This is not a TPC-H benchmark result.
这不是一个TPC - H的基准测试结果。
The first column represents the TPC-H query number.
第一列表示TPC-H查询号。
Over 1 TB of TPC-H data was loaded in under 30 minutes.
它能在不足30分钟加载超过1TB的TPC- H的数据。
Multiple competitors have published results based on TPC-H data.
多家竞争对手已经在TPC - H的数据上公布了结果。
The following table gives a brief summary of the TPC-H benchmark result.
下表给出了TPC - h基准测试结果的简要总结。
The database queries in TPC-H are more complex than typical OLTP queries.
TPC - H中的数据库查询要比典型的OLTP查询更加复杂。
The performance test of TPC-H consists of two tests: the Power test and the Throughput test.
TPC-H性能测试包括两部分：能力（Power）测试和吞吐量（Throughput）测试。
The first step in maximizing the performance of the TPC-H benchmark is to look at scalability.
TPC - h基准测试性能最优化的第一步就是查看可伸缩性。
of course results will vary, but this test run was performed with the TPC-H query workload on 1 TB of data.
当然，结果将会变化，而该测试是通过执行包含1TB数据的TPC - H查询完成的。
This article describes the database setup and configuration for a leading 100gb TPC-H benchmark publication.
本文描述了针对领先的100gbTPC - h基准测试公布的数据库安装和配置。
We generated 4gb TPC-H data and divided the TPC-H tables among two databases on two separate physical machines.
我们生成了4gbTPC - H数据，并把TPC - H表分在两个单独物理机器上的两个数据库中。
Conversely, TPC-H is a data warehousing benchmark that requires the ability to perform complex queries efficiently.
相反，TPC - H是一种数据仓库基准，它要求能够有效地执行复杂查询。
They are not derived from a compliant TPC-H benchmark and should not be compared with any existing official results.
它们不是来自兼容的TPC - h基准测试，并且不应该拿来与任何现有的正式结果相比较。
Please note that the ETL loading results are not TPC-H benchmark results and should not be compared to TPC-H benchmark results.
请注意ETL装载结果并非的TPC - H的基准测试结果，不应该和TPC - H的基准测试相比。
TPC-H is a decision-support benchmark that consists of a suite of business-oriented ad-hoc queries and concurrent data modifications.
TPC-H是一个由一套面向商业的即席（ad-hoc ）查询和并发数据修改组成的决策支持基准测试。
This arrangement is made with the following concern: in the TPC-H workload, a significant amount of I/O operations are sequential reads.
这种方案是出于以下考虑而布置的：在TPC-H工作负载中，相当大一部分I/O操作都是连续的读取操作。
To test the performance of the MQTs over nicknames we used parts of the "TPC-H" benchmark workload adapted to fit a federated environment.
要在昵称上测试MQT的性能，我使用适应于联邦环境的部分“TPC - H ”基准测试工作负载。
In the federated database we defined servers to access the two DB2 databases and nicknames to map the TPC-H tables from those DB2 databases.
在联邦数据库中，我们定义了服务器来访问这两个DB 2数据库和昵称，以从这些DB 2数据库映射TPC - h表。
Tradata no longer benchmarks with TPC-H for reasons that I'm sure we'd disagree with, and SQL Server doens't have any results in at this metric.
Tradata不再以TPC - H为基准，因为我相信我们不会同意，而SQLServer在此度量中没有任何结果。
Because of the number of table scans and table sorts in the TPC-H workload, prefetching data from disks into memory is important for optimal performance.
因为TPC - H工作负载中表扫描和表排序的数量较多，所以为获得最佳性能将数据从磁盘预取到内存是很重要的。
The information contained in this article can be used to optimize decision-support and data-warehouse workloads that are similar in nature to the TPC-H benchmark.
本文所包含的信息可用于优化本质上类似TPC - h基准测试的决策支持工作负载和数据仓库工作负载。
This paper described the key setup and configuration of the IBM DB2 Universal Database on an Intel Itanium 2 processor-based platform for a TPC-H Benchmark publication.
本文描述了针对TPC - h基准测试公布，与在基于IntelItanium2处理器的平台上安装和配置IBMDB 2UniversalDatabase相关的关键问题。
When comparing the TPC-H 10 TB results, you'll note that DB2 V8.2.2 (on 8 8-way p5 575 servers) delivers the highest performing TPC-H benchmark ever (as of the time this article was written).
当比较TPC - H10TB结果时，您将注意到，DB 2V8.2.2(在8 8 -路p 5 575服务器上)交付了历史上最高的TPC - h基准(在本文编写之际)。
When comparing the TPC-H 10 TB results, you'll note that DB2 V8.2.2 (on 8 8-way p5 575 servers) delivers the highest performing TPC-H benchmark ever (as of the time this article was written).
当比较TPC - H10TB结果时，您将注意到，DB 2V8.2.2(在8 8 -路p 5 575服务器上)交付了历史上最高的TPC - h基准(在本文编写之际)。
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