Cassandra Data Model

the cassandra data model eben hewitt cassandra summit - san francisco 8.10.2010

the data model
no sql?
design patterns

things we know about cassandra
it’s eventually consistent
it’s column-oriented

these things are wrong.

consistency
eventual?
1

consistency
tune-able?
1

PACELC
Daniel Abadi
if Partition
Trade some Consistency for Availability
Else (normal circumstances)
Balance Consistency & Latency

cassandra is consistent when read replica count + write replica count > replication factor cassandra is consistent if you read & write at CL.QUORUM (once Q nodes are up) good place to start
R + W > N
r = # of nodes consulted during read op w = # of replicas consulted during write op n = replicas r + w + n = consistent

cassandra is row-oriented
each row is uniquely identifiable by key
rows group columns and super columns
2

column
atomic unit
name : value : timestamp
email : alison@foo.com : 12578123685

column family

User {
123 : { email: alison@foo.com,
img: },
456 : { email: eben@bar.com,
username: The Situation}
}
column family

super column super columns group columns under a common name

super column family

about super column families
sub-column names inside a SCF are not indexed
top level columns (SCF Name) are always indexed
often used for denormalizing data from standard CFs

PointOfInterest {
key: 85255 {
Phoenix Zoo { phone: 480-555-5555, desc: They have animals here. },
Spring Training { phone: 623-333-3333, desc: Fun for baseball fans. },
}, //end phx
key: 10019 {
Central Park { desc: Walk around. It's pretty.} ,
Empire State Building { phone: 212-777-7777, desc: Great view from
102nd floor. }
} //end nyc
}
s super column super column family flexible schema key column super column family

the data model
no sql?
design patterns

what about…
SELECT WHERE
ORDER BY
JOIN ON
GROUP
?

rdbms : domain-based model what answers do I have? cassandra : query-based model what questions do I have?

Questions
• Find hotels in a given area
• Find information about a given hotel, such as its name and location
• Find Points of Interest near a given hotel
• Find an available room in a given date range
• Find the rate and amenities about a room
• Book the selected room by entering guest information

SELECT WHERE
<<cf>>
USER
Key: UserID
Cols: username, email, birth date, city, state

To support a query like SELECT * FROM User WHERE city = ‘Austin’:
Create a new CF called UserCity:

<<cf>>
USERCITY
Key: city
Cols: IDs of the users in that city.
Also uses the Valueless Column pattern.

Use an aggregate row key
state:city: { user1, user2}
Get rows between TX: & TX;
for all Texas users
Get rows between TX:Austin & TX:Austin1
for all Austin users
SELECT WHERE pt 2

ORDER BY
Rows
are placed according to their Partitioner:
Random: MD5 of key
Order-Preserving: actual key
are sorted by key, regardless of partitioner
Columns are sorted according to CompareWith or CompareSubcolumnsWith

JOIN ON
“ join” means “create a relationship”
rdbms : pay at runtime
cassandra : pay at design time
representing the relationship
rdbms : opaque, in query
cassandra : transparent, first-class citizen

GROUP
SELECT COUNT(*) from Hotel GROUP BY ZipCode
 calculated column value

the data model
no sql?
design patterns

1.
materialized view

problem
You need to perform SELECT FROM WHERE queries.
solution
Create a new CF. Use the WHERE idea as the row key.
impacts
Must also write to the index every time you write to the primary CF. Or run as a job.
materialized view

2.
valueless column

problem
Indexes require repeating columns from other column families.
solution
Treat the name of the column as the value . Use a byte[0] as the column ‘value’.
impacts
Only works with <= 2B columns in 0.7
valueless column

3.
composite key

problem
Keys must support references and uniqueness.
solution
Fuse multiple values with a separator.
impacts
Can substitute for Super Column.
Use a Custom Comparator if necessary.
composite key

4.
semantic key

problem
Keys must be unique. You use OPP.
solution
Use a key that is meaningful in your application.
impacts
Harder to get right. Can proliferate Indexes. Range scans over keys less efficient.
semantic key

6.
client clock sync

problem
You need to keep clocks on different clients synchronized to support read repair.
solution
System.nanoTime() used in StorageProxy
NTP .
impacts
Consider geographic dispersement.
client clock sync

EXAMPLE

is cassandra a good fit?
very fast writes
need to be always writeable
lots of data
evolving schema

custom comparators
i want to compare with
float
lat/long

choose keys carefully
key-based routing to find data
queries are executed by key
keys need to be easily discoverable
you rely on keys for referential integrity

new use cases
geographic data
weather data
rfid
travel schedules
data services in soa
hotel reservations
CEP

see also
http://dfeatherston.com/cassandra-adf-uiuc-su10.pdf
http://github.com/ dietrichf/brireme

@ebenhewitt
cassandraguide.com

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Cassandra Data Model

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