Presentation of Apache Cassandra at Shift

1. Designing API
Rest vs gRPC vs GraphQL
‪ Which one should you pick ?
GraphQL Split, Croatia

2. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
About me
Cedrick Lunven
Developer Advocate
Creator Contributor

3. © DataStax, All Rights Reserved.Confidential © DataStax, All Rights Reserved.
Agenda 2
3
4 DECISION TREE
DEMONSTRATION AND CODE REVIEW
API DESIGN METHODOLOGY
1 APACHE CASSANDRA™ OVERVIEW

4. APACHE CASSANDRA™
Quick Overview

5. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
This is a DISTRIBUTED Database
Node
• Up to 1TB
• 3000 Tx/s/core

6. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
…which scale linearly

7. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
…anywhere
Cluster
Datacenter (Ring)

8. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Data is distributed
0
13
25
38
50
63
75
88 59 (data)
RF=2
59 (data)
RF=3
replicated

9. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Tuneable Consistency
RF=3
Client CL=ONECL=QUORUMCL=ALL

10. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Sweet spots
1. High Throughput (because we can keep up)
2. High Volume (because we scale linearly and still OLTP)
3. High Availability (replication, masterless)
4. Data distribution (read/write around the globe)

11. API DESIGN METHODOLOGY
From zero to hero

12. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Reference Application
http://killrvideo.github.io

13. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Api Design Methodology
1
killrvideo-dse
Drivers
DAO3
killrvideo-api-rest killrvideo-api-grpc killrvideo-api-graphql
2

14. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Designing Data Model
Entities & Relationships
Queries

15. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Conceptual Data Model

16. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Application Workflow
R1: Find comments related to target video using its identifier
• Get most recent first
• Implement Paging
R2: Find comments related to target user using its identifier
• Get most recent first
• Implement Paging
R3: Implement CRUD operations

17. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Mapping
Q2: Find comments posted for a user with a
known id (show most recent first)
comments_by_video
comments_by_user
Q1: Find comments for a video with a
known id (show most recent first)
Q3: CRUD Operations

18. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Logical Data Model
userid
creationdate
commentid
videoid
comment
comments_by_user
K
C
↑
videoid
creationdate
commentid
userid
comment
comments_by_video
C
↑
K
C
↑
↑C

19. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Physical Data Model
userid
commentid
videoid
comment
comments_by_user
TIMEUUID
K
TEXT
C
UUID
UUID
↑
videoid
commentid
userid
comment
comments_by_video
TIMEUUID
K
TEXT
C
UUID
UUID
↑

20. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Schema DDL
CREATE TABLE IF NOT EXISTS comments_by_user (
userid uuid,
commentid timeuuid,
videoid uuid,
comment text,
PRIMARY KEY ((userid), commentid)
) WITH CLUSTERING ORDER BY (commentid DESC);
CREATE TABLE IF NOT EXISTS comments_by_video (
videoid uuid,
commentid timeuuid,
userid uuid,
comment text,
PRIMARY KEY ((videoid), commentid)
) WITH CLUSTERING ORDER BY (commentid DESC);

21. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
How?
Conceptual Data
Model
(Entities, Relations)
Application Workflow
(Queries)
Database Family
(Technos +Table)

23. DECISION TREE
Because we are serious

24. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Analysis Criteria
📋 Conceptual
Data Model
Application
Workflow
(Queries)
Database Family
(Technos
+Table)
Caching
Syncvs AsyncReactive
SLA (Volume)
Data Integrity
Filters
Paging
Sort
Latencies Throughput
Versionning
Confidentiality
Atomicity
Cardinality
Developers
👤 Users/Consumers
Language
CodeFirst/
Vs SchemaFirst
Documentation
Test
Build
Packaging
Api Catalog
Internalvs
Public Techno
Profile
XP

25. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Analysis Matrix

26. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
Decision Tree

27. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
 Decoupling Client / Server (Schema on read)
 Api Lifecycle (Versioning)
 Tooling (API Management, Serverless)
 Verbose payloads (json, xml)
 No discoverability
 Not suitable for command-like (functions) API
 CRUD superstar
 Relevant for mutations (OLTP)
 Public and web APIs

28. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
 High Performances (http/2 – binary serialisation)
 Multiple stubs : Sync, Async, Streaming
 Multi languages - Interoperability
 Strongly coupled (schema with proto files)
 No discoverability
 Protobuf serialization format
 Distributed network of services (no waits)
 High throughput & streaming use cases
 Command-like (eg: slack)

29. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
 Discoverability, documentation
 Custom payloads
 Match standards (Json | Http)
 Single endpoint (versioning, monitoring, security)
 Complex implementation (tooling, still young)
 Nice for customers nasty for DB (N+1 select)
 Backend for frontend (JS)
 Service aggregation | composition (joins)
 When volume matters (mobile phones)
GraphQL

30. RESOURCES
Because COPY/PASTE is the most important skill for developers

31. @clunven | @shiftConf_co | SHIFT DEV CONF 2019
References
https://github.com/clun/shiftDevConf2019

32. THANK YOU