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sto usando MPTT in un modello per gestire un sistema di etichettatura (ogni tag ha un TreeForeignKey optional a un tag 'genitore')Django MPTT Postgres query di aggiornamento viene eseguito lentamente
Ogni volta che ho bisogno di salvare un modello di tag, la seguente domanda funziona incredibilmente lento (verso l'alto di 45 secondi)
UPDATE "taxonomy_taxonomy" SET "tree_id" = ("taxonomy_taxonomy"."tree_id" + %s) WHERE "taxonomy_taxonomy"."tree_id" > %s
mando il contenuto di articoli mediante un sistema di tagging automatico, che può generare verso l'alto di 20 tag. Ovviamente, quello non volerà :)
Ho aggiunto il db_index = Falso sperando di cambiare i tempi di scrittura (le letture non sembrano essere un problema) ma il problema persiste.
Ecco il modello in questione:
class Taxonomy(MPTTModel):
parent = TreeForeignKey('self',blank=True,null=True,related_name='children',verbose_name='Parent', db_index=False)
parent_name = models.CharField(max_length=64, blank=True, null=True, editable=False)
name = models.CharField(verbose_name='Title', max_length=100, db_index=True)
slug = models.SlugField(verbose_name='Slug', blank=True)
primary = models.BooleanField(
verbose_name='Is Primary',
default=False,
db_index=True,
)
type = models.CharField(max_length=30, db_index=True)
created_date = models.DateTimeField(auto_now_add=True, null=True)
updated_date = models.DateTimeField(auto_now=True, null=True)
publication_date = models.DateTimeField(null=True, blank=True)
scheduled_date = models.DateTimeField(null=True, blank=True)
workflowstate = models.CharField(max_length=30, default='draft')
created_by = models.ForeignKey(User, null=True)
paid_content = models.BooleanField(verbose_name='Is Behind the Paywall', default=False, blank=True)
publish_now = True
show_preview = False
temporary = models.BooleanField(default=False)
def save(self, *args, **kwargs):
if self.slug is None:
self.slug = self.name
if not self.slug:
self.slug = slugify(self.name)[:50]
if self.parent:
self.parent_name = self.parent.name
self.slug = slugify(self.slug)
self.workflowstate = "published"
super(Taxonomy, self).save(*args, **kwargs)
store_to_backend_mongo(self)
publish_to_frontend(self)
E il piano di query (come riportato dal Nuovo Relic):
1) Update on taxonomy_taxonomy (cost=0.00..133833.19 rows=90515 width=139)
2) -> Seq Scan on taxonomy_taxonomy (cost=0.00..133833.19 rows=90515 width=139)
3) Filter: ?
Infine, il traceback da una query:
Traceback (most recent call last):
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/newrelic-2.54.0.41/newrelic/api/web_transaction.py", line 711, in __iter__
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/newrelic-2.54.0.41/newrelic/api/web_transaction.py", line 1087, in __call__
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/core/handlers/wsgi.py", line 189, in __call__
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/core/handlers/base.py", line 132, in get_response
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/newrelic-2.54.0.41/newrelic/hooks/framework_django.py", line 499, in wrapper
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/contrib/auth/decorators.py", line 22, in _wrapped_view
File "./editorial/views.py", line 242, in calculate_queryly
File "./editorial/views.py", line 292, in queryly_function
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/models/manager.py", line 127, in manager_method
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/models/query.py", line 348, in create
File "./taxonomy/models.py", line 179, in save
File "./taxonomy/models.py", line 58, in save
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/mptt/models.py", line 946, in save
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/mptt/models.py", line 702, in insert_at
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/mptt/managers.py", line 467, in insert_node
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/mptt/managers.py", line 491, in insert_node
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/mptt/managers.py", line 726, in _create_tree_space
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/mptt/managers.py", line 364, in _mptt_update
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/models/query.py", line 563, in update
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/models/sql/compiler.py", line 1062, in execute_sql
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/models/sql/compiler.py", line 840, in execute_sql
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/backends/utils.py", line 79, in execute
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/django/db/backends/utils.py", line 64, in execute
File "/data/www/nj-cms/venv/lib/python3.4/site-packages/newrelic-2.54.0.41/newrelic/hooks/database_dbapi2.py", line 22, in execute
Qualche idea su come posso far risparmiare questi modelli per essere più veloce?
EDIT per ulteriori informazioni: Questo è in Postgres, con il motore psycopg2 'MOTORE': 'django.db.backends.postgresql_psycopg2',
SECONDO EDIT: Come richiesto, ho eseguito la query con SPIEGARE ANALIZZA. Il risultato è il seguente:
nj=# EXPLAIN ANALYZE UPDATE "taxonomy_taxonomy" SET "tree_id" = ("taxonomy_taxonomy"."tree_id" + 1) WHERE "taxonomy_taxonomy"."tree_id" > 1;
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------
Update on taxonomy_taxonomy (cost=0.00..9588.75 rows=24582 width=132) (actual time=258718.550..258718.550 rows=0 loops=1)
-> Seq Scan on taxonomy_taxonomy (cost=0.00..9588.75 rows=24582 width=132) (actual time=59.956..8271.209 rows=24582 loops=1)
Filter: (tree_id > 1)
Rows Removed by Filter: 2
Planning time: 28.763 ms
Execution time: 258718.661 ms
(6 rows)
Whad DB stai usando? se MySQL, quale motore, InnoDB o MyISAM? –
Ah, dovrebbe averlo incluso. Lo modificherò ora. Sto usando Postgres. Da settings.py: 'ENGINE': 'django.db.backends.postgresql_psycopg2', –
dovresti eseguire la stessa query su psql con EXPLAIN ANALYZE e aggiungere qui l'output (quello della nuova reliquia è incompleto) –