Performance • Computer performance is characterized by the amount of useful work accomplished by a computer system compared to the time and resources used. • Short response times. • High throughput. • High availability. Dienstag, 13. Oktober 2009
Before you proceed "We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil." Donald Knuth Whatever you do, measure, find the problem, find the solution, measure again. Dienstag, 13. Oktober 2009
The world • We are talking about portals. • We are talking about high read/save ratio (90% of the requests are read requests) • We are talking about SOA. • We are talking about 3T. Dienstag, 13. Oktober 2009
The Problem • Users want to see the results of an action ASAP. • Users want to store some data and to view a lot of other user’s data. • Databases can store data. • Databases aren’t meant to retrieve the data. Dienstag, 13. Oktober 2009
The Metaphor • Databases aren’t meant to retrieve the data, they are like cellars, you put everything in and hope that you’ll never need it again. Dienstag, 13. Oktober 2009
The Cellar • The best way to store all my clothes is to put them into the cellar. • They won’t take place in the flat (ram). • They will be labeled, categorized, and safely put away (indexes, tables, foreign keys). Dienstag, 13. Oktober 2009
The Cellar (II) • Problem: From time to time I want to dress myself. • Problem: I don’t want to run into the cellar for each peace (slow). Dienstag, 13. Oktober 2009
Permanent Cache • White shirt rack. Shoe cabinet. • Achieves high cache hit rates continuously. • May have a warm-up time (bad for restart). • Memory intensive, hard to calculate. • Can achieve 100% cache rate, very high cache hit rates. Dienstag, 13. Oktober 2009
Expiry Cache • Seasonal clothing. As soon as I stop wearing my winter jacket, it ‘expires’. • Caches away high traffic on presumably solid object state. • Hits on same object during one request, hits on same object during traffic peaks. • Trade off: performance vs. change visibility. Dienstag, 13. Oktober 2009
Query/Method Cache • Take the same piece blindfolded. • Presumes that same query must always return same result (May be combined with expiry cache to prevent change invisibility) • Mostly ineffective on well designed (rich) interfaces (compared to object cache). • Easy application: can be wrapped around an implementation. Dienstag, 13. Oktober 2009
Other • Partial Cache. Caches unmodifyable parts of objects only (i.e. registrationDate, Manolo Blahnik, 400$ shoes). • Negative cache. Caches non existing objects (Null Object Cache, You don’t have red shoes!). • Index cache. Caches attribute mappings for reverse lookups (name -> id, red -> shoes). Dienstag, 13. Oktober 2009
Usage of Caches • No general patent. • Requires deep understanding of the business case. • Most effect relies on good understanding of business case and application behaving. • HitRate = domain knowledge * operational knowledge. Dienstag, 13. Oktober 2009
Local Proxies • Keep the ski-suit in the cellar, but take the gloves into the flat for a dog-walk. • Reduces network traffic. Reduces traffic on a remote service. • Powerful in combination with expiry caches (transparent proxies). • Good in combination with partial caches (some methods are served locally). Dienstag, 13. Oktober 2009
Remote Proxies • A room in the cellar with stuff that I indeed do need often. A wall closet. • Reduces traffic on a remote service. • Powerful in combination with Permanent Caches, SoftReference Caches or Expiry Caches, dependent on the concrete use case. Dienstag, 13. Oktober 2009
Rerouting Proxies • A special cellar for special pieces. • Transparently reroute parts of traffic to another implementation. • Help to separate fast and slow traffic. Reduce load on a service. • Powerful in combination with SoftReference and Expiry Caches. Dienstag, 13. Oktober 2009
Load balancing • Functional - method based. • Traffic-oriented - parameter based (mod- ing). • Random - round robin. Whatever it is, it should be transparent to the application. Dienstag, 13. Oktober 2009
What mods - scales • Rerouting distributes traffic by method. • Mod-ing distributes traffic by parameter (i.e. userid % constant). Must be performed/ configured by the middleware. • Multiple instances of same service - linear scaleability. • Not always possible due to resource ownership (create - dilemma). Dienstag, 13. Oktober 2009
What doesn’t mod • Mods in combination with remote proxies, extract non-creating calls to proxies, mod- distribute proxies. • Use publish/subscriber model to synchronize multiple instances. • Distribute domains (Each service instance has its userid pool for creation etc). Dienstag, 13. Oktober 2009
Use Case • Assume we have a User Object we need upon each request at least once, but up to several hundreds (mailbox, favorite lists etc), with assumed mid value of 20. • Assume we have an incoming Traffic of 1000 Requests per Second. Dienstag, 13. Oktober 2009
Classic 3T • The DB will have to handle 20.000 requests per second. • Average response time must be 0,05 milliseconds. • No DB in the world can handle this (At least not one with less than 20 processors). Dienstag, 13. Oktober 2009
Optimized 3T • LocalServiceProxy can handle approx. 20% of the requests. • With Mod 5, 5 Instances of RemoteServiceProxy will handle 16000/s requests or 3200/s each. They will cache away 90% of the requests. • 1600 remaining requests per second will arrive at the UserService. Dienstag, 13. Oktober 2009
Optimized 3T (II) • Permanent cache of the user service will be able to cache away 98% of the requests. • NullUser Cache will cache away 1% of the original requests. • Max 16 Requests per second will reach to the DB, demanding a response time of 62,5ms --> Piece of cake. And no changes in client code at all! Dienstag, 13. Oktober 2009
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