Cassandra as Memcache
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Cassandra can be used as an alternative to Memcache for caching data from a database in order to improve performance. Cassandra offers advantages over Memcache like persistence of data, horizontal scaling, and simpler management as a single database tier rather than separate Memcache and database servers. While Memcache is faster for in-memory operations, Cassandra can serve data both from memory using caching as well as from disk, and offers different configuration options for balancing performance, consistency and fault tolerance.
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Web20expo Scalable Web Arch
The document discusses scalable web architectures and common patterns for scaling web applications. It covers key topics like load balancing, caching, database replication, and data federation. The overall goal of application architecture is to scale traffic and data while maintaining high availability and performance. Horizontal scaling by adding more servers is preferable to vertical scaling of buying larger servers.
Web20expo Scalable Web Arch
The document discusses scalable web architectures and common patterns for scaling web applications. It covers key topics like load balancing, caching, database replication and sharding, and asynchronous queuing to distribute workloads across multiple servers. The goal of these patterns is to scale traffic, data size, and maintainability through horizontal expansion rather than just vertical upgrades.
Web20expo Scalable Web Arch
The document discusses scalable web architectures and common patterns for scaling web applications. It covers key topics like load balancing, caching, database replication and sharding, and asynchronous queuing to distribute workloads across multiple servers. The goal of these patterns is to scale traffic, data size, and maintainability through horizontal expansion rather than just vertical upgrades.
Sql server performance tuning and optimization
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SQL Server Concepts/Structure
Performance Measuring & Troubleshooting Tools
Locking
Performance Problem : CPU
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Performance Problem : I/O
Performance Problem : Blocking
Query Tuning
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Caching and tuning fun for high scalability
Caching has been a 'hot' topic for a few years. But caching takes more than merely taking data and putting it in a cache : the right caching techniques can improve performance and reduce load significantly. But we'll also look at some major pitfalls, showing that caching the wrong way can bring down your site. If you're looking for a clear explanation about various caching techniques and tools like Memcached, Nginx and Varnish, as well as ways to deploy them in an efficient way, this talk is for you.
Redis and Bloom Filters - Atlanta Java Users Group 9/2014
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Scalable Web Architectures: Common Patterns and Approaches - Web 2.0 Expo NYC
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Zend Con 2008 Slides
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2. Implementing session persistence to maintain user sessions as clients are load balanced.
3. Separating static and dynamic content to improve performance by serving static files from optimized servers.
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MNPHP Scalable Architecture 101 - Feb 3 2011
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Similar to Cassandra as Memcache (20)
Overview of MongoDB and Other Non-Relational Databases
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Redis and Bloom Filters - Atlanta Java Users Group 9/2014
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Intravert Server side processing for Cassandra
The document provides examples of using CQL (Cassandra Query Language) to create and query tables in Cassandra. It shows how to create tables to store user and video data, insert sample records, and perform queries. It then discusses using the IntraVert library to execute more complex queries directly against Cassandra, such as joins, filters, and multi-table operations, in order to reduce network traffic and processing compared to doing everything on the client side.
M6d cassandra summit
The document discusses Cassandra and how it compares to other technologies for data storage and analytics. It provides examples of how Cassandra can be used for real-time analytics, search capabilities, and compression to improve performance. Cassandra is portrayed as having advantages over other technologies in areas like replication, scaling, consistency, backups and restores.
Apache Kafka Demo
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M6d cassandrapresentation
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Casbase presentation
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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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Cassandra as Memcache
- 1. Cassandra as Memcache Edward Capriolo Media6Degrees.com
- 3. Main Memory - Fast
- 4. Hard Disks - Slow
- 6. 8 MB RAM
- 7. 1 GB Disk
- 11. @ 4GHZ
- 12. 2GB RAM
- 13. 2TB Disk
- 14. 1/10Gb Ethernet
- 15. 64 bit FC 14
- 16. Sadly no more Packard bell
- 18. Until they take over and then they will be too fast and too big
- 20. Speaks some CGI alternative php|jsp|cfm|...
- 21. Logging
- 23. Stores and indexes data
- 24. Supports a data abstraction and manipulation language
- 26. id int auto_increment, name varchar UNIQUE,
- 27. pass varchar
- 28. )
- 29. create table book ( id int auto_increment, name varchar 25 unique, author varchar 25
- 30. )
- 31. Create table users_books ( uid int , bid int , unique (uid,bid), index (bid)
- 32. )
- 34. Totally random queries based on user login
- 35. Not often read - may not be helpful to cache
- 37. FROM user JOIN users_books
- 39. JOIN book ON book.id=bid
- 40. WHERE user.id=?
- 43. Result might be on users start page
- 44. Result might be often used by algorithms
- 46. No where clause!
- 48. Possible intermediate results to temp file
- 49. Result displayed on main index page
- 53. RAM not in use by a process
- 54. Used to Cache Disk
- 55. Blocks read often get cached in RAM
- 56. large disk to RAM ratio reduces hit chance
- 59. Does not add write capacity
- 63. Works with memory slabs
- 64. Set a key, value, and a Time To Live
- 65. Typically client controlled sharing
- 67. If found in cache return
- 70. Saves web server memory vs HttpSession
- 71. Fast to store and access data
- 72. Simple to use
- 73. Clients for many languages
- 75. 8GB hash table better then 8GB more in your database machine?
- 76. Another tier to manage
- 78. A highly un-suggested deployment
- 81. Linear Writes to sorted memtable
- 83. Bloom filters
- 84. Row Cache
- 89. Replication Factor = 3
- 90. Key Cache
- 95. Replication Factor = 3
- 96. Row cache
- 97. Read Repair Chance = 0 %
- 99. Minor possibility of not found/out of sync data (not much different then memcache)
- 101. Replication Factor = 3
- 102. Row Cache
- 103. Read Repair Chance = 0%
- 104. Dynamic Snitches + Pinning
- 106. Caches on each node have less duplication
- 108. Replication Factor 20! (only this keyspace)
- 109. Row Cache
- 110. Read Repair Chance = 0%
- 112. Writes do not scale (like master-slave replication)
- 114. 0.7.X brings Read Repair Chance
- 115. Can serve purely from memory
- 116. Can serve from disk
- 117. Replication Factor, Caching, Sharding many ways to tune
- 118. General Awesomeness