The document discusses the use of MongoDB for an e-commerce product catalog, highlighting its advantages such as agile releases, handling varying product schemas, and complex queries. It outlines the approach taken for schema design, querying, and the use of GridFS for large files, while also addressing challenges like schema management and locking mechanisms. Examples of querying techniques and document referencing are provided, demonstrating how to access product data effectively.

1. e-Com Product Catalog using
MongoDB
- Vishwas Bhagath
vbhagath@equalexperts.com
http://www.equalexperts.com/

2. Why MongoDB ?
● Agile incremental releases with a short time to market
● Feeds from multiple vendors containing products with
varying schema
● Complex queries on product attributes
● Rich Content user experience
● Capital risk mitigation
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3. How we approached...
● Modeling and schema design
● Querying
● Referencing one document in another
● Rich content using GridFS
● Indexes
● MongoDB challenges
➢ Locking mechanism
➢ Managing Schema and fat fingers
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4. Domain model
{"_id" : ObjectId("5082626144ae3a687919c094"),
"name" : "iPhone 5 Pop Blue Case",
"canonicalName" : "iphone-5-pop-blue-case",
"retailPrice" : 19.99,
"productCode" : "G4IC542G",
"category" : {
"categoryCode" : "CAS",
"name" : "Cases",
"canonicalName" : "cases"
},
"compatibleHandsets" : [{
"manufacturer" : {
"name" : "Apple",
"canonicalName" : "apple"
},
"model" : "iPhone 5 16GB",
"name" : "Apple_iPhone_5_16GB",
"canonicalName" : "apple_iphone_5_16gb"
}],
review_ids : ["review_id1", "review_id2"]
}
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5. Querying
● Querying for a accesory by a category :
db.accessory.find({"category.canonicalName" : "cases"})
● Querying for a accessory by list of categories :
db.accessory.find({"category.canonicalName" : {"$in" : ["cases",
"memory"]}})
● Getting distinct categories of products:
db.accessory.distinct("category");
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6. Querying contd...
● Querying all cases between a price range sorted by price
db.accessory.find( { $and : [{"category.canonicalName" : "cases"},
{"retailPrice" : {$gt : 15, $lt : 25}}]}).sort({“retailPrice” : 1})
● Querying accessories by text:
db.accessory.find( {"keywords" : { $regex : "iphone", $options : 'I'}})
● Querying embedded arrays:
db.accessory.find({"compatibleHandsets" : {$elemMatch :
{ "manufacturer.canonicalName" : "nokia"}}})
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7. Referencing documents
● Manual Referencing – Save the _id field of one
document in another as a reference manually.
Eg : Accessory - Reviews
● DBRefs – A standard convention for referencing a
document in another. It stores the name of the
collection and the _id of the parent document.
Eg : Basket - Accessory
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8. GridFS
● Storage specification for storing large binary objects in
mongoDB as BSON documents
● Easy to use and can store files upto 16MB
GridFS gfs = new GridFS(dbName);
//create file
gfs.createFile(inputStream, “myFileName”);
//retrieve file
gfs.findOne(“myFileName”);
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9. Indexes
● Indexes
db.accessory.ensureIndex({“name” : 1})
● Unique Keys
db.accessory.ensureIndex({“canonicalName” :
1}, {unique : true})
● Sparse Keys
db.order.ensureIndex({“uniqueActiveOrder” :
1}, {unique : true, sparse : true})
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10. Optimistic Locking mechanism
● Set ReadPreference on these collections to
Primary
● Give the lock key to each client who reads the
collection
● Each time you update generate a unique lock key
● Before update check if the lock key from client
matches the one in the DB, if not do not update
since the object is stale.
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11. Manging schemas
● DB to Object Convertors and vice versa
should be written to manually manage the old
schema to the current one as we release code
to production
● Requires high developer discipline and good
knowledge of previous object model
● Delayed replication node
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12. Questions
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