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I read from the Wikipedia is that cache pollution occurs when we access some data once and after that we do not use that data and since precious cache space occupied by such data. Some useful data is evicted in replacement.
is my understanding correct or am I missing something? Can I get more information on cache pollution?
Thanks.
Most cache memories use the last recently used replacement algorithm, i.e. they replace data in the cache that were not used longest. So if you fill the whole cache memory with new data, the data loaded earliest will be replaced, even if they will be used again, and the data loaded later not.
It therefore makes sense to keep the functionality of a cache memory in mind, if data intensive algorithms are developed.
I don't know which Wikipedia article you have read, but here is a good example.
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Which data structure is appropriate for operating over millions of records and later need to iterate over it.
While simple linked list might be sufficient for your needs, in case you also need to be able to maintain records in sorted order, and efficiently access records or begin iteration at a arbitrary point, I would recommend looking in to using a B-tree.
In case you want to persist it to disk, you should use a key-value store, which often use B-tree's (or LSM Trees) "under the hood" as well as providing ACID guarantees. Examples include LMDB, BerkeleyDB, LevelDB
In short, use a database.
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How LRU can be implemented in MIPS? The procedures that are used take in a lot of initialisations and the requirement of registers is quite high when trying to implement LRU with other functions like sort and other programs that use more variables. How can this issue be addressed?
Very few VM implementations actually use LRU, because of the cost. Instead they tend to use NRU (Not Recently Used) as an approximation. Associate each mapped in page with a bit which is set when that page is used (read from or written to). Have a process that regularly works round the pages in a cyclical order clearing this bit. When you want to evict a page, chose one that does not have this bit set, and so has not been used since the last time the cyclical process got round to it. If you don't even have a hardware-supported "not recently used" bit emulate it by having the cyclical process (this is sometimes known as the clock algorithm) clear the valid bit of the page table and have the interrupt handler for accessing an invalid page set a bit to say the page was referenced before setting the page as valid and restarting the instruction that trapped.
See e.g. http://homes.cs.washington.edu/~tom/Slides/caching2.pptx especially slide 19
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Do any computer languages not use a stack data structure to keep track of execution progress?
Or is the use of this data structure an emergent requirement stemming from something inherent to most computer languages or turing machines?
With a traditional "C-style" stack, certain language features are difficult or impossible to implement. For example, closures can't easily be implemented with a traditional stack because closures require a pointer to an old activation record to work correctly and that memory is automatically reclaimed in a C-style stack. As another example, generators and coroutines need their own memory to store local variables and relative offset information and therefore can't easily be implemented if you use a standard stack implementation.
Hope this helps!
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If a website is experiencing performance issues all of a sudden, what can be the reasons behind it?
According to me database can one reason or space on server can be one of few reasons, I would like to know more about it.
There can be n number of reasons and n depends on your specification
According to what you have specified you can have a look at,
System counters of webserver/appserver like cpu, memory, paging, io, disk
What changes you did to application if any, were those changes performance costly i.e. have a round of analysis on those changes to check whether any improvement is required.
If system counters are choking then check which one is bottleneck and try to resolve it.
Check all layers/tiers of application i.e. app server, database, directory etc.
if database is bottleneck then identify costly queries and apply indexes & other DB tuning
If app server is choking then, you need to identify & improve the method which is resource heavy.
Performance tuning is not a fast track process, it takes time, identify bottlenecks and try to solve it and repeat the process until you get desired performance.
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Which is better, small data size and more server requests, or large data size and fewer requests? Larger data size means longer processing time on ther server. How does this scale out thouh as the number of users and their activity increases?
It is always ideal to get all that you need in as many less calls as you can. If you can get all that you need in one call, definitely do it.
Also it will be very helpful if you can give some insight of what kind of application are we talking about here.