid) references venue(venueid), foreign key(catid) references category(catid), foreign key(dateid) references date(dateid)) diststyle all;

將資料插回至資料表,並執行 ANALYZE 命令來更新統計資訊。

insert into users select * from userscopy; insert into venue select * from venuecopy; insert into category select * from categorycopy; insert into date select * from datecopy; insert into event select * from eventcopy; analyze;

最後,捨棄副本。

drop table userscopy; drop table venuecopy; drop table categorycopy; drop table datecopy; drop table eventcopy;

再次搭配 EXPLAIN 執行相同的查詢,並檢查新的查詢計劃。聯結現在會顯示 DS_DIST_ALL_NONE,指出不需要重新分佈,因為已使用 DISTSTYLE ALL 將資料分佈至每一個節點。

QUERY PLAN XN Merge (cost=1000000047117.54..1000000047544.46 rows=1000 width=103) Merge Key: category.catname, sum(sales.pricepaid) -> XN Network (cost=1000000047117.54..1000000047544.46 rows=170771 width=103) Send to leader -> XN Sort (cost=1000000047117.54..1000000047544.46 rows=170771 width=103) Sort Key: category.catname, sum(sales.pricepaid) -> XN HashAggregate (cost=30568.37..32276.08 rows=170771 width=103) Filter: (sum(pricepaid) > 9999.00) -> XN Hash Join DS_DIST_ALL_NONE (cost=742.08..26299.10 rows=170771 width=103) Hash Cond: ("outer".buyerid = "inner".userid) -> XN Hash Join DS_DIST_ALL_NONE (cost=117.20..21831.99 rows=170766 width=97) Hash Cond: ("outer".dateid = "inner".dateid) -> XN Hash Join DS_DIST_ALL_NONE (cost=112.64..17985.08 rows=170771 width=90) Hash Cond: ("outer".catid = "inner".catid) -> XN Hash Join DS_DIST_ALL_NONE (cost=112.50..14142.59 rows=170771 width=84) Hash Cond: ("outer".venueid = "inner".venueid) -> XN Hash Join DS_DIST_ALL_NONE (cost=109.98..10276.71 rows=172456 width=47) Hash Cond: ("outer".eventid = "inner".eventid) -> XN Merge Join DS_DIST_NONE (cost=0.00..6286.47 rows=172456 width=30) Merge Cond: ("outer".listid = "inner".listid) -> XN Seq Scan on listing (cost=0.00..1924.97 rows=192497 width=14) -> XN Seq Scan on sales (cost=0.00..1724.56 rows=172456 width=24) -> XN Hash (cost=87.98..87.98 rows=8798 width=25) -> XN Seq Scan on event (cost=0.00..87.98 rows=8798 width=25) -> XN Hash (cost=2.02..2.02 rows=202 width=41) -> XN Seq Scan on venue (cost=0.00..2.02 rows=202 width=41) -> XN Hash (cost=0.11..0.11 rows=11 width=10) -> XN Seq Scan on category (cost=0.00..0.11 rows=11 width=10) -> XN Hash (cost=3.65..3.65 rows=365 width=11) -> XN Seq Scan on date (cost=0.00..3.65 rows=365 width=11) -> XN Hash (cost=499.90..499.90 rows=49990 width=14) -> XN Seq Scan on users (cost=0.00..499.90 rows=49990 width=14)