Google cloud datastore only store unique entity

Question

I am trying to learn NoSQL with Google Datastore but I am running into a problem with uniqueness.

Consider an ecommerce store, it has categories and products.

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Answer 1

Data model is a big subject but IMO there are two approaches you can choose. This is more fundamental rather specific to your question. It gives some ideas.

The first approach – storing a reference as a property

Same as thinking of product contains product variants ...

This approach sort of the same from RDBMS world. You can create products separately, and each product will have a reference in each product variants. It is similar to how foreign keys work in databases. So, you will have a new property for the product variant entities, which will contain a reference to the product to which it belongs. The product attribute will actually contain the key of an entity of the Product Kind. If it sounds confusing this is how u can dissect it. I will use python as example:

# product model
class Product(ndb.Model):
    name = ndb.StringProperty()

# product variant model
class ProductVariant(ndb.Model):
    name = ndb.StringProperty()
    price = ndb.IntegerProperty()
    # product key.
    product = ndb.KeyProperty(kind=Product)

hugoboss = Product(name="Hugo Boss", key=ndb.Key(Product, 'hugoboss'))
gap = Product(name="Gap", key=ndb.Key(Gap, 'gap'))

pants1 = ProductVariant(name="Black panst", price=300, product=hugoboss.key)
pants2 = ProductVariant(name="Grey pants", price=200, product=hugoboss.key)
tshirt = ProductVariant(name="White graphic tshirt", price=10, product=gap.key)

pants1.put()
pants2.put()
tshirt.put()

# so lets say give me all pants that has label hugoboss
for pants in ProductVariant.query(ProductVariant.product == hugoboss.key).fetch(10):
    print pants.name

# You should get something:
Black pants
Grey panst

The second approach – a product within the key

To take full advantage of it you need to know about sorting feature of Bigtable(Datastore build on top of Bigtable) row keys and how data manipulated around it. if you want to deep dive there is great paper Bigtable: A Distributed Storage System for Structured Data

# product model
class Product(ndb.Model):
    name = ndb.StringProperty()

# product variant model
class ProductVariant(ndb.Model):
    name = ndb.StringProperty()
    price = ndb.IntegerProperty()

hugoboss = ndb.Key(Product, 'hugoboss')
gap = ndb.Key(Product, 'gap')

Product(name="Hugo Boss", key=hugoboss).put()
Product(name="Gap", key=gap).put()

pants1 = ProductVariant(name="Black pants", price=300, parent=hugoboss)
pants2 = ProductVariant(name="Grey pants", price=200, parent=hugoboss)
tshirt = ProductVariant(name="White graphic tshirt", price=10, parent=gap)

pants1.put()
pants2.put()
tshirt.put()

# so lets say give me all pants that has label hugoboss
for pants in ProductVariant.query(ancestor=hugoboss).fetch(10):
    print pants.name

# You should get something:
Black pants
Grey pants

Second approach is very powerful! I hope this helps.