A Probe-Based Technique to Optimize Join Queries in Distributed Internet Databases

2000 ◽  
Vol 2 (3) ◽  
pp. 373-385 ◽  
Author(s):  
Cyrus Shahabi ◽  
Latifur Khan ◽  
Dennis McLeod
Keyword(s):  
Join Queries ◽  
Internet Databases

An Adaptive Probe-Based Technique to Optimize Join Queries in Distributed Internet Databases

2001 ◽  
Vol 12 (4) ◽  
pp. 3-14 ◽  
Author(s):  
Latifur Khan ◽  
Dennis McLeod ◽  
Cyrus Shahabi
Keyword(s):  
Join Queries ◽  
Internet Databases

Using EndNote with Internet Databases

2019 ◽  
pp. 165-210
Author(s):  
Abha Agrawal ◽  
Majid Rasouli
Keyword(s):  
Internet Databases

About projection-selection-join queries addressed to possibilistic relational databases

2005 ◽  
Vol 13 (1) ◽  
pp. 124-139 ◽  
Author(s):  
P. Bosc ◽  
O. Pivert
Keyword(s):  
Relational Databases ◽  
Join Queries

Efficient integrity checks for join queries in the cloud1

2016 ◽  
Vol 24 (3) ◽  
pp. 347-378 ◽  
Author(s):  
Sabrina De Capitani di Vimercati ◽  
Sara Foresti ◽  
Sushil Jajodia ◽  
Stefano Paraboschi ◽  
Pierangela Samarati
Keyword(s):  
Join Queries

scholarly journals Processing top-k join queries

2010 ◽  
Vol 3 (1-2) ◽  
pp. 860-870 ◽  
Author(s):  
Minji Wu ◽  
Laure Berti-Équille ◽  
Amélie Marian ◽  
Cecilia M. Procopiuc ◽  
Divesh Srivastava
Keyword(s):  
Join Queries

Inactivation of Sarcocystis bradyzoites in food; a review

2021 ◽  
Author(s):  
Hadi Valizadeh
Keyword(s):  
Systematic Review ◽  
Gamma Rays ◽  
Meat Industry ◽  
Review Of The Literature ◽  
Control Techniques ◽  
The World ◽  
Cardiac Muscles ◽  
Infected Meat ◽  
And Control ◽  
Internet Databases

The eradication of Sarcocystis-infected corpses costs the meat industry millions of dollars each year. Because this parasite is most commonly found in skeletal and cardiac muscles, preventative and control techniques such as inactivating or destroying the bradyzoites in infected meat are critical. The goal of this research was to look at the various methods for inactivating this parasite and to compare the results of these methods. Using internet databases from many fields and around the world, a systematic review of the literature was conducted. Heating, freezing, irradiation, and marination were all utilized to inactivate this parasite, and each had a distinct effect, according to the studies. Inactivation can be achieved by heating at 60°C for 20 min or freezing at -4ºC for 2 days. Also, 2 kGy of gamma rays and marination in 6% NaCl and 3% acetic acid for 48 h are enough.

A Genetic Algorithm for Selecting Horizontal Fragments

2011 ◽  
pp. 920-925
Author(s):  
Ladjel Bellatreche
Keyword(s):  
Database Systems ◽  
Data Partitioning ◽  
Materialized Views ◽  
Access Path ◽  
Multiple Dimensions ◽  
Physical Database Design ◽  
Join Queries ◽  
Speed Up ◽  
Disjoint Sets ◽  
Horizontal Partitioning

Decision support applications require complex queries, e.g., multi way joins defining on huge warehouses usually modelled using star schemas, i.e., a fact table and a set of data dimensions (Papadomanolakis & Ailamaki, 2004). Star schemas have an important property in terms of join operations between dimensions tables and the fact table (i.e., the fact table contains foreign keys for each dimension). None join operations between dimension tables. Joins in data warehouses (called star join queries) are particularly expensive because the fact table (the largest table in the warehouse by far) participates in every join and multiple dimensions are likely to participate in each join. To speed up star join queries, many optimization structures were proposed: redundant structures (materialized views and advanced index schemes) and non redundant structures (data partitioning and parallel processing). Recently, data partitioning is known as an important aspect of physical database design (Sanjay, Narasayya & Yang, 2004; Papadomanolakis & Ailamaki, 2004). Two types of data partitioning are available (Özsu & Valduriez, 1999): vertical and horizontal partitioning. Vertical partitioning allows tables to be decomposed into disjoint sets of columns. Horizontal partitioning allows tables, materialized views and indexes to be partitioned into disjoint sets of rows that are physically stored and usually accessed separately. Contrary to redundant structures, data partitioning does not replicate data, thereby reducing storage requirement and minimizing maintenance overhead. In this paper, we concentrate only on horizontal data partitioning (HP). HP may affect positively (1) query performance, by performing partition elimination: if a query includes a partition key as a predicate in the WHERE clause, the query optimizer will automatically route the query to only relevant partitions and (2) database manageability: for instance, by allocating partitions in different machines or by splitting any access paths: tables, materialized views, indexes, etc. Most of database systems allow three methods to perform the HP using PARTITION statement: RANGE, HASH and LIST (Sanjay, Narasayya & Yang, 2004). In the range partitioning, an access path (table, view, and index) is split according to a range of values of a given set of columns. The hash mode decomposes the data according to a hash function (provided by the system) applied to the values of the partitioning columns. The list partitioning splits a table according to the listed values of a column. These methods can be combined to generate composite partitioning. Oracle currently supports range-hash and range-list composite partitioning using PARTITION - SUBPARTITION statement. The following SQL statement shows an example of fragmenting a table Student using range partitioning.

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