Robert Stupp, Solutions Architect at DataStax Discusses about Data Modeling with DataStax Enterprise, database for cloud applications.

1. Data Modeling Basics for the Cloud
Robert Stupp
Solutions Architect @ DataStax – Committer to Apache Cassandra

2. Data Modeling for the Cloud
DSE is the database
for the cloud
1.Always On
2.Instantaneously
Responsive
3.Numerous Endpoints
4.Geographically Distributed
5.Predictively Scalable
© 2016 DataStax, All Rights Reserved. 2
CC BY 2.0, by Blake Patterson on Flickr
100000 transactions
per second
200000 transactions
per second

3. Application
Replication Factor 3
Eventual Consistency
© DataStax, All Rights Reserved. 3
… is not hopefully consistent
Some data
Some dataSome data
Consistency Level:
ONE

4. Application
UP
Replication Factor 3
Quorum Consistency
© DataStax, All Rights Reserved. 4
Some data
Some dataSome data
Consistency Level:
QUORUM
DOWN

5. DSE / Cassandra NodeApplication
Write Path
© DataStax, All Rights Reserved. 5
Memtable
Commit
Log
Files
SSTable
Some data
Some data
SSTable
SSTable SSTable
SSTable SSTable
Some data
Some data
Some data
Some data
Some data

6. Compaction
© DataStax, All Rights Reserved. 6
SSTable SSTable SSTable SSTable
SSTable

7. Compaction Strategies
• Size Tiered
• Leveled
• Date Tiered
© DataStax, All Rights Reserved. 7

8. Data Organization in DSE / Cassandra
Partition
Device ID Timestamp Temperature Humidity
01-32483-17383 2016-04-19 14:00 22 70
01-32483-17383 2016-04-19 15:00 21.5 65
01-32483-17383 2016-04-19 16:00 23.0 70
Partition
Key
Clustering
Key
Columns
Primary Key
Device ID Timestamp
01-32483-17383 2016-04-19 14:00
01-32483-17383 2016-04-19 15:00
01-32483-17383 2016-04-19 16:00
Device ID
01-32483-17383
01-32483-17383
01-32483-17383

9. Data Modeling 101
1. Understand your data
Conceptual data modeling
2. Collect queries
Understand your application
3. Model according to queries
Logical data modeling
4. Apply optimizations
Physical data modeling
© DataStax, All Rights Reserved. 9

10. Query driven modeling
1. Collect your use cases
2. Extract queries
3. Model your tables
© DataStax, All Rights Reserved. 10

11. Queries, yes
SELECT
timestamp, temperature, humidity
FROM
sensor_data
WHERE
sensor_id = ’01-32483-17383’
© 2016 DataStax, All Rights Reserved. 11
Always include the
Partition Key

12. Some standard use-cases
• Customer registration
• Customer login
• Delivery addresses
© DataStax, All Rights Reserved. 12

13. Customer registration
1. Check if customer exists
query by username
© 2016 DataStax, All Rights Reserved. 13
CREATE TABLE customers (
username text PRIMARY KEY,
password_hash text,
first_name text,
last_name text,
email text
);
SELECT username FROM customers WHERE username = ?

14. Customer login by username
1. Check if user exists and password matches
query by username
© 2016 DataStax, All Rights Reserved. 14
CREATE TABLE customers (
username text PRIMARY KEY,
password_hash text,
first_name text,
last_name text,
email text
);
SELECT password_hash FROM customers WHERE username = ?

15. Customer login by email
1. Check if user exists and password matches
query by email
© 2016 DataStax, All Rights Reserved. 15
CREATE TABLE customers (
username text PRIMARY KEY,
password_hash text,
first_name text,
last_name text,
email text
);
SELECT password_hash FROM customers WHERE email = ?
InvalidRequest: code=2200 [Invalid query]
message="Cannot execute this query as it might
involve data filtering and
thus may have unpredictable performance.

16. Customer login by email
1. Check if user exists and password matches
query by email
© 2016 DataStax, All Rights Reserved. 16
CREATE TABLE customers_by_email (
email text PRIMARY KEY,
password_hash text,
first_name text,
last_name text,
username text
);
SELECT password_hash FROM customers_by_email WHERE email = ?
This works

17. Modeling delivery addresses
© 2016 DataStax, All Rights Reserved. 17
CREATE TABLE customer_addresses (
username text,
address_type text,
street text,
zip text,
city text,
PRIMARY KEY ( username, address_type )
);
SELECT street,zip,city FROM customer_addresses WHERE username = ?;
SELECT street,zip,city FROM customer_addresses
WHERE username = ? AND address_type = ?;

18. Modeling delivery addresses
1. Print delivery address label
query by user by user name
query delivery address by user and type
© 2016 DataStax, All Rights Reserved. 18
SELECT first_name, last_name FROM customers WHERE username = ?;
SELECT street,zip,city FROM customer_addresses
WHERE username = ? AND address_type = ?;
This works,
But it’s not great.

19. Modeling delivery addresses
© 2016 DataStax, All Rights Reserved. 19
CREATE TYPE delivery_address (
street text,
zip text,
city text);
Just 1 read
CREATE TABLE customers (
username text PRIMARY KEY,
password_hash text,
first_name text,
last_name text,
email text,
delivery_addrs map < text, frozen < delivery_address > >
);
SELECT first_name, last_name, delivery_addrs
FROM customers WHERE username = ?;

20. Customer registration – the problem
SELECT username FROM customers
WHERE username = ?
(no results)
© 2016 DataStax, All Rights Reserved. 20
SELECT username FROM customers
WHERE username = ?
(no results)
INSERT INTO customers
(username, first_name, last_name)
VALUES
(‘snazy’, ‘Robert’, ‘Stupp’)
(success) INSERT INTO customers
(username, first_name, last_name)
VALUES
(‘snazy’, ‘Not’, ‘Robert’)
(success)
This one wins
This one gets
overwritten

21. Customer registration – the solution
SELECT username FROM customers
WHERE username = ?
(no results)
© 2016 DataStax, All Rights Reserved. 21
SELECT username FROM customers
WHERE username = ?
(no results)
INSERT INTO customers …
IF NOT EXISTS
 [applied] = true
INSERT INTO customers …
IF NOT EXISTS
 [applied] = false
Sorry, dude
OK

22. Customer registration – the even better
solution
© 2016 DataStax, All Rights Reserved. 22
INSERT INTO customers …
IF NOT EXISTS
 [applied] = true
INSERT INTO customers …
IF NOT EXISTS
 [applied] = false
Sorry, dude
OK

23. Customer login by email – w/ DSE 5.0
1. Check if user exists and password matches
query by email
© 2016 DataStax, All Rights Reserved. 23
CREATE TABLE customers (
username text PRIMARY KEY,
password_hash text,
first_name text,
last_name text,
email text
);
CREATE MATERIALIZED VIEW customers_by_email AS
SELECT email, username, first_name, last_name, password_hash
FROM customers
WHERE email IS NOT NULL
PRIMARY KEY ( email, username );
SELECT password_hash FROM customers_by_email WHERE email = ?;

24. May the node
be with you!
Robert Stupp Solutions Architect @ DataStax
robert.stupp@datastax.com Committer to Apache Cassandra
@snazy