An introduction to some basic concepts and data modeling techniques in Cassandra.

1. Introduction to Cassandra
Nick Bailey
@nickmbailey
Monday, October 28, 13

2. Who am I?
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3. What’s DataStax?
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4. On to the good stuff!
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5. Why Cassandra?
Cluster Architecture
Node Architecture
5
Data Modeling
Wrap up
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6. Why Cassandra?
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7. Time for buzz
words!
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Big Data!
NoSQL!
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8. Big Data
• Gartner: “...high-volume, high-velocity and
high-variety...”
• 2 sides of ‘big data’
•
•
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Analytics
Real-time
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9. NoSQL
• A terrible label
• Covers a wide range of DBs
•
•
•
•
•
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Cassandra
Redis
MongoDB
HBase
...
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10. Started by Facebook
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11. Dynamo (Amazon)
+
Big Table (Google)
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13. Cassandra is great for...
• Massive, linear scaling
(e.g. CERN hadron collider, Barracuda Networks)
• Extremely heavy writes
(e.g. BlueMountain Capital – financial tick data)
• High availability
(e.g. eBay, Eventbrite, Netflix, SoundCloud,
HeathCare Anytime, Comcast, GoDaddy, Sony
Entertainment Network)
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14. ©2012 DataStax
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15. ©2012 DataStax
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16. http://techblog.netflix.com/2012/07/lessons-netflix-learned-from-aws-storm.html
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17. One size does not fit all
Polyglot persistence
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18. More Resources
• PlanetCassandra.org
• Blog
• 5 minute interviews
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19. Cluster Architecture
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20. Data Distribution
0
75
25
50
Hash_Function(Partition Key) >> Token
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21. Replication
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22. Failure Modes
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23. Consistency Level
• Multiple options
•
•
•
•
•
ONE
QUORUM
ALL
LOCAL_QUORUM
...
• Can be specified per request
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24. Quorum
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25. Quorum
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26. Consistency
Write
CL: ONE
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27. Consistency
Read
CL: One
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28. Failure Types
• UnavailableException
•
Didn’t even try
•
Possible success or failure
• TimedOutException
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29. Multi DC
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30. Gossip
• Manages cluster state
•
•
Nodes up/down
Nodes joining/leaving
• Decentralized
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31. Snitch
• Responsible for determining cluster topology
• Tracks node responsiveness
• Simple, PropertyFile, Ec2Snitch, etc...
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32. Node Architecture
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33. Write Path
Write
Memtable
Memory
Disk
commit log
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SSTable
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34. Read Path
Read
Memtable
Memory
Disk
SSTable
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SSTable
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35. Data Modeling
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36. CQL
Cassandra Query Language
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37. Terminology
• Keyspace
• Table (Column Family)
• Row
• Column
• Partition Key
• Clustering Key (Optional)
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38. For Example:
CREATE KEYSPACE packagetracker WITH REPLICATION = { 'class' :
'SimpleStrategy', 'replication_factor' : 1 };
CREATE KEYSPACE packagetracker WITH REPLICATION = { 'class' :
'NetworkTopologyStrategy', 'dc1' : 2, 'dc2' : 2};
CREATE TABLE events (
package_id text,
status_timestamp timestamp,
location text,
notes text,
PRIMARY KEY (package_id, status_timestamp)
);
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39. Constructs
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40. Basic Data Types
• blob
• int
• text
• long
• uuid
• etc
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41. More Data Modeling Constructs
• Collections
•
map, set, list
• Time to live (TTL)
• Counters
• Secondary Indexes
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42. Approaching Data Modeling
• Model your queries, not your data
•
Optimize your data model for reads
• Don’t be afraid to denormalize
• You will get it wrong, iterate
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43. An Example:
User Logins
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44. The Query
What are the last 10 locations nickmbailey logged in from?
SELECT time, location FROM logins WHERE user = ‘nickmbailey’
ORDER BY time DESC LIMIT 10;
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45. The Query
What are the last 10 locations nickmbailey logged in from?
SELECT time, location FROM logins WHERE user = ‘nickmbailey’
ORDER BY time DESC LIMIT 10;
Partition Key
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46. The Query
What are the last 10 locations nickmbailey logged in from?
SELECT time, location FROM logins WHERE user = ‘nickmbailey’
ORDER BY time DESC LIMIT 10;
Clustering Key
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Partition Key
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47. The Query
What are the last 10 locations nickmbailey logged in from?
SELECT time, location FROM logins WHERE user = ‘nickmbailey’
ORDER BY time DESC LIMIT 10;
Clustering Key
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Partition Key
Additional Columns
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48. The Query
What are the last 10 locations nickmbailey logged in from?
SELECT time, location FROM logins WHERE user = ‘nickmbailey’
ORDER BY time DESC LIMIT 10;
Clustering Key
Partition Key
Additional Columns
CREATE COLUMN FAMILY logins (
user text,
time timestamp,
location text,
PRIMARY KEY (user, time));
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49. The Query
What are the last 10 locations nickmbailey logged in from?
SELECT time, location FROM logins WHERE user = ‘nickmbailey’
ORDER BY time DESC LIMIT 10;
CREATE COLUMN FAMILY logins (
user text,
time timestamp,
location text,
PRIMARY KEY (user, time));
Partition key
Primary key
User
Time
Location
nickmbailey
2013-07-19 09:22:18
Austin, Texas
nickmbailey
2013-07-19 14:49:27
Blacksburg, Virginia
jsmith
2013-07-20 07:59:34
Atlanta, Georgia
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50. Time-series data
• By far, the most common data model
• Event logs
• Metrics
• Sensor Data
• Etc
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51. Another Query
When was the last time nickmbailey logged in from San
Francisco, California?
SELECT time FROM logins WHERE user = ‘nickmbailey’ and
location=‘San Francisco, California’;
User
Time
Location
nickmbailey
2013-07-19 09:22:18
Austin, Texas
nickmbailey
2013-07-19 14:49:27
Blacksburg, Virginia
nickmbailey
2013-07-19 14:49:27
Austin, Texas
nickmbailey
2013-05-19 14:49:27
Austin, Texas
nickmbailey
2013-04-19 14:49:27
San Francisco, California
...
...
...
jsmith
2013-07-20 07:59:34
Atlanta, Georgia
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52. Another Query
When was the last time nickmbailey logged in from Austin,
Texas?
SELECT time FROM logins_by_location WHERE user = ‘nickmbailey’
and location=‘San Francisco, California’;
CREATE COLUMN FAMILY logins_by_location (
user text,
time timestamp,
location text,
PRIMARY KEY (user, location));
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53. Another Query
When was the last time nickmbailey logged in from Austin,
Texas?
SELECT time FROM logins_by_location WHERE user = ‘nickmbailey’
and location=‘San Francisco, California’;
CREATE COLUMN FAMILY logins_by_location (
user text,
time timestamp,
location text,
PRIMARY KEY (user, location));
User
Location
Time
nickmbailey
Austin, Texas
2013-07-19 09:22:18
nickmbailey
Blacksburg, Virginia
2013-07-19 14:49:27
nickmbailey
San Francisco, California
2013-07-19 14:49:27
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54. Denormalize
• Create materialized views of the same data to
support different queries
• Storage space is cheap, Cassandra is fast
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55. Debugging your data model
cqlsh> tracing on;
Now tracing requests.
cqlsh:foo> INSERT INTO test (a, b) VALUES (1, 'example');
Tracing session: 4ad36250-1eb4-11e2-0000-fe8ebeead9f9
activity
| timestamp
| source
| source_elapsed
-------------------------------------+--------------+-----------+---------------execute_cql3_query | 00:02:37,015 | 127.0.0.1 |
0
Parsing statement | 00:02:37,015 | 127.0.0.1 |
81
Preparing statement | 00:02:37,015 | 127.0.0.1 |
273
Determining replicas for mutation | 00:02:37,015 | 127.0.0.1 |
540
Sending message to /127.0.0.2 | 00:02:37,015 | 127.0.0.1 |
779
Messsage received from /127.0.0.1
Applying mutation
Acquiring switchLock
Appending to commitlog
Adding to memtable
Enqueuing response to /127.0.0.1
Sending message to /127.0.0.1
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56. A note on Transactions
• In general, you want to construct your data
model around them
• The latest version of Cassandra has ‘Compare
and swap’
•
•
•
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An implementation of Paxos
...IF NOT EXISTS;
...IF column1 = ‘value’;
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57. Try it out
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58. CCM
• CCM - Cassandra Cluster Manager
•
https://github.com/pcmanus/ccm
•
•
•
ccm create test -v 2.0.1
ccm populate -n 3
ccm start
• Warning: not lightweight
• Example:
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59. Clients
• Cqlsh
•
Bundled with Cassandra
•
•
•
•
java: https://github.com/datastax/java-driver
python: https://github.com/datastax/python-driver
.net: https://github.com/datastax/csharp-driver
and more: http://www.datastax.com/download/
clientdrivers
• Drivers
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60. Get Help
• IRC: #cassandra on freenode
• Mailing Lists
• Stack Overflow
• DataStax Docs
•
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http://www.datastax.com/docs
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61. Questions?
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62. Monday, October 28, 13