MySQL-Mixer-Livenation
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The document discusses various database backup methods and their advantages and disadvantages. It provides details on backup and restore times for different methods like mysqldump, mysqldump by table, online backups, and snapshots. It also discusses high availability options and using a slave for read-only queries. Additional sections cover database fabric sizing, pre-caching queries, new features in MySQL 5.7, and monitoring. Contact information is provided at the end for any questions.
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This session will focus on lessons learned along the way, as well as challenges related to supporting more than one database platforms. It should be interesting to anyone who is new to MySQL, anyone who is being asked to support more than one database platform, or anyone who wants to see how an outsider views the platform.
Optimizing Latency-sensitive queries for Presto at Facebook: A Collaboration ...
Optimizing Latency-sensitive queries for Presto at Facebook: A Collaboration ...Alluxio, Inc. Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Optimizing Latency-sensitive queries for Presto at Facebook: A Collaboration between Presto & Alluxio
Ke Wang, Software Engineer (Facebook)
Bin Fan, Founding Engineer, VP Of Open Source (Alluxio)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Percona XtraDB Cluster - Small Presentation
Percona XtraDB Cluster - Small PresentationJavier Tomas Zon This document summarizes a presentation about Percona XtraDB Cluster (PXC), a high availability solution for MySQL. It introduces PXC and how it uses synchronous replication and a Galera library to provide scalability and redundancy. A simple demonstration of PXC is provided. The presenter is identified as Javier Tomás Zon, a platform reliable engineer at Percona with over 12 years of system administration experience, including 8 years working with MySQL.
JSSUG: SQL Sever Performance Tuning
JSSUG: SQL Sever Performance TuningKenichiro Nakamura This document provides an overview of Microsoft SQL Server performance tuning. It discusses key concepts like bottlenecks, query optimization, indexing, statistics, and best practices. The presentation aims to help attendees understand performance from different perspectives and demystify common myths. It also highlights new performance features in SQL Server 2017.
An introduction to mysql Performance Optimization (2008)
An introduction to mysql Performance Optimization (2008)lmrei The very basics of mysql performance analysis, profiling and optimization. Commands, Storage engines, Indexes, Queries, table design,...
Barcamp PT 2008.
OSDC 2017 | Lessons from database failures by Colin Charles
OSDC 2017 | Lessons from database failures by Colin CharlesNETWAYS Lets learn from MySQL failures at scale, because we tie in the topic of High Availability, in where people are thinking about geographical redundancy, and even things like automatic failover. In the talk there will be case study material, e.g. where automatic failure caused a site to go offline, where a social network started of with not using fully automated failovers but evolved, etc. How is the MySQL world making things better, for example by allowing you to use semi-synchronous replication to run fully scalable services. The talk starts off with an even almost stupid example of how a business died due to incorrect MySQL backup procedures. It will go on to talk about security and encryption at rest as well. So a mix of problems from the field, big “fail whales”, and how you should avoid them by properly architecting solutions.
Investigate TempDB Like Sherlock Holmes
Investigate TempDB Like Sherlock HolmesRichard Douglas The document discusses TempDB, the temporary database in SQL Server. It begins by explaining what TempDB is used for, such as internal objects, version store, and query operators. It then describes the life cycle of a temporary object creation in TempDB and how it has changed in SQL Server 2016. The document concludes by providing ways to monitor and improve TempDB performance, such as using performance counters and baselining.
Jesse Yates: Hbase snapshots patch
Jesse Yates: Hbase snapshots patchDmitry Makarchuk HBase now includes a built-in snapshot feature that allows users to take point-in-time backups of tables with minimal impact on the running cluster. Snapshots can be taken in an offline, globally consistent, or timestamp consistent manner. The snapshots can then be exported to another cluster, used to clone a new table, or restore an existing table to a prior state captured by the snapshot. The snapshot functionality provides a simple, distributed, and high performance solution for backup and recovery of large HBase datasets.
HBase Snapshots
HBase SnapshotsJesse Yates HBase now includes a built-in snapshot feature that allows users to take point-in-time backups of tables with minimal impact on the running cluster. Snapshots can be taken in an offline, globally consistent, or timestamp consistent manner. The snapshots can then be exported to another cluster, used to clone a new table, or restore an existing table to a prior state captured by the snapshot. The snapshot functionality provides a simple, distributed, and high performance solution for backup and recovery of large HBase datasets.
Ruby and Distributed Storage Systems
Ruby and Distributed Storage SystemsSATOSHI TAGOMORI This document discusses using Ruby for distributed storage systems. It describes components like Bigdam, which is Treasure Data's new data ingestion pipeline. Bigdam uses microservices and a distributed key-value store called Bigdam-pool to buffer data. The document discusses designing and testing Bigdam using mocking, interfaces, and integration tests in Ruby. It also explores porting Bigdam-pool from Java to Ruby and investigating Ruby's suitability for tasks like asynchronous I/O, threading, and serialization/deserialization.
MySQL Optimization from a Developer's point of view
MySQL Optimization from a Developer's point of viewSachin Khosla Optimization from a developer's point of view. Optimization is not only the duty of a DBA but its should be done by all those who are involved in the ecosystem
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MySQL-Mixer-Livenation
- 1. • Backups • High Availability/Fabric • Performance • 5.7 Features • Misc • Q&A Topics
- 2. Backup Method Advantages Caveat Mysqldump • Native • Out of the box • No Cost • Table Locks • Takes Time • All OR Nothing Mysqldump by Table • Specific Tables • Table Locks • Takes Time MySQL Ent Backup • No Downtime • No Cost • Faster than above • All OR Nothing Snapshots • Fastest Bkup/Rest • No Cost • No Table Locks • DB in it’s own vol • DB Offline (Auxiliary DB) • All OR Nothing Snapshots(Flush Table with Read Lock) • Backup Main DB • No Lock No Backup • Floating Backup Time Backup Options
- 3. Backup Method Backup Time Restore Time Database Mysqldump 2 Hr 50 min 9 Hr 15 min Type : Heavy Reads, Less Transaction Size : Small Slave (Read only) Class : Dev,Test,Prod Mysqldump by table 2 Hr 40 min 8 Hr 30 min Same As Above Online Backup 50 min 1 Hr 30 min Type : Heavy Transaction Size : Small,Medium,Large Master, Slave (Read/Write) Class : Prod Snapshots Sec Sec (!scp) Type : Any Size : Any Auxiliary Class : Prod NetApp Snapshots (Flush Table with Read Lock) Sec Sec Main DB Backup Options
- 5. High Availability • Failover • Notify DBA • DBA Investigates • Coordinate Downtime • Stop DB and Apps • Manually apply Binary logs • Read/Write Enable • Failover • Fallback • Apply changes back to Master • Row count • Fallback • Slave Read Only
- 6. Fabric
- 7. Database Size 150G Query Cache 2G InnoDB Buffer Pool 160G Memory 256G CPU 24 Core Swap 16G Storage NetApp Filer Vertical Scale
- 8. Pre-Cache
- 9. Next • InnoDB Compression • SSD • Table Partition • 5.7.2 • ZFS Storage
- 10. 12C Monitoring
- 11. Geospatial