|Ajuda do DR7|
|Descrições das Tabelas|
|Introdução a SQL|
|Guia Formulário Busca|
|Limites de Busca|
|- Emacs interface|
|Sites do SkyServer|
|Página de Tráfego|
|Contatar Help Desk (em inglês)|
SDSS Query AnalyzerAuthor: Nolan Li & Tanu Malik, JHU
Date: March 2004
sdssQA is a GUI SQL query tool to help compose SQL queries. It was inspired by the SQL Server Query Analyzer, but runs as a Java application on UNIX, Macintosh, and Windows clients and is freely available from this web site. It connects via ODBC/JDBC (for local use) and via HTTP or SOAP for use over the Internet.
Command-Line SQL ToolAuthor: Tamas Budavari, JHU
Date: April 2003
sqlcl is a command-line SQL query tool to help compose SQL queries. It is a simple tool written in Python that let's you submit queries with the minimum of fuss.
GalaxyExplorer: a 3D visualization tool
Author: Szalay, Tamas
This tool enables an interactive, video game-like fly through of the 3D galaxy distribution in the Sloan Digital Sky Survey. This tool runs under Windows, requires DirectX8.0 or higher, and a graphics card supporting 3D.
The SDSS SkyServer – Public Access to the Sloan Digital Sky Survey Data
Author: Szalay, Alexander ; Gray, Jim ; Thakar, Ani ;
Kunszt, Peter Z. ; Malik, Tanu ;
The SkyServer provides Internet access to the public Sloan Digital Sky Survey (SDSS) data for both astronomers and for science education. This paper describes the SkyServer goals and architecture. It also describes our experience operating the SkyServer on the Internet. The SDSS data is public and well-documented so it makes a good test platform for research on database algorithms and performance. This appeared as a Microsoft Technical Report, MS-TR-2001-104.
Designing and Mining Multi-Terabyte Astronomy Archives: The Sloan Digital Sky Survey
Author: Szalay, Alexander S. ; Kunszt, Peter ; Thakar,
Ani ; Gray, Jim ; Slutz, Donald ; Brunner, Robert J.
The archive will enable astronomers to explore the data interactively. Data access will be aided by multidimensional spatial and attribute indices. The data will be partitioned in many ways. Small tag objects consisting of the most popular attributes will accelerate frequent searches. Splitting the data among multiple servers will allow parallel, scalable I/O and parallel data analysis. Hashing techniques will allow efficient clustering, and pair-wise comparison algorithms that should parallelize nicely. Randomly sampled subsets will allow debugging otherwise large queries at the desktop. Central servers will operate a data pump to support sweep searches touching most of the data. The anticipated queries will require special operators related to angular distances and complex similarity tests of object properties, like shapes, colors, velocity vectors, or temporal behaviors. These issues pose interesting data management challenges.
The paper describes our vision for the SkyServer, dated about a year before we started to build the production system. This appeared as a Microsoft Technical Report, MS-TR-99-30.