This document provides an overview of the key capabilities and requirements of MySQL NDB Cluster 8.0. It discusses the following: - High availability with less than 30 seconds of downtime per year and predictable low latency transactions. - Transparent distribution and replication across nodes, along with write and read scalability. - Support for SQL, LDAP, file systems and other interfaces through plug-ins. Mixed OLTP and OLAP capabilities for real-time analytics. - Requirements to handle concurrent and sequential failures automatically with in-memory storage and asynchronous operations.

1. Copyright © 2020 Oracle and/or its affiliates.
MySQL NDB Cluster 8.0,
Requirements
MySQL Cluster Development
Mikael Ronström

2. • Unavailable less than 30 seconds per year (Class 6)
• Predictable latency (transaction with 20 operations within 10 milliseconds at
high load, mixed read/write)
• Transparent Distribution and Replication
• Write and Read Scalability
• Highest Availability even with 2 replicas
• Support SQL, LDAP, File System interface, …
• Mixed OLTP and OLAP for real-time data analysis
• Follow HW development on CPUs, Network, Disks and Memory
Requirements on NDB Cluster

3. • Handle many concurrent and sequential failures
• Automatic restart at failure
• Synchronise with live nodes without log
• Online schema changes
• Global Replication
• Online Add Node
Class 6 Availability

4. • Defaults to In-Memory storage
• Asynchronous File Operations
• Complex operations divided into multiple executions
• Each execution must be completed within 5-10 microseconds
• Memory lockable to avoid swapping
• Realtime mode supported
• CPU spinning modes supported
Predictable Latency

5. • Application need not be concerned with Node configuration
• Automatic reconfiguration at failures
• Automatic restart at failure
• => Very simple Scalability models for cluster setup
• NDB Virtual machine makes it easy to distribute functionality
Transparent Distribution and Replication

6. • Asynchronous Programming => Extremely efficient handling
of both Reads and Writes, 200M reads/sec achieved 2013
• In-memory Data => Cheaper writes, only REDO log required
• Asynchronous Programming => Easy to parallelise reads/
writes even within a single transaction
Write and Read Scalability

7. Support SQL, LDAP, File System
Separation of Query Server and Data Server makes it possible to
support SQL in parallel with LDAP (Telcos) and File System (HopsFS)
Disk Data support to handle large binary objects
SQL support through MySQL Server
LDAP support through OpenLDAP
File System interface through HopsFS
Memcached supported through NDB memcached
Any other interface supported through NDB API (C++), ClusterJ
(Java), NodeJS API (Javascript)

8. • Complex SQL Support through MySQL Server
• Can fully parallelise filters
• Can parallelise part of join processing
• Major advances in this area since MySQL Cluster 7.5
Mixed OLTP and OLAP

9. • NDB Cluster 8.0 supports 16 TB memory
• NDB Cluster 8.0 tested with 30 TB of Disk Data (YCSB) in
one Node Group and 5 TB of memory
• Can scale to make 25G Ethernet become bottleneck
• Can scale to make 8 modern NVMe drives a bottleneck
• Can make efficient use of new generation of NVMe drives
• Scales to 64 cores per Data Node/MySQL Server
HW dev on CPU, Network, Disks, Memory

10. Thank you!