一个表包含超过 10 条 lacs 记录

Question

在我们项目的数据库中，我们只有一张表，其中有 10 多条 lac 记录。

这个特殊的表使我们的网络应用程序的性能太慢了。

Answer 1

你能补充更多细节吗？到目前为止，您分享的信息不足以给您很好的回应。可能有很多事情会导致性能问题。在寻找解决方案之前，您需要先缩小范围并清楚地隔离问题。

1. 选择@@VERSION 以获取完整版本
2. 这个盒子有多少内存？
3. 通过以下查询分享详细信息

    SELECT 
        object_name(s.object_id) AS 'Table Name'
        , i.name AS 'Index Name'
        , i.index_id
        , user_updates AS 'Total Writes'
        , user_seeks
        , user_scans 
        , user_lookups
    FROM sys.dm_db_index_usage_stats AS s WITH (NOLOCK)
    INNER JOIN sys.indexes AS i WITH (NOLOCK)
    ON s.object_id = i.object_id
    AND i.index_id = s.index_id
    WHERE objectproperty(s.object_id,'IsUserTable') = 1
    AND s.database_id = db_id()
    AND i.object_id = object_id('YourTableName')

1. 分享以下缺失索引 DMV 的详细信息，看看您是否有任何涉及上述表格的查询。

   
   SET TRANSACTION ISOLATION LEVEL READ UNCOMMITTED;
   WITH XMLNAMESPACES
   
      (DEFAULT 'http://schemas.microsoft.com/sqlserver/2004/07/showplan') 
   SELECT TOP 25--ecp.plan_handle,
           DENSE_RANK() OVER ( ORDER BY ecp.plan_handle ) AS ArbitraryPlanNumber ,
           n.value('(@StatementSubTreeCost)[1]', 'VARCHAR(128)')
           * ISNULL(n.value('(./QueryPlan/MissingIndexes/MissingIndexGroup/@Impact)[1]','float'), 0)
           * ecp.usecounts AS Improvement ,
           query_plan AS CompleteQueryPlan ,
           n.value('(@StatementId)[1]', 'float') AS StatementID ,
           n.value('(@StatementText)[1]', 'VARCHAR(4000)') AS StatementText ,
           n.value('(@StatementSubTreeCost)[1]', 'VARCHAR(128)') AS StatementSubTreeCost ,
           n.query('./QueryPlan/MissingIndexes') MissingIndex ,
           n.value('(./QueryPlan/MissingIndexes/MissingIndexGroup/@Impact)[1]','float') IndexImpact ,
           ecp.usecounts
   FROM    sys.dm_exec_cached_plans AS ecp
           CROSS APPLY sys.dm_exec_query_plan(plan_handle) AS eqp
           CROSS APPLY query_plan.nodes('/ShowPlanXML/BatchSequence/Batch/Statements/StmtSimple')
           AS qn ( n )
   WHERE   n.value('(./QueryPlan/MissingIndexes/MissingIndexGroup/@Impact)[1]','float') IS NOT NULL AND
           --ecp.usecounts > 100 AND
           eqp.query_plan.exist('declare default element namespace "http://schemas.microsoft.com/sqlserver/2004/07/showplan"; 
            /ShowPlanXML/BatchSequence/Batch/Statements/StmtSimple/QueryPlan/MissingIndexes') = 1 
   ORDER BY Improvement DESC

2. 您是否检查过高 CPU 使用率、逻辑读取、高执行次数的查询统计信息？

   
   -- Cached SP's By Execution Count
   SELECT TOP (100) OBJECT_NAME(qt.objectid) AS 'SP Name', qs.execution_count AS 'Execution Count',
   
   qs.execution_count/DATEDIFF(Second, qs.creation_time, GetDate()) AS 'Calls/Second',
   qs.total_worker_time/qs.execution_count AS 'AvgWorkerTime',
   qs.total_worker_time AS 'TotalWorkerTime',
   qs.total_elapsed_time/qs.execution_count AS 'AvgElapsedTime',
   qs.max_logical_reads, qs.max_logical_writes, qs.total_physical_reads, 
   DATEDIFF(Minute, qs.creation_time, GetDate()) AS 'Age in Cache'
   FROM sys.dm_exec_query_stats AS qs
   CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) AS qt
   WHERE qt.dbid = db_id() -- Filter by current database
   ORDER BY qs.execution_count DESC;
   
   -- Cached SP's By Worker Time
   SELECT TOP (50) OBJECT_NAME(qt.objectid) AS 'SP Name', qs.total_worker_time AS 'TotalWorkerTime', 
   qs.total_worker_time/qs.execution_count AS 'AvgWorkerTime',
   qs.execution_count AS 'Execution Count', 
   ISNULL(qs.execution_count/DATEDIFF(Second, qs.creation_time, GetDate()), 0) AS 'Calls/Second',
   ISNULL(qs.total_elapsed_time/qs.execution_count, 0) AS 'AvgElapsedTime', 
   qs.max_logical_reads, qs.max_logical_writes, 
   DATEDIFF(Minute, qs.creation_time, GetDate()) AS 'Age in Cache in Minutes'
   FROM sys.dm_exec_query_stats AS qs
   CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) AS qt
   WHERE qt.dbid = db_id() -- Filter by current database
   ORDER BY qs.total_worker_time DESC;
   
   -- Cached SP's By Logical Reads
   SELECT TOP (50) OBJECT_NAME(qt.objectid) AS 'SP Name', total_logical_reads, 
   qs.execution_count AS 'Execution Count', total_logical_reads/qs.execution_count AS 'AvgLogicalReads',
   qs.execution_count/DATEDIFF(Second, qs.creation_time, GetDate()) AS 'Calls/Second', 
   qs.total_worker_time/qs.execution_count AS 'AvgWorkerTime',
   qs.total_worker_time AS 'TotalWorkerTime',
   qs.total_elapsed_time/qs.execution_count AS 'AvgElapsedTime',
   qs.total_logical_writes,
   qs.max_logical_reads, qs.max_logical_writes, qs.total_physical_reads, 
   DATEDIFF(Minute, qs.creation_time, GetDate()) AS 'Age in Cache'
   FROM sys.dm_exec_query_stats AS qs
   CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) AS qt
   WHERE qt.dbid = db_id() -- Filter by current database
   ORDER BY total_logical_reads DESC;

3. 您查看过等待统计信息吗？

   
   WITH Waits AS
   (SELECT wait_type, wait_time_ms / 1000. AS wait_time_s,
       100. * wait_time_ms / SUM(wait_time_ms) OVER() AS pct,
       ROW_NUMBER() OVER(ORDER BY wait_time_ms DESC) AS rn
    FROM sys.dm_os_wait_stats
    WHERE wait_type NOT IN( 'BROKER_TASK_STOP', 
     'SQLTRACE_BUFFER_FLUSH', 'CLR_AUTO_EVENT', 'CLR_MANUAL_EVENT', 'BROKER_TRANSMITTER',
     'LAZYWRITER_SLEEP', 'SQLTRACE_WAIT_ENTRIES')) -- filter out additional irrelevant waits
   SELECT W1.wait_type, 
     CAST(W1.wait_time_s AS DECIMAL(12, 2)) AS wait_time_s,
     CAST(W1.pct AS DECIMAL(12, 2)) AS pct,
     CAST(SUM(W2.pct) AS DECIMAL(12, 2)) AS running_pct
   FROM Waits AS W1
   INNER JOIN Waits AS W2
   ON W2.rn <= W1.rn
   GROUP BY W1.rn, W1.wait_type, W1.wait_time_s, W1.pct
   HAVING SUM(W2.pct) - W1.pct < 99; -- percentage threshold

4. 您是否看到系统中有阻塞？