Orange: SQL Table - Revision history

Onnowpurbo: /* Contoh */

2020-01-10T01:33:35Z

Contoh

Onnowpurbo: /* MSSQL */

2020-01-10T01:32:14Z

MSSQL

Onnowpurbo at 01:31, 10 January 2020

2020-01-10T01:31:28Z

Onnowpurbo at 01:18, 10 January 2020

2020-01-10T01:18:23Z

Onnowpurbo at 01:17, 10 January 2020

2020-01-10T01:17:14Z

Onnowpurbo at 01:15, 10 January 2020

2020-01-10T01:15:30Z

Onnowpurbo at 01:12, 10 January 2020

2020-01-10T01:12:08Z

Onnowpurbo at 01:09, 10 January 2020

2020-01-10T01:09:03Z

Onnowpurbo at 01:08, 10 January 2020

2020-01-10T01:08:49Z

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]]

@@ Line 44: / Line 44: @@
 ==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]]
 ==Referensi==

@@ Line 40: / Line 40: @@
   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==

@@ Line 14: / Line 14: @@
 [[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==
@@ Line 30: / Line 30: @@
   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===

@@ 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.
-##Installation Instructions
+==Instalasi Pendukung==
-###PostgreSQL
+===PostgreSQL===
-Install the backend.
+Install
   pip install psycopg2
@@ Line 34: / Line 34: @@
 Install the extensions. [optional]
-###MSSQL
+===MSSQL===
-Install the backend.
+Install
   pip install pymssql

@@ Line 14: / Line 14: @@
 [[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.
 ##Installation Instructions
@@ Line 34: / Line 28: @@
 Install the backend.
-pip install psycopg2
+ pip install psycopg2
 Alternatively, you can follow these instructions for installing the backend.
@@ Line 44: / Line 38: @@
 Install the backend.
-pip install pymssql
+ pip install pymssql
 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.
@@ 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.
-../../_images/SQLTable-Example.png
+[[File:SQLTable-Example.png|center|600px|thumb]]

@@ 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.
-../../_images/SQLTable-stamped.png
+[[File:SQLTable-stamped.png|center|600px|thumb]]
      Database type (can be either PostgreSQL or MSSQL).

@@ 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

← Older revision		Revision as of 01:09, 10 January 2020
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	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.

← 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