loading data from a file
Once you have selected the type of file you want to load data from, by clicking the
Browse
button, you will be prompted with a standard Open file
dialog box that will enable you to select the file containing the data you wish the selected set to link to.
Once the file has been selected, enter all additional information required
to access the data in the file, such as password or column information. For example, in case you're loading data from a Microsoft Access database file you will be able to enter the password if the file is password protected. If you're using an Excel file, you might want to define if the First line contains field names
option.
In case the selected file supports multiple tables or worksheets, these will be loaded and listed in the center-screen combo box, after you have clicked the Load worksheets button (or Load tables, depending on the context). At this point you will be able to load the data using two different approaches:
- Select the table (or worksheet) you want to load data from, from the list of available tables.
- Select the last item "SQL...", and enter a SQL query to be executed against the selected data source (for advanced users).
Note:
The query result will depend on the type of data source selected. The query
must be
a SELECT query and must comply
with the SQL implementation supported by the data source.
Connection to the underlying data source
is always a read-only
connection
and the source data
will never be modified by Labeljoy.
If the query cannot be executed, an error message will be shown.
On the web, many sites offer resources that can help you learn and write basic SQL queries. Here's a few helpful links:
www.sqltutorial.org
beginner-sql-tutorial.com/sql.htm
Note:
The amount of data loaded
may decrease system performance
when large data sources are used. To ensure that Labeljoy keeps memory usage within an acceptable range, it is advisable to avoid
loading entire tables
containing hundreds of thousands of records. Depending on your system performance, it is suggested to avoid loading data sources
larger than 100,000 records
whenever possible
