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  • large test data for knapsack problem

    - by user347918
    i am researcher student. I am searching large data for knapsack problem. I wanted test my algorithm for knapsack problem. But i couldn't find large data. I need data has 1000 item and capacity is no matter. The point is item as much as huge it's good for my algorithm. Is there any huge data available in internet. Does anybody know please guys i need urgent.

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  • Best place to store large amounts of session data

    - by audiopleb
    I'm building an application that needs to store and re-use large amounts of data per session. So for example, the user selects a large list of list items (say 2000 or significantly more) which have a numeric value as their key then they save that selection and go off to another page, do something else and then come back to the original page and need to load their selections into that page. What is the quickest and most efficient way of storing and reusing that data? In a text file saved with the session id? In a temp db table? In the session data itself (db sessions so size isn't a limit) using a serialised string or using gzcompress or gzencode? Any advice or insight would be great! Thank you!!!!

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  • setting syntax on in vim with large C file makes complete very slow

    - by skeept
    when I have syntax on in a large C file (about 8000) lines the completion ctrl-p and ctrl-n are very slow (more than 20). When I turn syntax off then completion takes less than a second. Any ideas on how to solve this? Thanks! EDIT: I figured out a minimal way of reproducing this behaviour: with an empty .vimrc and .vim folder the only changed settings are :set syntax on :set foldmethod=syntax and a large C file to edit, completion (and even general editing) becomes very very slow.

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  • MySQL Config File for Large System

    - by Jonathon
    We are running MySQL on a Windows 2003 Server Enterpise Edition box. MySQL is about the only program running on the box. We have approx. 8 slaves replicated to it, but my understanding is that having multiple slaves connecting to the same master does not significantly slow down performance, if at all. The master server has 16G RAM, 10 Terabyte drives in RAID 10, and four dual-core processors. From what I have seen from other sites, we have a really robust machine as our master db server. We just upgraded from a machine with only 4G RAM, but with similar hard drives, RAID, etc. It also ran Apache on it, so it was our db server and our application server. It was getting a little slow, so we split the db server onto this new machine and kept the application server on the first machine. We also distributed the application load amongst a few of our other slave servers, which also run the application. The problem is the new db server has mysqld.exe consuming 95-100% of CPU almost all the time and is really causing the app to run slowly. I know we have several queries and table structures that could be better optimized, but since they worked okay on the older, smaller server, I assume that our my.ini (MySQL config) file is not properly configured. Most of what I see on the net is for setting config files on small machines, so can anyone help me get the my.ini file correct for a large dedicated machine like ours? I just don't see how mysqld could get so bogged down! FYI: We have about 100 queries per second. We only use MyISAM tables, so skip-innodb is set in the ini file. And yes, I know it is reading the ini file correctly because I can change some settings (like the server-id and it will kill the server at startup). Here is the my.ini file: #MySQL Server Instance Configuration File # ---------------------------------------------------------------------- # Generated by the MySQL Server Instance Configuration Wizard # # # Installation Instructions # ---------------------------------------------------------------------- # # On Linux you can copy this file to /etc/my.cnf to set global options, # mysql-data-dir/my.cnf to set server-specific options # (@localstatedir@ for this installation) or to # ~/.my.cnf to set user-specific options. # # On Windows you should keep this file in the installation directory # of your server (e.g. C:\Program Files\MySQL\MySQL Server X.Y). To # make sure the server reads the config file use the startup option # "--defaults-file". # # To run run the server from the command line, execute this in a # command line shell, e.g. # mysqld --defaults-file="C:\Program Files\MySQL\MySQL Server X.Y\my.ini" # # To install the server as a Windows service manually, execute this in a # command line shell, e.g. # mysqld --install MySQLXY --defaults-file="C:\Program Files\MySQL\MySQL Server X.Y\my.ini" # # And then execute this in a command line shell to start the server, e.g. # net start MySQLXY # # # Guildlines for editing this file # ---------------------------------------------------------------------- # # In this file, you can use all long options that the program supports. # If you want to know the options a program supports, start the program # with the "--help" option. # # More detailed information about the individual options can also be # found in the manual. # # # CLIENT SECTION # ---------------------------------------------------------------------- # # The following options will be read by MySQL client applications. # Note that only client applications shipped by MySQL are guaranteed # to read this section. If you want your own MySQL client program to # honor these values, you need to specify it as an option during the # MySQL client library initialization. # [client] port=3306 [mysql] default-character-set=latin1 # SERVER SECTION # ---------------------------------------------------------------------- # # The following options will be read by the MySQL Server. Make sure that # you have installed the server correctly (see above) so it reads this # file. # [mysqld] # The TCP/IP Port the MySQL Server will listen on port=3306 #Path to installation directory. All paths are usually resolved relative to this. basedir="D:/MySQL/" #Path to the database root datadir="D:/MySQL/data" # The default character set that will be used when a new schema or table is # created and no character set is defined default-character-set=latin1 # The default storage engine that will be used when create new tables when default-storage-engine=MYISAM # Set the SQL mode to strict #sql-mode="STRICT_TRANS_TABLES,NO_AUTO_CREATE_USER,NO_ENGINE_SUBSTITUTION" # we changed this because there are a couple of queries that can get blocked otherwise sql-mode="" #performance configs skip-locking max_allowed_packet = 1M table_open_cache = 512 # The maximum amount of concurrent sessions the MySQL server will # allow. One of these connections will be reserved for a user with # SUPER privileges to allow the administrator to login even if the # connection limit has been reached. max_connections=1510 # Query cache is used to cache SELECT results and later return them # without actual executing the same query once again. Having the query # cache enabled may result in significant speed improvements, if your # have a lot of identical queries and rarely changing tables. See the # "Qcache_lowmem_prunes" status variable to check if the current value # is high enough for your load. # Note: In case your tables change very often or if your queries are # textually different every time, the query cache may result in a # slowdown instead of a performance improvement. query_cache_size=168M # The number of open tables for all threads. Increasing this value # increases the number of file descriptors that mysqld requires. # Therefore you have to make sure to set the amount of open files # allowed to at least 4096 in the variable "open-files-limit" in # section [mysqld_safe] table_cache=3020 # Maximum size for internal (in-memory) temporary tables. If a table # grows larger than this value, it is automatically converted to disk # based table This limitation is for a single table. There can be many # of them. tmp_table_size=30M # How many threads we should keep in a cache for reuse. When a client # disconnects, the client's threads are put in the cache if there aren't # more than thread_cache_size threads from before. This greatly reduces # the amount of thread creations needed if you have a lot of new # connections. (Normally this doesn't give a notable performance # improvement if you have a good thread implementation.) thread_cache_size=64 #*** MyISAM Specific options # The maximum size of the temporary file MySQL is allowed to use while # recreating the index (during REPAIR, ALTER TABLE or LOAD DATA INFILE. # If the file-size would be bigger than this, the index will be created # through the key cache (which is slower). myisam_max_sort_file_size=100G # If the temporary file used for fast index creation would be bigger # than using the key cache by the amount specified here, then prefer the # key cache method. This is mainly used to force long character keys in # large tables to use the slower key cache method to create the index. myisam_sort_buffer_size=64M # Size of the Key Buffer, used to cache index blocks for MyISAM tables. # Do not set it larger than 30% of your available memory, as some memory # is also required by the OS to cache rows. Even if you're not using # MyISAM tables, you should still set it to 8-64M as it will also be # used for internal temporary disk tables. key_buffer_size=3072M # Size of the buffer used for doing full table scans of MyISAM tables. # Allocated per thread, if a full scan is needed. read_buffer_size=2M read_rnd_buffer_size=8M # This buffer is allocated when MySQL needs to rebuild the index in # REPAIR, OPTIMZE, ALTER table statements as well as in LOAD DATA INFILE # into an empty table. It is allocated per thread so be careful with # large settings. sort_buffer_size=2M #*** INNODB Specific options *** innodb_data_home_dir="D:/MySQL InnoDB Datafiles/" # Use this option if you have a MySQL server with InnoDB support enabled # but you do not plan to use it. This will save memory and disk space # and speed up some things. skip-innodb # Additional memory pool that is used by InnoDB to store metadata # information. If InnoDB requires more memory for this purpose it will # start to allocate it from the OS. As this is fast enough on most # recent operating systems, you normally do not need to change this # value. SHOW INNODB STATUS will display the current amount used. innodb_additional_mem_pool_size=11M # If set to 1, InnoDB will flush (fsync) the transaction logs to the # disk at each commit, which offers full ACID behavior. If you are # willing to compromise this safety, and you are running small # transactions, you may set this to 0 or 2 to reduce disk I/O to the # logs. Value 0 means that the log is only written to the log file and # the log file flushed to disk approximately once per second. Value 2 # means the log is written to the log file at each commit, but the log # file is only flushed to disk approximately once per second. innodb_flush_log_at_trx_commit=1 # The size of the buffer InnoDB uses for buffering log data. As soon as # it is full, InnoDB will have to flush it to disk. As it is flushed # once per second anyway, it does not make sense to have it very large # (even with long transactions). innodb_log_buffer_size=6M # InnoDB, unlike MyISAM, uses a buffer pool to cache both indexes and # row data. The bigger you set this the less disk I/O is needed to # access data in tables. On a dedicated database server you may set this # parameter up to 80% of the machine physical memory size. Do not set it # too large, though, because competition of the physical memory may # cause paging in the operating system. Note that on 32bit systems you # might be limited to 2-3.5G of user level memory per process, so do not # set it too high. innodb_buffer_pool_size=500M # Size of each log file in a log group. You should set the combined size # of log files to about 25%-100% of your buffer pool size to avoid # unneeded buffer pool flush activity on log file overwrite. However, # note that a larger logfile size will increase the time needed for the # recovery process. innodb_log_file_size=100M # Number of threads allowed inside the InnoDB kernel. The optimal value # depends highly on the application, hardware as well as the OS # scheduler properties. A too high value may lead to thread thrashing. innodb_thread_concurrency=10 #replication settings (this is the master) log-bin=log server-id = 1 Thanks for all the help. It is greatly appreciated.

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  • Javascript large number array compression

    - by gatapia
    Hi All, I've got a javascript application that sends a large amount of numerical data down the wire. This data is then stored in a database. I am having size issues (too much bandwidth, database getting too big). I am now ready to sacrifice some performance for compression. I was thinking of implementing a base 62 number.toString(62) and parseInt(compressed, 62). This would certainly reduce the size of the data but before I go ahead and do this I thought I would put it to the folks here as I know there must be some outside the box solution I have not considered. The basic specs are: - Compress large number arrays into strings for JSONP transfer (So I think UTF is out) - Be relatively fast, look I'm not expecting same performance as I have now but I also don't want gzip compression either. Any ideas would be greatly appreciated. Thanks Guido Tapia

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  • Download Large Files using java

    - by angelina
    Dear All, I M building a application in which i want to download large files on handset (mobile),but if size of file is large i m getting exception socket exception-broken pipe . inputStream = new FileInputStream(path); byte[] buffer = new byte[1024]; int bytesRead = 0; do { bytesRead = inputStream.read(buffer, offset, buffer.length); resp.getOutputStream().write(buffer, 0, bytesRead); } while (bytesRead == buffer.length); resp.getOutputStream().flush(); }

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  • Streaming large result sets with MySQL

    - by configurator
    I'm developing a spring application that uses large MySQL tables. When loading large tables, I get an OutOfMemoryException, since the driver tries to load the entire table into application memory. I tried using statement.setFetchSize(Integer.MIN_VALUE); but then every ResultSet I open hangs on close(); looking online I found that that happens because it tries loading any unread rows before closing the ResultSet, but that is not the case since I do this: ResultSet existingRecords = getTableData(tablename); try { while (existingRecords.next()) { // ... } } finally { existingRecords.close(); // this line is hanging, and there was no exception in the try clause } The hangs happen for small tables (3 rows) as well, and if I don't close the RecordSet (which happened in one method) then connection.close() hangs.

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  • Browser, upload large file

    - by Mike
    I'm looking for a way to allow a user to upload a large file (~1gb) to my unix server using a web page and browser. There are a lot of examples that illustrate how to do this with a traditional post request, however this doesn't seem like a good idea when the file is this large. I'm looking for recommendations on the best approach. Bonus points if the method includes a way of providing progress information to the user. For now security is not a major concern, as most users who will be using the service can be trusted. We can also assume that the connection between client and host will not be interrupted (or if it is they have to start over).

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  • Get count matches in query on large table very slow

    - by Roy Roes
    I have a mysql table "items" with 2 integer fields: seid and tiid The table has about 35000000 records, so it's very large. seid tiid ----------- 1 1 2 2 2 3 2 4 3 4 4 1 4 2 The table has a primary key on both fields, an index on seid and an index on tiid. Someone types in 1 or more tiid values and now I would like to get the seid with most results. For example when someone types 1,2,3, I would like to get seid 2 and 4 as result. They both have 2 matches on the tiid values. My query so far: SELECT COUNT(*) as c, seid FROM items WHERE tiid IN (1,2,3) GROUP BY seid HAVING c = (SELECT COUNT(*) as c, seid FROM items WHERE tiid IN (1,2,3) GROUP BY seid ORDER BY c DESC LIMIT 1) But this query is extremly slow, because of the large table. Does anyone know how to construct a better query for this purpose?

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  • Secrets of delivering .NET size large products?

    - by Joan Venge
    In software companies I have seen it's really hard to work on very large products where everything depends on everything else. For instance Microsoft works on C#, F#, .NET, WPF, Visual Studio where these things are interconnected. I don't know how many people are involved, but if it's in 100s, how do they keep in sync with everything, so they design and implement features without conflicting with other dependencies and future plans of other products? I am wondering that if MS is able to do this, they must have a very good system. Any guidelines or secrets for MS or non-MS very large software product delivering?

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  • Comparing large strings in JavaScript with a hash

    - by user4815162342
    I have a form with a textarea that can contain large amounts of content (say, articles for a blog) edited using one of a number of third party rich text editors. I'm trying to implement something like an autosave feature, which should submit the content through ajax if it's changed. However, I have to work around the fact that some of the editors I have as options don't support an "isdirty" flag, or an "onchange" event which I can use to see if the content has changed since the last save. So, as a workaround, what I'd like to do is keep a copy of the content in a variable (let's call it lastSaveContent), as of the last save, and compare it with the current text when the "autosave" function fires (on a timer) to see if it's different. However, I'm worried about how much memory that could take up with very large documents. Would it be more efficient to store some sort of hash in the lastSaveContent variable, instead of the entire string, and then compare the hash values? If so, can you recommend a good javascript library/jquery plugin that implements an appropriate hash for this requirement?

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  • Passing Large amount of data in PHP.

    - by Simple
    I would like to know what is the best way to pass a large amount of XML data from one PHP script to another. I have a script that reads in an XML feed of jobs. I would like to have the script display a list of the job titles as links. When the user clicks a link they would be taken to another page displaying the details for that job. The job details are too large to send in the query string, and it seems poor style to start a session for data that isn't specific to that user. Any ideas?

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  • Isometric layer moving inside map

    - by gronzzz
    i'm created isometric map and now trying to limit layer moving. Main idea, that i have left bottom, right bottom, left top, right top points, that camera can not move outside, so player will not see map out of bounds. But i can not understand algorithm of how to do that. It's my layer scale/moving code. - (void)touchBegan:(UITouch *)touch withEvent:(UIEvent *)event { _isTouchBegin = YES; } - (void)touchMoved:(UITouch *)touch withEvent:(UIEvent *)event { NSArray *allTouches = [[event allTouches] allObjects]; UITouch *touchOne = [allTouches objectAtIndex:0]; CGPoint touchLocationOne = [touchOne locationInView: [touchOne view]]; CGPoint previousLocationOne = [touchOne previousLocationInView: [touchOne view]]; // Scaling if ([allTouches count] == 2) { _isDragging = NO; UITouch *touchTwo = [allTouches objectAtIndex:1]; CGPoint touchLocationTwo = [touchTwo locationInView: [touchTwo view]]; CGPoint previousLocationTwo = [touchTwo previousLocationInView: [touchTwo view]]; CGFloat currentDistance = sqrt( pow(touchLocationOne.x - touchLocationTwo.x, 2.0f) + pow(touchLocationOne.y - touchLocationTwo.y, 2.0f)); CGFloat previousDistance = sqrt( pow(previousLocationOne.x - previousLocationTwo.x, 2.0f) + pow(previousLocationOne.y - previousLocationTwo.y, 2.0f)); CGFloat distanceDelta = currentDistance - previousDistance; CGPoint pinchCenter = ccpMidpoint(touchLocationOne, touchLocationTwo); pinchCenter = [self convertToNodeSpace:pinchCenter]; CGFloat predictionScale = self.scale + (distanceDelta * PINCH_ZOOM_MULTIPLIER); if([self predictionScaleInBounds:predictionScale]) { [self scale:predictionScale scaleCenter:pinchCenter]; } } else { // Dragging _isDragging = YES; CGPoint previous = [[CCDirector sharedDirector] convertToGL:previousLocationOne]; CGPoint current = [[CCDirector sharedDirector] convertToGL:touchLocationOne]; CGPoint delta = ccpSub(current, previous); self.position = ccpAdd(self.position, delta); } } - (void)touchEnded:(UITouch *)touch withEvent:(UIEvent *)event { _isDragging = NO; _isTouchBegin = NO; // Check if i need to bounce _touchLoc = [touch locationInNode:self]; } #pragma mark - Update - (void)update:(CCTime)delta { CGPoint position = self.position; float scale = self.scale; static float friction = 0.92f; //0.96f; if(_isDragging && !_isScaleBounce) { _velocity = ccp((position.x - _lastPos.x)/2, (position.y - _lastPos.y)/2); _lastPos = position; } else { _velocity = ccp(_velocity.x * friction, _velocity.y *friction); position = ccpAdd(position, _velocity); self.position = position; } if (_isScaleBounce && !_isTouchBegin) { float min = fabsf(self.scale - MIN_SCALE); float max = fabsf(self.scale - MAX_SCALE); int dif = max > min ? 1 : -1; if ((scale > MAX_SCALE - SCALE_BOUNCE_AREA) || (scale < MIN_SCALE + SCALE_BOUNCE_AREA)) { CGFloat newSscale = scale + dif * (delta * friction); [self scale:newSscale scaleCenter:_touchLoc]; } else { _isScaleBounce = NO; } } }

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  • Auto-resize large images with JavaScript?

    - by Yegor
    I have an application that allows people to post images on each others profiles with bb code. Problem is, some post very large images, which cover other parts of the site when are viewed. How can I scale down images, client-side, so they are no bigger than x by y dimensions?

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  • Very large database, very small portion most being retrieved in real time

    - by mingyeow
    Hi folks, I have an interesting database problem. I have a DB that is 150GB in size. My memory buffer is 8GB. Most of my data is rarely being retrieved, or mainly being retrieved by backend processes. I would very much prefer to keep them around because some features require them. Some of it (namely some tables, and some identifiable parts of certain tables) are used very often in a user facing manner How can I make sure that the latter is always being kept in memory? (there is more than enough space for these) More info: We are on Ruby on rails. The database is MYSQL, our tables are stored using INNODB. We are sharding the data across 2 partitions. Because we are sharding it, we store most of our data using JSON blobs, while indexing only the primary keys

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  • rsync from OS X to Ubuntu failing for large (>15GB) files

    - by johnny_bgoode
    I'm trying to rsync a 15 GB file from my OSX box to a box running Ubuntu 10.04 server. rsync is transferring ~300-700Mb and then closing the connection with the following error: Read from remote host my.host.name: Connection reset by peer rsync: writefd_unbuffered failed to write 4 bytes [sender]: Broken pipe (32) rsync: connection unexpectedly closed (397214 bytes received so far) [sender] rsync error: unexplained error (code 255) at /SourceCache/rsync/rsync-40/rsync/io.c(452) [sender=2.6.9] The exact command I am executing is: rsync --progress --archive --inplace my.15GB.file.tgz my.host.name:~/ I am sure that there is enough free space on the Ubuntu box. Any ideas what could be causing the connection to drop?

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  • Large virtual memory size of ElasticSearch JVM

    - by wfaulk
    I am running a JVM to support ElasticSearch. I am still working on sizing and tuning, so I left the JVM's max heap size at ElasticSearch's default of 1GB. After putting data in the database, I find that the JVM's process is showing 50GB in SIZE in top output. It appears that this is actually causing performance problems on the system; other processes are having trouble allocating memory. In asking the ElasticSearch community, they suggested that it's "just" filesystem caching. In my experience, filesystem caching doesn't show up as memory used by a particular process. Of course, they may have been talking about something other than the OS's filesystem cache, maybe something that the JVM or ElasticSearch itself is doing on top of the OS. But they also said that it would be released if needed, and that didn't seem to be happening. So can anyone help me figure out how to tune the JVM, or maybe ElasticSearch itself, to not use so much RAM. System is Solaris 10 x86 with 72GB RAM. JVM is "Java(TM) SE Runtime Environment (build 1.7.0_45-b18)".

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  • amazon dynamoDB or MySQL for storing large arrays inside each row

    - by Logan Besecker
    I am trying to decide which database I should use for an application I'm making. I was leaning toward dynamoDB because of its scalability, but then I read in the documentation which said: there is a limit of 64 KB on the item size although it looks like MySQL has a similar restriction documented here This application will be storing a lot of data in two arrays, which could contain upwards of 10,000-100,000 strings in each. I estimate that these strings will each be somewhere around 20 characters long, so each element of the array will be around 40bytes and each array could be around 4MB. Given this predicament, what database on amazon AWS would you use; or how would you get around the limit of size per row? Thanks in advance, Logan Besecker

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  • how to split a very large database on sql server

    - by ken jackson
    I have a 90 GB SQL Server database that I want to make more manageable. It stores stock data from 50+ different stocks from 2009 and 2010, and each stock is a separate table. Some tables have hundreds of millions of rows, and other have just a few million. What I want to do is somehow split the database, so that I don't have a single database file that is 90 GB. What I want is to be able to somehow magically split all the tables so that I can backup the 2009 data once and not have to keep on including it in the backup every time I backup the entire database, however, I would like the 2009 data to be included whenever I do a query. Is partitioning the database the way to go? Will it do the above for me, or will I need some other solution? I research partitioning, but I wasn't sure if that would solve all my problems. I wasn't able to find anything that would tell me whether or not it would migrate prexisting data, or whether it only worked for newly inserted data. Any help or pointers would be much appreciated. Thanks in advance, Ken

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  • trouble backing up large mysql database

    - by Patrick
    I have a wordpress MU database with something like 10,000+ tables for various user's blogs. I need to upgrade wordpress MU to newest version, but want to backup the DB before hand. PHPMyAdmin fails to even load the page when i click export. Ive tried going into the server (windows) and using dos command line: mysqldump -u USERNAME -p PASSWORD> BACKUP.sql but it hangs for a minute and gives me the error: error 23: out of resources when opinging file '.\USERNAME\wp_1037_links.MYD' (Errorcode: 24) when using LOCK Tables What am i doing wrong, or should i be doing? Is PHPMyAdmin right for something this size? Is there a better way of doing this than the two methods i tried? **Note that this is not my site, so any suggestions as to the setup of the DB ill have to run by the owner. Im just here for WP related crap, this is kind of out of scope for what i was brought on to do.

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  • Large mailbox in Outlook 2007 takes ages to index

    - by Reado
    In our company each user has a single mailbox and all email they have ever sent/received is in that mailbox. We don't do archiving to PST and we thought that was the way forward. The problem we now have is if someone switches to another PC for the day and opens Outlook, it has to download all emails first to that PC (cached mode) but even then when they try to search for something, Outlook says items are still being indexed. One user has over 100,000 items to be indexed and it's been saying that for about a week! As a temporary workaround I have turned off instant searching which allows them to search for anything, but it takes time to filter through, and Outlook doesn't exactly indicate if it's still searching for something, so in most cases the user thinks the search isn't working when really it is and it's just taking time to populate the results. I need a solution that allows the mailbox to be indexed really quickly if the user has to login to another PC. Are we best using Online Mode instead of Cached Mode or is there another way around this? Thanks in advance.

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