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Exemple de plan de requête
Cet exemple illustre la façon d’évaluer un plan de requête pour trouver des opportunités permettant d’optimiser la distribution.
Exécutez la requête suivante à l'aide d'une EXPLAIN commande pour produire un plan de requête.
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;
Dans la TICKIT base de données, SALES se trouve une table de faits et LISTING constitue sa plus grande dimension. Afin de colocaliser les tables, SALES est distribué sur leLISTID, qui est la clé étrangère pourLISTING, et LISTING est distribué sur sa clé primaire,LISTID. L'exemple suivant montre les CREATE TABLE commandes pour SALES etLISTING.
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));
Dans le plan de requête suivant, l'étape Merge Join pour la jointure LISTING indique DS_ DIST _NONE, ce qui indique qu'aucune redistribution n'est requise pour l'étape. SALES Toutefois, en remontant le plan de requête, les autres jointures internes affichent DS_ BCAST _INNER, ce qui indique que la table interne est diffusée dans le cadre de l'exécution de la requête. Du fait qu’une seule paire de tables peut être colocalisée à l’aide de la distribution de clés, cinq tables doivent être rediffusées.
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)
Une solution consiste à modifier les tables à avoir DISTSTYLEALL.
ALTER TABLE users ALTER DISTSTYLE ALL; ALTER TABLE venue ALTER DISTSTYLE ALL; ALTER TABLE category ALTER DISTSTYLE ALL; ALTER TABLE date ALTER DISTSTYLE ALL; ALTER TABLE event ALTER DISTSTYLE ALL;
Réexécutez la même requête avec EXPLAIN et examinez le nouveau plan de requête. Les jointures affichent désormais DS_ _ DIST ALL _NONE, ce qui indique qu'aucune redistribution n'est requise car les données ont été distribuées à tous les nœuds utilisateurs. DISTSTYLE ALL
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)
