ClustrixDB, now part of MariaDB, is a fully distributed and transactional RDBMS for applications with the highest scalability requirements. In this session Robbie Mihalyi, VP of Engineering for ClustrixDB, provides an introduction to ClustrixDB, followed by an in-depth technical overview of its architecture, with a focus on distributed storage, transactions and query processing – and its unique approach to index partitioning.

1. MARIADB
Clustrix Overview
Robbie Mihalyi Matthew White Peter Friedenbach
VP Engineering – Clustrix Director of Engineering Performance Architect

2. Scaling

3. Application
Scaling
 Scales Capacity
 Provides Fault Tolerance
 Dynamic and Flexible
DBMS Server
Load Balancer

4. Clustrix Scaling
 Scales Reads & Writes
 Provides Fault Tolerance
 Dynamic and Flexible
Clustrix
Load Balancer
MaxScale

5. SCALE-OUT RDBMS: CLUSTRIX
● Built from the ground-up - Shared nothing architecture
● All nodes are equal – any node can accept connections and can Read / Write
● Fine grained data distribution with data protection – built-in fault tolerance
● Distributed parallel query execution

6. SCALE-OUT RDBMS: CLUSTRIX
● To the application it looks like one Database System
● DDL and DML SQL statements are MySQL/MariaDB compatible
○ MySQL/MariaDB data types (including JSON support)
○ Referential integrity
○ Transactions – ACID compliant
○ Triggers and Stored Procedures
○ Complex Joins

7. SCALE-OUT RDBMS: CLUSTRIX
● Administration Features and Capabilities
○ On-line Schema changes
○ Replication
○ On-line Backup / Restore
● Multi-zone scale and availability

8. MARIADB
Clustrix Technology
Matthew White
Director of Engineering - Clustrix
MariaDB Corporation

9. Clustrix Technology
DATA DISTRIBUTION

10. Terminology - REPRESENTATION
26
BASE REPRESENTATION
Primary Key
ID col1 col2 col3
1 16 36 JANUARY
2 17 35 FEBRUARY
3 18 34 MARCH
4 19 33 APRIL
5 20 32 MAY
K1 REP
Index (col2)
col2 ID
32 5
33 4
34 3
35 2
36 1
K2 REP
Index col(3, 1)
col3 col1 ID
APRIL 19 4
FEBRUARY 17 2
JANUARY 16 1
MARCH 18 3
MAY 20 5

11. Terminology - SLICES
Slicing
● Each representation is split into slices
● The hash of keys mapped to slices
● Distribute representations independently
Independent Key Distribution
● Adapts to diverse access patterns
● Allows for broader range query evaluation
● Query plans scale with node count

12. Terminology - REPLICAS
Fault Tolerance
● Each slice has one or more copies
○ One node will never contain two replicas for the
same slice
● Replicas created on-line without blocking writes
● Default replicas is 2
● Can have replicas = number of nodes
○ Great for read-heavy tables
● Support for Availability Zones

13. ClustrixDB
S1 S2
S2
S3
S3
S4
S4
S5
S5
Dynamic Data Distribution
● Tables auto-split into slices
● Every slice has a replica on another node
○ Slices are auto distributed, auto-protected
S1
BillionsofRows
Database
Tables

14. ClustrixDB
S1
S2
S3
S3
S4
S4
S5
Adding Nodes – Flex Up
● Easy and simple Flex Up & Flex Down
○ Single minimal interruption of service
● Data is automatically rebalanced across the cluster
○ Tables are online for reads & writes
● All servers handle writes + reads
○ Workload is spread across more servers after Flex Up
ClustrixDB Overview 30
S1
ClustrixDB
S2
S5

15. ClustrixDB
S2
S5
S1
S2
S3
S3
S4
S4
S5
Loss of a Node – Automatic Fault Tolerance
● ClustrixDB detects the loss of a node
○ System automatically re-protects
○ Data is automatically redistributed
● Slices lost on the failed node are rapidly re-protected
○ Re-protection while tables are available for reads & writes
● Automated self-healing
○ After re-protect the cluster is fully protected and operational
ClustrixDB Overview 31
S1
ClustrixDB
S2
S5
S2
S5

16. Complexity Simplified
Q: How do you ensure data stays well distributed in a clustered environment?
• Initial Data Distributes the data into even slices across nodes
• Failed Nodes Re-protects slices to ensure proper replicas exist
• Data Growth Splits large slices into smaller slices
• Flex-Up/Flex-Down Moves slices to leverage new nodes and/or evacuate nodes
• Skewed Data Re-distributes the data to even out across nodes
• Hot Slice Balancing Finds hot slices and balances then across nodes
• Availability Zone Support Rebalancer will distribute replicas across zones
…while the DB stays open for reads & writesPatent 8,543,538
Patent 8,554,726
A: You let the REBALANCER handle it!

17. Clustrix Technology
QUERY PROCESSING

18. Query Processing Model
SQL-based
Applications
HW or SW Load
Balancer
● Load balancer spreads DB connections to all nodes
● A session is established on any node
● Session controls query execution
 Parse
 Plan
 Compile
UPDATE users
SET online = 1
WHERE id = 8797;
Session
VM VM
ID: 8797 |…| ONLINE:0
Fragment
VM

19. Query Processing Model
SQL-based
Applications
HW or SW Load
Balancer
● Load balancer spreads DB connections to all nodes
● A session is established on any node
● Session controls query execution
○ Parse SQL
○ Generate the execution plan
○ Compile into fragments
○ Start the execution of initial fragment
○ Send fragments
○ Coordinate transaction completion
GTM
UPDATE users
SET online = 1
WHERE id = 8797;
Session
VM VM
ID: 8797 |…| ONLINE:1 ID: 8797 |…| ONLINE:1
Commit Commit
Commit
VM

20. Parallel Query Processing
SQL-based
Applications
HW or SW Load
Balancer
VM VM
SELECT SUM(amount)
FROM donations;
 Parse
 Plan
 Compile
Session
VM
● Load balancer spreads DB connections to all nodes
● A session is established on any node
● Session controls query execution
○ Parse SQL
○ Generate the execution plan
○ Compile into fragments
○ Lookup record(s) location
○ Send fragments
○ Coordinate transaction completion
● Aggregate in parallel on all nodes
FragmentFragment

21. Parallel Query Processing
SQL-based
Applications
VM VM
Session
VM
● Load balancer spreads DB connections to all nodes
● A session is established on any node
● Session controls query execution
○ Parse SQL
○ Generate the execution plan
○ Compile into fragments
○ Lookup record(s) location
○ Send fragments
○ Coordinate transaction completion
● Aggregate in parallel on all nodes
AGGREGATE
LOCALLY
AGGREGATE
LOCALLY
AGGREGATE
LOCALLY
AGGREGATE
RESULTS
SELECT SUM(amount)
FROM donations;
HW or SW Load
Balancer

22. Clustrix Technology
ADMINISTRATION

23. Table
Online Schema Change
● Allows reads & writes during
ALTER TABLE operations
Table
QueueQueueQueue
MYTABLE __building_MYTABLE
Atomic Flip
Reads & Writes
ALTER TABLE mytable ADD (foo int);
 Queue is created to track changes
 Table is copied with new column
 Queues are applied to new copy until empty
 Atomic flip to new table

24. Table
Online Schema Change
● Allows reads & writes during
ALTER TABLE operations
Table
MYTABLE__retiring_MYTABLE
Atomic Flip
Reads & Writes
ALTER TABLE mytable ADD (foo int);

 Queue is created to track changes
 Table is copied with new column
 Queues are applied to new copy until empty
 Atomic flip to new table
 Original table is deleted

25. Backup, Replication & Disaster Recovery
Asynchronous multi-point Replication
ClustrixDB
Parallel Backup
Replicate to any cloud, any datacenter, anywhere

26. ClustrixGUI: Performance Monitoring

27. MARIADB
Clustrix Live Demo
Peter Friedenbach
Performance Architect
MariaDB Corporation

28. THANK YOU!