http://www.dotnettoscana.org/nosql-revolution.aspx

1. NoSQL revolution
An introduction to the NoSQL world with real life
examples using RavenDB and Redis
Matteo Baglini
http://it.linkedin.com/in/matteobaglini www.dotnettoscana.org
Nicola Baldi
http://it.linkedin.com/in/nicolabaldi
Luigi Berrettini
http://it.linkedin.com/in/luigiberrettini 15/12/2012

2. The movement

3. Document databases in practice
Nicola Baldi
http://it.linkedin.com/in/nicolabaldi
Luigi Berrettini
http://it.linkedin.com/in/luigiberrettini

4. Overview
15/12/2012 Document databases in practice 4

5. Unbounded result sets problem
Unbounded number of requests problem
15/12/2012 Document databases in practice - Overview 5

6.  They favor denormalization over
composition and joins
 Relations are different than in RDBMSs
 They are schema-less, but attention should
be paid in designing documents
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7. « a conceptual model should be drawn with
little or no regard for the software that might
implement it » (Martin Fowler, UML Distilled)
A domain model should be independent from
implementation details like persistence
In RavenDB this is somewhat true
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8.  RDBMS are schema-full
• tuples = sets of key-value pairs ⇒ flat structure
• more complex data structures are stored as relations
 Document databases are schema-less
• object graphs stored as docs ⇒ no flat structure
• each document is treated as a single entity
RavenDB suggested approach is to follow the
aggregate pattern from the DDD book
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9. ENTITY
 Some objects are not defined primarily by
their attributes
 They represent a thread of identity that runs
through time and often across distinct
representations
 Mistaken identity can lead to data corruption
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10. VALUE OBJECT
 When you care only about the attributes of an
element of the model, classify it as a value object
 Make it express the meaning of the attributes it
conveys and give it related functionality
 Treat the value object as immutable
 Don't give it any identity and avoid the design
complexities necessary to maintain entities
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11. AGGREGATE
 Invariants are consistency rules that must be
maintained whenever data changes
 They’ll involve relationships within an aggregate
(relations & foreign keys: order / orderlines)
 Invariants applied within an aggregate will be
enforced with the completion of each transaction
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12.  Cluster entities and value objects into aggregates
and define boundaries around each
 Choose one entity to be the root of each
aggregate and control all access to the objects
inside the boundary through the root
 Allow external objects to hold references to the
root only
 Transient references to internal members can be
passed out for use within a single operation only
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13.  Because the root controls access, it cannot
be blindsided by changes to the internals
 This arrangement makes it practical to
enforce all invariants for objects in the
aggregate and for the aggregate as a
whole in any state change
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14. Nested child document
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15. Document referenced by ID
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16. Denormalized reference
 we clone properties that we care about when
displaying or processing a containing document
 avoids many cross document lookups and results in
only the necessary data being transmitted over the
network
 it makes other scenarios more difficult: if we add
frequently changing data, keeping details in synch
could become very demanding on the server
 use only for rarely changing data or for data that
can be dereferenced by out-of-sync data
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17. 15/12/2012 Document databases in practice - Overview 17

18. Order contains
denormalized data
from Customer
and Product
Full data are
saved elsewhere
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20. Querying
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21.  DocumentStore
• used to connect to a RavenDB data store
• thread-safe
• one instance per database per application
 Session
• used to perform operations on the database
• not thread-safe
• implements the Unit of Work pattern
 in a single session, a single document (identified
by its key) always resolves to the same instance
 change tracking
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23.  Sequential GUID key
• when document key is not relevant (e.g. log entries)
• entity Id = sequential GUID (sorts well for indexing)
• Id property missing / not set ⇒ server generates a key
 Identity key
• entity Id = prefix + next available integer Id for it
• Id property set to a prefix = value ending with slash
• new DocumentStore ⇒ server sends a range of HiLo keys
 Assign a key yourself
• for documents which already have native id (e.g. users)
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25.  soft-limit = 128
no Take() replaced by Take(128)
 hard-limit = 1024
if x > 1024 Take(x) returns 1024 documents
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26.  RavenDB can skip over some results internally
⇒ TotalResults value invalidated
 For proper paging use SkippedResults:
Skip(currentPage * pageSize + SkippedResults)
 Assuming a page size of 10…
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29.  RavenDB supports Count and Distinct
 SelectMany, GroupBy and Join are not supported
 The let keyword is not supported
 For such operations an index is needed
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30. All queries use an index to return results
 Dynamic = created automatically by the server
 Static = created explicitly by the user
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31.  no matching static index to query ⇒ RavenDB
automatically creates a dynamic index on the
fly (on first user query)
 based on requests coming in, RavenDB can
decide to promote a temporary index to a
permanent one
15/12/2012 Document databases in practice – Querying 31

32.  permanent
 expose much more functionality
 low latency: on first run dynamic indexes
have performance issues
 map / reduce
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36. Advanced topics
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37.  an index is made of documents
 document
• atomic unit of indexing and searching
• flat ⇒ recursion and joins must be denormalized
• flexible schema
• made of fields
15/12/2012 Document databases in practice – Advanced topics 37

38.  field
• a name-value pair with associated info
• can be indexed if you're going to search on it
⇒ tokenization by analysis
• can be stored in order to preserve original
untokenized value within document
 example of physical index structure
{“__document_id”: “docs/1”, “tag”: “NoSQL”}
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39. 15/12/2012 Document databases in practice - Overview 39

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42. One to one
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43. One to many ⇒ SELECT N+1
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44. Value type
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45.  indexing: thread executed on creation or update
 server responds quickly BUT you may query stale
indexes (better stale than offline)
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47. documentStore.Conventions.DefaultQueryingConsistency
 ConsistencyOptions.QueryYourWrites
same behavior of
WaitForNonStaleResultsAsOfLastWrite
 ConsistencyOptions.MonotonicRead
you never go back in time and read older
data than what you have already seen
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51. Key-value databases in practice