C Programming Language :: efficient way of looking up huge hashes


	efficient way of looking up huge hashes Hi, I am a quiet a newbie to C programming. ( not new to programming itself though ) I am writing an email blacklist application that will lookup huge DB files like ---------- somedomain.com=emailid1 someotherdomain.com=emailid2 somedomain.com=senderdomain1 ... ... --------------------- there would be anywhere between 10k-200k such records What is the best way of looking up such a list. I want to have the queries return very fast , the memory footprint would ideally be low but that is not a limiting factor Should I use something like a Berkeley DB and read from a DB file or should I read the entire stuff into memory. Thanks Ram PS: Note to Spammers: Go ahead , send me spam r@netcore.co.in http://ecm.netcore.co.in/spamtrap.html In article <1180096402.126551.35@u36g2000prd.googlegroups.com>, Ram Prasad <ramprasad@gmail.com> wrote: >I am writing an email blacklist application that will lookup huge DB >files like >---------- >somedomain.com=emailid1 >someotherdomain.com=emailid2 >somedomain.com=senderdomain1 >... >... >--------------------- >there would be anywhere between 10k-200k such records Even with 200k records that's still only about 5MB, which is hardly huge. Does a single run of the program just do one lookup? If so, and it runs infrequently, you could just read the file in and compare the strings as you go. On the other hand, if it sits there repeatedly processing addresses, it would be reasonable to use an in-memory hash table. If you're doing single lookups but running the program very often (say once a second), or if you think the list could get much bigger, then an on-disk hash table such as Berkeley DB would be the way to go. It has the advantage that it won't read the whole file. -- Richarad -- "Consideration shall be given to the need for as many as 32 characters in some alphabets" - X3.4, 1963. On May 25, 5:46 pm, rich@cogsci.ed.ac.uk (Richard Tobin) wrote: - Hide quoted text - > In article <1180096402.126551.35@u36g2000prd.googlegroups.com>, > Ram Prasad <ramprasad@gmail.com> wrote: > >I am writing an email blacklist application that will lookup huge DB > >files like > >---------- > >somedomain.com=emailid1 > >someotherdomain.com=emailid2 > >somedomain.com=senderdomain1 > >... > >... > >--------------------- > >there would be anywhere between 10k-200k such records > Even with 200k records that's still only about 5MB, which is hardly > huge. Does a single run of the program just do one lookup? If so, > and it runs infrequently, you could just read the file in and compare > the strings as you go. On the other hand, if it sits there repeatedly > processing addresses, it would be reasonable to use an in-memory hash > table. > If you're doing single lookups but running the program very often (say > once a second), or if you think the list could get much bigger, then > an on-disk hash table such as Berkeley DB would be the way to go. It > has the advantage that it won't read the whole file. > -- Richarad > -- > "Consideration shall be given to the need for as many as 32 characters > in some alphabets" - X3.4, 1963. This will be running in a mail-filter daemon. A single instance would potentially do thousands of lookups. Since the proram would be a daemon there I could read the entire DB into memory during startup and use it from the memory Which libraries should I use for such a such lookups. I dont need a hash lookup , just an if_key_exists() lookup - Hide quoted text - On Fri, 25 May 2007 06:17:50 -0700, Ram Prasad wrote: > On May 25, 5:46 pm, rich@cogsci.ed.ac.uk (Richard Tobin) wrote: >> In article <1180096402.126551.35@u36g2000prd.googlegroups.com>, >> Ram Prasad <ramprasad@gmail.com> wrote: >> >I am writing an email blacklist application that will lookup huge DB >> >files like >> >---------- ><snip> > This will be running in a mail-filter daemon. A single instance > would potentially do thousands of lookups. Since the proram would be a > daemon there I could read the entire DB into memory during startup and > use it from the memory > Which libraries should I use for such a such lookups. I dont > need a hash lookup , just an if_key_exists() lookup http://judy.sourceforge.net/ - Hide quoted text - Ram Prasad wrote: > I am a quiet a newbie to C programming. ( not new to programming > itself though ) I am writing an email blacklist application that > will lookup huge DB files like > ---------- > somedomain.com=emailid1 > someotherdomain.com=emailid2 > somedomain.com=senderdomain1 > ... > --------------------- > there would be anywhere between 10k-200k such records > What is the best way of looking up such a list. I want to have the > queries return very fast , the memory footprint would ideally be > low but that is not a limiting factor Try hashlib. It is pure portable std C, available under the GPL, and can be found at: <http://cbfalconer.home.att.net/download/> Search, insert, etc. are all O(1) ops. -- <http://www.cs.auckland.ac.nz/~pgut001/pubs/vista_cost.txt> <http://www.securityfocus.com/columnists/423> <http://www.aaxnet.com/editor/edit043.html> <http://kadaitcha.cx/vista/dogsbreakfast/index.html> cbfalconer at maineline dot net -- Posted via a free Usenet account from http://www.teranews.com Ram Prasad wrote: > Should I use something like a Berkeley DB and read from a DB file or > should I read the entire stuff into memory. I'm having a similar problem, and was thinking about using Berkeley DB too. I wouldn't worry too much about the performance issue, if you have the table in memory, the OS might swap your unused memory pages to disk anyway. Likewise, if you access some disk location a lot, it will typically be in cache. So, using Berkeley DB is a good idea. Knuth once said: "premature optimization is the root of all evil" -- Tor <torust [at] online [dot] no> On May 26, 5:58 am, Tor Rustad <tor@online.no> wrote: > Ram Prasad wrote: > > Should I use something like a Berkeley DB and read from a DB file or > > should I read the entire stuff into memory. > I'm having a similar problem, and was thinking about using Berkeley DB too. > I wouldn't worry too much about the performance issue, if you have the table > in memory, the OS might swap your unused memory pages to disk anyway. > Likewise, if you access some disk location a lot, it will typically be in > cache. > So, using Berkeley DB is a good idea. I am evaluating multiple options. I think tinycdb looks very promising http://www.corpit.ru/mjt/tinycdb.html It compiles easily on my machine and the example scripts work without much fuss. Unfortunately with so many options available there is no single standard method. How does one make his choice - Hide quoted text - Ram Prasad wrote: > On May 26, 5:58 am, Tor Rustad <tor@online.no> wrote: >> Ram Prasad wrote: >>> Should I use something like a Berkeley DB and read from a DB file or >>> should I read the entire stuff into memory. >> I'm having a similar problem, and was thinking about using Berkeley DB too. >> I wouldn't worry too much about the performance issue, if you have the table >> in memory, the OS might swap your unused memory pages to disk anyway. >> Likewise, if you access some disk location a lot, it will typically be in >> cache. >> So, using Berkeley DB is a good idea. > I am evaluating multiple options. I think tinycdb looks very > promising > http://www.corpit.ru/mjt/tinycdb.html Nice and simple C API, but rather limited platform support. > Unfortunately with so many options available there is no single > standard method. How does one make his choice Yes, there are pro and cons, if I have a tuning problem, I would prototype multiple solutions, and select the one which get the job done, with minimal drawbacks. In practice, * robustness / maturity * maintainability * support / documentation * portability * fingerprint * security * error handling * simplicity etc. might be important design parameters too. I rarely select the fastest solution. The simplest solution to compare with, would perhaps be holding the blacklist in memory, and to use qsort()/bsearch(). That prototype can be made in no time. However, for expert advice, you should instead consult one of the many database news groups. -- Tor <torust [at] online [dot] no> On May 28, 7:46 pm, Tor Rustad <torust_at_online.no> wrote: - Hide quoted text - > Ram Prasad wrote: > > On May 26, 5:58 am, Tor Rustad <tor@online.no> wrote: > >> Ram Prasad wrote: > >>> Should I use something like a Berkeley DB and read from a DB file or > >>> should I read the entire stuff into memory. > >> I'm having a similar problem, and was thinking about using Berkeley DB too. > >> I wouldn't worry too much about the performance issue, if you have the table > >> in memory, the OS might swap your unused memory pages to disk anyway. > >> Likewise, if you access some disk location a lot, it will typically be in > >> cache. > >> So, using Berkeley DB is a good idea. > > I am evaluating multiple options. I think tinycdb looks very > > promising > > http://www.corpit.ru/mjt/tinycdb.html > Nice and simple C API, but rather limited platform support. > > Unfortunately with so many options available there is no single > > standard method. How does one make his choice > Yes, there are pro and cons, if I have a tuning problem, I would > prototype multiple solutions, and select the one which get the job done, > with minimal drawbacks. In practice, > * robustness / maturity > * maintainability > * support / documentation > * portability > * fingerprint > * security > * error handling > * simplicity > etc. > might be important design parameters too. I rarely select the fastest > solution. > The simplest solution to compare with, would perhaps be holding the > blacklist in memory, and to use qsort()/bsearch(). That prototype can be > made in no time. Can you pls explain figerprint ? Would you suggest bsearch() on a 5MB data would be better than a hash- db lookup. What are the implications of multiple instances running can they share the same data area Thanks Ram PS: Note to Spammers: Go ahead , send me spam r@netcore.co.in http://ecm.netcore.co.in/spamtrap.html Ram Prasad wrote: > Can you pls explain figerprint ? That was a typo, for "footprint", e.g. the memory usage. > Would you suggest bsearch() on a 5MB data would be better than a hash- > db lookup. The relevant question for you: is a simple qsort/bsearch sufficient? > What are the implications of multiple instances running can they share > the same data area Those implications are system specific, we don't discuss file locks, mutex, thread programming etc. here. -- Tor <torust [at] online [dot] no>