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ローカル・バッファ・キャッシュ
The chart represents the percentage of logical reads that read data from the buffer cache of other instances via DMA and from disk. It is essentially a profile of how much work is done in the local buffer cache, rather than the portion of non-local references that incur some latency overhead.
Shows the percentage of logical read operations that retrieved data from the buffer cache of other instances by way of Direct Memory Access and from disk. It is essentially a profile of how much work is performed in the local buffer cache, rather than the portion of remote references and physical reads, which both have higher latencies.
Concurrent read and write activity on shared data in a cluster is a frequently occurring activity. Depending on the service requirements, this activity does not usually cause performance problems. However, when global cache requests cause a performance problem, optimizing SQL plans and the schema to improve the rate at which data blocks are located in the local buffer cache, and minimizing I/O is a successful strategy for performance tuning. If the latency for consistent-read and current block requests reaches 10 milliseconds, then your first step in resolving the problem should be to go to the Cluster Cache Coherency page for more detailed information.
Use the Total Transfer by Instance page to view the number of logical reads that read data from the buffer cache of other instances through Direct Memory Access and from disk. This essentially profiles how much work is performed in the local buffer cache, rather than the portion of non-local references that incur some latency overhead.
≪インスタンスごとの転送合計|Total Transfer By Instance|emdw≫・ページを使用して、ダイレクト・メモリー・アクセスを経由して他のインスタンスのバッファ・キャッシュからデータを読み取る論理読取り、およびディスクからデータを読み取る論理読取りの数を表示します。これは、待機時間のオーバーヘッドの原因であるローカル参照以外の部分ではなく、ローカル・バッファ・キャッシュにおける処理量のプロファイルです。
Shows the percentage of logical read operations that retrieved data from the buffer cache of other instances by way of Direct Memory Access and from disk. It is essentially a profile of how much work is performed in the local buffer cache, rather than the portion of remote references that incur some latency overhead. Click the legends to the right of the chart to go to the Global Cache Block Transfers vs. Logical Reads by Instance and Physical Reads vs. Logical Reads by Instance pages. From there, you can click an instance legend under the chart to go to the Segment Statistics by Instance page, where you can see which segments are causing cache contention...
ダイレクト・メモリー・アクセス経由で他のインスタンスのバッファ・キャッシュからデータを取得した論理読取り操作と、ディスクからデータを取得した論理読取り操作の割合が表示されます。これは実質的には、待機時間のオーバーヘッドを発生させるリモート参照の割合ではなく、ローカル・バッファ・キャッシュで実行される処理の割合を表します。グラフの右にある凡例をクリックすると、インスタンスごとのグローバル・キャッシュ・ブロック転送と論理読取りに関するページおよびインスタンスごとの物理読取りと論理読取りに関するページに移動します。ここでグラフの下にあるインスタンスの凡例をクリックすると、≪インスタンスごとのセグメント統計|Segment Statistics By Instance|emdw≫ページに移動できます。このページでは、どのセグメントでキャッシュ競合が発生しているかを確認できます。
When a process attempts to access a data block, it first tries to locate a copy of the data block in the local buffer cache. If a copy of the data block is not found in the local buffer cache, a global cache operation is initiated. Before reading a data block from disk, the process attempts to find the data block in the buffer cache of another instance. If the data block is in the buffer cache of another instance, Cache Fusion transfers a version of the data block to the local buffer cache, rather than having one database instance write the data block to disk and requiring the other instance to reread the data block from disk. For example, after the sales1 instance loads a data block into its buffer cache, the sales2 instance can more quickly acquire the data block from the sales1 instance by using Cache Fusion rather than by reading the data block from disk.
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