Ndb cluster 80_requirements
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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.
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From the DoK Day EU 2022 (https://youtu.be/Xi-h4XNd5tE)
The storage topology in vogue seems to cycle every few years. Internal storage is followed by centralized Storage Area Networks only to be superseded by one-size-fits-all Hyperconverged models - until scalability constraints led to distributed storage. Then comes NVMe, offering blistering speeds that all of these storage stacks struggle with. Kubernetes inspires Container Attached Storage aspiring to be the perfect model, so why is disaggregated storage now making an appearance?
This talk considers the motivations behind yet another storage topology and examines a modern, flexible architecture for delivering high-performance storage under Kubernetes.
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Nick Connolly is a pioneer of storage virtualisation and the Chief Scientist at DataCore, where his background in real-time computing and multiprocessing led to the creation of a world-class high-performance storage stack on Windows. He holds patents ranging from highly scalable algorithms through to data protection techniques. Recently he has been working with OpenEBS to bring the power and performance of NVMe to Kubernetes.
Disaggregated Container Attached Storage - Yet Another Topology with What Pur...
Disaggregated Container Attached Storage - Yet Another Topology with What Pur...DoKC The storage topology in vogue seems to cycle every few years. Internal storage is followed by centralized Storage Area Networks only to be superseded by one-size-fits-all Hyperconverged models - until scalability constraints led to distributed storage. Then comes NVMe, offering blistering speeds that all of these storage stacks struggle with. Kubernetes inspires Container Attached Storage aspiring to be the perfect model, so why is disaggregated storage now making an appearance?
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Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
Preprint: https://arxiv.org/abs/2501.10037
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Ndb cluster 80_requirements
- 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!