INSERT: inserting multiple rows at once, or one by one?

I'm inserting multiple rows in a table, and I get this message:

MySQL server has gone away

My Query:

INSERT INTO table
 (a,b,c,d,e,f,g,h,i,j,k) 
     VALUES(1,2,3,4,5,6,7,8,9,10,11),(1,2,3,4,5,6,7,8,9,10,11), ...
        ON DUPLICATE KEY UPDATE
          c=VALUES(c),
          d=VALUES(d),
          e=VALUES(e),
          f=VALUES(f),
          g=VALUES(g),
          h=VALUES(h),
          i=VALUES(i),
          j=VALUES(j)

Is it because I stuffed too many values inside a single query? (There are like 5000 pairs of values from a array which I implode with ,).

If this is the reason - then should I insert each row one by one? Is it slower than inserting them all at once?

---

The PHP code:

foreach($data as 开发者_如何学Python&$entry)
 $entry = "('".implode("','", array(
   $entry->ID,
   addslashes($entry->field_1),
   addslashes($entry->field_2),
   ...

 ))."')";

$data = implode(',', $data);   

$query = "... VALUES{$data} ON ..."

$data is a array of STD type objects...

---

edit again :)

So I tried splitting my $data into smaller arrays of 100 elements each:

$data_chunks = array_chunk($data, 100);
foreach($data_chunks as $data_chunk)
  insert_into_db($data_chunk);

and it works, I don't get that error anymore...

So that means the issue was the very long query string...

Now I'm even more confused:

• Is there a length limit of the query, or maybe PHP arguments in general?
• Is there any difference between inserting row by row than inserting multiple rows? Is it worth the array_chunk() ?

---

it could be that your query is taking too long to complete, mysql times out and closes the connection. You can alter the system variables to wait longer.

http://dev.mysql.com/doc/refman/5.0/en/gone-away.html

---

I think your problem is with *max_allowed_packet*, although the error seems to point in different direction. Try doing as suggested here: http://dev.mysql.com/doc/refman/5.5/en/packet-too-large.html

Or, before making any changes to mysql configuration, simply strlen() your query and find out how long(in bytes) it actually is.