Cassandra By Example: Data Modelling with CQL3

Cassandra By Example:
Data Modelling with CQL3

Eric Evans
eevans@opennms.com
@jericevans

CQL is...
● Query language for Apache Cassandra
● Almost SQL (almost)
● Alternative query interface First class citizen
● More performant!
● Available since Cassandra 0.8.0 (almost 2
years!)

Bad Old Days: Thrift RPC
// Your Column
Column col = new Column(ByteBuffer.wrap("name".getBytes()));
col.setValue(ByteBuffer.wrap("value".getBytes()));
col.setTimestamp(System.currentTimeMillis());

// Don't ask
ColumnOrSuperColumn cosc = new ColumnOrSuperColumn();
cosc.setColumn(col);

// Prepare to be amazed
Mutation mutation = new Mutation();
mutation.setColumnOrSuperColumn(cosc);

List<Mutation> mutations = new ArrayList<Mutation>();
mutations.add(mutation);

Map mutations_map = new HashMap<ByteBuffer, Map<String, List<Mutation>>>();
Map cf_map = new HashMap<String, List<Mutation>>();
cf_map.set("Standard1", mutations);
mutations_map.put(ByteBuffer.wrap("key".getBytes()), cf_map);

cassandra.batch_mutate(mutations_map, consistency_level);

Better, no?

INSERT INTO (id, name) VALUES ('key', 'value');

Partitioning

Z A

Q E

M I

Partitioning

Z A

Q Cat E

M I

Partitioning

A

Pets

Animal Type Size Youtub-able

E Cat mammal small true

...

I

Cassandra By Example: Data Modelling with CQL3

Twissandra
● Twitter-inspired sample application
● Originally by Eric Florenzano, June 2009
● Python (Django)
● DBAPI-2 driver for CQL
● Favors simplicity over correctness!
● https://github.com/eevans/twissandra
○ See: cass.py

users

-- User storage
CREATE TABLE users (
username text PRIMARY KEY,
password text
);

users

-- Adding users (signup)
INSERT INTO users (username, password)
VALUES ('meg', 's3kr3t')

users

-- Lookup password (login)
SELECT password FROM users
WHERE username = 'meg'

following

-- Users a user is following
CREATE TABLE following (
username text,
followed text,
PRIMARY KEY(username, followed)
);

following

-- Meg follows Stewie
INSERT INTO following (username, followed)
VALUES ('meg', 'stewie')

-- Get a list of who Meg follows
SELECT followed FROM following
WHERE username = 'meg'

users @meg is following
followed
----------
brian
chris
lois
peter
stewie
quagmire
...

followers

-- The users who follow username
CREATE TABLE followers (
username text,
following text,
PRIMARY KEY(username, following)
);

followers

-- Meg follows Stewie
INSERT INTO followers (username, followed)
VALUES ('stewie', 'meg')

-- Get a list of who follows Stewie
SELECT followers FROM following
WHERE username = 'stewie'

redux: following / followers

-- @meg follows @stewie
BEGIN BATCH
INSERT INTO following (username, followed)
VALUES ('meg', 'stewie')
INSERT INTO followers (username, followed)
VALUES ('stewie', 'meg')
APPLY BATCH

tweets

-- Tweet storage (think: permalink)
CREATE TABLE tweets (
tweetid uuid PRIMARY KEY,
username text,
body text
);

tweets
-- Store a tweet
INSERT INTO tweets (
tweetid,
username,
body
) VALUES (
60780342-90fe-11e2-8823-0026c650d722,
'stewie',
'victory is mine!'
)

Query tweets by ... ?
● author, time descending
● followed authors, time descending
● date starting / date ending

userline
-- Materialized view of the tweets
-- created by user.
CREATE TABLE userline (
username text,
tweetid timeuuid,
body text,
PRIMARY KEY(username, tweetid)
);

Wait, WTF is a timeuuid?
● Aka "Type 1 UUID" (http://goo.gl/SWuCb)
● 100 nano second units since Oct. 15, 1582
● Timestamp is first 60 bits (sorts temporally!)
● Used like timestamp, but:
○ more granular
○ globally unique

userline
-- Range of tweets for a user
SELECT
dateOf(tweetid), body
FROM
userline
WHERE
username = 'stewie' AND
tweetid > minTimeuuid('2013-03-01 12:10:09')
ORDER BY
tweetid DESC
LIMIT 40

@stewie's most recent tweets
dateOf(posted_at) | body
--------------------------+-------------------------------
2013-03-19 14:43:15-0500 | victory is mine!
2013-03-19 13:23:24-0500 | generate killer bandwidth
2013-03-19 13:23:24-0500 | grow B2B e-business
2013-03-19 13:23:24-0500 | innovate vertical e-services
2013-03-19 13:23:24-0500 | deploy e-business experiences
2013-03-19 13:23:24-0500 | grow intuitive infrastructures
...

timeline
tweets from those a user follows

timeline
-- Materialized view of tweets from
-- the users username follows.
CREATE TABLE timeline (
username text,
tweetid timeuuid,
posted_by text,
body text,
PRIMARY KEY(username, tweetid)
);

timeline
-- Range of tweets for a user
SELECT
dateOf(tweetid), posted_by, body
FROM
timeline
WHERE
username = 'stewie' AND
tweetid > '2013-03-01 12:10:09'
ORDER BY
tweetid DESC
LIMIT 40

redux: tweets
-- @stewie tweets
BEGIN BATCH
INSERT INTO tweets ...
INSERT INTO userline ...
INSERT INTO timeline ...
...
APPLY BATCH

In Conclusion:
● Think in terms of your queries, store that
● Don't fear duplication; Space is cheap to scale
● Go wide; Rows can have 2 billion columns!
● The only thing better than NoSQL, is MoSQL
● Python hater? Java ❤'r?
○ https://github.com/eevans/twissandra-j
● http://goo.gl/zPOD

Cassandra By Example: Data Modelling with CQL3

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