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Data and models



This page uses Studio code blocks so you can run the examples directly in the browser. You only need to sign up for SA Studio (it's free). Once you have done that you can execute the code blocks on this page.
When you exit sa.studio the database is by default not saved and thus it disappears. The command `save` saves the database image on disk so that all data and function definitions remain the next time you use sa.studio.

Example:

save
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The command will save the current database in a database image file named sa.engine.dmp inside the bin folder of your SA home folder. The result of save is the full database image file name.

Note

In the free web-based sandbox version of sa.engine the saved database image will disappear when the sandbox is restarted after 1-2 days. When the sandbox is restarted, it will use the 'factory' database image instead. You can find the exact location of the current image file by calling the function image_file().

You get the current SA home folder by evaluating:

sa_home()
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Under Windows the SA home folder is located in %USERPROFILE%\Documents\SA, under OSX in ~/Documents/SA, and under Linux in ~/SA. The database image is by default saved in sa.engine.dmp in the bin folder under the SA home folder.

You can list the files in your SA home bin folder by calling:

dir(sa_home()+"bin")
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Erasing the database image file​

You can erase the current database disk image and reset it to the original 'factory' database by:

erase_image()
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The function returns the name of the erased database image if it was found. The next time the system is started it will use the 'factory' database image instead.

You can change your mind and restore an erased image in the same session if you call save after you have erased it.

Image loading order​

When sa.engine is started it uses the default image name sa.engine.dmp.

In general, the system will look for the image file to use in the following directory order:

  1. It first looks in the bin subfolder under the user's SA home folder. The home folder is returned by calling sa_home().

  2. Then it looks in the startup directory where the sa.engine executable is located. This folder is returned by calling startup_dir().

User models​

It is not practical to always save all function definitions and data in the database during development. In order to organize the definitions systematically, it is recommended to create user model folders containing files with your functions and meta-data. To show how this works do the following:

Go to the OSQL-editor by clicking <> in the navigator tab up to the left and create there a new model folder in the following way:

  • Right click User models and choose Create new model, then enter the name of your new model, e.g. my_c_to_f for storing the ctof function in the pull-down menu. Then click OK to create a new model folder named my_c_to_f.

  • Choose the Documentation tab to get back here

Check that my_c_to_f is added to your models by being included in the result of:

models:list()
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The model folder my_c_to_f is located in the subfolder models under sa_home(). Check its contents by:

dir(models:folder("my_c_to_f"))
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A model folder always contains an OSQL file master.osql where the analysis model is defined. To edit master.osql navigate to the OSQL editor view by clicking the symbol <> in the navigator bar to the left. Then expand the Models folder in the side bar of the OSQL editor view. You will the see my_c_to_f in the sidebar under User models. Select it and click on master.osql. You will enter a text editor for the file where you can paste the definition of the function ctof() Don't forget to save the model file by clicking save or pressing ctrl+s. Quit the editor by clicking close.

You can now load the model into the database by running:

models:load('my_c_to_f')
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Check that the model has been loaded into the database by:

models:loaded()
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At this point my_c_to_f should be included in the result. If not, you have probably forgotten to save the master.osql file.

Check that function ctof is in the database by:

sourcecode('ctof')
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Call save to save the model in the database so that it is available next time you run sa.studio.

System models​

There is a library of predefined system models available. They are by default not loaded into the database. To see what system models are available click <> -> System Models and you can choose among a number of predefined system models. Some of these implement AI learning algorithms.

To load a system model you can click the button publishto the right of the model name whereby it will be loaded into the stream server.

For example, load the non-supervised learning algorithm dbscan for automatically forming clusters of feature vectors. Choose to load it on the server.

You can do the same for the k-means clustering algorithm or for linear regression.

Undo changes​

The system logs all changes made by users if transaction logging is enabled. This means that the sa.engine user can undo all model definitions in a session by the command rollback. This is very practical when building models since buggy models definitions can easily be undone by executing rollback and then re-enter corrected model code.

When the model is ready you can save the database on disk using save. A new session is thereby started so that the next rollback stops at the save call.

You can also make a save point by executing the command commit. The next rollback will stop at the commit but, unlike save, the database is not saved on disk. This is practical when a part of the model has been developed.

Note

OSQL statements are by default auto-committed which means that there is an implicit commit statement executed after each (set of) OSQL statements sent to the system. Auto-commit is disabled by calling auto_commit(false).

Note

The free web based sandbox version of sa.studio has limited memory that may be exhausted by the extra space needed to enable long rollbacks if auto-commit is disabled. This can be alleviated by issuing the commit command now and then to free space for the log.

The next tutorial shows how to query potentially infinite streams.