SlideShare une entreprise Scribd logo
1  sur  29
MariaDB Enterprise
Tools
Andrew Hutchings
Software Engineering Manager
MariaDB Corporation
1
About Me
2
● Andrew (LinuxJedi) Hutchings
● Previously Lead Engineer / Manager for
MariaDB ColumnStore
● Many years of experience in database, cloud
and web technologies
● Co-author of MySQL 5.1 Plugin Development
● Twitter: @LinuxJedi
● EMail: linuxjedi@mariadb.com
Intended Audience
● DBAs who use command line tools
● Or really anyone who uses command line tools
3
The Problem...
4
● MariaDB’s growing suite of products each has its own set of tools to use
● Some of the tools have different interfaces
● Several of the tools have not had many changes in years
● DBA tools that MariaDB do not have equivalents of yet also have different
interfaces
The Idea
● A unified utility that encompases the entire MariaDB stack
● Modular design so extra tools can be added
● Easy / inviting to use for beginners and power users
● Newer features that MariaDB clients should have had long ago
5
6
The Solution - Codename Narwhal
What is it?
7
● A unified command line framework for Linux, Windows and macOS
○ The “Swiss Army Knife” of MariaDB
● Designed from the ground up to be easy to use
○ Run from your laptop (or on-prem server) to connect to multiple servers and cloud
○ Wizard driven, help screens, extensive documentation
○ Many advanced features for power users
● High-performance non-blocking core
● Extendable using modular interface
○ Can also execute external tools as modules
● Developed from the ground-up by MariaDB Corporation
8
Target Users
9
● DBAs / RDBAs & Developers
● MariaDB field engineers (using MariaDB Tools on site)
● DevOps / SRE
● From beginner to expert
Project Status
10
Project Status
● Early technical preview stage
● Multi-window support
● Plugin architecture created
● SQL Prompt and ‘top’-like module created
● Builds and runs in macOS and Linux
● User and module developer documentation written
11
12
Menu bar
Current DB
name in
prompt
Precise
execution
time
Bold column
names (only for
terminal output)
Unicode table
layout
characters
Host / port,
shows
padlock for
SSL
User authenticated as Current character set (UTF-8
default) Current table layout type
Indicator for
terminal / file
output
Current
delimiter
Status bar
13
Current Features - Core
● Entirely event driven asynchronous core
● Handles multiple SQL connections simultaneously in a single thread
● Multi-window capable
● Multiple possible table layouts
● Unicode from the ground-up (but can fall-back to ASCII)
○ Powerline support too
● Mouse support (scrolling only for now)
● Connection URL support (mariadb://user@hostname/database)
● SSL certification verification by default
Current Features - Core - Table Layouts
● ASCII - Like the traditional client
● Unicode - A more fancy output
● CSV - For direct input into other tools
● Vertical - Like using “G” in the traditional client
● Markdown - For directly creating tables in documents
● JSON - Can be used for building REST requests
● Many more possible
14
Current Features - SQL Prompt
● Smarter query processing, no need for a delimiter for single line queries
● Easier to understand query history search
● Modular command parser
○ New commands are simple to add
15
Current Features - Module API
● Well documented API for modules
● Currently written in C
● Gives functionality for
○ Window manipulation
○ Async SQL queries
○ Command parsing
○ General utilities
16
Current Features - Top Module
● Similar to Linux / Unix ‘top’ command
● Shows live usage statistics for a MariaDB server
● Shows processlist
17
The Future
18
Planned Features - Core
● Help improvements
● UI improvements to aid users
● Full mouse support
● Windows support
● Connection details manager
19
Planned Features - SQL Watch Module
● A module to execute a single query repeatedly and watch for changes
○ New rows
○ Modified rows
● Can be useful to see state changes in status variables or live changes to parts
of tables
20
Planned Features - Shell Exec Wizard
● Provides a form to execute an external application
○ mariabackup as an example
● Uses a simple configuration file to map form details to executable options
● Output renders inside the UI
○ Interactive input may also be possible later
● Makes it extremely easy to add extra features just with configuration files
21
Planned Features - Command Modules
● Modules that a user can run with a single command
○ They execute something
○ Echo to screen if needed
○ Then return
● Can take zero or more parameters
● Executed by just typing in the command name in SQL Prompt with any
parameters
22
Planned Features - SQL Prompt
● Autocomplete suggestions
● Live syntax highlighting
● More commands
23
Planned Features - Backup
● A multi-threaded warm backup module
○ Think the regular dump tool but many times faster
○ Uses transaction snapshots
○ Possibly also use replication stream to get the data between start and end of
snapshot
● A hot backup (snapshot) module
○ Implementation details to be decided
24
Planned Features - SkySQL
● Simple user interface to create and manage SkySQL instances
● A new instance could automatically be stored in the connection list
25
More Features?
● MariaDB’s tools, ColumnStore tools, Xpand’s tools, MaxScale’s tools, etc...
● Database browser? Replication visualisations? Split window view?
● We are open to suggestions
● This is a modular core, we can do a lot with it
26
Demo Time
27
Summary
28
● We are building a simple unified DBA tool for the entire MariaDB stack
● Expect more about this tool in the coming months as we complete the first
release
Thank You!
29

Contenu connexe

Tendances

Faster, better, stronger: The new InnoDB
Faster, better, stronger: The new InnoDBFaster, better, stronger: The new InnoDB
Faster, better, stronger: The new InnoDBMariaDB plc
 
How we switched to columnar at SpendHQ
How we switched to columnar at SpendHQHow we switched to columnar at SpendHQ
How we switched to columnar at SpendHQMariaDB plc
 
ClustrixDB at Samsung Cloud
ClustrixDB at Samsung CloudClustrixDB at Samsung Cloud
ClustrixDB at Samsung CloudMariaDB plc
 
How Orwell built a geo-distributed Bank-as-a-Service with microservices
How Orwell built a geo-distributed Bank-as-a-Service with microservicesHow Orwell built a geo-distributed Bank-as-a-Service with microservices
How Orwell built a geo-distributed Bank-as-a-Service with microservicesMariaDB plc
 
CCV: migrating our payment processing system to MariaDB
CCV: migrating our payment processing system to MariaDBCCV: migrating our payment processing system to MariaDB
CCV: migrating our payment processing system to MariaDBMariaDB plc
 
ClustrixDB: how distributed databases scale out
ClustrixDB: how distributed databases scale outClustrixDB: how distributed databases scale out
ClustrixDB: how distributed databases scale outMariaDB plc
 
Getting started in the cloud for developers
Getting started in the cloud for developersGetting started in the cloud for developers
Getting started in the cloud for developersMariaDB plc
 
Global Data Replication with Galera for Ansell Guardian®
Global Data Replication with Galera for Ansell Guardian®Global Data Replication with Galera for Ansell Guardian®
Global Data Replication with Galera for Ansell Guardian®MariaDB plc
 
Deploying MariaDB databases with containers at Nokia Networks
Deploying MariaDB databases with containers at Nokia NetworksDeploying MariaDB databases with containers at Nokia Networks
Deploying MariaDB databases with containers at Nokia NetworksMariaDB plc
 
Auto Europe's ongoing journey with MariaDB and open source
Auto Europe's ongoing journey with MariaDB and open sourceAuto Europe's ongoing journey with MariaDB and open source
Auto Europe's ongoing journey with MariaDB and open sourceMariaDB plc
 
How to power microservices with MariaDB
How to power microservices with MariaDBHow to power microservices with MariaDB
How to power microservices with MariaDBMariaDB plc
 
Introducing workload analysis
Introducing workload analysisIntroducing workload analysis
Introducing workload analysisMariaDB plc
 
SkySQL MariaDB 云数据组件
SkySQL MariaDB 云数据组件SkySQL MariaDB 云数据组件
SkySQL MariaDB 云数据组件YUCHENG HU
 
How MariaDB is approaching DBaaS
How MariaDB is approaching DBaaSHow MariaDB is approaching DBaaS
How MariaDB is approaching DBaaSMariaDB plc
 
MariaDB ColumnStore
MariaDB ColumnStoreMariaDB ColumnStore
MariaDB ColumnStoreMariaDB plc
 
Webseminar: MariaDB Enterprise und MariaDB Enterprise Cluster
Webseminar: MariaDB Enterprise und MariaDB Enterprise ClusterWebseminar: MariaDB Enterprise und MariaDB Enterprise Cluster
Webseminar: MariaDB Enterprise und MariaDB Enterprise ClusterMariaDB Corporation
 
The role of databases in modern application development
The role of databases in modern application developmentThe role of databases in modern application development
The role of databases in modern application developmentMariaDB plc
 
M|18 Analyzing Data with the MariaDB AX Platform
M|18 Analyzing Data with the MariaDB AX PlatformM|18 Analyzing Data with the MariaDB AX Platform
M|18 Analyzing Data with the MariaDB AX PlatformMariaDB plc
 
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with Scylla
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with ScyllaScylla Summit 2016: Why Kenshoo is about to displace Cassandra with Scylla
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with ScyllaScyllaDB
 
Scylla Summit 2022: How ScyllaDB Powers This Next Tech Cycle
Scylla Summit 2022: How ScyllaDB Powers This Next Tech CycleScylla Summit 2022: How ScyllaDB Powers This Next Tech Cycle
Scylla Summit 2022: How ScyllaDB Powers This Next Tech CycleScyllaDB
 

Tendances (20)

Faster, better, stronger: The new InnoDB
Faster, better, stronger: The new InnoDBFaster, better, stronger: The new InnoDB
Faster, better, stronger: The new InnoDB
 
How we switched to columnar at SpendHQ
How we switched to columnar at SpendHQHow we switched to columnar at SpendHQ
How we switched to columnar at SpendHQ
 
ClustrixDB at Samsung Cloud
ClustrixDB at Samsung CloudClustrixDB at Samsung Cloud
ClustrixDB at Samsung Cloud
 
How Orwell built a geo-distributed Bank-as-a-Service with microservices
How Orwell built a geo-distributed Bank-as-a-Service with microservicesHow Orwell built a geo-distributed Bank-as-a-Service with microservices
How Orwell built a geo-distributed Bank-as-a-Service with microservices
 
CCV: migrating our payment processing system to MariaDB
CCV: migrating our payment processing system to MariaDBCCV: migrating our payment processing system to MariaDB
CCV: migrating our payment processing system to MariaDB
 
ClustrixDB: how distributed databases scale out
ClustrixDB: how distributed databases scale outClustrixDB: how distributed databases scale out
ClustrixDB: how distributed databases scale out
 
Getting started in the cloud for developers
Getting started in the cloud for developersGetting started in the cloud for developers
Getting started in the cloud for developers
 
Global Data Replication with Galera for Ansell Guardian®
Global Data Replication with Galera for Ansell Guardian®Global Data Replication with Galera for Ansell Guardian®
Global Data Replication with Galera for Ansell Guardian®
 
Deploying MariaDB databases with containers at Nokia Networks
Deploying MariaDB databases with containers at Nokia NetworksDeploying MariaDB databases with containers at Nokia Networks
Deploying MariaDB databases with containers at Nokia Networks
 
Auto Europe's ongoing journey with MariaDB and open source
Auto Europe's ongoing journey with MariaDB and open sourceAuto Europe's ongoing journey with MariaDB and open source
Auto Europe's ongoing journey with MariaDB and open source
 
How to power microservices with MariaDB
How to power microservices with MariaDBHow to power microservices with MariaDB
How to power microservices with MariaDB
 
Introducing workload analysis
Introducing workload analysisIntroducing workload analysis
Introducing workload analysis
 
SkySQL MariaDB 云数据组件
SkySQL MariaDB 云数据组件SkySQL MariaDB 云数据组件
SkySQL MariaDB 云数据组件
 
How MariaDB is approaching DBaaS
How MariaDB is approaching DBaaSHow MariaDB is approaching DBaaS
How MariaDB is approaching DBaaS
 
MariaDB ColumnStore
MariaDB ColumnStoreMariaDB ColumnStore
MariaDB ColumnStore
 
Webseminar: MariaDB Enterprise und MariaDB Enterprise Cluster
Webseminar: MariaDB Enterprise und MariaDB Enterprise ClusterWebseminar: MariaDB Enterprise und MariaDB Enterprise Cluster
Webseminar: MariaDB Enterprise und MariaDB Enterprise Cluster
 
The role of databases in modern application development
The role of databases in modern application developmentThe role of databases in modern application development
The role of databases in modern application development
 
M|18 Analyzing Data with the MariaDB AX Platform
M|18 Analyzing Data with the MariaDB AX PlatformM|18 Analyzing Data with the MariaDB AX Platform
M|18 Analyzing Data with the MariaDB AX Platform
 
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with Scylla
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with ScyllaScylla Summit 2016: Why Kenshoo is about to displace Cassandra with Scylla
Scylla Summit 2016: Why Kenshoo is about to displace Cassandra with Scylla
 
Scylla Summit 2022: How ScyllaDB Powers This Next Tech Cycle
Scylla Summit 2022: How ScyllaDB Powers This Next Tech CycleScylla Summit 2022: How ScyllaDB Powers This Next Tech Cycle
Scylla Summit 2022: How ScyllaDB Powers This Next Tech Cycle
 

Similaire à MariaDB Enterprise Tools introduction

DocDoku: Using web technologies in a desktop application. OW2con'15, November...
DocDoku: Using web technologies in a desktop application. OW2con'15, November...DocDoku: Using web technologies in a desktop application. OW2con'15, November...
DocDoku: Using web technologies in a desktop application. OW2con'15, November...OW2
 
DocDokuPLM presentation - OW2Con 2015 Community Award winner
DocDokuPLM presentation - OW2Con 2015 Community Award winnerDocDokuPLM presentation - OW2Con 2015 Community Award winner
DocDokuPLM presentation - OW2Con 2015 Community Award winnerDocDoku
 
BlackRay - The open Source Data Engine
BlackRay - The open Source Data EngineBlackRay - The open Source Data Engine
BlackRay - The open Source Data Enginefschupp
 
Drupal Architecture and functionality
Drupal Architecture and functionality Drupal Architecture and functionality
Drupal Architecture and functionality Ann Lam
 
What's New in OpenLDAP
What's New in OpenLDAPWhat's New in OpenLDAP
What's New in OpenLDAPLDAPCon
 
Blackray @ SAPO CodeBits 2009
Blackray @ SAPO CodeBits 2009Blackray @ SAPO CodeBits 2009
Blackray @ SAPO CodeBits 2009fschupp
 
Instant developer onboarding with self contained repositories
Instant developer onboarding with self contained repositoriesInstant developer onboarding with self contained repositories
Instant developer onboarding with self contained repositoriesYshay Yaacobi
 
SAP BO and Teradata best practices
SAP BO and Teradata best practicesSAP BO and Teradata best practices
SAP BO and Teradata best practicesDmitry Anoshin
 
Ready player 2 Multiplayer Red Teaming Against macOS
Ready player 2  Multiplayer Red Teaming Against macOSReady player 2  Multiplayer Red Teaming Against macOS
Ready player 2 Multiplayer Red Teaming Against macOSCody Thomas
 
Hong Kong Drupal User Group - 2014 March 8th
Hong Kong Drupal User Group - 2014 March 8thHong Kong Drupal User Group - 2014 March 8th
Hong Kong Drupal User Group - 2014 March 8thWong Hoi Sing Edison
 
Node.js Web Apps @ ebay scale
Node.js Web Apps @ ebay scaleNode.js Web Apps @ ebay scale
Node.js Web Apps @ ebay scaleDmytro Semenov
 
What’s new in MariaDB ColumnStore
What’s new in MariaDB ColumnStoreWhat’s new in MariaDB ColumnStore
What’s new in MariaDB ColumnStoreMariaDB plc
 
Devoxx : being productive with JHipster
Devoxx : being productive with JHipsterDevoxx : being productive with JHipster
Devoxx : being productive with JHipsterJulien Dubois
 
Container images for OpenShift
Container images for OpenShiftContainer images for OpenShift
Container images for OpenShiftFrederic Giloux
 

Similaire à MariaDB Enterprise Tools introduction (20)

DocDoku: Using web technologies in a desktop application. OW2con'15, November...
DocDoku: Using web technologies in a desktop application. OW2con'15, November...DocDoku: Using web technologies in a desktop application. OW2con'15, November...
DocDoku: Using web technologies in a desktop application. OW2con'15, November...
 
DocDokuPLM presentation - OW2Con 2015 Community Award winner
DocDokuPLM presentation - OW2Con 2015 Community Award winnerDocDokuPLM presentation - OW2Con 2015 Community Award winner
DocDokuPLM presentation - OW2Con 2015 Community Award winner
 
BlackRay - The open Source Data Engine
BlackRay - The open Source Data EngineBlackRay - The open Source Data Engine
BlackRay - The open Source Data Engine
 
Drupal Architecture and functionality
Drupal Architecture and functionality Drupal Architecture and functionality
Drupal Architecture and functionality
 
Embedded Linux - Building toolchain
Embedded Linux - Building toolchainEmbedded Linux - Building toolchain
Embedded Linux - Building toolchain
 
What's New in OpenLDAP
What's New in OpenLDAPWhat's New in OpenLDAP
What's New in OpenLDAP
 
PostgreSQL and MySQL
PostgreSQL and MySQLPostgreSQL and MySQL
PostgreSQL and MySQL
 
Blackray @ SAPO CodeBits 2009
Blackray @ SAPO CodeBits 2009Blackray @ SAPO CodeBits 2009
Blackray @ SAPO CodeBits 2009
 
OpenCms Days 2015 Workflow using Docker and Jenkins
OpenCms Days 2015 Workflow using Docker and JenkinsOpenCms Days 2015 Workflow using Docker and Jenkins
OpenCms Days 2015 Workflow using Docker and Jenkins
 
Instant developer onboarding with self contained repositories
Instant developer onboarding with self contained repositoriesInstant developer onboarding with self contained repositories
Instant developer onboarding with self contained repositories
 
SAP BO and Teradata best practices
SAP BO and Teradata best practicesSAP BO and Teradata best practices
SAP BO and Teradata best practices
 
YugabyteDB Developer Tools
YugabyteDB Developer ToolsYugabyteDB Developer Tools
YugabyteDB Developer Tools
 
Enterprise Griffon
Enterprise GriffonEnterprise Griffon
Enterprise Griffon
 
Ready player 2 Multiplayer Red Teaming Against macOS
Ready player 2  Multiplayer Red Teaming Against macOSReady player 2  Multiplayer Red Teaming Against macOS
Ready player 2 Multiplayer Red Teaming Against macOS
 
Hong Kong Drupal User Group - 2014 March 8th
Hong Kong Drupal User Group - 2014 March 8thHong Kong Drupal User Group - 2014 March 8th
Hong Kong Drupal User Group - 2014 March 8th
 
Node.js Web Apps @ ebay scale
Node.js Web Apps @ ebay scaleNode.js Web Apps @ ebay scale
Node.js Web Apps @ ebay scale
 
What’s new in MariaDB ColumnStore
What’s new in MariaDB ColumnStoreWhat’s new in MariaDB ColumnStore
What’s new in MariaDB ColumnStore
 
Next.js with drupal, the good parts
Next.js with drupal, the good partsNext.js with drupal, the good parts
Next.js with drupal, the good parts
 
Devoxx : being productive with JHipster
Devoxx : being productive with JHipsterDevoxx : being productive with JHipster
Devoxx : being productive with JHipster
 
Container images for OpenShift
Container images for OpenShiftContainer images for OpenShift
Container images for OpenShift
 

Plus de MariaDB plc

MariaDB Paris Workshop 2023 - MaxScale 23.02.x
MariaDB Paris Workshop 2023 - MaxScale 23.02.xMariaDB Paris Workshop 2023 - MaxScale 23.02.x
MariaDB Paris Workshop 2023 - MaxScale 23.02.xMariaDB plc
 
MariaDB Paris Workshop 2023 - Newpharma
MariaDB Paris Workshop 2023 - NewpharmaMariaDB Paris Workshop 2023 - Newpharma
MariaDB Paris Workshop 2023 - NewpharmaMariaDB plc
 
MariaDB Paris Workshop 2023 - Cloud
MariaDB Paris Workshop 2023 - CloudMariaDB Paris Workshop 2023 - Cloud
MariaDB Paris Workshop 2023 - CloudMariaDB plc
 
MariaDB Paris Workshop 2023 - MariaDB Enterprise
MariaDB Paris Workshop 2023 - MariaDB EnterpriseMariaDB Paris Workshop 2023 - MariaDB Enterprise
MariaDB Paris Workshop 2023 - MariaDB EnterpriseMariaDB plc
 
MariaDB Paris Workshop 2023 - Performance Optimization
MariaDB Paris Workshop 2023 - Performance OptimizationMariaDB Paris Workshop 2023 - Performance Optimization
MariaDB Paris Workshop 2023 - Performance OptimizationMariaDB plc
 
MariaDB Paris Workshop 2023 - MaxScale
MariaDB Paris Workshop 2023 - MaxScale MariaDB Paris Workshop 2023 - MaxScale
MariaDB Paris Workshop 2023 - MaxScale MariaDB plc
 
MariaDB Paris Workshop 2023 - novadys presentation
MariaDB Paris Workshop 2023 - novadys presentationMariaDB Paris Workshop 2023 - novadys presentation
MariaDB Paris Workshop 2023 - novadys presentationMariaDB plc
 
MariaDB Paris Workshop 2023 - DARVA presentation
MariaDB Paris Workshop 2023 - DARVA presentationMariaDB Paris Workshop 2023 - DARVA presentation
MariaDB Paris Workshop 2023 - DARVA presentationMariaDB plc
 
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server MariaDB plc
 
MariaDB SkySQL Autonome Skalierung, Observability, Cloud-Backup
MariaDB SkySQL Autonome Skalierung, Observability, Cloud-BackupMariaDB SkySQL Autonome Skalierung, Observability, Cloud-Backup
MariaDB SkySQL Autonome Skalierung, Observability, Cloud-BackupMariaDB plc
 
Einführung : MariaDB Tech und Business Update Hamburg 2023
Einführung : MariaDB Tech und Business Update Hamburg 2023Einführung : MariaDB Tech und Business Update Hamburg 2023
Einführung : MariaDB Tech und Business Update Hamburg 2023MariaDB plc
 
Hochverfügbarkeitslösungen mit MariaDB
Hochverfügbarkeitslösungen mit MariaDBHochverfügbarkeitslösungen mit MariaDB
Hochverfügbarkeitslösungen mit MariaDBMariaDB plc
 
Die Neuheiten in MariaDB Enterprise Server
Die Neuheiten in MariaDB Enterprise ServerDie Neuheiten in MariaDB Enterprise Server
Die Neuheiten in MariaDB Enterprise ServerMariaDB plc
 
What’s new in Galera 4
What’s new in Galera 4What’s new in Galera 4
What’s new in Galera 4MariaDB plc
 
Beyond the basics: advanced SQL with MariaDB
Beyond the basics: advanced SQL with MariaDBBeyond the basics: advanced SQL with MariaDB
Beyond the basics: advanced SQL with MariaDBMariaDB plc
 
Inside CynosDB: MariaDB optimized for the cloud at Tencent
Inside CynosDB: MariaDB optimized for the cloud at TencentInside CynosDB: MariaDB optimized for the cloud at Tencent
Inside CynosDB: MariaDB optimized for the cloud at TencentMariaDB plc
 
Migrating from InnoDB and HBase to MyRocks at Facebook
Migrating from InnoDB and HBase to MyRocks at FacebookMigrating from InnoDB and HBase to MyRocks at Facebook
Migrating from InnoDB and HBase to MyRocks at FacebookMariaDB plc
 
How THINQ runs both transactions and analytics at scale
How THINQ runs both transactions and analytics at scaleHow THINQ runs both transactions and analytics at scale
How THINQ runs both transactions and analytics at scaleMariaDB plc
 
Configuring workload-based storage and topologies
Configuring workload-based storage and topologiesConfiguring workload-based storage and topologies
Configuring workload-based storage and topologiesMariaDB plc
 

Plus de MariaDB plc (19)

MariaDB Paris Workshop 2023 - MaxScale 23.02.x
MariaDB Paris Workshop 2023 - MaxScale 23.02.xMariaDB Paris Workshop 2023 - MaxScale 23.02.x
MariaDB Paris Workshop 2023 - MaxScale 23.02.x
 
MariaDB Paris Workshop 2023 - Newpharma
MariaDB Paris Workshop 2023 - NewpharmaMariaDB Paris Workshop 2023 - Newpharma
MariaDB Paris Workshop 2023 - Newpharma
 
MariaDB Paris Workshop 2023 - Cloud
MariaDB Paris Workshop 2023 - CloudMariaDB Paris Workshop 2023 - Cloud
MariaDB Paris Workshop 2023 - Cloud
 
MariaDB Paris Workshop 2023 - MariaDB Enterprise
MariaDB Paris Workshop 2023 - MariaDB EnterpriseMariaDB Paris Workshop 2023 - MariaDB Enterprise
MariaDB Paris Workshop 2023 - MariaDB Enterprise
 
MariaDB Paris Workshop 2023 - Performance Optimization
MariaDB Paris Workshop 2023 - Performance OptimizationMariaDB Paris Workshop 2023 - Performance Optimization
MariaDB Paris Workshop 2023 - Performance Optimization
 
MariaDB Paris Workshop 2023 - MaxScale
MariaDB Paris Workshop 2023 - MaxScale MariaDB Paris Workshop 2023 - MaxScale
MariaDB Paris Workshop 2023 - MaxScale
 
MariaDB Paris Workshop 2023 - novadys presentation
MariaDB Paris Workshop 2023 - novadys presentationMariaDB Paris Workshop 2023 - novadys presentation
MariaDB Paris Workshop 2023 - novadys presentation
 
MariaDB Paris Workshop 2023 - DARVA presentation
MariaDB Paris Workshop 2023 - DARVA presentationMariaDB Paris Workshop 2023 - DARVA presentation
MariaDB Paris Workshop 2023 - DARVA presentation
 
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server
MariaDB Tech und Business Update Hamburg 2023 - MariaDB Enterprise Server
 
MariaDB SkySQL Autonome Skalierung, Observability, Cloud-Backup
MariaDB SkySQL Autonome Skalierung, Observability, Cloud-BackupMariaDB SkySQL Autonome Skalierung, Observability, Cloud-Backup
MariaDB SkySQL Autonome Skalierung, Observability, Cloud-Backup
 
Einführung : MariaDB Tech und Business Update Hamburg 2023
Einführung : MariaDB Tech und Business Update Hamburg 2023Einführung : MariaDB Tech und Business Update Hamburg 2023
Einführung : MariaDB Tech und Business Update Hamburg 2023
 
Hochverfügbarkeitslösungen mit MariaDB
Hochverfügbarkeitslösungen mit MariaDBHochverfügbarkeitslösungen mit MariaDB
Hochverfügbarkeitslösungen mit MariaDB
 
Die Neuheiten in MariaDB Enterprise Server
Die Neuheiten in MariaDB Enterprise ServerDie Neuheiten in MariaDB Enterprise Server
Die Neuheiten in MariaDB Enterprise Server
 
What’s new in Galera 4
What’s new in Galera 4What’s new in Galera 4
What’s new in Galera 4
 
Beyond the basics: advanced SQL with MariaDB
Beyond the basics: advanced SQL with MariaDBBeyond the basics: advanced SQL with MariaDB
Beyond the basics: advanced SQL with MariaDB
 
Inside CynosDB: MariaDB optimized for the cloud at Tencent
Inside CynosDB: MariaDB optimized for the cloud at TencentInside CynosDB: MariaDB optimized for the cloud at Tencent
Inside CynosDB: MariaDB optimized for the cloud at Tencent
 
Migrating from InnoDB and HBase to MyRocks at Facebook
Migrating from InnoDB and HBase to MyRocks at FacebookMigrating from InnoDB and HBase to MyRocks at Facebook
Migrating from InnoDB and HBase to MyRocks at Facebook
 
How THINQ runs both transactions and analytics at scale
How THINQ runs both transactions and analytics at scaleHow THINQ runs both transactions and analytics at scale
How THINQ runs both transactions and analytics at scale
 
Configuring workload-based storage and topologies
Configuring workload-based storage and topologiesConfiguring workload-based storage and topologies
Configuring workload-based storage and topologies
 

Dernier

Biometric Authentication: The Evolution, Applications, Benefits and Challenge...
Biometric Authentication: The Evolution, Applications, Benefits and Challenge...Biometric Authentication: The Evolution, Applications, Benefits and Challenge...
Biometric Authentication: The Evolution, Applications, Benefits and Challenge...GQ Research
 
Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Colleen Farrelly
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our WorldEduminds Learning
 
GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]📊 Markus Baersch
 
20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdf20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdfHuman37
 
ASML's Taxonomy Adventure by Daniel Canter
ASML's Taxonomy Adventure by Daniel CanterASML's Taxonomy Adventure by Daniel Canter
ASML's Taxonomy Adventure by Daniel Cantervoginip
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPTBoston Institute of Analytics
 
9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service
9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service
9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort servicejennyeacort
 
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝DelhiRS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhijennyeacort
 
Machine learning classification ppt.ppt
Machine learning classification  ppt.pptMachine learning classification  ppt.ppt
Machine learning classification ppt.pptamreenkhanum0307
 
Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Seán Kennedy
 
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfPredicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfBoston Institute of Analytics
 
RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.natarajan8993
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsVICTOR MAESTRE RAMIREZ
 
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一fhwihughh
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...Boston Institute of Analytics
 
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
From idea to production in a day – Leveraging Azure ML and Streamlit to build...From idea to production in a day – Leveraging Azure ML and Streamlit to build...
From idea to production in a day – Leveraging Azure ML and Streamlit to build...Florian Roscheck
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanMYRABACSAFRA2
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfchwongval
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectBoston Institute of Analytics
 

Dernier (20)

Biometric Authentication: The Evolution, Applications, Benefits and Challenge...
Biometric Authentication: The Evolution, Applications, Benefits and Challenge...Biometric Authentication: The Evolution, Applications, Benefits and Challenge...
Biometric Authentication: The Evolution, Applications, Benefits and Challenge...
 
Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024Generative AI for Social Good at Open Data Science East 2024
Generative AI for Social Good at Open Data Science East 2024
 
Learn How Data Science Changes Our World
Learn How Data Science Changes Our WorldLearn How Data Science Changes Our World
Learn How Data Science Changes Our World
 
GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]GA4 Without Cookies [Measure Camp AMS]
GA4 Without Cookies [Measure Camp AMS]
 
20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdf20240419 - Measurecamp Amsterdam - SAM.pdf
20240419 - Measurecamp Amsterdam - SAM.pdf
 
ASML's Taxonomy Adventure by Daniel Canter
ASML's Taxonomy Adventure by Daniel CanterASML's Taxonomy Adventure by Daniel Canter
ASML's Taxonomy Adventure by Daniel Canter
 
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default  Presentation : Data Analysis Project PPTPredictive Analysis for Loan Default  Presentation : Data Analysis Project PPT
Predictive Analysis for Loan Default Presentation : Data Analysis Project PPT
 
9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service
9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service
9711147426✨Call In girls Gurgaon Sector 31. SCO 25 escort service
 
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝DelhiRS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
RS 9000 Call In girls Dwarka Mor (DELHI)⇛9711147426🔝Delhi
 
Machine learning classification ppt.ppt
Machine learning classification  ppt.pptMachine learning classification  ppt.ppt
Machine learning classification ppt.ppt
 
Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...Student Profile Sample report on improving academic performance by uniting gr...
Student Profile Sample report on improving academic performance by uniting gr...
 
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdfPredicting Salary Using Data Science: A Comprehensive Analysis.pdf
Predicting Salary Using Data Science: A Comprehensive Analysis.pdf
 
RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.RABBIT: A CLI tool for identifying bots based on their GitHub events.
RABBIT: A CLI tool for identifying bots based on their GitHub events.
 
Advanced Machine Learning for Business Professionals
Advanced Machine Learning for Business ProfessionalsAdvanced Machine Learning for Business Professionals
Advanced Machine Learning for Business Professionals
 
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
办理学位证纽约大学毕业证(NYU毕业证书)原版一比一
 
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
NLP Data Science Project Presentation:Predicting Heart Disease with NLP Data ...
 
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
From idea to production in a day – Leveraging Azure ML and Streamlit to build...From idea to production in a day – Leveraging Azure ML and Streamlit to build...
From idea to production in a day – Leveraging Azure ML and Streamlit to build...
 
Identifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population MeanIdentifying Appropriate Test Statistics Involving Population Mean
Identifying Appropriate Test Statistics Involving Population Mean
 
Multiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdfMultiple time frame trading analysis -brianshannon.pdf
Multiple time frame trading analysis -brianshannon.pdf
 
Heart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis ProjectHeart Disease Classification Report: A Data Analysis Project
Heart Disease Classification Report: A Data Analysis Project
 

MariaDB Enterprise Tools introduction

  • 1. MariaDB Enterprise Tools Andrew Hutchings Software Engineering Manager MariaDB Corporation 1
  • 2. About Me 2 ● Andrew (LinuxJedi) Hutchings ● Previously Lead Engineer / Manager for MariaDB ColumnStore ● Many years of experience in database, cloud and web technologies ● Co-author of MySQL 5.1 Plugin Development ● Twitter: @LinuxJedi ● EMail: linuxjedi@mariadb.com
  • 3. Intended Audience ● DBAs who use command line tools ● Or really anyone who uses command line tools 3
  • 4. The Problem... 4 ● MariaDB’s growing suite of products each has its own set of tools to use ● Some of the tools have different interfaces ● Several of the tools have not had many changes in years ● DBA tools that MariaDB do not have equivalents of yet also have different interfaces
  • 5. The Idea ● A unified utility that encompases the entire MariaDB stack ● Modular design so extra tools can be added ● Easy / inviting to use for beginners and power users ● Newer features that MariaDB clients should have had long ago 5
  • 6. 6 The Solution - Codename Narwhal
  • 7. What is it? 7 ● A unified command line framework for Linux, Windows and macOS ○ The “Swiss Army Knife” of MariaDB ● Designed from the ground up to be easy to use ○ Run from your laptop (or on-prem server) to connect to multiple servers and cloud ○ Wizard driven, help screens, extensive documentation ○ Many advanced features for power users ● High-performance non-blocking core ● Extendable using modular interface ○ Can also execute external tools as modules ● Developed from the ground-up by MariaDB Corporation
  • 8. 8
  • 9. Target Users 9 ● DBAs / RDBAs & Developers ● MariaDB field engineers (using MariaDB Tools on site) ● DevOps / SRE ● From beginner to expert
  • 11. Project Status ● Early technical preview stage ● Multi-window support ● Plugin architecture created ● SQL Prompt and ‘top’-like module created ● Builds and runs in macOS and Linux ● User and module developer documentation written 11
  • 12. 12 Menu bar Current DB name in prompt Precise execution time Bold column names (only for terminal output) Unicode table layout characters Host / port, shows padlock for SSL User authenticated as Current character set (UTF-8 default) Current table layout type Indicator for terminal / file output Current delimiter Status bar
  • 13. 13 Current Features - Core ● Entirely event driven asynchronous core ● Handles multiple SQL connections simultaneously in a single thread ● Multi-window capable ● Multiple possible table layouts ● Unicode from the ground-up (but can fall-back to ASCII) ○ Powerline support too ● Mouse support (scrolling only for now) ● Connection URL support (mariadb://user@hostname/database) ● SSL certification verification by default
  • 14. Current Features - Core - Table Layouts ● ASCII - Like the traditional client ● Unicode - A more fancy output ● CSV - For direct input into other tools ● Vertical - Like using “G” in the traditional client ● Markdown - For directly creating tables in documents ● JSON - Can be used for building REST requests ● Many more possible 14
  • 15. Current Features - SQL Prompt ● Smarter query processing, no need for a delimiter for single line queries ● Easier to understand query history search ● Modular command parser ○ New commands are simple to add 15
  • 16. Current Features - Module API ● Well documented API for modules ● Currently written in C ● Gives functionality for ○ Window manipulation ○ Async SQL queries ○ Command parsing ○ General utilities 16
  • 17. Current Features - Top Module ● Similar to Linux / Unix ‘top’ command ● Shows live usage statistics for a MariaDB server ● Shows processlist 17
  • 19. Planned Features - Core ● Help improvements ● UI improvements to aid users ● Full mouse support ● Windows support ● Connection details manager 19
  • 20. Planned Features - SQL Watch Module ● A module to execute a single query repeatedly and watch for changes ○ New rows ○ Modified rows ● Can be useful to see state changes in status variables or live changes to parts of tables 20
  • 21. Planned Features - Shell Exec Wizard ● Provides a form to execute an external application ○ mariabackup as an example ● Uses a simple configuration file to map form details to executable options ● Output renders inside the UI ○ Interactive input may also be possible later ● Makes it extremely easy to add extra features just with configuration files 21
  • 22. Planned Features - Command Modules ● Modules that a user can run with a single command ○ They execute something ○ Echo to screen if needed ○ Then return ● Can take zero or more parameters ● Executed by just typing in the command name in SQL Prompt with any parameters 22
  • 23. Planned Features - SQL Prompt ● Autocomplete suggestions ● Live syntax highlighting ● More commands 23
  • 24. Planned Features - Backup ● A multi-threaded warm backup module ○ Think the regular dump tool but many times faster ○ Uses transaction snapshots ○ Possibly also use replication stream to get the data between start and end of snapshot ● A hot backup (snapshot) module ○ Implementation details to be decided 24
  • 25. Planned Features - SkySQL ● Simple user interface to create and manage SkySQL instances ● A new instance could automatically be stored in the connection list 25
  • 26. More Features? ● MariaDB’s tools, ColumnStore tools, Xpand’s tools, MaxScale’s tools, etc... ● Database browser? Replication visualisations? Split window view? ● We are open to suggestions ● This is a modular core, we can do a lot with it 26
  • 28. Summary 28 ● We are building a simple unified DBA tool for the entire MariaDB stack ● Expect more about this tool in the coming months as we complete the first release