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Managing Large Tables


I recently inherited a database (version 5.0.18) that has 1 table constantly growing out of hand between 10GB -30GB, therefore making is difficult/impossible to query. Also, the Archive Storage Engine is not installed. Currently, the table is manually renamed (i.e. tablename_daterange) and a new table created. ....




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Managing A Large Piece Of Data
I have a table set up for all of my pages of content. There are columns that store certain small, various information about the page. Then, there is the main content column that holds the page content (actual article). One of my staff members that writes content for my site is complaining that the content gets cut off. I imagine it's because it's bigger than 65,000 bytes, which is all that the "TEXT" type of field will allow (that's what type of field my main content is... TEXT)

My question is what type of field should I change my main content column to an order to fit a larger piece of data? I've never had to this before, so I don't really know anything other than TEXT. Sixty-five thousand bytes isn't cutting it though.

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Managing A Very Big Number Of Tables
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Large Tables
So i've got a table with 15 million rows. id is the primary key

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Very Large Tables
I am looking at using mysql to store some particle physics data. So the idea is (for example) I would have a table with a list of events, then a table with a list of particle types (one event can have many particles) and so on. The problem is that quite often I want to calculate something for every single event, but this table might run into 10s of millions of events and many GB. Obviously it would be mad to load the whole result set into memory then iterate over it. My question is: is there any way to have the db push results to the users one (or a few) at a time in an effiecent way? I was thinking of something like an iterator that pulls the data from the disk one (or few) at a time. An alternative (but much less useful) method might be to hand the function I want to calculate to mysql, for example:
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I have a linux box with mysql installed. I want to manage the mysql server using the default web admin page. But I don't know where that page is located. Is there a standard location for the admin page?
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Large Table Or Many Tables?
I posted a similar question about 6~12 months ago with no definate answer, so I will give it another go, as the choice has popped up again in my programming life:

If the number of entries is the same is it more efficient (better) to have a single table with many columns, or many tables with few columns? The obvious answer is a single table, because there is less closing and opening tables, but the reason why I ask is what about searching through a lot of columns being even more inefficient?

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Large DB Should Use Multiple Tables?
I have a social networking site similar to myspace, currently my table which links who is who's friend on my site is 2 weeks old and is at 300,000 rows but is only at 15mb in size, this is the most accessed table of all my tables.

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select userid,friendid,status from friend_friend where userid='$temp[auto_id]' and status='1'

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GUI For Managing MySQL On A Win Platform
I have decided to start learning MySQL, but I'm kind of a very old (long
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Managing MySQL Connections...
MySQL is currently reaching its limit of connections, and is not responding to new ones. What would prevent against this?

Would closing the connection through PHP at the end of every page help with mysqli_close();

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Join Tables On A Large Database 200 Meg
i am trying to work out the most efficient way to list say multipl=
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Optimizing Mysql For Large Tables
I have been working with Mysql for about 5 years - mainly in LAMP shops. The tables have been between 20-100 thousand records size. Now I have a project where the tables are in the millions of records.
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Slow Join On Large Tables
I have two tables:

D (500,000 recs), and DL (2,500,000 recs)

D has a PK and an index on HLQ. DL has a PK and an index on ID.

The following SQL:

SELECT
HLQ as "HLQ",
count(*)
FROM
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WHERE
D.DLID=DL.ID
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produces the following explain:
tabletypepossible_keyskeykey_lenrefrowsExtra
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One Large Table Or Many Small Tables?
I'm trying to decide whether to use one large table or many small tables.
I need to gather information from various devices (about 500). Each device
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Should I use only one table with an indexed column for the ID and another
column for the data, or should I use 500 tables each with only one column
for the data?

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One Large Table Or Several Smaller Tables
From a speed of access standpoint, is it better to have one large table or several smaller tables? I'm in the early stages of development, so I can go either direction with this.

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Large Tables, Very Slow Deletes.
I've been using MySQL for a while now and are starting to run into limitations. Either my own, or something else.

I have this really large table, it stores images, it has a mediumblob field, an unsigned id integer field and a timestamp field. This table contains up to a few million rows and is constantly filled real time. It grows up to sizes between 50 and 100 gb and in the future probably even larger.

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Now the temporary solution I have is to delete 500 rows at time, but this means I must do that every 10 seconds just to maintain status quo. I would much rather check every 5 minutes or so, and if needed delete 15.000 rows in one go.

I use MyISAM tables and tried setting the key size to 128M, no luck. I run this on a dual Opteron system with a GB of memory and WinXP-SP2 Proffesional.

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Large Unused Tables Vs Performance
I've been working on a website with a rather large a database. One of the about 100 tables in there was about 1/4 of the total database size.

The table had no use anymore at the time I worked the website, so it was just sitting there, doing absolutely nothing. Obviously to spare diskspace we deleted the table.

But the question I have now, can unused large tables affect the perfomance of Mysql?
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One Large Table Vs. Many Small Tables
I'm working on a design using PHP & MySQL and I'd like to get some opinions on this.

My design has several tables that will be referenced but I'm wondering if those tables should be broken down even more and referenced more dynamically. The reason that I wonder about this is for long term goals. I hope that eventually there will be two or three thousand records that will be used on a regular basis. These records will need to be separated into groups, but I'm not sure if I should use a field in the database table or create a new table for each group.

If a few hundred records could be in each group, do you think it's better to use one large table with a field for the group ID, or a new table for each group?

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Large Number Of Tables And Columns
i'm developing an online portal, which my MYSQL database contains 100 tables.. my doubt is if any table contains 30-40 columns will it become a problem? like my html front end form has 40 fields for data insertion. and i'm not maintaing any duplicate data if my DB contains 100-150 tables will it create any problems?

as i'm inserting data from EXCEL via PHP to MYSQL, please suggest me whether a healthy MYSQL table is dependent or independent on NO:OF COLUMNS(FIELDS) or not?

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Managing Data Structure Evolution
I'm not talking about version of the MySql database, but about my customers database structure version.

I need to set a label (version number) on their db to be able to follow the evolution. The next time my customer ask me for an upgrade of my soft, I will have to execute scripts to upgrade its database structure according to the evolution of my soft.

My questions are :

1. Is it possible to set a label (version number) on a MySql database structure ?
2. Is it possible to compare 2 MySql databases architecture in order to generate scripts to upgrade from one version to the next one ?

I'm still in testing different databases and those 2 points are the most important to be able to manage in the same time the evolutioin of the database structure and the soft.

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Speeding Up Large MySQL MyISAM Tables
I'm somewhat new to MySql. I've been using it for a while, but pretty much
out of the box setup, and am starting to suffer heavily with my larger
tables. I have a table with 5,000,000+ rows that I have to search and do
joins on. Although I have an index set up for it, the joined select will
still take some 400+ seconds to return, which is obviously unacceptable.
This is due to enormous HD access.

Perhaps someone can help me with indexes here; I was under
the impression that the index for the tables are cached in memory, and
therefore permitted "instant" searchability, without having to retrieve data
from each of the rows of the DB. Is there a startup parameter, or
something in the mysql.ini file, that must be set to allow for this? I have
the index configured properly, and have made sure that the query uses there
parameters in the where clause in the same order that they appear in the
index. Code:

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Speed Of InnoDB DELETEs On Large Tables
I am finding delete queries on large InnoDB tables very slow - are
there ways to speed this up?

I have a table with about 100 million rows:

I am trying to delete just a few of these rows (the following select
takes a couple of seconds):
[color=blue]
> SELECT count(*)[/color]
-> FROM UserSnap
-> WHERE LogDate<now() - INTERVAL 750 DAY;
+----------+
| count(*) |
+----------+
| 308969 |
+----------+
[color=blue]
> DELETE FROM UserSnap WHERE LogDate<now() - INTERVAL 750 DAY;[/color]

That delete query takes hours to run. The structure of the table is:
[color=blue]
> desc UserSnap;[/color]
+----------+-------------+------+-----+---------------------+-------+
| Field | Type | Null | Key | Default | Extra |
+----------+-------------+------+-----+---------------------+-------+
| LogDate | datetime | | PRI | 0000-00-00 00:00:00 | |
| Period | tinyint(4) | | PRI | 0 | |
| UserName | varchar(50) | | PRI | | |
| RateType | varchar(50) | | PRI | default | |
| Rate | float | YES | | NULL | |
+----------+-------------+------+-----+---------------------+-------+

Any suggestions on why this is slow, and what to do about it?

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Random Records :: Rand() On Large Tables?
Im told that ORDER by rand() isnt a good idea to use on large tables, so Im interested to know how else this could be done. I need to display 20 random records (there are conditions in the WHERE clause as well).

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Loading Large Tables From Files (wikipedia)
I'm an Oracle DBA and new to MySQL.
I was trying to load a 5.6 GB xml file onto mysql database using mediawiki tools.
The performance decreased gradually and crashed at ~60% completion.
Now I'm planning to use xml2sql tools to convert the dumps to txt format.
Then I'm planning to load this using mysqlimport.
I would like to run this load faster, and on Oracle, I would use the IMP parameters
such as INDEXES=n and so on. What are the recommended steps when using mysql?
Should I target any of the system variables?
I have a 4G ram on the server and can use all of it for the load.
Any pointers?

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Create Table Syntax For Large Tables
How do i create tables with sizes larger than 4 GB? Do I need to specify any additional clauses such as heap etc when creating tables?

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Time Out Message When Query Large Tables
I'm trying to get data from 6 large tables but the volume of data in each table is too large and even select * from one of them make the system stop. I have afew questions:

1-what can I do to avoid the system stop or time out message?

2- To use several tabels infomation should I use 'View' command or can I use other methods?

3-I need to create a new table and insert the result from query in it. If I use the "view" can I insert the result of the view in a table?

(I use postgresql).

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Selecting From Multiple Large Tables Quickly
My skills with MySQL typically end at "SELECT * FROM table WHERE stuff", so I've had a lot of trouble with optimizing this query. I've tried doing multiple select statements for this, but that usually comes out with an average execution time of 99s. This method has a execution time of 6s still, so I'd like to get it down.

I have 4 important tables here (I'm only posting the columns which I use):

`auth`

UID mediumint(8) unsigned PRI NULL auto_increment
username varchar(32) MUL
clan_id mediumint(8) unsigned MUL 0
clan_abbrev varchar(7) MUL
`clans`


ID mediumint(8) unsigned PRI NULL auto_increment
Abbrev varchar(7) MUL
Name varchar(64)
icon_id smallint(5) unsigned 0
`stats`

UID int(10) unsigned PRI 0
kills mediumint(9) NULL
`usernames`

UID int(10) unsigned 0
ID int(10) unsigned PRI NULL auto_increment
Name varchar(32)
Uses mediumint(9) 0
`auth`, `stats`, and `usernames` are linked by `UID`. `clans` is linked to a row in `auth` based on it's `clan_id`.

I need to search the `usernames` table for a `Name` which matches a certain text (I use "storm" in my example below). I need to return a result with matches to that search, with each row containing:The `UID` which links the tables together for that user.The matching `Name` from `usernames`The matching `username` from `auth`The `Uses` from `usernames`.The `clan_id` from `auth`.The `Abbrev` from `clans`.The `Name` from `clans`.The `icon_id` from `clans`.The `kills` from `stats`.
The result should be ordered by `Uses` (from `usernames`) -- highest to lowest.

The tricky part is that some users may have &#390;' as their `clan_id` in the `auth` table, in which case the clan id, abbrev, name, and icon_id should all be blank (0 or '' based on the type).

Here's what I managed to hammer out with my limited knowledge of SQL:


(
SELECT usernames.UID AS `UID` , usernames.Name AS `result` , auth.username AS `playername` , usernames.Uses AS `Uses` , auth.clan_id AS `clan_id` , clans.Abbrev AS `clan_abbrev` , clans.Name AS `clan_name` , clans.icon_id AS `clan_icon` , stats.kills AS `kills`
FROM `usernames` , `auth` , `clans` , `stats`
WHERE usernames.Name LIKE '%storm%'
AND auth.UID = usernames.UID
AND clans.ID = auth.clan_id
AND stats.UID = auth.UID
)
UNION (

SELECT usernames.UID AS `UID` , usernames.Name AS `result` , auth.username AS `playername` , usernames.Uses AS `Uses` , 0 AS `clan_id` , '' AS `clan_abbrev` , '' AS `clan_name` , 0 AS `clan_icon` , stats.kills AS `kills`
FROM `usernames` , `auth` , `stats`
WHERE usernames.Name LIKE '%storm%'
AND auth.UID = usernames.UID
AND auth.clan_id =0
AND stats.UID = auth.UID
)
ORDER BY `Uses` DESC
It works great, but the average query takes around 6s (these tables have several thousand entries in each).


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Creating / Managing Database(s) Cross Platform
Is it possible to create / edit database(s) in my iBook laptop and copy the database files straight back to the Windows 2000 server? Coz I wanna do the design and testings in my laptop and 'migrate' it to the server once it's finsihed debugging.

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Large Db
i have some problem when trying make insert a lot of row in a large db.
I have to pharse a 10 file of 1 million of record and insert it into a
table ...
when arrive at around 1 million of record, every 1000 / 2000 records,
the query take 1 or 2 second to make 1 insert, then restart with a
normal fast inserting ...

in first i think was an hardware problem (like hd with bad sector or
similar) but i changed pc and the problem persist

the so is slackware 10.1 with recompiled mysql 5.1
the client program that made the insert is a vb application and the
odbc is 3.51

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Large SQL
Just wondering if there is a better way to view SQL code. Reason I ask this is because I have downloaded a backup of my database onto my local machine (desktop) and the only way I can view the .sql file is in Note Pad but it takes ages to load.
Is there any software that allows me to view my msSQL backup?

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Large Databases
We are in the process of building an application to front end a
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handle this kind of volume then we will have to go in for commercial
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Precaution For A Large Db
I have to handle a very big (~50 gigabyte) database (quite all in a
table), and I am going to use mysql.
Can mysql handle all that ammount of data?
What problems I am going to have?
Should I take any precaution?
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Posgresql maybe?

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A Large *.sql Import
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Can I optimize the amount of memory or processor dedicated to php or mysql to speed this up? Is there a way to add some sql parameters to the import to only import parts of the database I am working with? One of the columns is a unix timestamp which would also solve my problem.

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Large Result Set
I have a question regarding working w/ an extremely large result set - or maybe better yet how I could possibly avoid it. I have a table w/ several million records and I need to loop thru and check each record against an entry in another table and if a match is found write most of the current row's fields out to a file. My problem is when I query for the first set the result set is too large and I blow my memory.

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Very Large Bin Logs
We're getting several very large binary logs, reaching overall over 10GB which is a problem:

- When does mysql decide to purge the logs if at all
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Large Table
I have a website with over 36,000 registered users. I have a table with 5 million+ records, each of which correspond to a particular user. Obviously some users are tied to a few of these records, others are tied to thousands.I am trying to decide:

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My Table's Name Seems Too Large :S
If I execute a query to a mysql datasource and select any table that has this name:

select * from 2006-catalogo-productos

.... gives me an error: You have an error in your SQL syntax; check the manual that corresponds to your MySQL server version for the right syntax to use near &#55614;&#57158;-catalogo-productos' at line 1

but, i don't have that effect if I select another table of the same datasource, eg:

select * from artistas

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VERY Large Database
I have such question - how I should split large data for the better performance?
Its seems to be old question, but can't find it in search

Lets say if I have 10000 items, each have 10000 records - at the start and much more later.
Main operations - INSERT/SELECT (search for the records on some item by key)
DELETE/UPDATE almost will not be used (because of the implementation)

I see few possible options
1. Create 100 databases, in each 100 tables, in each 10000 records (records for the 1 item).
2. Create 1 large table with internal index.

As I understand, main difference between 1 and 2, that in case 2 main load will be drived to the mysql and index, in case 1 main load will be drived to the FAT (or whatever else used at the server).

But before mysql will use index large file (or its index) will need to be loaded, so in case 2 FAT will be loaded too.

IMHO option 1 is better from performance side.

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Large Queries
What would be the easiest way to split an sql file of 80mb into multiple smaller sql files?

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Large DB Restore
I'm trying to restore a fairly large database in MySQL.
Either my wireless connection drops or in the last instance, the session stayed logged in, and it gave me a message that i lost connection to the MySQL server(which was local). The restore file is on the server, and the command I'm using is just "mysql < localhost.sql", but after several atmysqlts,

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MySQL With Large Table.
I am using MySQL for a table which will have 100M+ records, avg length
of records being 130 bytes.

When the number of records reach approx. 25M (and the file size close
to 4GB), the rate of inserts falls drastically from 800 per second to
30-40 per second.

Details:
* MySQL 3.23.58 on Fedora Core 3
* Table has 4 indices.
* I have got rid of 4GB file size problem with MAX_ROWS=1000000000.
* File system : ext3 on single disk. ext3 could create 10G file
without much trouble. So I am convinced that ext3 is not the
bottleneck.
* Tried using InnoDB engine but it also doesn't meet the requirements.

Requirements of database:
* A single table in the database with 100M+ rows, each of size 130
bytes (approx).
* 500-600 inserts per second.
* 200 selects and 200 updates per second. (These statements will
affect only one row)
* 3-5 select statements per minute which can return 10k to 500k
records.
* No foreign keys/ACID transaction requirements.
* Fast recovery in case of crash.

Questions:
* Does MySQL performance drops when the table grows beyond 4G?
* Which are most important server variables which need to fine tuned?
Currently I am using only key_buffer = 512M.

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Large Record Count
I have a client who wants me to take on a project wherein they have, on
another table in another DB, about 1.2 million records. I am going to have
to consider, in this project, a record length of about 200 bytes, and am
wondering if MYSQL (5.x, on a first-rate Windows server) can handle such
size. Does anyone have experience with something that large?

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I am having huge problems migrating large db’s from one server to
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migrate it to my production server. Then I try to use this:
mysql dbname < filename
but if the tables are too large, it simply does not work.

So I tried the following two work-arounds, which work but are tedious.
Is there a nicer way to do it:

Solution A: Create a dump file with subset of all the tables, to
reduce size

Solution B: Take a zip of the table structure directly, and then copy
that. Problem here is that all the tables have to be individually
"repaired" so that mysql is in synch with its new data.

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Large Test Table
How do I create a very large table, for testing? Can I download one somewhere? I've tried to search google, but couldn't find anything.

The contents dosn't need to mean anything, so a random function with a
loop or so should do it, but if I could download a large test table
somewhere with "meaning" that would be great.

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Import Large Database
I saved my website databgase to my home computer. I am setting up a local
version of the site, and need to import the database. I have mysql and
everything set up.

But when I try to run the sql script that I exported from
my site's control panel, I get an out of memory error. What is the proper
way to import this database? Do I need to increase some memory setting?

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Reduce Large Sql Queries
I will be working on a project which i can see having quite large tables of data, particularly a transaction table which will store credit and debits from users accounts. Obviously to get a balance I would just need to sum all the transaction on the account and that would produce the current balance. My concern is that the table may become very large and displaying the account balance may end being a large query.
Is there a better may to approach this? I know i could have a balance field but I don't like the idea of that in case it become erroneous.

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Breaking Up A Large Table
I'm working with a web-based project management app that stores task information for multiple users in a common 'tasks' table. The table has over 500K rows at this point and is accessed by around 1000 users. The queries are optimized and the table is indexed properly (I think) but as the db grows performance is starting to lag. I'm thinking that the quick fix would be to break up the tasks table into smaller ones by user. So ...
is that a good idea? All of a sudden I'm going to have 1000 more tables. Also the app code will be adding tables on the fly as new users come on board. (The existing tables are all of type MyISAM)

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Large Number Of Queries
Ive currently got a loop on a php page which takes ~7000 rows from an sql table, parses information from it and does inserts/updates/deletes depending on the information.
At the moment, it does a new mysql_query for each of the inserts/updates/deletes so it ends up doing ~10k queries each time its run.
Im wondering if its better to use an array to store the queries and then put them all together (";" seperated) and run all the queries at once in the same mysql_query.
One thing to bear in mind is some of the data involved in the queries relies on previous data from queries in the loop, would this cause any problems with the combined query

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Large DataBase Columns
I am developing, what i consider to be, an extremely large database, using mysql and php.
im concerned that one of my sql tables will be too large.
tonight, im running some tests, but i was hoping the forums
could toss me some good advise.
The table will be around 1500 columns long, and
about 500 rows on average.
each column will not be any larger than 20 varchars.
i've never created anything beyond 30 columns.
is this beyond what's recommended with using mysql ???
i know the queries may take a little bit to load, but is
this simply a bad idea anyway, or am i just getting nervous
for no reason at all.

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