Orange: SQL Table - Revision history

Onnowpurbo: /* Contoh */

2020-01-10T01:33:35Z

Contoh

← Older revision		Revision as of 01:33, 10 January 2020
Line 44:		Line 44:
	==Contoh==		==Contoh==

	~~Here is a simple example on how to use the~~ SQL ~~Table widget~~. ~~Place the~~ widget ~~on the canvas~~, ~~enter your database credentials and connect to your database~~. ~~Then select the table you wish to analyse~~.		Berikut adalah contoh sederhana tentang cara menggunakan widget Tabel SQL. Tempatkan widget di atas kanvas, masukkan kredensial basis data anda dan sambungkan ke basis data anda. Kemudian pilih tabel yang ingin anda analisis.

	~~Connect~~ SQL Table to Data Table ~~widget to inspect the~~ output. ~~If the table is populated~~, ~~your~~ data ~~has transferred correctly~~. ~~Now~~, ~~you can use the~~ SQL Table widget ~~in the same way as the~~ File ~~widget~~.		Hubungkan SQL Table ke widget Data Table untuk memeriksa output. Jika tabel diisi, maka data anda telah ditransfer dengan benar. Sekarang, anda bisa menggunakan widget SQL Table dengan cara yang sama seperti widget File.

	[[File:SQLTable-Example.png\|center\|600px\|thumb]]		[[File:SQLTable-Example.png\|center\|600px\|thumb]]






	==Referensi==		==Referensi==

Onnowpurbo: /* MSSQL */

2020-01-10T01:32:14Z

MSSQL

← Older revision		Revision as of 01:32, 10 January 2020
Line 40:		Line 40:
	pip install pymssql		pip install pymssql

	~~If you are encountering issues~~, ~~follow these instructions~~.		Jika Anda mengalami masalah, ikuti [https://github.com/biolab/orange3/wiki/Installation-of-SQL-extensions#mssql instruksi ini].

	==Contoh==		==Contoh==

Onnowpurbo at 01:31, 10 January 2020

2020-01-10T01:31:28Z

← Older revision		Revision as of 01:31, 10 January 2020
Line 14:		Line 14:
	[[File:SQLTable-stamped.png\|center\|600px\|thumb]]		[[File:SQLTable-stamped.png\|center\|600px\|thumb]]

	Database type (can be either PostgreSQL or MSSQL).		* Database type (can be either PostgreSQL or MSSQL).
	Host name.		* Host name.
	Database name.		* Database name.
	Username.		* Username.
	Password.		* Password.
	~~Press the blue button to connect to the~~ database. ~~Then select the table in the~~ dropdown.		* Tekan tombol biru untuk terhubung ke database. Kemudian pilih tabel dalam menu dropdown.
	Auto-discover categorical variables ~~will cast~~ INT ~~and~~ CHAR ~~columns with less than~~ 20 ~~distinct values as categorical variables~~ (~~finding all distinct values can be slow on large tables~~). ~~When not selected~~, INT ~~will be treated as numeric and~~ CHAR ~~as text~~. ~~Download to local memory downloads the selected table to your local machine~~.		* Auto-discover categorical variables akan menampilkan kolom INT dan CHAR dengan kurang dari 20 nilai berbeda sebagai variabel kategori (menemukan semua nilai berbeda bisa lambat pada tabel besar). Ketika tidak dipilih, INT akan diperlakukan sebagai numerik dan CHAR sebagai teks. Unduh ke memori lokal unduh tabel yang dipilih ke mesin lokal Anda.

	==Instalasi Pendukung==		==Instalasi Pendukung==
Line 30:		Line 30:
	pip install psycopg2		pip install psycopg2

	~~Alternatively~~, ~~you can follow these instructions for installing the~~ backend.		Atau, kita dapat mengikuti [https://blog.biolab.si/2018/02/16/how-to-enable-sql-widget-in-orange/ instruksi ini] untuk menginstal backend.

	Install ~~the extensions~~. [optional]		[https://github.com/biolab/orange3/wiki/Installation-of-SQL-extensions Install extension]. [optional]

	===MSSQL===		===MSSQL===

Onnowpurbo at 01:18, 10 January 2020

2020-01-10T01:18:23Z

← Older revision		Revision as of 01:18, 10 January 2020
Line 22:		Line 22:
	Auto-discover categorical variables will cast INT and CHAR columns with less than 20 distinct values as categorical variables (finding all distinct values can be slow on large tables). When not selected, INT will be treated as numeric and CHAR as text. Download to local memory downloads the selected table to your local machine.		Auto-discover categorical variables will cast INT and CHAR columns with less than 20 distinct values as categorical variables (finding all distinct values can be slow on large tables). When not selected, INT will be treated as numeric and CHAR as text. Download to local memory downloads the selected table to your local machine.

	~~##Installation Instructions~~		==Instalasi Pendukung==

	~~###~~PostgreSQL		===PostgreSQL===

	Install ~~the backend.~~		Install

	pip install psycopg2		pip install psycopg2
Line 34:		Line 34:
	Install the extensions. [optional]		Install the extensions. [optional]

	~~###~~MSSQL		===MSSQL===

	Install ~~the backend.~~		Install

	pip install pymssql		pip install pymssql

Onnowpurbo at 01:17, 10 January 2020

2020-01-10T01:17:14Z

← Older revision		Revision as of 01:17, 10 January 2020
Line 14:		Line 14:
	[[File:SQLTable-stamped.png\|center\|600px\|thumb]]		[[File:SQLTable-stamped.png\|center\|600px\|thumb]]

	Database type (can be either PostgreSQL or MSSQL).		Database type (can be either PostgreSQL or MSSQL).
			Host name.
	Host name.		Database name.
			Username.
	Database name.		Password.
			Press the blue button to connect to the database. Then select the table in the dropdown.
	Username.		Auto-discover categorical variables will cast INT and CHAR columns with less than 20 distinct values as categorical variables (finding all distinct values can be slow on large tables). When not selected, INT will be treated as numeric and CHAR as text. Download to local memory downloads the selected table to your local machine.

	Password.

	Press the blue button to connect to the database. Then select the table in the dropdown.

	Auto-discover categorical variables will cast INT and CHAR columns with less than 20 distinct values as categorical variables (finding all distinct values can be slow on large tables). When not selected, INT will be treated as numeric and CHAR as text. Download to local memory downloads the selected table to your local machine.

	##Installation Instructions		##Installation Instructions
Line 34:		Line 28:
	Install the backend.		Install the backend.

	pip install psycopg2		pip install psycopg2

	Alternatively, you can follow these instructions for installing the backend.		Alternatively, you can follow these instructions for installing the backend.
Line 44:		Line 38:
	Install the backend.		Install the backend.

	pip install pymssql		pip install pymssql

	If you are encountering issues, follow these instructions.		If you are encountering issues, follow these instructions.

	~~##Example~~		==Contoh==

	Here is a simple example on how to use the SQL Table widget. Place the widget on the canvas, enter your database credentials and connect to your database. Then select the table you wish to analyse.		Here is a simple example on how to use the SQL Table widget. Place the widget on the canvas, enter your database credentials and connect to your database. Then select the table you wish to analyse.
Line 54:		Line 48:
	Connect SQL Table to Data Table widget to inspect the output. If the table is populated, your data has transferred correctly. Now, you can use the SQL Table widget in the same way as the File widget.		Connect SQL Table to Data Table widget to inspect the output. If the table is populated, your data has transferred correctly. Now, you can use the SQL Table widget in the same way as the File widget.

	~~../../_images/~~SQLTable-Example.png		[[File:SQLTable-Example.png\|center\|600px\|thumb]]

Onnowpurbo at 01:15, 10 January 2020

2020-01-10T01:15:30Z

← Older revision		Revision as of 01:15, 10 January 2020
Line 12:		Line 12:
	Untuk menangani basis data besar, Orange mencoba untuk mengeksekusi bagian dari perhitungan di dalam basis data itu sendiri tanpa mengunduh data. Ini hanya berfungsi dengan database PostgreSQL dan membutuhkan ekstensi quantile dan tsm_system_time yang diinstal di server. Jika ekstensi ini tidak diinstal, data akan diunduh secara lokal.		Untuk menangani basis data besar, Orange mencoba untuk mengeksekusi bagian dari perhitungan di dalam basis data itu sendiri tanpa mengunduh data. Ini hanya berfungsi dengan database PostgreSQL dan membutuhkan ekstensi quantile dan tsm_system_time yang diinstal di server. Jika ekstensi ini tidak diinstal, data akan diunduh secara lokal.

	~~../../_images/~~SQLTable-stamped.png		[[File:SQLTable-stamped.png\|center\|600px\|thumb]]

	Database type (can be either PostgreSQL or MSSQL).		Database type (can be either PostgreSQL or MSSQL).

Onnowpurbo at 01:12, 10 January 2020

2020-01-10T01:12:08Z

← Older revision		Revision as of 01:12, 10 January 2020
Line 2:		Line 2:


	~~Reads~~ data ~~from an~~ SQL database.		Membaca data dari SQL database.

	~~Outputs~~		==Output==

	Data: dataset from the database		Data: dataset from the database

	~~The~~ SQL ~~widget accesses~~ data ~~stored in an~~ SQL ~~database~~. ~~It can connect to~~ PostgreSQL (~~requires~~ psycopg2 ~~module~~) or SQL Server (~~requires~~ pymssql ~~module~~).		Widget SQL mengakses data yang disimpan dalam database SQL. Widget SQL dapat terhubung ke PostgreSQL (memerlukan modul psycopg2) atau SQL Server (memerlukan modul pymssql).

	~~To handle large databases~~, Orange ~~attempts to execute a part of the computation in the database itself without downloading the~~ data. ~~This only works with~~ PostgreSQL ~~database and requires~~ quantile ~~and~~ tsm_system_time ~~extensions installed on~~ server. ~~If these extensions are not installed~~, ~~the~~ data ~~will be downloaded locally~~.		Untuk menangani basis data besar, Orange mencoba untuk mengeksekusi bagian dari perhitungan di dalam basis data itu sendiri tanpa mengunduh data. Ini hanya berfungsi dengan database PostgreSQL dan membutuhkan ekstensi quantile dan tsm_system_time yang diinstal di server. Jika ekstensi ini tidak diinstal, data akan diunduh secara lokal.

	../../_images/SQLTable-stamped.png		../../_images/SQLTable-stamped.png

Onnowpurbo at 01:09, 10 January 2020

2020-01-10T01:09:03Z

← Older revision		Revision as of 01:09, 10 January 2020
Line 1:		Line 1:
	Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html		Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html




	~~SQL Table~~

	Reads data from an SQL database.		Reads data from an SQL database.

Onnowpurbo at 01:08, 10 January 2020

2020-01-10T01:08:49Z

← Older revision		Revision as of 01:08, 10 January 2020
Line 1:		Line 1:
	Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html		Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html




			SQL Table

			Reads data from an SQL database.

			Outputs

			Data: dataset from the database

			The SQL widget accesses data stored in an SQL database. It can connect to PostgreSQL (requires psycopg2 module) or SQL Server (requires pymssql module).

			To handle large databases, Orange attempts to execute a part of the computation in the database itself without downloading the data. This only works with PostgreSQL database and requires quantile and tsm_system_time extensions installed on server. If these extensions are not installed, the data will be downloaded locally.

			../../_images/SQLTable-stamped.png

			Database type (can be either PostgreSQL or MSSQL).

			Host name.

			Database name.

			Username.

			Password.

			Press the blue button to connect to the database. Then select the table in the dropdown.

			Auto-discover categorical variables will cast INT and CHAR columns with less than 20 distinct values as categorical variables (finding all distinct values can be slow on large tables). When not selected, INT will be treated as numeric and CHAR as text. Download to local memory downloads the selected table to your local machine.

			##Installation Instructions

			###PostgreSQL

			Install the backend.

			pip install psycopg2

			Alternatively, you can follow these instructions for installing the backend.

			Install the extensions. [optional]

			###MSSQL

			Install the backend.

			pip install pymssql

			If you are encountering issues, follow these instructions.

			##Example

			Here is a simple example on how to use the SQL Table widget. Place the widget on the canvas, enter your database credentials and connect to your database. Then select the table you wish to analyse.

			Connect SQL Table to Data Table widget to inspect the output. If the table is populated, your data has transferred correctly. Now, you can use the SQL Table widget in the same way as the File widget.

			../../_images/SQLTable-Example.png

Onnowpurbo: Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html ==Referensi== * https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html..."

2020-01-10T01:08:17Z

Created page with "Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html ==Referensi== * https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html..."

New page

Sumber: https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html

==Referensi==

* https://docs.biolab.si//3/visual-programming/widgets/data/sqltable.html

==Pranala Menarik==

* [[Orange]]