RDMS have their data modeling methodology and diagrams. What about Cassandra? Let's discover the key principles of Cassandra data modeling with the Chebotko methodology. Have a look at KDM, a Chebotko modeling tool. And finally, let's talk about the time dimension in Cassandra. This presentation was made for the Lyon Cassandra Users meetup (France).

1. Cassandra
Advanced
data modeling
Lyon Cassandra Users
Romain Hardouin
2016-05-31

2. $ who
Romain
$ pgrep -fl work
Cassandra architect
$ whatis teads
No.1 Video Advertising Marketplace

3. I. Introduction
II. Key principles
III. Chebotko methodology
IV. Time handling
Data modeling

4. I. Introduction

5. Theory

6. Theory
Chebotko diagrams
E&R

7. II. Key principles

8. Know your
data
DenormalizeKnow your
queries
Key Principles
Nest Data
Duplicate Data

9. Know your domain
Conceptual Data Model, E&R
●
Entities
●
Relationships
●
Attributes / Keys
●
Cardinalities
●
Constraints
Know your
data

10. Entities &
relationships
Know your
data

11. Query-driven model
Application Workflow
New needs?
●
New queries => new tables
●
Alter table possible?
Know your
data
Know your
queries

12. Goal: one partition per query
Anti-pattern:
●
Table scan
●
Client joins (a.k.a multi-table)
●
Secondary index
●
Allow filtering
Know your
data
Know your
queries

13. Nest Data
Clustering columns
Collection columns
UDT columns
Know your
data
Denormalize

14. Nest Data
Know your
data
Denormalize
CREATE TABLE actors_by_video (
video_id uuid,
actor_name text,
character_name text,
PRIMARY KEY ((video_id),
actor_name, character_name)
);

15. Duplicate data
Writes are cheap: « Joins on write »
Duplication occurs at different levels:
●
Table: Materialized views
●
Partition
●
Rows
Know your
data
Denormalize

16. III. Chebotko Methodology

17. From « A Big Data Modeling Methodology for Apache Cassandra »From « A Big Data Modeling Methodology for Apache Cassandra »
Application workflowApplication workflow
Query workflow Query list

18. From « A Big Data Modeling Methodology for Apache Cassandra »From « A Big Data Modeling Methodology for Apache Cassandra »
Chebotko DiagramChebotko Diagram

19. actors_by_video
video_id uuid K
actor_name text C↑
character_name text C↑
CREATE TABLE actors_by_video (
video_id uuid,
actor_name text,
character_name text,
PRIMARY KEY ((video_id), actor_name, character_name)
);
Chebotko DiagramChebotko Diagram

20. MR 1
Entities & Relationships
MR 2
Equality
search attributes
MR 3
Inequality
search attribues
Chebotko mapping rules
MR 5
Key attributes,
uniqueness
MR 4
Ordering attributes
<>=
↑↓

21. From « A Big Data Modeling Methodology for Apache Cassandra »From « A Big Data Modeling Methodology for Apache Cassandra »
Chebotko mapping rulesChebotko mapping rules

22. Internet of Things
Demo
Kashlev Data Modeler

23. IV. Time handling
- Tombstones
- TTL
- UPSERTs

24. IV. Time handling
- Tombstones
- TTL
- UPSERTs

25. Eventually consistency
No instant deletes
Deletes are writes
SSTables are immutable files
Writes are spread across many files

27. Goal: avoid to read too many* tombstones
...
...
* see tombstone_warn_threshold & tombstone_failure_threshold

28. IV. Time handling
- Tombstones
- TTL
- UPSERTs

29. TTLsTTLs
Data must be designed to be TTL'ed
tombstones

30. Why?
What we add?

31. TIMEdimension

32. IV. Time handling
- Tombstones
- TTL
- UPSERTs

33. UPSERTsUPSERTs
Same INSERT over and over again?
UPSERTs hide this behavior
What if… one day you want to add time

35. Questions?

36. Resources
« A Big Data Modeling Methodology for Apache Cassandra »
- Artem Chebotko, Andrey Kashlev & Shiyong Lu
- www.cs.wayne.edu/andrey/papers/TR-BIGDATA-05-2015-CKL.pdf
KDM
- Andrey Kashlev
- kdm.dataview.org