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Full Discussion: SAN vs. Local disk.
Top Forums UNIX for Beginners Questions & Answers SAN vs. Local disk. Post 303031269 by rbatte1 on Monday 25th of February 2019 06:26:43 AM
Old 02-25-2019
It all comes down to the homonyms cash & cache.

How much is you budget for cache? That's the key really. SSD is slightly slower than cache.

For write operations, you would have to balance off the time to commit the update to real disk (even if it is SSD) between the two. if you pass the update to a SAN, it will respond very quickly to say that you have written it, but it will actually write the data in its own time. The update is cached for write but you can continue. There will be cache batteries for power loss before it's really written. For local disk, it depends. Does the RAID controller have a good cache allocation and would therefore behave in the same way? If not, you (the operating system) must ensure that the write is complete before you proceed (costing CPU Sys time I think) and that can confusingly make local IO slower.

You have, of course, stated that this is a read intensive server so your other thing to consider is cache/RAM in the server. The server will fill up with the data you read in normally anyway, but if you wish, you could pre-read the data to give it a head-start. Beware that you need to have lots of memory for this else you will just drop it again. You can just do a find for the files of data you want and cat them to /dev/null so that they get read. Is 512Gb sufficient for your data? You don't say how much you have.



I hoe that my thoughts help,
Robin
 

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Cache(3pm)						User Contributed Perl Documentation						Cache(3pm)

NAME
Tie::Cache - LRU Cache in Memory SYNOPSIS
use Tie::Cache; tie %cache, 'Tie::Cache', 100, { Debug => 1 }; tie %cache2, 'Tie::Cache', { MaxCount => 100, MaxBytes => 50000 }; tie %cache3, 'Tie::Cache', 100, { Debug => 1 , WriteSync => 0}; # Options ################################################################## # # Debug => 0 - DEFAULT, no debugging output # 1 - prints cache statistics upon destroying # 2 - prints detailed debugging info # # MaxCount => Maximum entries in cache. # # MaxBytes => Maximum bytes taken in memory for cache based on approximate # size of total cache structure in memory # # There is approximately 240 bytes used per key/value pair in the cache for # the cache data structures, so a cache of 5000 entries would take # at approximately 1.2M plus the size of the data being cached. # # MaxSize => Maximum size of each cache entry. Larger entries are not cached. # This helps prevent much of the cache being flushed when # you set an exceptionally large entry. Defaults to MaxBytes/10 # # WriteSync => 1 - DEFAULT, write() when data is dirtied for # TRUE CACHE (see below) # 0 - write() dirty data as late as possible, when leaving # cache, or when cache is being DESTROY'd # ############################################################################ # cache supports normal tied hash functions $cache{1} = 2; # STORE print "$cache{1} "; # FETCH # FIRSTKEY, NEXTKEY while(($k, $v) = each %cache) { print "$k: $v "; } delete $cache{1}; # DELETE %cache = (); # CLEAR DESCRIPTION
This module implements a least recently used (LRU) cache in memory through a tie interface. Any time data is stored in the tied hash, that key/value pair has an entry time associated with it, and as the cache fills up, those members of the cache that are the oldest are removed to make room for new entries. So, the cache only "remembers" the last written entries, up to the size of the cache. This can be especially useful if you access great amounts of data, but only access a minority of the data a majority of the time. The implementation is a hash, for quick lookups, overlaying a doubly linked list for quick insertion and deletion. On a WinNT PII 300, writes to the hash were done at a rate 3100 per second, and reads from the hash at 6300 per second. Work has been done to optimize refreshing cache entries that are frequently read from, code like $cache{entry}, which moves the entry to the end of the linked list inter- nally. INSTALLATION
Tie::Cache installs easily using the make or nmake commands as shown below. Otherwise, just copy Cache.pm to $PERLLIB/site/Tie > perl Makefile.PL > make > make test > make install * use nmake for win32 ** you can also just copy Cache.pm to $perllib/Tie BENCMARKS
There is another simpler LRU cache implementation in CPAN, Tie::Cache::LRU, which has the same basic size limiting functionality, and for this functionality, the exact same interface. Through healthy competition, Michael G Schwern got Tie::Cache::LRU mostly faster than Tie::Cache on reads & writes: Cache Size 5000 Tie::Cache 0.17 Tie::Cache::LRU 0.21 10000 Writes 1.55 CPU sec 1.10 CPU sec 40000 Reads 1.82 CPU sec 1.58 CPU sec 10000 Deletes 0.55 CPU sec 0.59 CPU sec Unless you are using TRUE CACHE or MaxBytes functionality, using Tie::Cache::LRU should be an easy replacement for Tie::Cache. TRUE CACHE
To use class as a true cache, which acts as the sole interface for some data set, subclass the real cache off Tie::Cache, with @ISA = qw( 'Tie::Cache' ) notation. Then override the read() method for behavior when there is a cache miss, and the write() method for behavior when the cache's data changes. When WriteSync is 1 or TRUE (DEFAULT), write() is called immediately when data in the cache is modified. If set to 0, data that has been modified in the cache gets written out when the entries are deleted or during the DESTROY phase of the cache object, usually at the end of a script. To have the dirty data write() periodically while WriteSync is set to 0, there is a flush() cache API call that will flush the dirty writes in this way. Just call the flush() API like: my $write_flush_count = tied(%cache)->flush(); The flush() API was added in the .17 release thanks to Rob Bloodgood. TRUE CACHE EXAMPLE
use Tie::Cache; # personalize the Tie::Cache object, by inheriting from it package My::Cache; @ISA = qw(Tie::Cache); # override the read() and write() member functions # these tell the cache what to do with a cache miss or flush sub read { my($self, $key) = @_; print "cache miss for $key, read() data "; rand() * $key; } sub write { my($self, $key, $value) = @_; print "flushing [$key, $value] from cache, write() data "; } my $cache_size = $ARGV[0] || 2; my $num_to_cache = $ARGV[1] || 4; my $Debug = $ARGV[2] || 1; tie %cache, 'My::Cache', $cache_size, {Debug => $Debug}; # load the cache with new data, each through its contents, # and then reload in reverse order. for(1..$num_to_cache) { print "read data $_: $cache{$_} " } while(my($k, $v) = each %cache) { print "each data $k: $v "; } for(my $i=$num_to_cache; $i>0; $i--) { print "read data $i: $cache{$i} "; } # flush writes now, trivial use since will happen in DESTROY() anyway tied(%cache)->flush(); # clear cache in 2 ways, write will flush out to disk %cache = (); undef %cache; NOTES
Many thanks to all those who helped me make this module a reality, including: :) Tom Hukins who provided me insight and motivation for finishing this module. :) Jamie McCarthy, for trying to make Tie::Cache be all that it can be. :) Rob Fugina who knows how to "TRULY CACHE". :) Rob Bloodgood, for the TRUE CACHE flush() API AUTHOR
Please send any questions or comments to Joshua Chamas at chamas@alumni.stanford.org COPYRIGHT
Copyright (c) 1999-2002 Joshua Chamas, Chamas Enterprises Inc. Sponsored by development on NodeWorks http://www.nodeworks.com All rights reserved. This program is free software; you can redistribute it and/or modify it under the same terms as Perl itself. perl v5.8.8 2008-03-01 Cache(3pm)
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