69 lines
4.1 KiB
Markdown
69 lines
4.1 KiB
Markdown
# Data Controller for SAS: File Uploads
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Files can be uploaded via the Editor interface - first choose the library and table, then click "Upload". All versions of excel are supported.
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Uploaded data may *optionally* contain a column named `_____DELETE__THIS__RECORD_____` - where this contains the value "Yes" the row is marked for deletion.
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If loading very large files (eg over 10mb) it is more efficient to use CSV format, as this bypasses the local rendering engine, but also the local DQ checks - so be careful! Examples of local (excel) but not remote (CSV) file checks include:
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* Length of character variables - CSV files are truncated at the max target column length
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* Length of numeric variables - if the target numeric variable is below 8 bytes then the staged CSV value may be rounded if it is too large to fit
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* NOTNULL - this rule is only applied at backend when the constraint is physical (rather than a DC setting)
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* MINVAL
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* MAXVAL
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* CASE
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Note that the HARDSELECT_*** hooks are not applied to the rendered Excel values (they are currently only applied when editing a cell).
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## Excel Uploads
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Thanks to our pro license of [sheetJS](https://sheetjs.com/), we can support all versions of excel, large workbooks, and extract data extremely fast. We also support the ingest of [password-protected workbooks](/videos#uploading-a-password-protected-excel-file).
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The rules for data extraction are:
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* Scan the spreadsheet until a row is found with all the target columns (not case sensitive)
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* Extract data below until the *first row containing a blank primary key value*
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This is incredibly flexible, and means:
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* data can be anywhere, on any worksheet
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* data can contain additional columns (they are just ignored)
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* data can be completely surrounded by other data
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A copy of the original Excel file is also uploaded to the staging area. This means that a complete audit trail can be captured, right back to the original source data.
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!!! note
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If the excel contains more than one range with the target columns (eg, on different sheets), only the FIRST will be extracted.
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## CSV Uploads
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The following should be considered when uploading data in this way:
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- A header row (with variable names) is required
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- Variable names must match those in the target table (not case sensitive). An easy way to ensure this is to download the data from Viewer and use this as a template.
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- Duplicate variable names are not permitted
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- Missing columns are not permitted
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- Additional columns are ignored
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- The order of variables does not matter EXCEPT for the (optional) `_____DELETE__THIS__RECORD_____` variable. When using this variable, it must be the **first**.
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- The delimiter is extracted from the header row - so for `var1;var2;var3` the delimeter would be assumed to be a semicolon
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- The above assumes the delimiter is the first special character! So `var,1;var2;var3` would fail
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- The following characters should **not** be used as delimiters
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- doublequote
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- quote
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- space
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- underscore
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When loading dates, be aware that Data Controller makes use of the `ANYDTDTE` and `ANYDTDTTME` informats (width 19).
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This means that uploaded date / datetime values should be unambiguous (eg `01FEB1942` vs `01/02/42`), to avoid confusion - as the latter could be interpreted as `02JAN2042` depending on your locale and options `YEARCUTOFF` settings. Note that UTC dates with offset values (eg `2018-12-26T09:19:25.123+0100`) are not currently supported. If this is a feature you would like to see, contact us.
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!!! tip
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To get a copy of a file in the right format for upload, use the [file download](/dc-userguide/#usage) feature in the Viewer tab
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!!! warning
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Lengths are taken from the target table. If a CSV contains long strings (eg `"ABCDE"` for a $3 variable) then the rest will be silently truncated (only `"ABC"` staged and loaded). If the target variable is a short numeric (eg 4., or 4 bytes) then floats or large integers may be rounded. This issue does not apply to excel uploads, which are first validated in the browser.
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