Appengine NDB: Putting 880 rows, exceeding datasto

问题:

I have an application which imports 880 rows into an NDB datastore, using put_async(). Whenever I run this import it exceeds the daily quota of 50,000 write ops to the datastore.

I'm trying to understand why this operation is so expensive and what can be done to stay under quota.

There are 13 columns like so:

stringbool = ['true', 'false']
class BeerMenu(ndb.Model):
  name = ndb.StringProperty()
  brewery = ndb.StringProperty()
  origin = ndb.StringProperty()
  abv = ndb.FloatProperty()
  size = ndb.FloatProperty()
  meas = ndb.StringProperty()
  price = ndb.FloatProperty()
  active = ndb.StringProperty(default="false", choices=stringbool)
  url = ndb.StringProperty()
  bartender = ndb.StringProperty()
  lineno = ndb.IntegerProperty()
  purdate = ndb.DateProperty()
  costper = ndb.FloatProperty()

I've trimmed the indexing back to one:

- kind: BeerMenu
  properties:
    - name: brewery
    - name: name

According to the SDK datastore viewer, each row is 29 write ops, so that would generate 25520 writes! I'm assuming that the indexes consume the rest of the write ops, but I don't know exactly how many because AppEngine just says I've exceeded the quota.

What are the best strategies for reducing the number of write ops?

回答1:

All properties except text and blob properties are indexed by default. So if you deindex the string properties, all the float, int, and date properties are still indexed. You should add indexed=False to the other properties to decrease writes.

Indexes listed in index.yaml are additional indexes to the property indexes. index.yaml indexes are for things like ordered and relational queries (i.e., a query with date > date_property will generate an entry in index.yaml).

回答2:

Here, check out the Costs for Datastore Calls part to give you more idea:

Paid Apps: Budgeting, Billing, and Buying Resources

Hope this helps too.