I'm not sure I'd attempt the type of paging shown on the sqlauthority blog
on a table as large as that. Is there an identity field (sequential #) that
you can use to split it up? Also, have you tried to disable transactions as
well? For LARGE sets that can usually speed it up and avoid timeouts of
course you get partial data if it fails.

Nathan Palmer


On Mon, Jun 10, 2013 at 7:15 PM, TJ Roche <tdro...@gmail.com> wrote:

> It is a single large table fairly narrow, mostly ints.  I have a couple
> other tables that are hovering right around the 1/2 billion row mark but I
> am reasonably okay with them, I have had reasonable luck splitting them out
> based on cardinality or taking the processing out into different aspects of
> my migration routine.
>
> I am only moving it in house so I am not necessarily worried about the
> bandwidth, more concerned with speed and time.
>
> I have a 36 hour downtime window and if possible I would like to be able
> to finish my migration within that window.
>
>
>
>
> On Thursday, June 6, 2013 3:53:50 PM UTC-7, Nathan Palmer wrote:
>
>> Well, 2.5 billion is a large set :)
>>
>> When I was dealing with data of that size what I had to do to avoid
>> timeouts was disable parallel processing in certain parts and enable it in
>> others. It's going to depend on your data and structure though on how best
>> to do it. Is it a single table? I was dealing with multiple large tables so
>> I kept each table a single stream but ran them concurrently. I also had to
>> break up the export into chunks of 100k since I was dealing with a
>> geographical conversion (moving it about 3k miles so bandwidth was a
>> consideration.)
>>
>> Nathan Palmer
>>
>>
>> On Wed, Jun 5, 2013 at 7:14 PM, TJ Roche <tdr...@gmail.com> wrote:
>>
>>> So I have around 2.5 billion records that i am trying to take from sql
>>> server on one system to sql server on another system.
>>>
>>> Obviously this is slightly beyond the bounds of the standard input
>>> command -> batch/bulk command scenario.
>>>
>>> Is there an accepted methodology to use here?
>>>
>>> The way that keeps tickling my brain is to split the query using some
>>> combination of querying the system table partitions to gather the count,
>>> the paged sql here http://blog.sqlauthority.**com/2013/04/14/sql-server-
>>> **tricks-for-row-offset-and-**paging-in-various-versions-of-**
>>> sql-server/<http://blog.sqlauthority.com/2013/04/14/sql-server-tricks-for-row-offset-and-paging-in-various-versions-of-sql-server/>
>>>  and
>>> some kind of parallel PartialProcessOperation, I can get some decent
>>> throughput, 10million in around 40 sec, but when I point it to the full
>>> result set I receive a SqlTimeoutException.
>>>
>>> Which reveals a fun little bit of microsoft shenanigans, apparently the
>>> SqlTimeoutException will also throw if you have exceeded the number of
>>> available connections in the pool or if they are all busy when a request
>>> comes in.
>>>
>>> So I may be OVER paralleling the query. *sigh*
>>>
>>> Any help would be greatly appreciated.
>>>
>>>
>>>
>>>
>>>
>>>
>>>
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