row-overflow data造句
例句與造句
- Cumulative count of row - overflow data bytes retrieved
檢索到的行溢出數據字節數的累積計數。 - Index , in - row , lob , and row - overflow data pages are correctly linked
是否已正確鏈接索引、行內、 lob以及行溢出數據頁。 - 3 row - overflow data
3 =行溢出數據 - Cumulative count of column values for lob data and row - overflow data that is pulled in - row
已請求到行內的lob數據和行溢出數據的列值的累積計數。 - To obtain information about tables or indexes that might contain row - overflow data , use the
若要獲得有關可能包含行溢出數據的表或索引的信息，請使用 - It's difficult to find row-overflow data in a sentence. 用row-overflow data造句挺難的
- Cumulative count of row - overflow data pages retrieved from the row overflow data allocation unit
從row _ overflow _ data分配單元檢索到的行溢出數據頁數的累積計數。 - You can include columns that contain row - overflow data as key or nonkey columns of a nonclustered index
可以包括包含行溢出數據的列，作為非聚集索引的鍵列或非鍵列。 - In - row data , lob data , and row - overflow data represent the three allocation units that make up a partition
行內數據、 lob數據以及行溢出數據表示構成分區的三個分配單元。 - If row - overflow data exists in the table , one row is returned for the row overflow data allocation unit in each partition
如果表中存在行溢出數據，則針對每個分區中的row _ overflow _ data分配單元，返回與其對應的一行。 - Cumulative count of column values for lob data and row - overflow data that is pushed off - row to make an inserted or updated row fit within a page
已推出行外以使插入或更新的行可容納在頁中的lob數據和行溢出數據的列值累積計數。 - Displays information about the space used to store and manage in - row data lob data , and row - overflow data for all partitions in a database
Sys . dm _ db _ partition _ stats顯示用于存儲和管理數據庫中全部分區的行內數據lob數據和行溢出數據的空間的有關信息。 - If there are likely to be frequent queries on many rows of row - overflow data , consider normalizing the table so that some columns are moved to another table
如果可能需要經常查詢行溢出數據中的許多行，請考慮對表格進行規范化處理，以使某些列移動到另一個表中。 - Also , querying and performing other select operations , such as sorts or joins on large records that contain row - overflow data slows processing time , because these records are processed synchronously instead of asynchronously
此外，執行查詢和其他選擇操作（例如，對包含行溢出數據的大型記錄進行排序或合并）將延長處理時間，因為這些記錄將同步處理，而不是異步處理。