Remove 2003 Remove Benchmarking Remove Database Remove Scalability
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What Adrian Did Next?—?Part 2?—?Sun Microsystems

Adrian Cockcroft

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. We had specializations in hardware, operating systems, databases, graphics, etc.

Tuning 52
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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).

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HammerDB MySQL and MariaDB Best Practice for Performance and Scalability

HammerDB

Similarly for this guide MySQL can be swapped for a mySQL based databases such as MariaDB. As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. As is exactly the same with PostgreSQL for system choice a 2 socket system is optimal for MySQL OLTP performance.

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HammerDB Concepts and Architecture

HammerDB

However if you have downloaded the source code and are looking to add features or make modifications such as adding new databases you may be wondering once you have the source code where to start. However HammerDB will not be able to connect to a database yet and the librarycheck command included with the CLI gives an indication why.

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SQL Server I/O Basics Chapter #2

SQL Server According to Bob

KB sectors run on smaller sectors   14 System and sample databases   15 Determining the formatted sector size of database   15 What sector sizes does SQL Server support? SQL Server 2005 introduces the snapshot database feature for point-in-time databases ​​ and online DBCC operations.

Servers 40
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Data Mining Problems in Retail

Highly Scalable

To a certain extent, such a high diversity of recommendation techniques is attributed to several implementation challenges like a sparsity of customer ratings, computational scalability, and lack of information on new items and customers. Prairie, 2003. PZ07] Content-based Recommendation Systems, M. Pazzani, D. Billsus, 2007.

Retail 152