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データ・ロードのパフォーマンス
To improve data load performance by maximizing use of processor resource for your situation, you can use these settings to enable additional multiple-thread processing within the preparation and write stages of data load processing.
The methods described earlier in this chapter give you the most substantial data load performance enhancements. If you have not done so, carefully evaluate your processor speed and memory requirements and upgrade your computers to meet them.
Essbase uses the index cache size to determine how much of the index can be paged into memory. Adjusting the size of the index cache may also improve data load performance.
Average clustering ratio: Indicates the fragmentation level of data (.pag) files. The maximum value, 1, indicates no you are experiencing degraded retrieval, calculation, or data load performance and the clustering ratio value is significantly less than 1, consider performing an export and reload to rewrite the data files. Essbase also rewrites the data files during outline restructures that are triggered by changes to dense dimensions. Rewriting the data files defragments them, resulting in a clustering ratio closer to 1.
Specifies how many threads Essbase may use during the data load preparation stage, which organizes the source data in memory in preparation for storing the data into blocks. Multiple threads, processing in parallel, may improve data load performance.
Average clustering ratio-Fragmentation level of data (.pag) files. The maximum value, 1, indicates no you are experiencing degraded retrieval, calculation, or data load performance and the clustering ratio value is significantly less than 1, consider forcing a rewrite of data files by exporting and reloading data. Rewriting files defragments the files, resulting in a clustering ratio closer to 1.
Specifies how many threads Essbase may use during the stage of the data load process that writes blocks on the disk. Multiple threads, processing in parallel, may improve data load performance.
To improve data load performance by maximizing use of processor resource for your situation, you can use these settings to enable additional multiple-thread processing within the preparation and write stages of data load processing. For more information about parallel thread processing in data loads, see the "Optimizing Data Loads" chapter in the Oracle Essbase Database Administrator's Guide.
To optimize data load performance, think in terms of database structure. Essbase loads data block by block. For each unique combination of sparse dimension members, one data block contains the data for all the dense dimension combinations, assuming that at least one cell contains faster access to block locations, Essbase uses an index. Each entry in the index corresponds to one data block. See Sparse and Dense Dimensions, Selection of Dense and Sparse Dimensions, and Dense and Sparse Selection Scenarios.
Instructs Essbase to load data using a single thread per processing stage, or to use the thread values specified in the DLTHREADSPREPARE and DLTHREADSWRITE configuration settings. By working with these three configuration settings you may be able to test and improve data load performance.
You can use Teradata Parallel Transporter (TPT) from Teradata Tools and Utilities to significantly improve data load performance. With this method, ODBC is used to extract the database schema; then TPT retrieves the data.
Depending on the number of enabled triggers in a database, there may be a small decrease in performance of calculation and data load. You can control the maximum amount of memory used by the triggers feature by specifying the TRIGMAXMEMSIZE configuration setting in the essbase.cfg file. By default, TRIGMAXMEMSIZE is set to 4096 bytes. Choosing to write information to a file, rather than sending e-mail, may improve calculation and data load performance by reducing network traffic.
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Synoniemen voor data load performance in het Engels