Queues, Pools, Caches

Queues, Pools,and CachesPresented by: Gwen shapira, Senior consultant

Why PythianRecognized Leader:• Global industry-leader in remote database administration services and consulting for Oracle, Oracle Applications, MySQL and SQL Server• Work with over 150 multinational companies such as Forbes.com, Fox Sports, Nordion and Western Union to help manage their complex IT deploymentsExpertise:• One of the world’s largest concentrations of dedicated, full-time DBA expertise. Employ 7 Oracle ACEs/ACE Directors• Hold 7 Specializations under Oracle Platinum Partner program, including Oracle Exadata, Oracle GoldenGate & Oracle RACGlobal Reach & Scalability:• 24/7/365 global remote support for DBA and consulting, systems administration, special projects or emergency response 3 © 2009/2010 Pythian

Connection Pools1

Objection!Problem: We can’t load testSolution: Guesstimate1. How many cores are available?2. How much time is spent squatting a connection without running database queries?3. How much workload is IO-bound? © 2009/2010 Pythian

Queues2

What do we do? 1. “Your call is important to us…” 2. Show them static content 3. Distract them with funny cat photos 4. Prioritize them 5. Acknowledge them and handle the request later 6. Jump them to the head of line 7. Tell them how long the wait is27 © 2009/2010 Pythian

New Problems Stuff developers say about message queues: 1. It is impossible to reliably monitor queues 2. Queues are not necessary if you do proper capacity planning 3. Message queues are unnecessarily complicated.30 © 2009/2010 Pythian

Capacity Planning Myth: With proper capacity planning, queues are not necessary Fact: Over-provisioning is not proper capacity planning Fact: Queue theory is capacity planning tool. Fact: Introduction of a few well defined and well understood queues will help capacity planning.33 © 2009/2010 Pythian

Caches3

Use Case - Select function get_username(int userid) { /* first try the cache */ name = memcached_fetch("username:" + userid); if (!name) { /* not found : request database */ name = db_select("SELECT username FROM users WHERE userid = ?", userid); /* then store in cache until next get */ memcached_add("username:" + userid, username); } return data; }44 © 2009/2010 Pythian

Use Case - Update function update_username(int userid, string username) { /* first update database */ result = db_execute("Update users set username=? WHERE userid=?", userid,username); if (result) { /* database update successful: update cache */ memcached_set("username:" + userid, username); }45 © 2009/2010 Pythian

Monitor 1. Number of items, gets, sets and misses 2. Number of evictions and eviction time. 3. Low hit rate and high eviction rate? 4. Swapping 5. Average response time 6. Number of connections50 © 2009/2010 Pythian

Thank you and Q&A To contact us… sales@pythian.com 1-866-PYTHIAN To follow us… http://www.pythian.com/news/ http://www.facebook.com/pages/The-Pythian-Group/ http://twitter.com/pythian http://www.linkedin.com/company/pythian52 © 2009/2010 Pythian

Queues, Pools, Caches

by Chen (Gwen) Shapira on Mar 09, 2012

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Queues, Pools, Caches Presentation Transcript