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SQL Server has two input buffers (read buffers) and one output buffer per client. Double-buffering is needed for the reads because while SQL Server reads a stream of data from the client connection, it must also look for a possible attention. (This allows that Query That Wouldn t Die to be canceled directly from the issuer. Although the ability to cancel a request is extremely important, it is relatively unusual among client/server products.) Attentions can be thought of as out-of-band data, though they can be sent with network protocols that do not explicitly have an out-of-band channel. The SQL Server development team at Microsoft experimented with double-buffering and asynchronous techniques for the write buffers, but these did not improve performance substantially. The single network output buffer works very nicely. Even though the writes are not posted asynchronously, SQL Server does not need to write through the operating system caching for these as it does for writes to disk. Because the operating system provides caching of network writes, write operations appear to complete immediately with no significant latency that is, no significant time expires between the request for a write and the occurrence of the write itself. But if several writes are issued to the same client and the client is not currently reading data from the network, the network cache eventually becomes full and the write is blocked. The previous sentence is incomplete. This is essentially a throttle. As long as the client application is processing results, SQL Server has a few buffers queued up and ready for the client connection to process. But if the client s queue is already stacked up with results and is not processing them, SQL Server stalls sending them, and the network write operation to that connection has to wait. Since the server has only one output buffer per client, data cannot be sent to that client connection until it reads information off the network to free up room for the write to complete. (Writes to other client connections are not held up, however; only those for the laggard client are affected.) SQL Server adds rows to the output buffer as it retrieves them. Often, SQL Server can still be gathering additional rows that meet the query s criteria while rows already retrieved are being sent to the client.
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Stalled network writes can also affect locks. For example, if READ COMMITTED isolation is in effect (the default), a share lock can normally be released after SQL Server has completed its scan of that page of data. (Exclusive locks used for changing data must always be held until the end of the transaction, to ensure that the changes can be rolled back.) However, if the scan finds more qualifying data and the output buffer is not free, the scan stalls. When the previous network write completes, the output buffer becomes available and the scan resumes. But, as stated above, that write will not complete until the client connection drains (reads) some data to free up some room in the pipe (the virtual circuit between the SQL Server and client connection). If a client connection delays processing results that are sent to it, concurrency issues can result because locks are held longer than they otherwise would be. A sort of chain reaction occurs: If the client connection has not read several outstanding network packets, further writing of the output buffer at the SQL Server side must wait, because the pipe is full. Since the output buffer is not available, the scan for data might also be suspended, because no space is available to add qualifying rows. Since the scan is held up, any lock on the data cannot be released. In short, if a client application does not process results in a timely manner, database concurrency can suffer. The size of the network buffer can also affect the speed at which the client receives the first result set. As mentioned earlier, the output buffer is sent when the batch, not simply the command, is done, even if the buffer is not full. (A batch is one or more commands sent to SQL Server to be parsed and executed together. For example, if you are using OSQL.EXE or the Query Analyzer, a batch is the collection of all the commands that appear before a specific GO command.) If two queries exist in the same batch and the first query has only a small amount of data, its results are not sent back to the client until the second query is done or has supplied enough data to fill the output buffer. If both queries are fast, this is not a problem. But suppose the first query is fast and the second is slow. And suppose the first query returns 1,000 bytes of data. If the network packet size is 4,096 bytes, the first result set must wait in the output buffer for the second query to fill it. The obvious solution here is either to make the first command
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