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• Darlis Heru Murti 2006-07-01 Full Text Available Query merupakan bagian dari bahasa pemrograman SQL (Structured Query Language yang berfungsi untuk mengambil data (read dalam DBMS (Database Management System, termasuk Oracle [3]. Pada Oracle, ada tiga tahap proses yang dilakukan dalam pengeksekusian query, yaitu Parsing, Execute dan Fetch. Sebelum proses execute dijalankan, Oracle terlebih dahulu membuat execution plan yang akan menjadi skenario dalam proses excute.Dalam proses pengeksekusian query, terdapat faktor-faktor yang mempengaruhi kinerja query, di antaranya access path (cara pengambilan data dari sebuah tabel dan operasi join (cara menggabungkan data dari dua tabel. Untuk mendapatkan query dengan kinerja optimal, maka diperlukan pertimbangan-pertimbangan dalam menyikapi faktor-faktor tersebut. Optimasi query merupakan suatu cara untuk mendapatkan query dengan kinerja seoptimal mungkin, terutama dilihat dari sudut pandang waktu.
Ada banyak metode untuk mengoptimasi query, tapi pada Penelitian ini, penulis membuat sebuah aplikasi untuk mengoptimasi query dengan metode restrukturisasi SQL statement. Pada metode ini, objek yang dianalisa adalah struktur klausa yang membangun sebuah query. Aplikasi ini memiliki satu input dan lima jenis output. Input dari aplikasi ini adalah sebuah query sedangkan kelima jenis output aplikasi ini adalah berupa query hasil optimasi, saran perbaikan, saran pembuatan indeks baru, execution plan dan data statistik. Cara kerja aplikasi ini dibagi menjadi empat tahap yaitu mengurai query menjadi sub query, mengurai query per-klausa, menentukan access path dan operasi join dan restrukturisasi query.Dari serangkaian ujicoba yang dilakukan penulis, aplikasi telah dapat berjalan sesuai dengan tujuan pembuatan Penelitian ini, yaitu mendapatkan query dengan kinerja optimal.Kata Kunci: Query, SQL, DBMS, Oracle, Parsing, Execute, Fetch, Execution Plan, Access Path, Operasi Join, Restrukturisasi SQL statement. • Al-Mahrouqi, Aadil; Tobin, Patrick; Abdalla, Sameh; Kechadi, Tahar 2015-01-01 Network Forensics is a subtopic of Digital Forensics wherein research on artificat investigations and intrusions evidence acquisition is addressed.
Among many challenges in the field, the problem of losing data artifacts in the state of flux, (i.e., live volatile data), when network devices are suddenly non-operational remains a topic of interest to many investigators. The main objective of this article is to simulate an SQL injection attack scenarios in a complex network environment. A.; Klouda, G. A.; Benner, B. A.; Garrity, K.; Eglinton, T. The identification of unique isotopic, elemental, and molecular markers for sources of combustion aerosol has growing practical importance because of the potential effects of fine particle aerosol on health, visibility and global climate. It is urgent, therefore, that substantial efforts be directed toward the validation of assumptions involving the use of such tracers for source apportionment.
We describe here three independent routes toward carbonaceous aerosol molecular marker identification and validation: (1) tracer regression and multivariate statistical techniques applied to field measurements of mixed source, carbonaceous aerosols; (2) a new development in aerosol.
Q: What is AWS Device Farm? AWS Device Farm allows developers to increase application quality, time to market, and customer satisfaction by testing and interacting with real Android and iOS devices in the AWS Cloud. Developers can upload their app and test scripts and run automated tests in parallel across 100s of real devices, getting results, screenshots, video, and performance data in minutes. They can also debug and reproduce customer issues by swiping, gesturing, and interacting with a device through their web browser. Q: Who should use AWS Device Farm and why? Ontario electrical code pdf torrent.
AWS Device Farm is designed for developers, QA teams, and customer support representatives who are building, testing, and supporting mobile apps to increase the quality of their apps. Application quality is increasingly important, and also getting complex due to the number of device models, variations in firmware and OS versions, carrier and manufacturer customizations, and dependencies on remote services and other apps. AWS Device Farm accelerates the development process by executing tests on multiple devices, giving developers, QA and support professionals the ability to perform automated tests and manual tasks like reproducing customer issues, exploratory testing of new functionality, and executing manual test plans. AWS Device Farm also offers significant savings by eliminating the need for internal device labs, lab managers, and automation infrastructure development. Q: How do you clean up devices after my testing is completed? After test execution completes, we perform a series of cleanup tasks on each device, including uninstallation of your app. If we cannot verify uninstallation of your app or any of the other cleanup steps, the device will be removed and will no longer be available.