MongoDB Datacenter Awareness (mongosf2012)
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The document discusses strategies for managing data across multiple online data centers, including using replication to provide high availability and distribute data across regions, implementing sharding with replica sets to partition and distribute data while taking advantage of replication, and new features in MongoDB like read preferences and tagged balancing to help optimize reads and distribution of data locally among data centers.
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A long time open-source programmer and entrepreneur, Gabriele has a degree in Statistics from the University of Florence. After having consistently contributed to the growth of 2ndQuadrant and its members through nurturing a lean and devops culture, he is now leading the Cloud Native initiative at EDB. Gabriele lives in Prato, a small but vibrant city located in the northern part of Tuscany, Italy - famous for having hosted the first European PostgreSQL conferences. His second home is Melbourne, Australia, where he studied at Monash University and worked in the ICT sector. He loves playing the Blues with his Fender Stratocaster, but his major passions are called Elisabeth and Charlotte!
KEY TAKE-AWAYS FROM THE TALK
- A methodology for benchmarking a PostgreSQL database in Kubernetes
- Open source set of tools for benchmarking a PostgreSQL database in Kubernetes
- Reasons why benchmarking both the storage and the database is important
https://github.com/EnterpriseDB/cnp-sandbox
https://github.com/EnterpriseDB/cnp-bench
When is Myrocks good? 2020 Webinar Series
In this talk, we'll walk through RocksDB technology and look into areas where MyRocks is a good fit by comparison to other engines such as InnoDB. We will go over internals, benchmarks, and tuning of MyRocks engine. We also aim to explore the benefits of using MyRocks within the MySQL ecosystem. Attendees will be able to conclude with the latest development of tools and integration within MySQL.
One of the benefits of using MySQL is the fact you can choose a storage engine fitting your requirements. Even though InnoDB is prevalent, it is helpful to know the available choices. Lately, LSM-tree based storage engines and engines using ideas of the technique, are seeing a rise in popularity and use. MyRocks brings LSM-tree benefits and tradeoffs to MySQL. In this talk, we'll walk through RocksDB technology and look into areas where MyRocks is a good fit by comparison to other engines such as InnoDB. We will go over internals, benchmarks, and tuning of MyRocks engine. We also aim to explore the benefits of using MyRocks within the MySQL ecosystem. Attendees will be able to conclude with the latest development of tools and integration within MySQL.
Data Infra Meetup | ByteDance's Native Parquet Reader
Data Infra Meetup
Jan. 25, 2024
Organized by Alluxio
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Shengxuan Liu (Software Engineer, @ByteDance)
Shengxuan Liu from ByteDance presents the new ByteDance’s native Parquet Reader. The talk covers the architecture and key features of the Reader, and how the new Reader is able to facilitate data processing efficiency.
Caching in
Modern computationally intensive tasks are rarely bottlenecked by the absolute performance of your processor cores. The real bottleneck in 2013 is getting data out of memory. CPU caches are designed to alleviate the difference in performance between CPU core clock speed and main memory clock speed, but developers rarely understand how this interaction works or how to measure or tune their application accordingly. This session aims to address this by:
• Describing how CPU caches work in the latest Intel hardware
• Showing what and how to measure in order to understand the caching behavior of software
• Giving examples of how this affects Java program performance and what can be done to address poor cache utilization
Mongodb meetup
This document discusses Chartbeat's use of MongoDB and Amazon EC2. Chartbeat stores real-time analytics data and historical data in MongoDB clusters running on EC2. They faced challenges with disappearing EC2 instances, poor I/O performance on EBS volumes, and unpredictable EC2 performance. To address these, Chartbeat uses replica sets for high availability, preallocates data to reduce fragmentation, and heavily monitors servers and MongoDB for issues. Automating processes and monitoring are important strategies for stable MongoDB on EC2.
Similar to MongoDB Datacenter Awareness (mongosf2012) (20)
DAX: A Widely Distributed Multi-tenant Storage Service for DBMS Hosting
DAX: A Widely Distributed Multi-tenant Storage Service for DBMS Hosting
PGConf APAC 2018 - High performance json postgre-sql vs. mongodb
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Abstract:
Replication in MongoDB requires deep integration with almost every part of the codebase, and has important hooks in various systems like storage, indexing, command processing and querying. Most of the replication components have seen a major overhaul recently in order to make further improvements. In this talk we will address what those pieces are, how they interact, and interesting choices made during their design. In this talk we get into the interaction of the replication protocols, commands really, writes and write concern enforcement, consensus (elections/ leader/follower/ majority) behaviors, and down into the depths of oplog generation and application on replicas. While a large part of the talk will be a technical overview of the big pieces we will dive into many important areas in order to ensure better understanding. The audience will be able to greatly affect which areas we focus on during the session, so come with ideas and a focus.
Advanced Replication Internals
Internals of replication in mongodb. These internals cover replication selection, the replication process, elections (and the rules), and oplog transformation.
This presentation was given at the MongoDB San Francisco conference.
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MongoDB Operational Best Practices (mongosf2012)
The document outlines operational best practices learned from analyzing real support cases. It describes 3 scenarios where performance issues were identified: 1) response time timeouts due to disk monitoring and instrumentation issues, 2) high CPU usage due to poorly indexed queries, and 3) general slowdowns due to large disk read-ahead size. Key learnings include monitoring logs and systems, performance testing before deployments, using database profilers and indexes, and planning rollouts and configurations.
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This document provides an overview of Morphia, a Java object mapping library for MongoDB. It discusses Morphia's advantages over using raw MongoDB drivers, including type safety and the ability to work with POJOs rather than generic maps. Key features covered include annotation-based mapping of entities to collections, lifecycle callbacks, queries, updates, and support for relationships and object graphs. The document aims to demonstrate how Morphia reduces boilerplate and provides a more object-oriented interface for working with MongoDB in Java applications.
MongoDB: Easy Java Persistence with Morphia
This document provides an overview of Morphia, a Java object mapping library for MongoDB. It discusses Morphia's advantages over using raw MongoDB drivers, including type safety and the ability to work with POJOs rather than generic maps. Key features covered include annotation-based mapping of entities to collections, lifecycle callbacks, queries, updates, and support for relationships and object graphs. The document aims to demonstrate how Morphia simplifies common data access patterns while retaining performance.
MongoDB: Mastering the shell
The document discusses using the MongoDB shell for debugging queries, testing, and administration. It notes some limitations of using JavaScript in the shell, like number and date handling. It then demonstrates various shell commands like insert, find, runCommand, and profiling. Finally it discusses additional shell features like loading scripts, exposing functions, and printing indexes.
MongoDB: Backup, Restore, and DR
This document discusses backup, restore, and disaster recovery options for MongoDB databases. It covers topics such as mongodump for backups, filesystem snapshots, replication for disaster recovery, and restoration procedures for both online and offline servers. Tips are provided for mongodump/restore operations and cleaning up snapshots.
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The document discusses MongoDB as a scalable, open-source NoSQL database that provides agility, scalability, and high performance. It supports document-oriented data with dynamic schemas, horizontal scaling through autosharding and replication for high availability. MongoDB provides a simple interface that is similar to but more flexible than SQL.
What's new in the MongoDB Java Driver (2.5)?
1) The MongoDB 2.5 Java driver includes improvements to URI handling, replica set support, map/reduce functionality, and error handling.
2) Notable updates include better replica set member detection, inline map/reduce results, merge and re-reduce options for map/reduce, and checking for max document size directly from the server.
3) There are some breaking changes as well, such as map/reduce now using a temporary collection by default and changes to GridFS metadata fields.
MongoDB Aug2010 SF Meetup
This document provides an overview of MongoDB and the Morphia object-document mapper for Java. It discusses MongoDB concepts like document storage, indexing, and concurrency model. It then covers Morphia's annotations for mapping Java objects to MongoDB documents, including entity configuration, relationships, and common data access patterns using queries and updates. Code examples are provided for mapping object graphs, querying, and updating documents.
MongoDB: tips, trick and hacks
This document provides tips and explanations for various MongoDB concepts and operations. It discusses basic expectations of MongoDB including indexing order, write and query threads, and memory mapped data files. It also summarizes indexes, shell functions, connections, getLastError commands, profiling, log configuration, limiting and sorting queries, bulk data loading, collection statistics, backups, and the mongostat monitoring tool.
Mastering the MongoDB Javascript Shell
The document discusses using the MongoDB shell for debugging, testing, and administration tasks. It notes some limitations of using JavaScript in the shell, such as number and date handling. It provides examples of common shell commands like insert, update, remove, loading scripts, running commands, and profiling. Useful shell functions are also demonstrated like printjson and forEach. The document concludes by showing how to print indexes, find the largest document, use cursors, define aliases, and work with DBRefs.
Java Development with MongoDB
This document summarizes options for using MongoDB with Java, including raw drivers, object mapping libraries like Morphia, and examples of common operations. It discusses using the MongoDB Java driver to directly encode data to BSON format, as well as higher-level libraries that allow working with Java objects like with Morphia annotations and queries. Examples demonstrate basic CRUD operations, embedding vs referencing relationships, and updating documents.
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
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MongoDB Datacenter Awareness (mongosf2012)
- 1. Data Center Awareness Scott Hernandez, 10gen
- 2. Agenda ● Infrastructure ● Players and moving pieces ● Goals and challenges ● MongoDB solutions ○ Now (Replication, Sharding, Tagging) ○ Future (+=, Shard affinity, more Tagging)
- 3. Multiple Online Data Centers ● Europe ● USA ○ App ○ App ○ Data ○ Data ● Asia ○ App
- 4. Infrastructure ● Geographically disparate clients ● Geo-DNS/Load Balancer (LB) ● Accelerators/Reverse-Proxies ● Server/Application
- 5. Players Introduction ● Users ● Data Centers ○ Application Servers ○ Databases ● Application Awareness ○ Configuration ○ Why?
- 6. Goals ● Reduce network ○ latency ○ Inter-dc traffic ● Localize resource use ○ Reduce failure cases ○ Increase availability ○ Isolate dependencies ● Provide multiple active sites ● Partition geo/regional data
- 7. Challenges ● Data concistency ○ User experience ○ Backup and operational needs ● Scaling ● Partitioning/Sharding
- 8. Multiple Online Data Centers ● Europe ● USA ○ App ○ App ○ Data ○ Data ● Asia ○ App
- 9. Non-default behaviors Default: Multi-DC needs: ● Primary read/write ● Read locally ● No stale reads ● Support some stale reads
- 10. Replication ● Replica Sets ○ Possible to read from non-primary replicas ○ Copy of data ○ Write Concern ■ Tagging ■ Verifiable writes ● Provides ○ Isolation (possible stale reads) ○ Availability ○ Distribution of read, possibly stale (WriteConcern)
- 11. Replica Writes Client Write Replica_Safe USA-NY Ack USA-CA Query EUROPE Client
- 12. Tagged Writes Uses ● Multiple Racks/DCs ● Backups ● Disaster Recovery
- 13. Sharding + Replication ● Range-based sharding (chunks) ○ Not tag aware ○ Random distribution (balancer) ● Shards made up of Replica Sets ○ All advantages ● Writes to (primary) shard per chunk ● Reads ○ From Primary by default ○ Optional non-primary reads
- 14. New Features ● ReadPreference ○ Primary (only) ○ Secondary (preferred) ○ PrimaryFirst? ○ SecondayOnly? ○ Any (closest) ● Replica Sets ○ ReadPreference ● Sharding ○ Tagged balancing ○ ReadPreference
- 15. Sharding - Reads ● Local when non-primary ● Tagged ○ Custom Tagging ○ By region/dc/rack?
- 16. Sharding - Balancing/Distribution ● Tag chunks/ranges ● Possible super-chunks (grouping)